Note: Descriptions are shown in the official language in which they were submitted.
CA 02548375 2006-06-13
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CA 02548375 2006-06-13
ASSESSMENT OF RISK FOR COLORECTAL CANCER
FIELD OF THE INVENTION
This invention relates to prediction of the susceptibility of an individual to
colorectal cancer. Basis for
the prediction lies in relating an individual's genetic makeup, as through
molecular analysis, to the
genetic makeup of a population of individuals.
BACKGROUND
During the course of evolution, spontaneous mutations arise in the genomes of
organisms. Variations
in genomic DNA sequences are created continuously at a rate of about 100 new
base changes per
individual (Kondrashov, 1995; Crow, 1995). These germ-line changes may produce
an evolutionary
advantage and be retained in the population, or they may be deleterious and
ultimately eliminated. In
many cases, equilibrium between multiple germline forms of a sequence is
established within a
population if reproductive ability of individuals containing either
polymorphism is not affected. Over
time, significant numbers of mutations have accumulated within the human
population that may be
observed to varying extents in geographically separated groups based upon the
presence of common
ancestors.
Colorectal cancer is the third most common cancer and the third most common
cause of death from
cancer for both men and women. Colorectal cancer is responsible for more
deaths that are not due
primarily to tobacco use than any other type of cancer and inflicts a huge
financial burden. Early
detection of some human tumors such as uterine cervical cancer has
dramatically reduced mortality
from this condition (Herzog, 2003). Early detection of colorectal cancer can
reasonably be expected to
prevent death from this condition by identifying patients at risk for the
disease, or those with the
disease in an early stage and allow life saving intervention. A validated
genetic test for colon cancer
predisposition will have clinical utility, allowing prevention of cancer
mortality through targeted
screening programs. There are good reasons to expect that at least some of the
genetic risks of
common disease is due to common variants - for example, based on evolutionary
arguments, and the
fact that most human genetic variation is common. Although approximately 20%
of colorectal cancers
have a familial component with relatives exhibiting a doubling of risk
(Carstensen et al., 1996), less
than 5% of colorectal cancer is explained by rare, highly penetrant genetic
syndromes such as APC
and HNPCC (de Leon et al., 1999). Familial colon cancer occurring in patterns
inconsistent with
classical inherited syndromes suggests that variation in genome sequence plays
a major role in
determining individual risk to colon cancer. These genetic causes appear
complex due to a variety of
reasons such as genetic heterogeneity, incomplete penetrance, phenocopies and
variation in exposures
CA 02548375 2006-06-13
to environmental co-factors etc. There is little insight into the genetic or
environmental determinants
of almost 90% of cases of human colorectal carcinoma (Lynch and de La, 2003).
Although common human genetic variation is limited compared to other species,
it remains
impractical to discover and test every one of the estimated 10,000,000 common
genotype variants
(Sachidanandam et al., 2001) as predictors of disease risk. Genotypic
complexity is reduced through
linkage disequilibrium that exists across long segments of the human genome
with restriction in the
diversity of haplotypes observed (Daly et al., 2001; Rioux et al., 2001; Liu
et al., 2004). That is,
single nucleotide polymorphisms found at specific locations within the human
genome are inherited in
conjunction with nucleotides that can be polymorphic that are physically
located near by. In European
genomes, allelic association between pairs of markers typically extends over
10-50k, although there is
tremendous variability in the magnitude of association observed at any given
distance (Clark et al.,
1998; Kikuchi et al., 2003; Dunning et al., 2000; Abecasis et al., 2001).
Genome-wide data (Gabriel
et al., 2002; Reich et al., 2001; Dawson et al., 2002) supports the generality
of this description as well
as its application across populations. This confirms that measurement of
single nucleotide
polymorphisms at sites in tight linkage disequilibrium with adjacent genomic
regions can provide
information about the presence of diversity not just at sites actually
measured, but also about large
areas of the adjacent genome.
Numerous types of polymorphisms exist and are created when DNA sequences are
either inserted or
deleted from the genome. Another source of sequence variation results from the
presence of repeated
sequences in the genome variously termed short tandem repeats (STR), variable
number of tandem
repeats (VNTR), short sequence repeats (SSR) or microsatellites. These repeats
commonly are
comprised of 1 to 5 base pairs. Polymorphism occurs due to variation in the
number of repeated
sequences found at a particular locus.
The most common form of genomic variability are single nucleotide
polymorphisms or SNPs. SNPs
account for as much as 90% of human DNA polymorphism (Collins et al., 1998).
SNPs are single
base pair positions in genomic DNA at which different sequence alternatives
(genotypes) exist in a
population. By common definition, the least frequent allele occurs at least 1%
of the time. These
nucleotide substitutions may be a transition, which is the substitution of one
purine by another purine
or the substitution of one pyrimidine by another, or they may be transversions
in which a purine is
replaced by a pyrimidine or vice versa.
Typically SNPs are observed in about 1 in 1000 base pairs (Wang et al., 1998;
Taillon-Miller et al.,
1999). The frequency of SNPs varies with the type and location of the change.
Specifically, two-thirds
of the substitutions involve the C t-> T (G H A) type, which may occur due to
5-methylcytosine
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deamination reactions that occur commonly. SNPs occur at a much higher
frequency in non-coding
regions than they do in coding regions.
SUMMARY OF THE INVENTION
It has been discovered that polymorphic variations in a number of loci in
human genomic DNA are
associated with susceptibility to colorectal cancer. This invention thus
includes methods for
identifying a subject at risk of colorectal and/or determining risk of
colorectal cancer in a subject,
which comprise detecting the presence or absence of one or more polymorphic
variations associated
with colorectal cancer in a nucleic acid sample from the subject. In a
specific embodiment, this
invention relates to identifying an individual who is at altered risk for
developing colorectal cancer
based on the presence of specific genotypes defined by 51 single nucleotide
polymorphism (SNPs),
observed alone or in combination.
Through large scale genotyping studies on 2373 blood samples from patients
with colon cancer and
2296 control samples from unaffected individuals we have identified 51
polymorphic markers found
in 25 genes which are found more frequently in patients with colorectal cancer
than in those without
this disease. These markers, or those in close linkage disequilibrium, may
change the composition,
function or abundance of the elements of cellular constituents resulting in a
predisposition to
colorectal cancer. Measuring these markers in individuals who do not
ostensibly have colon cancer
will identify those at heightened risk for the subsequent development of
colorectal cancer, providing
benefit for, but not limited to, individuals, insurers, care givers and
employers. Genes containing
colorectal cancer-associated polymorphic markers that we have identified and
genes found in linkage
disequilibrium with these that we have identified are valuable targets for the
development of
therapeutics that inhibit or augment the activity of the gene products of
these genes for therapeutic use
in, but not restricted to, colon cancer. Information obtained from the
detection of SNPs associated
with colorectal cancer is of great value in the treatment and prevention of
this condition.
Accordingly, one aspect of the present invention provides a method for
diagnosing a genetic
predisposition to colon cancer in a subject, comprising obtaining a sample
containing at least one
polynucleotide from the subject and analyzing the polynucleotide to detect the
genetic polymorphism
wherein the presence or absence of the polymorphism is associated with an
altered susceptibility to
developing colorectal cancer. In one embodiment, one or more of the 51
polymorphisms found
distributed among 25 genes that we have identified may be used.
Another aspect of the present invention provides an isolated nucleic acid
sequence comprising at least
16 contiguous nucleotides or their complements found in the genomic sequences
of the 25 genes
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adjacent to and including the 51 polymorphic sites the inventors have
identified to be associated with
colorectal cancer.
Yet another aspect of the invention provides a method for treating colon
cancer comprising obtaining
a sample of biological material containing at least one polynucleotide from
the subject, analyzing the
polynucleotides to detect the presence of at least one polymorphism associated
with colon cancer and
treating the subject in such a way as to counteract the effect of any such
polymorphism detected.
Still another aspect of the invention provides a method for the prophylactic
treatment of a subject
identified with a genetic predisposition to colon cancer identified through
the measurement of all or
some of the 51 polymorphic SNP markers described in Tables 1 to 51.
Further scope of the applicability of the present invention will become
apparent from the detailed
description provided below. It should be understood however, that the
following detailed description
and examples, while indicating preferred embodiments of the invention, are
given by way of
illustration only, since various changes and modification within the spirit
and scope of the invention
will become apparent to those skilled in the art from the following detailed
description.
Tables 1 to 51 report the result of a genotyping analysis of 4669 samples by
measuring 99,632 single
nucleotide polymorphisms in peripheral blood DNA from 2475 subjects (1234
cases with colorectal
cancer and 1241 age matched individuals undiseased at the time of testing),
and validating the
identified CRC-associated alleles by using peripheral blood DNA from a second,
different, group of
2194 subjects (1139 cases with colorectal cancer and 1055 age matched
individuals undiseased at the
time of testing).
DETAILED DESCRIPTION OF THE INVENTION
It has been discovered that polymorphic variants in a number of sequences, SEQ
ID NOs: 1 to 1119
are associated with an altered risk of developing colorectal cancer in
subjects. The present invention
thus provides SNPs associated with colorectal cancer, nucleic acid molecules
containing SNPs,
methods and reagents for the detection of the SNPs disclosed herein, uses of
these SNPs for the
development of detection reagents, and assays or kits that utilize such
reagents. The colorectal cancer-
associated SNPs disclosed herein are useful for diagnosing, screening for, and
evaluating
predisposition to colorectal cancer and related pathologies in humans.
Furthermore, such SNPs and
their encoded products are useful targets for the development of therapeutic
agents.
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A large number of colorectal cancer-associated SNPs have been identified by
genotyping DNA from
4669 individuals, 2373 of these individuals having been previously diagnosed
with colorectal cancer
and 2296 being "control" or individuals thought to be free of colorectal
cancer.
The present invention thus provides individual SNPs associated with colorectal
cancer, genomic
sequences (SEQ ID NOs: 1120 to 1144) containing SNPs, and transcript sequences
amino acid
sequences. The invention includes methods of detecting these polymorphisms in
a test sample,
methods of determining the risk of an individual of having or developing
colorectal cancer, methods
of screening for compounds useful for treating disorders associated with a
variant gene/protein such as
colorectal cancer, compounds identified by these screening methods, methods of
using the disclosed
SNPs to select a treatment strategy, methods of treating a disorder associated
with a variant
gene/protein (i.e., therapeutic methods), and methods of using the SNPs of the
present invention for
human identification.
When the presence in the genome of an individual of a particular base, e.g.,
adenine, at a particular
location in the genome correlates with an increased probability of that
individual contracting
colorectal cancer vis-a-vis a population not having that base at that location
in the genome, that
individual is said to be at "increased risk" of contracting colorectal cancer,
i.e., to have an increased
susceptibility. In certain cases, this effect can be a "dominant" effect in
which case such increased
probability exists when the base is present in one or the other or both
alleles of the individual. In
certain cases, the effect can be said to be "recessive", in which case such
increased probability exists
only when the base is present in both alleles of the individual.
When the presence in the genome of an individual of a particular base, e.g.,
adenine, at a particular
location in the genome decreases the probability of that individual
contracting colorectal cancer vis-6-
vis a population not having that base at that location in the genome, that
individual is said to be at
"decreased risk" of contracting colorectal cancer, i.e., to have a decreased
susceptibility. Such an
allele is sometimes referred to in the art as being "protective". As with
increased risk, it is also
possible for a decreased risk to be characterized as dominant or recessive.
An "altered risk" means either an increased or a decreased risk.
The genetic analysis detailed below linked colorectal cancer with SNPs in the
human genome. A SNP
is a particular type of polymorphic site, a polymorphic site being a region in
a nucleic acid sequence at
which two or more alternative nucleotides are observed in a significant number
of individuals from a
population. A polymorphic site may be a nucleotide sequence of two or more
nucleotides, an inserted
nucleotide or nucleotide sequence, a deleted nucleotide or nucleotide
sequence, or a microsatellite, for
example. A polymorphic site that is two or more nucleotides in length may be
3, 4, 5, 6, 7, 8, 9, 10,
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11, 12, 13, 14, 15 or more, 20 or more, 30 or more, 50 or more, 75 or more,
100 or more, 500 or more,
or about 1000 nucleotides in length, where all or some of the nucleotide
sequences differ within the
region. Each of the specific polymorphic sites found in SEQ ID NOs:1120 to
1144 is a "single
nucleotide polymorphism" or a "SNP."
Where there are two, three, or four alternative nucleotide sequences at a
polymorphic site, each
nucleotide sequence is referred to as a "polymorphic variant" or "nucleic acid
variant." Where two
polymorphic variants exist, for example, the polymorphic variant represented
in a majority of samples
from a population is sometimes referred to as a "prevalent allele" and the
polymorphic variant that is
less prevalently represented is sometimes referred to as an "uncommon allele."
An individual who
possesses two prevalent alleles or two uncommon alleles is "homozygous" with
respect to the
polymorphism, and an individual who possesses one prevalent allele and one
uncommon allele is
"heterozygous" with respect to the polymorphism. Individuals who are
homozygous with respect to
one allele are sometimes predisposed to a different phenotype as compared to
individuals who are
heterozygous or homozygous with respect to another allele.
A genotype or polymorphic variant may also be expressed in terms of a
"haplotype," which refers to
the identiy of two or more polymorphic variants occurring within genomic DNA
on the same strand of
DNA. For example, two SNPs may exist within a gene where each SNP position may
include a
cytosine variation or an adenine variation. Certain individuals in a
population may carry an allele
(heterozygous) or two alleles (homozygous) having the gene with a cytosine at
each SNP position. As
the two cytosines corresponding to each SNP in the gene travel together on one
or both alleles in these
individuals, the individuals can be characterized as having a
cytosine/cytosine haplotype with respect
to the two SNPs in the gene.
A "phenotype" is a trait which can be compared between individuals, such as
presence or absence of a
condition, for example, occurrence of colorectal cancer.
Polymorphic variants are often reported without any determination of whether
the variant is
represented in a significant fraction of a population. Some reported variants
are sequencing errors
and/or not biologically relevant. Thus, it is often not known whether a
reported polymorphic variant is
statistically significant or biologically relevant until the presence of the
variant is detected in a
population of individuals and the frequency of the variant is determined.
A polymorphic variant may be detected on either or both strands of a double-
stranded nucleic acid.
Also, a polymorphic variant may be located within an intron or exon of a gene
or within a portion of a
regulatory region such as a promoter, a 5' untranslated region (UTR), a 3'
UTR, and in DNA (e.g.,
genomic DNA (gDNA) and complementary DNA (cDNA)), RNA (e.g., mRNA, tRNA, and
rRNA), or
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a polypeptide. Polymorphic variations may or may not result in detectable
differences in gene
expression, polypeptide structure, or polypeptide function.
In our genetic analysis associating colorectal cancer with the polymorphic
variants set forth in the
tables, samples from individuals having been diagnosed with colorectal cancer
and individuals not
having cancer were allelotyped and genotyped. The allele frequency for each
polymorphic variant
among cases and controls was determined. These allele frequencies were
compared in cases and
controls, or combinations. Particular SNPs were thus found to be associated
with colorectal cancer
when genotype and haplotype frequency differences calculated between case and
control pools were
established to be statistically significant.
As mentioned above, polymorphic variants can travel together. Such variants
are said to be in "linkage
disequilibrium" so that heritable elements e.g., alleles that have a tendency
to be inherited together
instead of being inherited independently by random assortment are in linkage
disequilibrium. Alleles
are randomly assorted or inherited independently of each other if the
frequency of the two alleles
together is the product of the frequencies of the two alleles individually.
For example, if two alleles at
different polymorphic sites are present in 50% of the chromosomes in a
population, then they would
be said to assort randomly if the two alleles are present together on 25% of
the chromosomes in the
population. A higher percentage would mean that the two alleles are linked.
For example, a first
polymorphic site P1 having two alleles, e.g. A and C--each appearing in 50% of
the individuals in a
given population, is said to be in linkage disequilibrium with a second
polymorphic site P2 having two
alleles e.g. G and T--each appearing in 50% of the individuals in a given
population, if particular
combinations of alleles are observed in individuals at a frequency greater
than 25% (if the
polymorphic sites are not linked, then one would expect a 50% chance of an
individual having A at P 1
and a 50% chance of having G at P2 thus leading to a 25% chance of having the
combination of A at
P1 and G at P2 together). Heritable elements that are in linkage
disequilibrium are said to be "linked"
or "genetically linked" to each other.
One can see that in the case of a group of SNPs that are in linkage
disequilibrium with each other,
knowledge of the existence of all such SNPs in a particular individual
generally provides redundant
information. Thus, when identifying an individual who has an altered risk for
developing colorectal
cancer according to this invention, it is necessary to detect only one SNP of
such a group of SNPs
associated with an altered risk of developing colorectal cancer.
It has been shown that each SNP in the genomic sequences identified as SEQ ID
NOs: 1120 to 1144 is
associated with the occurrence of colorectal cancer. Thus, featured herein are
methods for identifying
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CA 02548375 2006-06-13
a risk of colorectal cancer in a subject, which includes detecting the
presence or absence of one or }
more of the SNPs described herein in a human nucleic acid sample.
Three different analyses were performed for each marker and significant
results reported below are
derived from one or more of the following tests: (a) a test of trend across
the 3 genotypes (Sasieni et
al. 1997); (b) a dominant model where the homozygous genotype for allele "B"
is combined with the
prevalent heterozygote genotype; and (c) a recessive model where the
homozygous genotype for allele
"A" is combined with the heterozygous genotype. Asymptotic significance and
empirical significance
based on permutation tests were estimated for each test; when both were
significant, only the
empirical significance level is reported. Odds ratios measuring the strength
of the association are also
reported for each analysis, and are calculated in a model-specific manner as
described in the next
paragraph.
Pertinent results for each SNP are summarized in the tables: Chromosomal
number and position-
using the International Human Genome Sequencing Consortium build 35
(http://www.ncbi.nlm.nih.gov/genome/seq/) as made available by the National
Center for
Biotechnology Information (NCBI), National Library of Medicine, Building 38A,
Bethesda, Maryland
20894 U.S.A., gene marker name-using the nomenclature of the NCBI dbSNP
(http://www.ncbi.nlm.nih.gov/SNP/) and gene name-using the unigene naming
convention. Under the
"Case Flag" the number 1 designates Cases and the number 0 designates
Controls. The identity of the
base designated "A" in the analysis is indicated where 1= A (adenine), 2 = C
(cytosine), 3 = G
(guanine) and 4 = T (thymidine). "B" indicates the polymorphic allele. AA, AB,
BB are the counts of
the number of individuals with the given genotype, by cases/controls. For
dominant models, an odds
ratio measuring the increase in risk associated with one or two copies of
allele B is calculated. For
recessive models, an odds ratio associated with exactly two copies of allele B
is calculated. For the
trend models, the Mantel-Haenszel odds ratio showing the increase in risk with
each additional copy
of allele B is calculated. A superscript "e" on the p-value means that it was
empirically estimated by
permutation analysis, whereas the superscript "a" means that the p-value was
estimated
asymptotically, comparing the relevant test statistic to a chi-squared
distribution with one degree of
freedom.
It has been discovered that each polymorphic variation in the genomic
sequences identified as SEQ ID
NOs:1120 to 1144 is associated with the occurrence of colorectal cancer. Thus,
featured herein are
methods for identifying a risk of colorectal cancer in a subject, which
comprises detecting the
presence or absence of one or more of the polymorphic variations described
herein in a human nucleic
acid sample. The polymorphic variation, SNP, are detailed in the tables.
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Methods for determining whether a subject is susceptible to, i.e., at risk of
colorectal cancer are
provided herein. These methods include detecting the presence or absence of
one or more
polymorphic variations, i.e., SNPs, associated with colorectal cancer in a
sample from a subject.
SNPs can be associated with a disease state in humans or in animals. The
association can be direct, as
in conditions where the substitution of a base results in alteration of the
protein coding sequence of a
gene which contributes directly to the pathophysiology of the condition.
Common examples of this
include diseases such as sickle cell anemia and cystic fibrosis. The
association can be indirect when
the SNP plays no role in the disease, but is located close to the defective
gene such that there is a
strong association between the presence of the SNP and the disease state.
Because of the high
frequency of SNPs within the genome, there is a greater probability that a SNP
will be linked to a
genetic locus of interest than other types of genetic markers.
Disease-associated SNPs can occur in coding and non-coding regions of the
genome. When located in
the coding region altered function of the ensuing protein sequence may occur.
If it occurs in the
regulatory region of a gene it may affect expression of the protein. If the
protein is involved in
protecting the body against pathological conditions this can result in disease
susceptibility.
Numerous methods exist for the measurement of specific SNP genotypes.
Individuals carrying
mutations in one or more SNPs of the present invention may be detected at the
DNA level by a variety
of techniques. Nucleic acids for diagnosis may be obtained from a patient's
cells, such as from blood,
urine, saliva, tissue biopsy and autopsy material.
The genomic DNA may be used directly for detection or may be amplified
enzymatically by using
PCR prior to analysis (Saiki et al., 1986). RNA or cDNA may also be used in
the same ways. As an
example, PCR primers complementary to the nucleic acid of one or more SNPs of
the present
invention can be used to identify and analyze the presence or absence of the
SNP. For example,
deletions and insertions can be detected by a change in size of the amplified
product in comparison to
the normal genotype. Point mutations can be identified by hybridizing
amplified DNA to radiolabeled
SNP RNA of the present invention or alternatively, radiolabeled SNP antisense
DNA sequences of the
present invention. Perfectly matched sequences can be distinguished from
mismatched duplexes by
RNase A digestion or by differences in melting temperatures.
Sequence differences between a reference gene and genes having mutations also
may be revealed by
direct DNA sequencing. In addition, cloned DNA segments may be employed as
probes to detect
specific DNA segments. The sensitivity of such methods can be greatly enhanced
by appropriate use
of PCR or another amplification method. For example, a sequencing primer is
used with double-
stranded PCR product or a single-stranded template molecule generated by a
modified PCR. The
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sequence determination is performed by conventional procedures with
radiolabeled nucleotide or by
automatic sequencing procedures with fluorescent-tags.
Genetic testing based on DNA sequence differences may be achieved by detection
of alteration in
electrophoretic mobility of DNA fragments in gels, with or without denaturing
agents. Small sequence
deletions and insertions can be visualized by high resolution gel
electrophoresis. DNA fragments of
different sequences may be distinguished on denaturing formamide gradient gels
in which the
mobilities of different DNA fragments are retarded in the gel at different
positions according to their
specific melting or partial melting temperatures (Myers et al., 1985).
Sequence changes at specific locations also may be revealed by nuclease
protection assays, such as
RNase and S1 protection or the chemical cleavage method (Cotton et al., 1988).
Thus, the detection of a specific DNA sequence may be achieved by methods
which include, but are
not limited to, hybridization, RNase protection, chemical cleavage, direct DNA
sequencing or the use
of restriction enzymes, (e.g., restriction fragment length polymorphisms
("RFLP") and Southern
blotting of genomic DNA).
In addition to more conventional gel-electrophoresis and DNA sequencing,
mutations also can be
detected by in situ analysis.
Genetic mutations can be identified by hybridizing a sample and control
nucleic acids, e.g., DNA or
RNA, to high density arrays containing hundreds or thousands of
oligonucleotides probes (Cronin et
al., 1996; Kozal et al., 1996). For example, genetic mutations can be
identified in two-dimensional
arrays containing light-generated DNA probes as described in Cronin et al.,
supra. Briefly, a first
hybridization array of probes can be used to scan through long stretches of
DNA in a sample and
control to identify base changes between the sequences by making linear arrays
of sequential
overlapping probes. This step allows the identification of point mutations.
This step is followed by a
second hybridization array that allows the characterization of specific
mutations by using smaller,
specialized probe arrays complementary to all variants or mutations detected.
Each mutation array is
composed of parallel probe sets, one complementary to the wild-type gene and
the other
complementary to the mutant gene. Specific mutations can also be determined
through direct
sequencing of one or both strands of DNA using dideoxy nucleotide chain
termination chemistry,
electrophoresis through a semi-solid matrix and fluorescent or radioactive
chain length detection
techniques. Further mutation detection techniques may involve differential
susceptibility of the
polymorphic double strand to restriction endonuclease digestion, or altered
electrophoretic gel
mobility of single or double stranded gene fragments containing one
polymorphic form. Other
techniques to detect specific DNA polymorphisms or mutation may involve
evaluation of the
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CA 02548375 2006-06-13
structural characteristics at the site of polymorphism using nuclear magnetic
resonance or x-ray
diffraction techniques.
These genetic tests are useful for prognosing and/or diagnosing colorectal
cancer and often are useful
for determining whether an individual is at an increased or decreased risk of
developing or having
colorectal cancer.
Thus, the invention includes a method for identifying a subject at risk of
colorectal cancer, which
includes detecting in a nucleic acid sample from the subject the presence or
absence of a SNP
associated with colorectal cancer at a polymorphic site in a nucleotide
sequence identified as SEQ ID
NOs:l to 1144.
Results from prognostic tests may be combined with other test results to
diagnose colorectal cancer.
For example, prognostic results may be gathered, a patient sample may be
ordered based on a
determined predisposition to colorectal cancer, the patient sample analyzed,
and the results of the
analysis may be utilized to diagnose colorectal cancer. Also colorectal cancer
diagnostic methods can
be developed from studies used to generate prognostic/diagnostic methods in
which populations are
stratified into subpopulations having different progressions of colorectal
cancer. In another
embodiment, prognostic results may be gathered; a patient's risk factors for
developing colorectal
cancer analyzed (e.g., age, family history); and a patient sample may be
ordered based on a
determined predisposition to colorectal cancer. In an alternative embodiment,
the results from
predisposition analyses may be combined with other test results indicative of
colorectal cancer, which
were previously, concurrently, or subsequently gathered with respect to the
predisposition testing. In
these embodiments, the combination of the prognostic test results with other
test results can be
probative of colorectal cancer, and the combination can be utilized as a
colorectal cancer diagnostic.
Risk of colorectal cancer sometimes is expressed as a probability, such as an
odds ratio, percentage, or
risk factor. The risk is based upon the presence or absence of one or more of
the SNP variants
described herein, and also may be based in part upon phenotypic traits of the
individual being tested.
Methods for calculating risk based upon patient data are well known (Agresti,
2001). Allelotyping and
genotyping analyses may be carried out in populations other than those
exemplified herein to enhance
the predictive power of the prognostic method. These further analyses are
executed in view of the
exemplified procedures described herein, and may be based upon the same
polymorphic variations or
additional polymorphic variations. Risk determinations for colorectal cancer
are useful in a variety of
applications. In one embodiment, colorectal cancer risk determinations are
used by clinicians to direct
appropriate detection, preventative and treatment procedures to subjects who
most require these. In
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another embodiment, colorectal cancer risk determinations are used by health
insurers for preparing
actuarial tables and for calculating insurance premiums.
The nucleic acid sample typically is isolated from a biological sample
obtained from a subject. For
example, nucleic acid can be isolated from blood, saliva, sputum, urine, cell
scrapings, and biopsy
tissue. The nucleic acid sample can be isolated from a biological sample using
standard techniques.
The nucleic acid sample may be isolated from the subject and then directly
utilized in a method for
determining the presence of a polymorphic variant, or alternatively, the
sample may be isolated and
then stored (e.g., frozen) for a period of time before being subjected to
analysis.
The presence or absence of a polymorphic variant is determined using one or
both chromosomal
complements represented in the nucleic acid sample. Determining the presence
or absence of a
polymorphic variant in both chromosomal complements represented in a nucleic
acid sample is useful
for determining the zygosity of an individual for the polymorphic variant
(i.e., whether the individual
is homozygous or heterozygous for the polymorphic variant). Any
oligonucleotide-based diagnostic
may be utilized to determine whether a sample includes the presence or absence
of a polymorphic
variant in a sample. For example, primer extension methods, ligase sequence
determination methods
(e.g., U.S. Pat. Nos. 5,679,524 and 5,952,174, and WO 01/27326), mismatch
sequence determination
methods (e.g., U.S. Pat. Nos. 5,851,770; 5,958,692; 6,110,684; and 6,183,958),
microarray sequence
determination methods, restriction fragment length polymorphism (RFLP), single
strand conformation
polymorphism detection (SSCP) (e.g., U.S. Pat. Nos. 5,891,625 and 6,013,499),
PCR-based assays
(e.g., TAQMANTM PCR System (Applied Biosystems)), and nucleotide sequencing
methods may be
used.
Oligonucleotide extension methods typically involve providing a pair of
oligonucleotide primers in a
polymerase chain reaction (PCR) or in other nucleic acid amplification methods
for the purpose of
amplifying a region from the nucleic acid sample that comprises the
polymorphic variation. One
oligonucleotide primer is complementary to a region 3' of the polymorphism and
the other is
complementary to a region 5' of the polymorphism. A PCR primer pair may be
used in methods
disclosed in U.S. Pat. Nos. 4,683,195; 4,683,202, 4,965,188; 5,656,493;
5,998,143; 6,140,054; WO
01/27327; and WO 01/27329 for example. PCR primer pairs may also be used in
any commercially
available machines that perform PCR, such as any of the GENEAMPTM, systems
available from
Applied Biosystems. Also, those of ordinary skill in the art will be able to
design oligonucleotide
primers based upon the nucleotide sequences set forth in SEQ ID NOs: 1 to
1144.
Also provided is an extension oligonucleotide that hybridizes to the amplified
fragment adjacent to the
polymorphic variation. An adjacent fragmen refers to the 3' end of the
extension oligonucleotide being
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often 1 nucleotide from the 5' end of the polymorphic site, and sometimes 2,
3, 4, 5, 6, 7, 8, 9, or 10
nucleotides from the 5' end of the polymorphic site, in the nucleic acid when
the extension
oligonucleotide is hybridized to the nucleic acid. The extension
oligonucleotide then is extended by
one or more nucleotides, and the number and/or type of nucleotides that are
added to the extension
oligonucleotide determine whether the polymorphic variant is present.
Oligonucleotide extension
methods are disclosed, for example, in U.S. Pat. Nos. 4,656,127; 4,851,331;
5,679,524; 5,834,189;
5,876,934; 5,908,755; 5,912,118; 5,976,802; 5,981,186; 6,004,744; 6,013,431;
6,017,702; 6,046,005;
6,087,095; 6,210,891; and WO 0 1/20039. Oligonucleotide extension methods
using mass
spectrometry are described, for example, in U.S. Pat. Nos. 5,547,835;
5,605,798; 5,691,141;
5,849,542; 5,869,242; 5,928,906; 6,043,031; and 6,194,144. Multiple extension
oligonucleotides may
be utilized in one reaction, which is referred to as multiplexing.
A microarray can be utilized for determining whether a SNP is present or
absent in a nucleic acid
sample. A microarray may include any oligonucleotides described herein, and
methods for making
and using oligonucleotide microarrays suitable for diagnostic use are
disclosed in U.S. Pat. Nos.
5,492,806; 5,525,464; 5,589,330; 5,695,940; 5,849,483; 6,018,041; 6,045,996;
6,136,541; 6,142,681;
6,156,501; 6,197,506; 6,223,127; 6,225,625; 6,229,911; 6,239,273; WO 00/52625;
WO 01/25485; and
WO 01/29259. The microarray typically comprises a solid support and the
oligonucleotides may be
linked to this solid support by covalent bonds or by non-covalent
interactions. The oligonucleotides
may also be linked to the solid support directly or by a spacer molecule. A
microarray may comprise
one or more oligonucleotides complementary to a SNP set forth in the tables.
A kit also may be utilized for determining whether a polymorphic variant is
present or absent in a
nucleic acid sample. A kit can include one or more pairs of oligonucleotide
primers useful for
amplifying a fragment of a nucleotide sequence of interest, where the fragment
includes a
polymorphic site. The kit sometimes comprises a polymerizing agent, for
example, a thermostable
nucleic acid polymerase such as one disclosed in U.S. Pat. Nos. 4,889,818 or
6,077,664. Also, the kit
often comprises an elongation oligonucleotide that hybridizes to the
nucleotide sequence in a nucleic
acid sample adjacent to the polymorphic site. Where the kit includes an
elongation oligonucleotide, it
can also include chain elongating nucleotides, such as dATP, dTTP, dGTP, dCTP,
and dITP,
including analogs of dATP, dTTP, dGTP, dCTP and dITP, provided that such
analogs are substrates
for a thermostable nucleic acid polymerase and can be incorporated into a
nucleic acid chain
elongated from the extension oligonucleotide. Along with chain elongating
nucleotides would be one
or more chain terminating nucleotides such as ddATP, ddTTP, ddGTP, ddCTP. The
kit can include
one or more oligonucleotide primer pairs, a polymerizing agent, chain
elongating nucleotides, at least
one elongation oligonucleotide, and one or more chain terminating nucleotides.
Kits optionally
include buffers, vials, microtiter plates, and instructions for use.
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An individual identified as being susceptible to colorectal cancer may be
heterozygous or
homozygous with respect to the allele associated with an increased risk of
colorectal cancer, as
indicated in the tables. A subject homozygous for an allele associated with an
increased risk of
colorectal cancer is at a comparatively high risk of colorectal cancer as far
as that SNP is concerned
whether or not the allelic effect has been determined to be dominant or
recessive. A subject who is
heterozygous for an allele associated with an increased risk of colorectal
cancer, in which the allelic
effect is recessive would likely be at a comparatively reduced risk of
colorectal cancer predicted by
that SNP.
Individuals carrying mutations in one or more SNP of the present invention may
be detected at the
protein level by a variety of techniques. Cells suitable for diagnosis may be
obtained from a patient's
blood, urine, saliva, tissue biopsy and autopsy material.
Also featured are methods for determining risk of colorectal cancer and/or
identifying a subject at risk
of colorectal cancer by contacting a polypeptide or protein encoded by a
nucleotide sequence from a
subject with an antibody that specifically binds to an epitope associated with
an altered, usually
increased risk of colorectal cancer in the polypeptide.
Isolated Nucleic Acids
Oligonucleotides can be linked to a second moiety, which can be another
nucleic acid molecule to
provide, for example, a tail sequence (e.g., a polyadenosine tail), an adapter
sequence (e.g., phage
M13 universal tail sequence), etc. Alternatively, the moiety might be one that
facilitates linkage to a
solid support or a detectable label, e.g., a radioactive label, a fluorescent
label, a chemiluminescent
label, a paramagnetic label, etc.
Nucleic acid sequences shown in the tables can be used for diagnostic purposes
for detection and
control of polypeptide expression. Also, oligonucleotide sequences such as
antisense RNA, small-
interfering RNA (siRNA) and DNA molecules and ribozymes that function to
inhibit translation of a
polypeptide are part of this invention.
Antisense RNA and DNA molecules, siRNA and ribozymes can be prepared by known
methods.
These include techniques for chemically synthesizing oligodeoxyribonucleotides
such as solid phase
phosphoramidite chemical synthesis. Alternatively, RNA molecules may be
generated by in vitro and
in vivo transcription of DNA sequences encoding the antisense RNA molecule.
Such DNA sequences
can be incorporated into vectors which incorporate suitable RNA polymerase
promoters such as the
T7 or SP6 polymerase promoters, or antisense cDNA constructs that synthesize
antisense RNA
constitutively or inducibly, depending on the promoter used, can be introduced
stably into cell lines.
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DNA encoding a polypeptide can also be used in the diagnosis of colorectal
cancer, resulting from
aberrant expression of a target gene. For example, the nucleic acid sequence
can be used in
hybridization assays of biopsies or autopsies to diagnose abnormalities of
expression or function (e.g.,
Southern or Northern blot analysis, in situ hybridization assays).
Expression of a polypeptide during embryonic development can also be
determined using nucleic acid
encoding the polypeptide, particularly production of a functionally impaired
polypeptide that is the
cause of colorectal cancer. In situ hybridizations using a polypeptide as a
probe can be employed to
predict problems related to colorectal cancer. Administration of human active
polypeptide,
recombinantly produced can be used to treat disease states related to
functionally impaired
polypeptide. Alternatively, gene therapy approaches may be employed to remedy
deficiencies of
functional polypeptide or to replace or compete with a dysfunctional
polypeptide.
Included as part of this invention are nucleic acid vectors, often expression
vectors, which contain a
nucleotide sequence set forth in the tables. A vector is a nucleic acid
molecule capable of transporting
another nucleic acid to which it has been linked and can include a plasmid,
cosmid, or viral vector.
The vector can be capable of autonomous replication or it can integrate into a
host DNA. Viral vectors
may include replication defective retroviruses, adenoviruses and adeno-
associated viruses for
example.
A vector can include a nucleotide sequence from the tables in a form suitable
for expression of an
encoded protein or nucleic acid in a host cell. The recombinant expression
vector generally includes
one or more regulatory sequences operatively linked to the nucleic acid
sequence to be expressed. A
regulatory sequence includes promoters, enhancers and other expression control
elements (e.g.,
polyadenylation signals). Regulatory sequences include those that direct
constitutive expression of a
nucleotide sequence, as well as tissue-specific regulatory and/or inducible
sequences. The design of
the expression vector can depend on such factors as the choice of the host
cell to be transformed, the
level of expression of polypeptide desired, etc. Expression vectors can be
introduced into host cells to
produce the desired polypeptides, including fusion polypeptides.
Recombinant expression vectors can be designed for expression of polypeptides
in prokaryotic or
eukaryotic cells. For example, the polypeptides can be expressed in E. coli,
insect cells (e.g., using
baculovirus expression vectors), yeast cells, or mammalian cells. Suitable
host cells are discussed
further by Goeddel (Goeddel, 1990).A recombinant expression vector can also be
transcribed and
translated in vitro, for example using T7 promoter regulatory sequences and T7
polymerase.
Expression of polypeptides in prokaryotes can be carried out in E. coli with
vectors containing
constitutive or inducible promoters directing the expression of either fusion
or non-fusion
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polypeptides. Fusion vectors add a number of amino acids to a polypeptide.
Such fusion vectors
typically serve to increase expression of recombinant polypeptide, to increase
the solubility of the
recombinant polypeptide and/or to aid in the purification of the recombinant
polypeptide by acting as
a ligand during purification. Often, a proteolytic cleavage site is introduced
at the junction of the
fusion moiety and the recombinant polypeptide to enable separation of the
recombinant polypeptide
from the fusion moiety after purification of the fusion polypeptide. Such
enzymes, and their cognate
recognition sequences, include Factor Xa, thrombin and enterokinase. Typical
fusion expression
vectors include pGEX (Pharmacia Biotech Inc; (Smith & Johnson, 1988)), pMAL
(New England
Biolabs, Beverly, Mass.) and pRIT5 (Pharmacia, Piscataway, N.J.) which fuse
glutathione S-
transferase (GST), maltose E binding polypeptide, or polypeptide A,
respectively, to the target
recombinant polypeptide.
Purified fusion polypeptides can be used in screening assays and to generate
antibodies specific for
polypeptides. In a therapeutic embodiment, fusion polypeptide expressed in a
retroviral expression
vector can be used to infect bone marrow cells that are subsequently
transplanted into irradiated
recipients. The pathology of the subject recipient is then examined after
sufficient. time has passed.
Expressing a polypeptide in host bacteria with an impaired capacity to
proteolytically cleave the
recombinant polypeptide can be used to maximize recombinant polypeptide
expression (Gottesman,
1990). The nucleotide sequence of the nucleic acid to be inserted into an
expression vector can be
changed so that the individual codons for each amino acid are those
preferentially utilized in E. coli
(Wada et al., 1992).
When used in mammalian cells, the expression vector's control functions are
often provided by viral
regulatory elements. For example, commonly used promoters are derived from
polyoma, Adenovirus
2, cytomegalovirus and Simian Virus 40. Recombinant mammalian expression
vectors can be capable
of directing expression of the nucleic acid in a particular cell type (e.g.,
tissue-specific regulatory
elements are used to express the nucleic acid). Examples of suitable tissue-
specific promoters include
an albumin promoter (Pinkert et al., 1987), lymphoid-specific promoters
(Calame and Eaton, 1988)
(Winoto and Baltimore, 1989), promoters of immunoglobulins (Banerji et al.,
1983; Queen and
Baltimore, 1983), neuron-specific promoters (Byrne and Ruddle, 1989), pancreas-
specific promoters
(Edlund et al., 1985), and mammary gland-specific promoters (e.g., milk whey
promoter; U.S. Pat.
No. 4,873,316 and European Application Publication No. 264,166).
Developmentally-regulated
promoters are sometimes utilized, for example, the murine hox promoters
(Kessel and Gruss, 1990)
and the .alpha.-fetopolypeptide promoter (Camper and Tilghman, 1989).
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A nucleic acid from one of the tables might be cloned into an expression
vector in an antisense
orientation. Regulatory sequences (e.g., viral promoters and/or enhancers)
operatively linked to a
nucleic acid cloned in the antisense orientation can be chosen for directing
constitutive, tissue specific
or cell type specific expression of antisense RNA in a variety of cell types.
Antisense expression
vectors can be in the form of a recombinant plasmid, phagemid or attenuated
virus.
The invention includes host cells having a nucleotide sequence from the tables
within a recombinant
expression vector or a fragment of such a sequence which facilitate homologous
recombination into a
specific site of the host cell genome. Terms such as host cell and recombinant
host cell refer not only
to the particular subject cell but also to the progeny of a cell. Because
certain modifications may occur
in succeeding generations due to either mutation or environmental influences,
such progeny may not,
in fact, be identical to the parent cell. A host cell can be any prokaryotic
or eukaryotic cell. For
example, a polypeptide can be expressed in bacterial cells such as E. coli,
insect cells, yeast or
mammalian cells (such as Chinese hamster ovary cells (CHO) or COS cells).
Vectors can be introduced into host cells via conventional transformation or
transfection techniques.
The terms transformation and transfection refer to a variety of techniques
known for introducing
foreign nucleic acid (e.g., DNA) into a host cell, including calcium phosphate
or calcium chloride co-
precipitation, transduction/infection, DEAE-dextran-mediated transfection,
lipofection, or
electroporation.
A host cell can be used to produce a polypeptide. Accordingly, methods for
producing a polypeptide
using the host cells are included as part of this invention. Sucha a method
can include culturing host
cells into which a recombinant expression vector encoding a polypeptide has
been introduced in a
suitable medium such that the polypeptide is produced. The method can further
include isolating the
polypeptide from the medium or the host cell.
The invention also includes cells or purified preparations of cells which
include a transgene from the
tables, or which otherwise misexpress a polypeptide. Cell preparations can
consist of human or non-
human cells, e.g., rodent cells, e.g., mouse or rat cells, rabbit cells, or
pig cells. The transgene can be
misexpressed, e.g., overexpressed or underexpressed. In other embodiments, the
cell or cells include a
gene which misexpress an endogenous polypeptide (e.g., expression of a gene is
disrupted, also
known as a knockout). Such cells can serve as a model for studying disorders
which are related to
mutated or mis-expressed alleles or for use in drug screening. Also provided
are human cells (e.g.,
hematopoietic stem cells) transformed with a nucleic acid from the tables.
The invention includes cells or a purified preparation thereof (e.g., human
cells) in which an
endogenous nucleic acid from the tables is under the control of a regulatory
sequence that does not
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normally control the expression of the endogenous gene corresponding to the
sequence. The
expression characteristics of an endogenous gene within a cell (e.g., a cell
line or microorganism) can
be modified by inserting a heterologous DNA regulatory element into the genome
of the cell such that
the inserted regulatory element is operably linked to the corresponding
endogenous gene. For
example, an endogenous corresponding gene (e.g., a gene which is
transcriptionally silent, not
normally expressed, or expressed only at very low levels) may be activated by
inserting a regulatory
element which is capable of promoting the expression of a normally expressed
gene product in that
cell. Techniques such as targeted homologous recombinations, can be used to
insert the heterologous
DNA as described in, e.g., Chappel, U.S. Pat. No. 5,272,071; WO 91/06667,
published on May 16,
1991.
Non-human transgenic animals that express a heterologous polypeptide (e.g.,
expressed from a nucleic
acid from the tables) can be generated. Such animals are useful for studying
the function and/or
activity of a polypeptide and for identifying and/or evaluating modulators of
the activity of the nucleic
acids and encoded polypeptides. A transgenic animal is a non-human animal such
as a mammal (e.g.,
a non-human primate such as chimpanzee, baboon, or macaque; an ungulate such
as an equine,
bovine, or caprine; or a rodent such as a rat, a mouse, or an Israeli sand
rat), a bird (e.g., a chicken or a
turkey), an amphibian (e.g., a frog, salamander, or newt), or an insect (e.g.,
Drosophila melanogaster),
in which one or more of the cells of the animal includes a transgene. A
transgene is exogenous DNA
or a rearrangement (e.g., a deletion of endogenous chromosomal DNA) that is
often integrated into or
occurs in the genome of cells in a transgenic animal. A transgene can direct
expression of an encoded
gene product in one or more cell types or tissues of the transgenic animal.
Thus, a transgenic animal
can be one in which an endogenous nucleic acid homologous to a nucleic acid
from the tables has
been altered by homologous recombination between the endogenous gene and an
exogenous DNA
molecule introduced into a cell of the animal (e.g., an embryonic cell of the
animal) prior to
development of the animal.
Intronic sequences and polyadenylation signals can also be included in the
transgene to increase
expression efficiency of the transgene. One or more tissue-specific regulatory
sequences can be
operably linked to a nucleotide sequence from the tables to direct expression
of an encoded
polypeptide to particular cells. A transgenic founder animal can be identified
based upon the presence
of the nucleotide sequence in its genome and/or expression of encoded mRNA in
tissues or cells of the
animals. A transgenic founder animal can then be used to breed additional
animals carrying the
transgene. Moreover, transgenic animals carrying a nucleotide sequence can
further be bred to other
transgenic animals carrying other transgenes.
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Polypeptides can be expressed in transgenic animals or plants by introducing a
nucleic acid encoding
the polypeptide into the genome of an animal. In certain embodiments the
nucleic acid is placed under
the control of a tissue specific promoter, e.g., a milk or egg specific
promoter, and recovered from the
milk or eggs produced by the animal. Also included is a population of cells
from a transgenic animal.
Isolated polypeptides encoded by a nucleotide sequence from the tables can be
synthesized. Isolated
polypeptides include both the full-length polypeptide and the mature
polypeptide (i.e., the polypeptide
minus the signal sequence or propeptide domain). An isolated, or purified,
polypeptide or protein is
substantially free of cellular material or other contaminating proteins from
the cell or tissue source
from which the protein is derived, or is substantially free from chemical
precursors or other chemicals
when chemically synthesized. Substantially free means a preparation of a
polypeptide having less than
about 5% (by dry weight) of contaminating protein, or of chemical precursors
or non-target chemicals.
When the desired polypeptide is recombinantly produced, it is typically
substantially free of culture
medium, specifically, where culture medium represents less than about 10% of
the polypeptide
preparation.
Also, polypeptides may exist as chimeric or fusion polypeptides. As used
herein, a "target chimeric
polypeptide" or "target fusion polypeptide" includes a target polypeptide
linked to a different
polypeptide. The target polypeptide in the fusion polypeptide can correspond
to an entire or nearly
entire polypeptide as it exists in nature or a fragment thereof. The other
polypeptide can be fused to
the N-terminus or C-terminus of the target polypeptide.
Fusion polypeptides can include a moiety having high affinity for a ligand.
For example, the fusion
polypeptide can be a GST-target fusion polypeptide in which the target
sequences are fused to the C-
terminus of the GST sequences, or a polyhistidine-target fusion polypeptide in
which the target
polypeptide is fused at the N- or C-terminus to a string of histidine
residues. Such fusion polypeptides
can facilitate purification of recombinant target polypeptide. Expression
vectors are commercially
available that already encode a fusion moiety (e.g., a GST polypeptide), and a
nucleotide sequence
from the tables, or a substantially identical nucleotide sequence thereof, can
be cloned into an
expression vector such that the fusion moiety is linked in-frame to the target
polypeptide. Further, the
fusion polypeptide can be a target polypeptide containing a heterologous
signal sequence at its N-
terminus. In certain host cells (e.g., mammalian host cells), expression,
secretion, cellular
internalization, and cellular localization of a target polypeptide can be
increased through use of a
heterologous signal sequence. Fusion polypeptides can also include all or a
part of a serum
polypeptide (e.g., an IgG constant region or human serum albumin).
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Target polypeptides can be incorporated into pharmaceutical compositions and
administered to a
subject in vivo. Administration of these polypeptides can be used to affect
the bioavailability of a
substrate of the polypeptide and may effectively increase polypeptide
biological activity in a cell.
Target fusion polypeptides may be useful therapeutically for the treatment of
disorders caused by, for
example, (i) aberrant modification or mutation of a gene encoding a
polypeptide; (ii) mis-regulation of
the gene encoding the polypeptide; and (iii) aberrant post-translational
modification of a polypeptide.
Also, target polypeptides can be used as immunogens to produce anti-target
antibodies in a subject, to
purify the polypeptide ligands or binding partners, and in screening assays to
identify molecules
which inhibit or enhance the interaction of a polypeptide with a substrate.
Polypeptides can be differentially modified during or after translation, e.g.,
by glycosylation,
acetylation, phosphorylation, amidation, derivatization by known
protecting/blocking groups,
proteolytic cleavage, linkage to an antibody molecule or other cellular
ligand, etc. Any known
modification including specific chemical cleavage by cyanogen bromide,
trypsin, chymotrypsin,
papain, V8 protease, NaBH4; acetylation, formylation, oxidation, reduction;
metabolic synthesis in the
presence of tunicamycin; etc. may be used. Additional post-translational
modifications include, for
example, N-linked or 0-linked carbohydrate chains, processing of N-terminal or
C-terminal ends),
attachment of chemical moieties to the amino acid backbone, chemical
modifications of N-linked or
0-linked carbohydrate chains, and addition or deletion of an N-terminal
methionine residue as a result
of prokaryotic host cell expression. The polypeptide fragments may also be
modified with a detectable
label, such as an enzymatic, fluorescent, isotopic or affinity label to allow
for detection and isolation
of the polypeptide.
Chemically modified derivatives of polypeptides that can provide additional
advantages such as
increased solubility, stability and circulating time of the polypeptide, or
decreased immunogenicity
(see e.g., U.S. Pat. No. 4,179,337) are also part of this invention. The
chemical moieties for
derivitization may be selected from water soluble polymers such as
polyethylene glycol, ethylene
glycol/propylene glycol copolymers, carboxymethylcellulose, dextran, polyvinyl
alcohol and the like.
The polypeptides may be modified at random positions within the molecule, or
at predetermined
positions within the molecule and may include one, two, three or more attached
chemical moieties.
The polymer may be of any molecular weight, and may be branched or unbranched.
For polyethylene
glycol, the molecular weight often is between about 1 kDa and about 100 kDa
for ease in handling and
manufacturing. Other sizes may be used, depending on the desired therapeutic
profile (e.g., the
duration of sustained release desired, the effects, if any on biological
activity, the ease in handling, the
degree or lack of antigenicity and other known effects of the polyethylene
glycol to a therapeutic
protein or analog).
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The polymers can be attached to the polypeptide with consideration of effects
on functional or
antigenic domains of the polypeptide. There are a number of attachment methods
available to those
skilled in the art (e.g., EP 0 401 384 (coupling PEG to G-CSF) and Malik et
al. (Malik et al., 1992)
For example, polyethylene glycol may be covalently bound through amino acid
residues via a reactive
group, such as a free amino or carboxyl group. Reactive groups are those to
which an activated
polyethylene glycol molecule may be bound. The amino acid residues having a
free amino group may
include lysine residues and the N-terminal amino acid residues; those having a
free carboxyl group
may include aspartic acid residues, glutamic acid residues and the C-terminal
amino acid residue.
Sulfhydryl groups may also be used as a reactive group for attaching the
polyethylene glycol
molecules. For therapeutic purposes, the attachment sometimes is at an amino
group, such as
attachment at the N-terminus or lysine group.
Proteins can be chemically modified at the N-terminus. Using polyethylene
glycol, for example, one
may select from a variety of polyethylene glycol molecules (by molecular
weight, branching, and the
like), the proportion of polyethylene glycol molecules to protein
(polypeptide) molecules in the
reaction mix, the type of pegylation reaction to be performed, and the method
of obtaining the selected
N-terminally pegylated protein. The method of obtaining the N-terminally
pegylated preparation (i.e.,
separating this moiety from other monopegylated moieties if necessary) may be
by purification of the
N-terminally pegylated material from a population of pegylated protein
molecules. Selective proteins
chemically modified at the N-terminus may be accomplished by reductive
alkylation, which exploits
differential reactivity of different types of primary amino groups (lysine
versus the N-terminal)
available for derivatization in a particular protein. Under the appropriate
reaction conditions,
substantially selective derivatization of the protein at the N-terminus with a
carbonyl group containing
polymer is achievable.
Applications of Prognostic and Diagnostic Results to Pharmacogenomic Methods
Pharmacogenomics is a discipline that involves tailoring a treatment for a
subject according to the
subject's genotype. For example, based upon the outcome of a prognostic test,
a clinician or physician
may target pertinent information and preventative or therapeutic treatments to
a subject who would be
benefited by the information or treatment and avoid directing such information
and treatments to a
subject who would not be benefited (e.g., the treatment has no therapeutic
effect and/or the subject
experiences adverse side effects). As therapeutic approaches for colorectal
cancer continue to evolve
and improve, the goal of treatments for colorectal cancer related disorders is
to intervene even before
clinical signs manifest themselves. Thus, genetic markers associated with
susceptibility to colorectal
cancer prove useful for early diagnosis, prevention and treatment of
colorectal cancer.
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The following is an example of a pharmacogenomic embodiment. A particular
treatment regimen can
exert a differential effect depending upon the subject's genotype. Where a
candidate therapeutic
exhibits a significant beneficial interaction with a prevalent allele and a
comparatively weak
interaction with an uncommon allele (e.g., an order of magnitude or greater
difference in the
interaction), such a therapeutic typically would not be administered to a
subject genotyped as being
homozygous for the uncommon allele, and sometimes not administered to a
subject genotyped as
being heterozygous for the uncommon allele. In another example, where a
candidate therapeutic is not
significantly toxic when administered to subjects who are homozygous for a
prevalent allele but is
comparatively toxic when administered to subjects heterozygous or homozygous
for an uncommon
allele, the candidate therapeutic is not typically administered to subjects
who are genotyped as being
heterozygous or homozygous with respect to the uncommon allele.
Methods of the invention are applicable to pharmacogenomic methods for
detecting, preventing,
alleviating and/or treating colorectal cancer. For example, a nucleic acid
sample fi=om an individual
may be subjected to a genetic test. Where one or more SNPs associated with
increased risk of
colorectal cancer are identified in a subject, information for detecting,
preventing or treating colorectal
cancer and/or one or more colorectal cancer detection, prevention and/or
treatment regimens then may
be directed to and/or prescribed to that subject.
In certain embodiments, a detection, preventative and/or treatment regimen is
specifically prescribed
and/or administered to individuals who will most benefit from it based upon
their risk of developing
colorectal cancer assessed by the methods described herein. Methods are thus
provided for identifying
a subject at risk of colorectal cancer and then prescribing a detection,
therapeutic or preventative
regimen to individuals identified as being at increased risk of colorectal
cancer. Thus, certain
embodiments are directed to methods for treating colorectal cancer in a
subject, reducing risk of
colorectal cancer in a subject, or early detection of colorectal cancer in a
subject, which comprise:
detecting the presence or absence of a SNP associated with colorectal cancer
in a nucleotide sequence
set forth in SEQ ID NOs: l to 1144, and prescribing or administering a
colorectal cancer treatment
regimen, preventative regimen and/or detection regimen to a subject from whom
the sample originated
where the presence of one or more SNPs associated with colorectal cancer are
detected in the
nucleotide sequence. In these methods, genetic results may be utilized in
combination with other test
results to diagnose colorectal cancer as described above.
The use of certain colorectal cancer treatments are known in the art, and
include surgery,
chemotherapy and/or radiation therapy. Any of the treatments may be used in
conibination to treat or
prevent colorectal cancer (e.g., surgery followed by radiation therapy or
chemotherapy).
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Pharmacogenomics methods also may be used to analyze and predict a response to
a colorectal cancer
treatment or a drug. For example, if pharmacogenomics analysis indicates a
likelihood that an
individual will respond positively to a colorectal cancer treatment with a
particular drug, the drug may
be administered to the individual. Conversely, if the analysis indicates that
an individual is likely to
respond negatively to treatment with a particular drug, an alternative course
of treatment may be
prescribed. A negative response may be defined as either the absence of an
efficacious response or the
presence of toxic side effects. The response to a therapeutic treatment can be
predicted in a
background study in which subjects in any of the following populations are
genotyped: a population
that responds favorably to a treatment regimen, a population that does not
respond significantly to a
treatment regimen, and a population that responds adversely to a treatment
regiment (e.g., exhibits one
or more side effects). These populations are provided as examples and other
populations and
subpopulations may be analyzed. Based upon the results of these analyses, a
subject is genotyped to
predict whether he or she will respond favorably to a treatment regimen, not
respond significantly to a
treatment regimen, or respond adversely to a treatment regimen.
The methods described herein also are applicable to clinical drug trials. One
or more SNPs indicative
of response to an agent for treating colorectal cancer or to side effects to
an agent for treating
colorectal cancer may be identified. Thereafter, potential participants in
clinical trials of such an agent
may be screened to identify those individuals most likely to respond favorably
to the drug and exclude
those likely to experience side effects. In that way, the effectiveness of
drug treatment may be
measured in individuals who respond positively to the drug, without lowering
the measurement as a
result of the inclusion of individuals who are unlikely to respond positively
in the study and without
risking undesirable safety problems.
Thus, another embodiment is a method of selecting an individual for inclusion
in a clinical trial of a
treatment or drug comprising the steps of: (a) obtaining a nucleic acid sample
from an individual; (b)
determining the identity of a polymorphic variant, e.g., SNP which is
associated with a positive
response to the treatment or the drug, or at least one SNP which is associated
with a negative response
to the treatment or the drug in the nucleic acid sample, and (c) including the
individual in the clinical
trial if the nucleic acid sample contains the SNP associated with a positive
response to the treatment or
the drug or if the nucleic acid sample lacks said SNP associated with a
negative response to the
treatment or the drug. The SNP may be in a sequence selected individually or
in any combination
from those disclosed in the tables. Step (c) can also include administering
the drug or the treatment to
the individual if the nucleic acid sample contains the SNP associated with a
positive response to the
treatment or the drug and the nucleic acid sample lacks the SNP associated
with a negative response to
the treatment or the drug.
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Compositions Comprising Colorectal Cancer-Directed Molecules
The invention includes a composition made up of a colorectal cancer cell and
one or more molecules
specifically directed and targeted to a nucleic acid comprising a nucleotide
sequence shown in the
tables, or a polypeptide encoded thereby. Such directed molecules include, but
are not limited to, a
compound that binds to a nucleic acid or a polypeptide; a RNAi or siRNA
molecule having a strand
complementary to a nucleotide sequence; an antisense nucleic acid
complementary to an RNA
encoded by a DNA sequence; a ribozyme that hybridizes to a nucleotide
sequence; a nucleic acid
aptamer that specifically binds a polypeptide; and an antibody that
specifically binds to a polypeptide
or binds to a nucleic acid. In specific embodiments, the colorectal cancer
directed molecule interacts
with a nucleic acid or polypeptide variant associated with colorectal cancer.
Compounds
Compounds can be obtained using any of numerous approaches in combinatorial
library methods
known in the art, including: biological libraries; peptoid libraries
(libraries of molecules having the
functionalities of peptides, but with a novel, non-peptide backbone which are
resistant to enzymatic
degradation but which nevertheless remain bioactive (Zuckermann et al., 1994).
Biological library
and peptoid library approaches are typically limited to peptide libraries,
while the other approaches
are applicable to peptide, non-peptide oligomer or small molecule libraries of
compounds (Lam,
1997). Examples of methods for synthesizing molecular libraries are described,
for example, in
DeWitt et al. (DeWitt et al., 1993), Erb et al. (Erb et al., 1994), Zuckermann
et al. (Zuckermann et
al., 1994), Cho et al. (Cho et al., 1993) and Gallop et al. (Gallop et al.,
1994).
Libraries of compounds may be presented in solution (Houghten et al., 1992),
or on beads (Lam et
al., 1991), chips (Fodor et al., 1993), bacteria or spores (Ladner, U.S. Pat.
No. 5,223,409), plasmids
(Cull et al., 1992) or on phage (Scott and Smith, 1990; Devlin et al., 1990;
Cwirla et al., 1990; Felici
et al., 1991).
A compound sometimes alters expression and sometimes alters activity of a
target polypeptide and
may be a small molecule. Small molecules include peptides, peptidoniimetics
(e.g., peptoids), amino
acids, amino acid analogs, polynucleotides, polynucleotide analogs,
nucleotides, nucleotide analogs,
organic or inorganic compounds (i.e., including heteroorganic and
organometallic compounds) having
a molecular weight less than about 10,000 grams per mole, organic or inorganic
compounds having a
molecular weight less than about 5,000 grams per mole, organic or inorganic
compounds having a
molecular weight less than about 1,000 grams per mole, organic or inorganic
compounds having a
molecular weight less than about 500 grams per mole, and salts, esters, and
other pharmaceutically
acceptable forms of such compounds.
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An antisense nucleic acid refers to a nucleotide sequence complementary to a
sense nucleic acid
encoding a polypeptide, e.g., complementary to the, coding strand of a double-
stranded cDNA
molecule or complementary to an mRNA sequence. The antisense nucleic acid can
be complementary
to an entire coding strand in a nucleic acid molecule having a sequence of one
of SEQ ID NOs: 1120
to 1144, or to a portion thereof. In another embodiment, the antisense nucleic
acid molecule is
antisense to a noncoding region of the coding strand of a nucleotide sequence,
e.g., 5' and 3'
untranslated regions.
An antisense nucleic acid can be designed such that it is complementary to the
entire coding region of
an mRNA encoded by a nucleotide sequence of interest, and often the antisense
nucleic acid is an
oligonucleotide antisense to only a portion of a coding or noncoding region of
the mRNA. For
example, the antisense oligonucleotide can be complementary to the region
surrounding the
translation start site of the mRNA, e.g., between the -10 and +10 regions of
the target gene nucleotide
(SNP) sequence of interest. An antisense oligonucleotide can be, for example,
about 7, 10, 15, 20, 25,
30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, or more nucleotides in length. The
antisense nucleic acids,
which include the ribozymes described below, can be designed to target a
nucleotide sequence in any
of SEQ ID NOs:1120 to 1144. Uncommon alleles and prevalent alleles can be
targeted, and those
associated with an increased risk of colon cancer are often designed, tested,
and administered to
subjects.
An antisense nucleic acid can be constructed using chemical synthesis and
enzymatic ligation
reactions using standard procedures. For example, an antisense nucleic acid
molecule can be
chemically synthesized using naturally occurring nucleotides or variously
modified nucleotides
designed to increase the biological stability of the molecules or to increase
the physical stability of the
duplex formed between the antisense and sense nucleic acids, e.g.,
phosphorothioate derivatives and
acridine substituted nucleotides can be used. Antisense nucleic acid also can
be produced biologically
using an expression vector into which a nucleic acid has been subcloned in an
antisense orientation
(i.e., RNA transcribed from the inserted nucleic acid will be of an antisense
orientation to a target
nucleic acid of interest.
When utilized as therapeutics, antisense nucleic acids typically are
administered to a subject (e.g., by
direct injection at a tissue site) or generated in situ such that they
hybridize with or bind to cellular
mRNA and/or genomic DNA encoding a polypeptide and thereby inhibit expression
of the
polypeptide, for example, by inhibiting transcription and/or translation.
Alternatively, antisense
nucleic acid molecules can be modified to target selected cells and then are
administered systemically.
For systemic administration, antisense molecules can be modified such that
they specifically bind to
receptors or antigens expressed on a selected cell surface, for example, by
linking antisense nucleic
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acid molecules to peptides or antibodies which bind to cell surface receptors
or antigens. Antisense
nucleic acid molecules can also be delivered to cells using vectors.
Sufficient intracellular
concentrations of antisense molecules are achieved by incorporating a strong
promoter, such as a pol
II or pol III promoter, in the vector construct.
Antisense nucleic acid molecules sometimes are anomeric nucleic acid molecules
(Gautier et al.,
1987). Antisense nucleic acid molecules can also comprise a 2'-o-
methylribonucleotide (Inoue et al.,
1987a) or a chimeric RNA-DNA analogue (Inoue et al., 1987b). Antisense nucleic
acids sometimes
are composed of DNA or peptide nucleic acid (PNA).
In another embodiment, an antisense nucleic acid is a ribozyme. A ribozyme
having specificity for a
target nucleotide sequence can include one or more sequences complementary to
such a nucleotide
sequence, and a sequence having a known catalytic region responsible for mRNA
cleavage (see e.g.,
U.S. Pat. No. 5,093,246 or Haselhoff and Gerlach (Haseloff and Gerlach, 1988).
.For example, a
derivative of a Tetrahymena L- 19 IVS RNA is sometimes utilized in which the
nucleotide sequence of
the active site is complementary to the nucleotide sequence to be cleaved in a
n1RNA (see e.g., Cech
et al., U.S. Pat. No. 4,987,071; and Cech et al., U.S. Pat. No. 5,116,742).
Also, target mRNA
sequences can be used to select a catalytic RNA having a specific ribonuclease
activity from a pool of
RNA molecules (Bartel and Szostak, 1993).
Colorectal cancer directed molecules include in certain embodiments nucleic
acids that can form triple
helix structures with a target nucleotide sequence, especially one that
includes a regulatory region that
controls expression of a polypeptide. Gene expression can be inhibited by
targeting nucleotide
sequences complementary to the regulatory region of a target nucleotide
sequence (e.g., promoter
and/or enhancers) to form triple helical structures that prevent transcription
of a gene in target cells
(Helene, 1991; Helene et al., 1992; Maher, III, 1992). Potential sequences
that can be targeted for
triple helix formation can be increased by creating a switchback nucleic acid
molecule. Switchback
molecules are synthesized in an alternating 5'-3',3'-5' manner, such that they
base pair with first one
strand of a duplex and then the other, eliminating the necessity for a
sizeable stretch of either purines
or pyrimidines to be present on one strand of a duplex.
Colorectal cancer directed molecules include RNAi and siRNA nucleic acids.
Gene expression may be
inhibited by the introduction of double-stranded RNA (dsRNA), which induces
potent and specific
gene silencing, a phenomenon called RNA interference or RNAi. See, e.g., Fire
et al., U.S. Pat. No.
6,506,559; Tuschl et al., PCT International Publication No. WO 01/75164; Kay
et al., PCT
International Publication No. WO 03/010180A1; or Bosher J M, Labouesse (Bosher
and Labouesse,
2000). This process has been improved by decreasing the size of the double-
stranded RNA to 20-24
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base pairs (to create small-interfering RNAs or siRNAs) that switched off
genes in mammalian cells
without initiating an acute phase response, i.e., a host defense mechanism
that often results in cell
death (Caplen et al., 2001a) (Elbashir et al., 2002). There is increasing
evidence of post-
transcriptional gene silencing by RNA interference (RNAi) for inhibiting
targeted expression in
mammalian cells at the mRNA level, in human cells. There is additional
evidence of effective
methods for inhibiting the proliferation and migration of tumor cells in human
patients, and for
inhibiting metastatic cancer development (see, e.g., U.S. patent application
No. US2001000993183;
Caplen et al. (Caplen et al., 2001b), Abderrahman et al. (Abderrahmani et al.,
2001).
An siRNA or RNAi is a nucleic acid that forms a double stranded RNA and has
the ability to reduce
or inhibit expression of a gene or target gene when the siRNA is delivered to
or expressed in the same
cell as the gene or target gene. siRNA is short double-stranded RNA formed by
the complementary
strands. Complementary portions of the siRNA that hybridize to form the double
stranded molecule
often have substantial or complete identity to the target molecule sequence.
In one embodiment, an
siRNA is a nucleic acid that has substantial or complete identity to a target
gene and forms a double
stranded siRNA.
When designing the siRNA molecules, the targeted region often is selected from
a given DNA
sequence beginning 50 to 100 nucleotides downstream of the start codon. See,
e.g., Elbashir et al.
(Elbashir et al., 2002). Initially, 5' or 3' UTRs and regions nearby the start
codon were avoided
assuming that UTR-binding proteins and/or translation initiation complexes may
interfere with
binding of the siRNP or RISC endonuclease complex. Sometimes regions of the
target 23 nucleotides
in length conforming to the sequence motif AA (N19)TT (N, an nucleotide), and
regions with
approximately 30% to 70% G/C-content (often about 50% G/C-content) often are
selected. If no
suitable sequences are found, the search often is extended using the motif NA
(N2 1). The sequence of
the sense siRNA sometimes corresponds to (N19) TT or N21 (position 3 to 23 of
the 23-nt motif),
respectively. In the latter case, the 3' end of the sense siRNA often is
converted to TT. The rationale
for this sequence conversion is to generate a symmetric duplex with respect to
the sequence
composition of the sense and antisense 3' overhangs. The antisense siRNA is
synthesized as the
complement to position 1 to 21 of the 23-nt motif. Because position 1 of the
23-nt motif is not
recognized sequence-specifically by the antisense siRNA, the 3'-most
nucleotide residue of the
antisense siRNA can be chosen deliberately. However, the penultimate
nucleotide of the antisense
siRNA (complementary to position 2 of the 23-nt motif) often is complementary
to the targeted
sequence. For simplifying chemical synthesis, TT often is utilized. siRNAs
corresponding to the target
motif NAR (N17)YNN, where R is purine (A,G) and Y is pyrimidine (C,U), often
are selected.
Respective 21 nucleotide sense and antisense siRNAs often begin with a purine
nucleotide and can
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also be expressed from pol III expression vectors without a change in
targeting site. Expression of
RNAs from po1 III promoters can be more efficient when the first transcribed
nucleotide is a purine.
The sequence of the siRNA can correspond to the full length target gene, or a
subsequence thereof.
Often, the siRNA is about 15 to about 50 nucleotides in length (e.g., each
complementary sequence of
the double stranded siRNA is 15 to 50 nucleotides in length, and the double
stranded siRNA is about
to 50 base pairs in length, sometimes about 20 to 30 nucleotides in length or
about 20 to 25
nucleotides in length, e.g., 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, or 30
nucleotides in length. The
siRNA sometimes is about 21 nucleotides in length. Methods of using siRNA are
known in the art,
and specific siRNA molecules may be purchased from a number of companies
including Dharmacon
10 Research, Inc.
Antisense, ribozyme, RNAi and siRNA nucleic acids can be altered to form
modified nucleic acid
molecules. The nucleic acids can be altered at base moieties, sugar moieties
or phosphate backbone
moieties to improve stability, hybridization, or solubility of the molecule.
For example, the
deoxyribose phosphate backbone of nucleic acid molecules can be modified to
generate peptide
15 nucleic acids (see Hyrup et al., Bioorganic & Medicinal Chemistry 4 (1): 5-
23 (1996)). A peptide
nucleic acid, or PNA, refers to a nucleic acid mimic such as a DNA mimic, in
which the deoxyribose
phosphate backbone is replaced by a pseudopeptide backbone and only the four
natural nucleobases
are retained. The neutral backbone of a PNA can allow for specific
hybridization to DNA and RNA
under conditions of low ionic strength. Synthesis of PNA oligomers can be
performed using standard
solid phase peptide synthesis protocols as described, for example, in Hyrup et
al. (Hyrup and Nielsen,
1996), and Perry-O'Keefe et al. (Abderrahmani et al., 2001).
PNA nucleic acids can be used in prognostic, diagnostic, and therapeutic
applications. For example,
PNAs can be used as antisense or antigene agents for sequence-specific
modulation of gene
expression by, for example, inducing transcription or translation arrest or
inhibiting replication. PNA
nucleic acid molecules can also be used in the analysis of SNPs in a gene,
(e.g., by PNA-directed PCR
clamping); as artificial restriction enzymes when used in combination with
other enzymes, (e.g., S1
nucleases (Hyrup and Nielsen, 1996) or as probes or primers for DNA sequencing
or hybridization
(Hyrup and Nielsen, 1996; Perry-O'Keefe et al., 1996).
In other embodiments, oligonucleotides may include other appended groups such
as peptides (e.g., for
targeting host cell receptors in vivo), or agents facilitating transport
across cell membranes (see e.g.,
Letsinger et al. (Letsinger et al., 1989); Lemaitre et al. (Lemaitre et al.,
1987) and PCT Publication
No. W088/09810) or the blood-brain barrier (see, e.g., PCT Publication No.
W089/10134). In
addition, oligonucleotides can be modified with hybridization-triggered
cleavage agents (van der Krol
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et al., 1988) or intercalating agents (Zon, 1988). To this end, the
oligonucleotide may be conjugated to
another molecule, (e.g., a peptide, hybridization triggered cross-linking
agent, transport agent, or
hybridization-triggered cleavage agent).
Also included as part of this invention are molecular beacon oligonucleotide
primer and probe
molecules having one or more regions complementary to a target nucleotide
sequence, two
complementary regions one having a fluorophore and one a quencher such that
the molecular beacon
is useful for quantifying the presence of the nucleic acid in a sample.
Molecular beacon nucleic acids
are described, for example, in Lizardi et al., U.S. Pat. No. 5,854,033;
Nazarenko et al., U.S. Pat. No.
5,866,336, and Livak et al., U.S. Pat. No. 5,876,930.
Antibodies
An immunogen typically is used to prepare antibodies by immunizing a suitable
subject, (e.g., rabbit,
goat, mouse or other mammal). An appropriate immunogenic preparation can
contain, for example,
recombinantly expressed chemically synthesized polypeptide. The preparation
can further include an
adjuvant, such as Freund's complete or incomplete adjuvant, or a similar
immunostimulatory agent.
Amino acid polymorphisms can be detected using antibodies specific for the
altered epitope by
western analysis after the electrophoresis of denatured proteins. Protein
polymorphism can also be
detected using fluorescently identified antibodies which bind to specific
polymorphic epitopes and
detected in whole cells using fluorescence activated cell sorting techniques
(FACS). Polymorphic
protein sequence may also be determined by NMR spectroscopy or by x-ray
diffraction studies.
Further, determination of polymorphic sites in proteins may be accomplished by
observing differential
cleavage by specific or non specific proteases.
An antibody is an immunoglobulin molecule or immunologically active portion
thereof, i.e., an
antigen-binding portion. Examples of immunologically active portions of
immunoglobulin molecules
include F(ab) and F(ab')2 fragments which can be generated by treating the
antibody with an enzyme
such as pepsin. An antibody can be polyclonal, monoclonal, or recombinant
(e.g., a chimeric or
humanized), fully human, non-human (e.g., murine), or a single chain antibody.
An antibody may
have effector function and can fix complement, and is sometimes coupled to a
toxin or imaging agent.
A full-length polypeptide or antigenic peptide fragment encoded by a target
nucleotide sequence can
be used as an immunogen or can be used to identify antibodies made with other
immunogens, e.g.,
cells, membrane preparations, and the like. An antigenic peptide often
includes at least 8 amino acid
residues of the amino acid sequences encoded by a nucleotide sequence of one
of SEQ ID NOs:1120
to 1144, and encompasses an epitope. Antigenic peptides sometimes include 10
or more amino acids,
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15 or more amino acids, 20 or more amino acids, or 30 or more amino acids.
Hydrophilic and
hydrophobic fragments of polypeptides sometimes are used as immunogens.
Epitopes encompassed by the antigenic peptide are regions located on the
surface of the polypeptide
(e.g., hydrophilic regions) as well as regions with high antigenicity. For
example, an Emini surface
probability analysis of the human polypeptide sequence can be used to indicate
the regions that have a
particularly high probability of being localized to the surface of the
polypeptide and are thus likely to
constitute surface residues useful for targeting antibody production. The
antibody may bind an epitope
on any domain or region on polypeptides for use in the invention.
Also, chimeric, humanized, and completely human antibodies are useful for
applications which
include repeated administration to subjects. Chimeric and humanized monoclonal
antibodies,
comprising both human and non-human portions, can be made using standard
recombinant DNA
techniques. Such chimeric and humanized monoclonal antibodies can be produced
by recombinant
DNA techniques, for example using methods described in Robinson et al.,
Intemational Application
No. PCT/US86/02269; Akira, et al., European Patent Application 184,187;
Taniguchi, M., European
Patent Application 171,496; Morrison et al., European Patent Application
173,494; Neuberger et al.,
PCT International Publication No. WO 86/01533; Cabilly et al., U.S. Pat. No.
4,816,567; Cabilly et
al., European Patent Application 125,023; (Better et al., 1988; Liu et al.,
1987a; Liu et al., 1987b; Sun
et al., 1987; Nishimura et al., 1987) (Wood et al., 1985; Shaw et al., 1988;
Morrison, 1985) and
Winter U.S. Pat. No. 5,225,539, (Verhoeyen et al., 1988; Beidler et al.,
1988).
Completely human antibodies can be particularly desirable for therapeutic
treatment of human
patients. Such antibodies can be produced using transgenic mice that are
incapable of expressing
endogenous immunoglobulin heavy and light chains genes, but which can express
human heavy and
light chain genes. See, for example, Lonberg and Huszar (Lonberg and Huszar,
1995) and U.S. Pat.
Nos. 5,625,126; 5,633,425; 5,569,825; 5,661,016; and 5,545,806. In addition,
companies such as
Abgenix, Inc. (Fremont, Calif.) and Medarex, Inc. (Princeton, N.J.), can be
engaged to provide human
antibodies directed against a selected antigen. Completely human antibodies
that recognize a selected
epitope also can be generated using guided selection. In this approach a
selected non-human
monoclonal antibody (e.g., a murine antibody) is used to guide the selection
of a completely human
antibody recognizing the same epitope. This technology is described for
example by Jespers et al.
(Jespers et al., 1994).
An antibody can be a single chain antibody. A single chain antibody (scFV) can
be engineered (see,
e.g., Colcher et al. (Colcher et al., 1999) and Reiter (Reiter and Pastan,
1996). Single chain antibodies
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can be dimerized or multimerized to generate multivalent antibodies having
specificities for different
epitopes of the same target polypeptide.
Antibodies also may be selected or modified so that they exhibit reduced or no
ability to bind an Fc
receptor. For example, an antibody may be an isotype or subtype, fragment or
other mutant, which
does not support binding to an Fc receptor (e.g., it has a mutagenized or
deleted Fc receptor binding
region).
Also, an antibody (or fragment thereof) may be conjugated to a therapeutic
moiety such as a
cytotoxin, a therapeutic agent or a radioactive metal ion. A cytotoxin or
cytotoxic agent includes any
agent that is detrimental to cells. Examples include taxol, cytochalasin B,
gramicidin D, ethidium
bromide, emetine, mitomycin, etoposide, tenoposide, vincristine, vinblastine,
colchicin, doxorubicin,
daunorubicin, dihydroxy anthracin dione, mitoxantrone, mithramycin,
actinomycin D, I
dehydrotestosterone, glucocorticoids, procaine, tetracaine, lidocaine,
propranolol, and puromycin and
analogs or homologs thereof. Therapeutic agents include antimetabolites (e.g.,
methotrexate, 6-
mercaptopurine, 6-thioguanine, cytarabine, 5-fluorouracil decarbazine),
alkylating agents (e.g.,
mechlorethamine, thiotepa chlorambucil, melphalan, carmustine (BCNU) and
lomustine (CCNU),
cyclophosphamide, busulfan, dibromomannitol, streptozotocin, mitomycin C, and
cis-dichlorodiamine
platinum (II) (DDP) cisplatin), anthracyclines (e.g., daunorubicin (formerly
daunomycin) and
doxorubicin), antibiotics (e.g., dactinomycin (formerly actinomycin),
bleomycin, mithramycin, and
anthramycin (AMC)), and anti-mitotic agents (e.g., vincristine and
vinblastine).
Antibody conjugates can be used for modifying a given biological response. For
example, the drug
moiety may be a protein or polypeptide possessing a desired biological
activity. Such proteins may
include, for example, a toxin such as abrin, ricin A, pseudomonas exotoxin, or
diphtheria toxin; a
polypeptide such as tumor necrosis factor, -y-interferon, ac-interferon, nerve
growth factor, platelet
derived growth factor, tissue plasminogen activator; or, biological response
modifiers such as, for
example, lymphokines, interleukin-1 ("IL-1"), interleukin-2 ("IL-2"),
interleukin-6 ("IL-6"),
granulocyte macrophage colony stimulating factor ("GM-CSF"), granulocyte
colony stimulating
factor ("G-CSF"), or other growth factors. Also, an antibody can be conjugated
to a second antibody
to form an antibody heteroconjugate as described by Segal in U.S. Pat. No.
4,676,980, for example.
An antibody (e.g., monoclonal antibody) can be used to isolate target
polypeptides by standard
techniques, such as affinity chromatography or immunoprecipitation. Moreover,
an antibody can be
used to detect a target polypeptide (e.g., in a cellular lysate or cell
supematant) in order to evaluate the
abundance and pattern of expression of the polypeptide. Antibodies can be used
diagnostically to
monitor polypeptide levels in tissue as part of a clinical testing procedure,
e.g., to determine the
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efficacy ofa given treatment regimen. Detection can be facilitated by coupling
(i.e., physically
linking) the antibody to a detectable substance. Examples of detectable
substances include various
enzymes, prosthetic groups, fluorescent materials, luminescent materials,
bioluminescent materials,
and radioactive materials. Examples of suitable enzymes include horseradish
peroxidase, alkaline
phosphatase, B-galactosidase, or acetylcholinesterase; examples of suitable
prosthetic group
complexes include streptavidin/biotin and avidin/biotin; examples of suitable
fluorescent materials
include umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine,
dichlorotriazinylamine
fluorescein, dansyl chloride or phycoerythrin; an example of a luminescent
material includes luminol;
examples of bioluminescent materials include luciferase, luciferin, and
aequorin, and examples of
suitable radioactive material include1251 131I, 35S or 3H. Also, an antibody
can be utilized as a test
molecule for determining whether it can treat colorectal cancer, and as a
therapeutic for administration
to a subject for treating colorectal cancer.
An antibody can be made by immunizing with a purified antigen, or a fragment
thereof, a membrane
associated antigen, tissues, e.g., crude tissue preparations, whole cells,
preferably living cells, lysed
cells, or cell fractions.
Included as part of this invention are antibodies which bind only a native
polypeptide, only denatured
or otherwise non-native polypeptide, or which bind both, as well as those
having linear or
conformational epitopes. Conformational epitopes sometimes can be identified
by selecting antibodies
that bind to native but not denatured polypeptide. Also featured are
antibodies that specifically bind to
a polypeptide variant associated with colorectal cancer.
Screening Assays
The invention includes methods for identifying a candidate therapeutic for
treating colorectal cancer.
The methods include contacting a test molecule with a target molecule in a
system. A target molecule
is a nucleic acid molecule having a sequence of any of SEQ ID NOs: l to 1144,
or a fragment thereof,
or an encoded polypeptide of SEQ ID NOs:1120 to 1144. The method also includes
determining the
presence or absence of an interaction between the test molecule and the target
molecule, where the
presence of an interaction between the test molecule and the nucleic acid or
polypeptide identifies the
test molecule as a candidate colorectal cancer therapeutic. The interaction
between the test molecule
and the target molecule may be quantified.
Test molecules and candidate therapeutics include compounds, antisense nucleic
acids, siRNA
molecules, ribozymes, polypeptides or proteins encoded by target nucleic
acids, and
immunotherapeutics (e.g., antibodies and HLA-presented polypeptide fragments).
A test molecule or
candidate therapeutic may act as a modulator of target molecule concentration
or target molecule
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function in a system. A modulator may agonize (i.e., up-regulates) or
antagonize (i.e., down-regulates)
a target molecule concentration partially or completely in a system by
affecting such cellular functions
as DNA replication and/or DNA processing (e.g., DNA methylation or DNA
repair), RNA
transcription and/or RNA processing (e.g., removal of intronic sequences
and/or translocation of
spliced mRNA from the nucleus), polypeptide production (e.g., translation of
the polypeptide from
mRNA), and/or polypeptide post-translational modification (e.g.,
glycosylation, phosphorylation, and
proteolysis of pro-polypeptides). A modulator may also agonize or antagonize a
biological function of
a target molecule partially or completely, where the function may include
adopting a certain structural
conformation, interacting with one or more binding partners, ligand binding,
catalysis (e.g.,
phosphorylation, dephosphorylation, hydrolysis, methylation, and
isomerization), and an effect upon a
cellular event (e.g., effecting progression of colorectal cancer).
According to an aspect of this invention a system, i.e., a cell free in vitro
environment and a cell-based
environment such as a collection of cells, a tissue, an organ, or an organism,
is contacted with a test
molecule in a variety of manners, including adding molecules in solution and
allowing them to
interact with one another by diffusion, cell injection, and any administration
routes in an animal. An
interaction refers to an effect of a test molecule on test molecule, where the
effect sometimes is
binding between the test molecule and the target molecule, and sometimes is an
observable change in
cells, tissue, or organism.
There are known methods for detecting the presence or absence of interaction
between a test molecule
and a target molecule. For example, titrametric, acidimetric, radiometric,
NMR, monolayer,
polarographic, spectrophotometric, fluorescent, and ESR assays probative of a
target molecule
interaction may be utilized.
Test molecule/target molecule interactions can be detected and/or quantified
using known assays. For
example, an interaction can be determined by labeling the test molecule and/or
the target molecule,
where the label is covalently or non-covalently attached to the test molecule
or target molecule. The
label is sometimes a radioactive molecule such as 125I1' 3' I, 35S or 3H,
which can be detected by direct
counting of radioemission or by scintillation counting. Also, enzymatic labels
such as horseradish
peroxidase, alkaline phosphatase, or luciferase may be utilized where the
enzymatic label can be
detected by determining conversion of an appropriate substrate to product. In
addition, presence or
absence of an interaction can be determined without labeling. For example, a
microphysiometer (e.g.,
Cytosensor) is an analytical instrument that measures the rate at which a cell
acidifies its environment
using a light-addressable potentiometric sensor (LAPS). Changes in this
acidification rate can be used
as an indication of an interaction between a test molecule and target molecule
(McConnell et al.,
1992).
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In cell-based systems, cells typically include a nucleic acid from SEQ ID NOs:
1 to 1144 or an
encoded polypeptide from SEQ ID NOs: 1120 to 1144, and are often of mammalian
origin, although
the cell can be of any origin. Whole cells, cell homogenates, and cell
fractions (e.g., cell membrane
fractions) can be subjected to analysis. Where interactions between a test
molecule with a target
polypeptide are monitored, soluble and/or membrane bound forms of the
polypeptide may be utilized.
Where membrane-bound forms of the polypeptide are used, it may be desirable to
utilize a
solubilizing agent. Examples of such solubilizing agents include non-ionic
detergents such as n-
octylglucoside, n-dodecylglucoside, n-dodecylmaltoside, octanoyl-N-
methylglucamide, decanoyl-N-
methylglucamide, TritonTMX-100, TritonTM X-114, etc.
An interaction between a test molecule and target molecule also can be
detected by monitoring
fluorescence energy transfer (FET) (see, e.g., Lakowicz et al., U.S. Pat. No.
5,631,169;
Stavrianopoulos et al., U.S. Pat. No. 4,868,103). A fluorophore label on a
first, donor molecule is
selected such that its emitted fluorescent energy will be absorbed by=a
fluorescent label on a second,
acceptor molecule, which in turn is able to fluoresce due to the absorbed
energy. Alternately, the
donor polypeptide molecule may simply utilize the natural fluorescent energy
of tryptophan residues.
Labels are chosen that emit different wavelengths of light, such that the
acceptor inolecule label may
be differentiated from that of the donor. Since the efficiency of energy
transfer between the labels is
related to the distance separating the molecules, the spatial relationship
between the molecules can be
assessed. In a situation in which binding occurs between the molecules, the
fluorescent emission of
the acceptor molecule label in the assay should be maximal. An FET binding
event can be
conveniently measured through standard fluorometric detection means well known
in the art (e.g.,
using a fluorimeter).
In another embodiment, determining the presence or absence of an interaction
between a test molecule
and a target molecule can be effected by monitoring surface plasmon resonance
(Sjolander and
Urbaniczky, 1991; Szabo et al., 1995). Surface plasmon resonance (SPR) or
biomolecular interaction
analysis (BIA) can be utilized to detect biospecific interactions in real
time, without labeling any of
the interactants (e.g., BlAcore). Changes in the mass at the binding surface
(indicative of a binding
event) result in alterations of the refractive index of light near the surface
(the optical phenomenon of
surface plasmon resonance, resulting in a detectable signal which can be used
as an indication of real-
time reactions between biological molecules.
In another embodiment, the target molecule or test molecules are anchored to a
solid phase,
facilitating the detection of target molecule/test molecule complexes and
separation of the complexes
from free, uncomplexed molecules. The target molecule or test molecule is
immobilized to the solid
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support. In one embodiment, the target molecule is anchored to a solid
surface, and the test molecule,
which is not anchored, can be labeled, either directly or indirectly, with
detectable labels.
It may be desirable to immobilize a target molecule, an anti-target molecule
antibody, and/or test
molecules to facilitate separation of target molecule/test molecule complexes
from uncomplexed
forms, as well as to accommodate automation of the assay. The attachment
between a test molecule
and/or target molecule and the solid support may be covalent or non-covalent
(see, e.g., U.S. Pat. No.
6,022,688 for non-covalent attachments). The solid support may be one or more
surfaces of the
system, such as one or more surfaces in each well of a microtiter plate, a
surface of a silicon wafer, a
surface of a bead (Lam et al., 1991) that is optionally linked to another
solid support, or a channel in a
microfluidic device, for example. Types of solid supports, linker molecules
for covalent and non-
covalent attachments to solid supports, and methods for immobilizing nucleic
acids and other
molecules to solid supports are known (see, e.g., U.S. Pat. Nos. 6,261,776;
5,900,481; 6,133,436; and
6,022,688; and WIPO publication WO 01/18234).
In one embodiment, a target molecule may be immobilized to surfaces via biotin
and streptavidin. For
example, a biotinylated polypeptide can be prepared from biotin-NHS (N-
hydroxysuccinimide, e.g.,
biotinylation kit, Pierce Chemicals, Rockford, Ill.), and immobilized in the
wells of streptavidin-
coated 96 well plates (Pierce Chemical). In another embodiment, a target
polypeptide can be prepared
as a fusion polypeptide. For example, glutathione-S-transferase/-polypeptide
fusion can be adsorbed
onto glutathione sepharose beads (Sigma Chemical, St. Louis, Mo.) or
glutathione derivatized
microtiter plates, which are then combined with a test molecule under
conditions conducive to
complex formation (e.g., at physiological conditions for salt and pH).
Following incubation, the beads
or microtiter plate wells are washed to remove any unbound components, or the
matrix is immobilized
in the case of beads, and complex formation is determined directly or
indirectly as described above.
Alternatively, the complexes can be dissociated from the matrix, and the level
of target molecule
binding or activity is determined using standard techniques.
In one embodiment, the non-immobilized component is added to the coated
surface containing the
anchored component. After the reaction is complete, unreacted components are
removed (e.g., by
washing) under conditions such that a significant percentage of complexes
formed will remain
immobilized to the solid surface. The detection of complexes anchored on the
solid surface can be
accomplished in a number of manners. Where the previously non-immobilized
component is pre-
labeled, the detection of label immobilized on the surface indicates that
complexes were formed.
Where the previously non-immobilized component is not pre-labeled, an indirect
label can be used to
detect complexes anchored on the surface, e.g., by adding a labeled antibody
specific for the
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immobilized component, where the antibody, in turn, can be directly labeled or
indirectly labeled
with, e.g., a labeled anti-Ig antibody.
In another embodiment, an assay is performed utilizing antibodies that
specifically bind a target
molecule or test molecule but do not interfere with binding of the target
molecule to the test molecule.
Such antibodies can be linked to a solid support, and unbound target molecule
may be immobilized by
antibody conjugation. Methods for detecting such complexes, in addition to
those described above for
the GST-immobilized complexes, include immunodetection of complexes using
antibodies reactive
with the target molecule, as well as enzyme-linked assays which rely on
detecting an enzymatic
activity associated with the target molecule.
Cell free assays also can be conducted in a liquid phase. In such an assay,
reaction products are
separated from unreacted components, by known techniques, including:
differential centrifugation
(Rivas and Minton, 1993); electrophoresis (1999) and immunoprecipitation
(1999). Media and
chromatographic techniques are known (Heegaard, 1998; Hage and Tweed, 1997).
Further,
fluorescence energy transfer may also be conveniently utilized to detect
binding without further
purification of the complex from solution.
In another embodiment, modulators of target molecule expression are
identified. For example, a cell
or cell free mixture is contacted with a candidate compound and the expression
of target mRNA or
polypeptide is evaluated relative to the level of expression of target mRNA or
polypeptide in the
absence of the candidate compound. When expression of target mRNA or
polypeptide is greater in the
presence of the candidate compound than in its absence, the candidate compound
is identified as an
agonist of target mRNA or polypeptide expression. Alternatively, when
expression of target mRNA or
polypeptide is less (e.g., less with statistical significance) in the presence
of the candidate compound
than in its absence, the candidate compound is identified as an antagonist or
inhibitor of target mRNA
or polypeptide expression. The level of target mRNA or polypeptide expression
can be determined by
methods described herein.
In another embodiment, binding partners that interact with a target molecule
are detected. The target
molecules can interact with one or more cellular or extracellular
macromolecules, such as
polypeptides in vivo, and these interacting molecules or binding partners.
Binding partners can
agonize or antagonize target molecule biological activity. Also, test
molecules that agonize or
antagonize interactions between target molecules and binding partners can be
useful as therapeutic
molecules as they can up-regulate or down-regulated target molecule activity
in vivo and thereby treat
colorectal cancer.
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Binding partners of target molecules can be identified by known methods. For
example, binding
partners may be identified by lysing cells and analyzing cell lysates by
electrophoretic techniques.
Alternatively, a two-hybrid assay or three-hybrid assay can be utilized
(Zervos et al., 1993; Madura et
al., 1993; Bartel et al., 1993; Iwabuchi et al., 1993): see also, e.g., U.S.
Pat. No. 5,283,317 and Brent
W094/10300. A two-hybrid system is based on the modular nature of most
transcription factors,
which consist of separable DNA-binding and activation domains. The assay often
utilizes two
different DNA constructs. In one construct, a nucleic acid from one of SEQ ID
NOs: 1120 to 1144,
sometimes referred to as the bait, is fused to a gene encoding the DNA binding
domain of a known
transcription factor (e.g., GAL-4). In another construct, a DNA sequence from
a library of DNA
sequences that encodes a potential binding partner, sometimes referred to as
the prey, is fused to a
gene that encodes an activation domain of the known transcription factor.
Sometimes, a target nucleic
acid can be fused to the activation domain. If the bait and the prey molecules
interact in vivo, the
DNA-binding and activation domains of the transcription factor are brought
into close proximity. This
proximity allows transcription of a reporter gene (e.g., lacZ) which is
operably linked to a
transcriptional regulatory site responsive_ to the transcription factor.
Expression of'the reporter gene
can be detected and cell colonies containing the functional transcription
factor can be isolated and
used to identify the potential binding partner.
In an embodiment for identifying test molecules that antagonize or agonize
complex formation
between target molecules and binding partners, a reaction mixture containing
the target molecule and
the binding partner is prepared, under conditions and for a time sufficient to
allow complex formation.
The reaction mixture often is provided in the presence or absence of the test
molecule. The test
molecule can be included initially in the reaction mixture, or can be added at
a time subsequent to the
addition of the target molecule and its binding partner. Control reaction
mixtures are incubated
without the test molecule or with a placebo. Formation of any complexes
between the target molecule
and the binding partner then is detected. Decreased formation of a complex in
the reaction mixture
containing test molecule as compared to in a control reaction mixture
indicates that the molecule
antagonizes target molecule/binding partner complex formation. Alternatively,
increased formation of
a complex in the reaction mixture containing test molecule as compared to in a
control reaction
mixture, indicates that the molecule agonizes target molecule/binding partner
complex formation. In
another embodiment, complex formation of target molecule/binding partner can
be compared to
complex formation of mutant target molecule/binding partner (e.g., amino acid
modifications in a
target polypeptide). Such a comparison can be important in those cases where
it is desirable to identify
test molecules that modulate interactions of mutant but not non-mutated target
gene products.
The assays can be conducted in a heterogeneous or homogeneous format. In
heterogeneous assays, a
target molecule and/or the binding partner are immobilized to a solid phase,
and complexes are
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detected on the solid phase at the end of the reaction. In homogeneous assays,
the entire reaction is
carried out in a liquid phase. In either approach, the order of addition of
reactants can be varied to
obtain different information about the molecules being tested. For example,
test compounds that
agonize target molecule/binding partner interactions can be identified by
conducting the reaction in
the presence of the test molecule in a competition format. Alternatively, test
molecules that agonize
preformed complexes, e.g., molecules with higher binding constants that
displace one of the
components from the complex, can be tested by adding the test compound to the
reaction mixture after
complexes have been formed.
In a heterogeneous assay, the target molecule or the binding partner is
anchored onto a solid surface
(e.g., a microtiter plate), while the non-anchored species is labeled, either
directly or indirectly. The
anchored molecule can be immobilized by non-covalent or covalent attachments.
Alternatively, an
immobilized antibody specific for the molecule to be anchored can be used to
anchor the molecule to
the solid surface. The partner of the immobilized species is exposed to the
coated surface with or
without the test molecule. After the reaction is complete, unreacted
components are removed (e.g., by
washing) such that a significant portion of any complexes formed will remain
immobilized on the
solid surface. Where the non-immobilized species is pre-labeled, the detection
of label immobilized
on the surface is indicative of complex. Where the non-immobilized species is
not pre-labeled, an
indirect label can be used to detect complexes anchored to the surface; e.g.,
by using a labeled
antibody specific for the initially non-immobilized species. Depending upon
the order of addition of
reaction components, test compounds that inhibit complex formation or that
disrupt preformed
complexes can be detected.
The reaction can be conducted in a liquid phase in the presence or absence of
test molecule, where the
reaction products are separated from unreacted components, and the complexes
are detected (e.g.,
using an immobilized antibody specific for one of the binding components to
anchor any complexes
formed in solution, and a labeled antibody specific for the other partner to
detect anchored
complexes). Again, depending upon the order of addition of reactants to the
liquid phase, test
compounds that inhibit complex or that disrupt preformed complexes can be
identified.
In an alternate embodiment, a homogeneous assay can be utilized. For example,
a preformed complex
of the target gene product and the interactive cellular or extracellular
binding partner-product is
prepared. One or both of the target molecule or binding partner is labeled,
and the signal generated by
the label(s) is quenched upon complex formation (e.g., U.S. Pat. No. 4,109,496
that-utilizes this
approach for immunoassays). Addition of a test molecule that competes with and
displaces one of the
species from the preformed complex will result in the generation of a signal
above background. In this
way, test substances that disrupt target molecule/binding partner complexes
can be identified.
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Identification of Candidate Therapeutics
Candidate therapeutics for treating colorectal cancer are identified from a
group of test molecules that
interact with a target molecule. Test molecules are normally ranked according
to the degree with
which they modulate (e.g., agonize or antagonize) a function associated with
the target molecule (e.g.,
DNA replication and/or processing, RNA transcription and/or processing,
polypeptide production
and/or processing, and/or biological function/activity), and then top ranking
modulators are selected.
Also, pharmacogenomic information can determine the rank of a modulator. The
top 10% of ranked
test molecules often are selected for further testing as candidate
therapeutics, and sometimes the top
15%, 20%, or 25% of ranked test molecules are selected for further testing as
candidate therapeutics.
Candidate therapeutics typically are formulated for administration to a
subject.
Therapeutic Formulations
Formulations and pharmaceutical compositions typically include in combination
Nvith a
pharmaceutically acceptable carrier one or more target molecule modulators.
The modulator often is a
test molecule identified as having an interaction with a target molecule by a
screening method. The
modulator may be a compound, an antisense nucleic acid, a ribozyme, an
antibody, or a binding
partner. Also, formulations may include a polypeptide combination with a
pharmaceutically
acceptable carrier.
A pharmaceutically acceptable carrier includes solvents, dispersion media,
coatings, antibacterial and
antifungal agents, isotonic and absorption delaying agents, and the like,
compatible with
pharmaceutical administration. See for example, Remington's Pharmaceutical
Sciences (2005).
Supplementary active compounds can also be incorporated into the compositions.
Pharmaceutical
compositions can be included in a container, pack, or dispenser together with
instructions for
administration.
A pharmaceutical composition typically is formulated to be compatible with its
intended route of
administration. Examples of routes of administration include parenteral, e.g.,
intravenous, intradermal,
subcutaneous, oral (e.g., inhalation), transdermal (topical), transmucosal,
and rectal administrations
Solutions or suspensions used for parenteral, intradermal, or subcutaneous
application can include the
following components: a sterile diluent such as water for injection, saline
solution, fixed oils,
polyethylene glycols, glycerin, propylene glycol or other synthetic solvents;
antibacterial agents such
as benzyl alcohol or methyl parabens; antioxidants such as ascorbic acid or
sodiuin bisulfite; chelating
agents such as ethylenediaminetetraacetic acid; buffers such as acetates,
citrates or phosphates and
agents for the adjustment of tonicity such as sodium chloride or dextrose. pH
can be adjusted with
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acids or bases, such as hydrochloric acid or sodium hydroxide. The parenteral
preparation can be
enclosed in ampoules, disposable syringes or multiple dose vials made of glass
or plastic.
Oral compositions generally include an inert diluent or an edible carrier. For
the purpose of oral
therapeutic administration, the active compound can be incorporated with
excipients and used in the
form of tablets, troches, or capsules, e.g., gelatin capsules. Oral
compositions can also be prepared
using a fluid carrier for use as a mouthwash. Pharmaceutically compatible
binding agents, and/or
adjuvant materials can be included as part of the composition. The tablets,
pills, capsules, troches and
the like can contain any of the following ingredients, or compounds of a
similar nature: a binder such
as microcrystalline cellulose, gum tragacanth or gelatin; an excipient such as
starch or lactose, a
disintegrating agent such as alginic acid, Primogel, or corn starch; a
lubricant such as magnesium
stearate; a glidant such as colloidal silicon dioxide; a sweetening agent such
as sucrose or saccharin;
or a flavoring agent such as peppermint, methyl salicylate, or orange
flavoring.
Pharmaceutical compositions suitable for injectable use include sterile
aqueous solutions (where water
soluble) or dispersions and sterile powders for the extemporaneous preparation
of sterile injectable
solutions or dispersion. For intravenous administration, suitable carriers
include physiological saline,
bacteriostatic water, Cremophor ELTM (BASF, Parsippany, N.J.) or phosphate
buffered saline (PBS).
The composition must be sterile and should be fluid to the extent that easy
syringability exists. It
should be stable under the conditions of manufacture and storage and must be
preserved against the
contaminating action of microorganisms such as bacteria and fungi. The carrier
can be a solvent or
dispersion medium containing, for example, water, ethanol, polyol (for
example, glycerol, propylene
glycol, and liquid polyethylene glycol, and the like), and suitable mixtures
thereof. The proper fluidity
can be maintained, for example, by the use of a coating such as lecithin, by
the maintenance of the
required particle size in the case of dispersion and by the use of
surfactants. Prevention of the action
of microorganisms can be achieved by various antibacterial and antifungal
agents, for example,
parabens, chlorobutanol, phenol, ascorbic acid, thimerosal, and the like. In
many cases, it will be
preferable to include isotonic agents, for example, sugars, polyalcohols such
as mannitol, sorbitol,
sodium chloride in the composition. Prolonged absorption of the injectable
compositions can be
brought about by including in the composition an agent which delays
absorption, for example,
aluminum monostearate and gelatin.
Sterile injectable solutions can be prepared by incorporating the active
compound in the required
amount in an appropriate solvent with one or a combination of ingredients
enumerated above, as
required, followed by filtered sterilization. Generally, dispersions are
prepared by incorporating the
active compound into a sterile vehicle which contains a basic dispersion
medium and the required
other ingredients from those enumerated above. In the case of sterile powders
for the preparation of
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sterile injectable solutions, the methods of preparation often utilized are
vacuum drying and freeze-
drying which yields a powder of the active ingredient plus any additional
desired ingredient from a
previously sterile-filtered solution thereof.
Systemic administration might be by transmucosal or transdermal means. For
transmucosal or
transdermal administration, penetrants appropriate to the barrier to be
permeated are used in the
formulation. Such penetrants are generally known in the art, and include, for
example, for
transmucosal administration, detergents, bile salts, and fusidic acid
derivatives. Transmucosal
administration can be accomplished through the use of nasal sprays or
suppositories. For transdermal
administration, the active compounds are formulated into ointments, salves,
gels, or creams as
generally known in the art. Molecules can also be prepared in the form of
suppositories (e.g., with
conventional suppository bases such as cocoa butter and other glycerides) or
retention enemas for
rectal delivery.
hi one embodiment, active molecules are prepared with carriers that will
protect the compound against
rapid elimination from the body, such as a controlled release formulation,
including implants and
microencapsulated delivery systems. Biodegradable, biocompatible polymers can
be used, such as
ethylene vinyl acetate, polyanhydrides, polyglycolic acid, collagen,
polyorthoesters, and polylactic
acid. Methods for preparation of such formulations will be apparent to those
skilled in the art.
Materials can also be obtained commercially from Alza Corporation and Nova
Pharmaceuticals, Inc.
Liposomal suspensions (including liposomes targeted to infected cells with
monoclonal antibodies to
viral antigens) can also be used as pharmaceutically acceptable carriers.
These can be prepared
according to methods known to those skilled in the art, for example, as
described in U.S. Pat. No.
4,522,811.
It is advantageous to formulate oral or parenteral compositions in dosage unit
form for ease of
administration and uniformity of dosage. Each unit containing a predetermined
quantity of active
compound is calculated to produce the desired therapeutic effect in
association with the required
pharmaceutical carrier.
Toxicity and therapeutic efficacy of such compounds can be determined by
standard pharmaceutical
procedures in cell cultures or experimental animals, e.g., for determining the
LD50 (the dose lethal to
50% of the population) and the ED<sub>50</sub> (the dose therapeutically effective
in 50% of the
population). The dose ratio between toxic and therapeutic effects is the
therapeutic index and it can be
expressed as the ratio LD50/ED50. Molecules which exhibit high therapeutic
indices often are utilized.
While molecules that exhibit toxic side effects may be used, care should be
taken to design a delivery
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system that targets such compounds to the site of affected tissue in order to
minimize potential
damage to uninfected cells and, thereby, reduce side effects.
The data obtained from the cell culture assays and animal studies can be used
in formulating a range
of dosage for use in humans. The dosage of such molecules typically lies
within a range of circulating
concentrations that include the ED50 with little or no toxicity. The dosage
may vary within this range
depending upon the dosage form employed and the route of administration
utilized. For any molecules
used in methods described herein, the therapeutically effective dose can be
estimated initially from
cell culture assays. A dose may be formulated in animal models to achieve a
circulating plasma
concentration range that includes the IC<sub>50</sub> (i.e., the concentration of
the test compound which
achieves a half-maximal inhibition of symptoms) as determined in cell culture.
Such information can
be used to more accurately determine useful doses in humans. Levels in plasma
may be measured, for
example, by high performance liquid chromatography.
As defined herein, a therapeutically effective amount of protein or
polypeptide (i.e., an effective
dosage) ranges from about 0.001 to 30 mg/kg body weight, sometimes about 0.01
to 25 mg/kg body
weight, often about 0.1 to 20 mg/kg body weight, and more often about 1 to 10
mg/kg, 2 to 9 mg/kg, 3
to 8 mg/kg, 4 to 7 mg/kg, or 5 to 6 mg/kg body weight. The protein or
polypeptide can be
administered one time per week for between about 1 to 10 weeks, sometimes
between 2 to 8 weeks,
often between about 3 to 7 weeks, and more often for about 4, 5, or 6 weeks.
The skilled artisan will
appreciate that certain factors may influence the dosage and timing required
to effectively treat a
subject, including but not limited to the severity of the disease or disorder,
previous treatments, the
general health and/or age of the subject, and other diseases present.
Moreover, treatment of a subject
with a therapeutically effective amount of a protein, polypeptide, or antibody
can include a single
treatment or, can include a series of treatments.
For antibodies, a dosage of 0.1 mg/kg of body weight (generally 10 mg/kg to 20
mg/kg) is often
utilized. If the antibody is to act in the brain, a dosage of 50 mg/kg to 100
mg/kg is often appropriate.
Generally, partially human antibodies and fully human antibodies have a longer
half-life within the
human body than other antibodies. Accordingly, lower dosage and less frequent
administration is
often possible. Modifications such as lipidation can be used to stabilize
antibodies and to enhance
uptake and tissue penetration (e.g., into the brain). A method for lipidation
of antibodies is described
by Cruikshank et al. (Cruikshank et al., 1997).
Antibody conjugates can be used for modifying a given biological response, the
drug moiety is not to
be construed as limited to classical chemical therapeutic agents. For example,
the drug moiety may be
a protein or polypeptide possessing a desired biological activity. Such
proteins may include, for
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example, a toxin such as abrin, ricin A, pseudomonas exotoxin, or diphtheria
toxin; a polypeptide such
as tumor necrosis factor, alpha-interferon, beta-interferon, nerve growth
factor, platelet derived
growth factor, tissue plasminogen activator; or, biological response modifiers
such as, for example,
lymphokines, interleukin-1 ("IL-1"), interleukin-2 ("IL-2"), interleukin-6
("IL-6"), granulocyte
macrophage colony stimulating factor ("GM-CSF"), granulocyte colony
stimulating factor ("G-
CSF"), or other growth factors. Alternatively, an antibody can be conjugated
to a second antibody to
form an antibody heteroconjugate as described by Segal in U.S. Pat. No.
4,676,980.
For compounds, exemplary doses include milligram or microgram amounts of the
compound per
kilogram of subject or sample weight, for example, about 1 microgram per
kilogram to about 500
milligrams per kilogram, about 100 micrograms per kilogram to about 5
milligrams per kilogram, or
about 1 microgram per kilogram to about 50 micrograms per kilogram. It is
understood that
appropriate doses of a small molecule depend upon the potency of the small
molecule with respect to
the expression or activity to be modulated. When one or more of these small
molecules is to be
administered to an animal (e.g., a human) in order to modulate expression or
activity of a polypeptide
or nucleic acid described herein, a physician, veterinarian, or researcher
may, for example, prescribe a
relatively low dose at first, subsequently increasing the dose until an
appropriate response is obtained.
In addition, it is understood that the specific dose level for any particular
animal subject will depend
upon a variety of factors including the activity of the specific compound
employed, the age, body
weight, general health, gender, and diet of the subject, the time of
administration, the route of
administration, the rate of excretion, any drug combination, and the degree of
expression or activity to
be modulated.
With regard to nucleic acid formulations, gene therapy vectors can be
delivered to a subject by, for
example, intravenous injection, local administration (see, e.g., U.S. Pat. No.
5,328,470) or by
stereotactic injection (Chen et al., 1994). Pharmaceutical preparations of
gene therapy vectors can
include a gene therapy vector in an acceptable diluent, or can comprise a slow
release matrix in which
the gene delivery vehicle is imbedded. Alternatively, where the complete gene
delivery vector can be
produced intact from recombinant cells (e.g., retroviral vectors) the
pharmaceutical preparation can
include one or more cells which produce the gene delivery system. Examples of
gene delivery vectors
are described herein.
Therapeutic Methods
A therapeutic formulation described above can be administered to a subject in
need of a therapeutic
for treating colorectal cancer. Therapeutic formulations can be administered
by any of the paths
described herein. With regard to both prophylactic and therapeutic methods of
treatment, such
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CA 02548375 2006-06-13
treatments may be specifically tailored or modified, based on knowledge
obtained from
pharmacogenomic analyses described herein.
A treatment is the application or administration of a therapeutic formulation
to a subject, or
application or administration of a therapeutic agent to an isolated tissue or
cell line from a subject with
the purpose to cure, heal, alleviate, relieve, alter, remedy, ameliorate,
improve or affect colorectal
cancer, symptoms of colorectal cancer or a predisposition towards colorectal
cancer. A therapeutic
formulation includes small molecules, peptides, antibodies, ribozymes and
antisense oligonucleotides.
Administration of a therapeutic formulation can occur prior to the
manifestation of symptoms
characteristic of colorectal cancer, such that the cancer is prevented or
delayed in its progression. The
appropriate therapeutic composition can be determined based on screening
assays described herein.
As discussed, successful treatment of colorectal cancer can be brought about
by techniques that serve
to agonize target molecule expression or function, or alternatively,
antagonize target molecule
expression or function. These techniques include administration of modulators
that include, but are
not limited to, small organic or inorganic molecules; antibodies (including,
for example, polyclonal,
monoclonal, humanized, anti-idiotypic, chimeric or single chain antibodies,
and FAb, F(ab')2 and FAb
expression library fragments, scFV molecules, and epitope-binding fragments
thereof); and peptides,
phosphopeptides, or polypeptides.
Further, antisense and ribozyme molecules that inhibit expression of the
target gene can also be used
to reduce the level of target gene expression, thus effectively reducing the
level of target gene activity.
Still further, triple helix molecules can be utilized in reducing the level of
target gene activity.
Antisense, ribozyme and triple helix molecules are discussed above. It is
possible that the use of
antisense, ribozyme, and/or triple helix molecules to reduce or inhibit mutant
gene expression can also
reduce or inhibit the transcription (triple helix) and/or translation
(antisense, ribozyme) of mRNA
produced by normal target gene alleles, such that the concentration of normal
target gene product
present can be lower than is necessary for a normal phenotype. In such cases,
nucleic acid molecules
that encode and express target gene polypeptides exhibiting normal target gene
activity can be
introduced into cells via gene therapy method. Alternatively, in instances in
that the target gene
encodes an extracellular polypeptide, it can be preferable to co-administer
normal target gene
polypeptide into the cell or tissue in order to maintain the requisite level
of cellular or tissue target
gene activity.
Another method by which nucleic acid molecules may be utilized in treating or
preventing colorectal
cancer is use of aptamer molecules specific for target molecules. Aptamers are
nucleic acid molecules
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CA 02548375 2006-06-13
having a tertiary structure which permits them to specifically bind to ligands
(Osborne et al., 1997;
Patel, 1997).
Yet another method of utilizing nucleic acid molecules for colorectal cancer
treatment is gene therapy,
which can also be referred to as allele therapy. The invention thus includes a
gene therapy method for
treating colorectal cancer in a subject, which includes contacting one or more
cells in the subject or
from the subject with a nucleic acid having a first nucleotide sequence.
Genomic DNA in the subject
includes a second nucleotide sequence having one or more SNPs associated with
colorectal cancer.
The first and second nucleotide sequences typically are substantially
identical to one another, and the
first nucleotide sequence comprises fewer SNPs associated with colorectal
cancer than the second
nucleotide sequence. The first nucleotide sequence may comprise a gene
sequence that encodes a full-
length polypeptide or a fragment thereof. The subject is often a human. Allele
therapy methods often
are utilized in conjunction with a method of first determining whether a
subject has genomic DNA
that includes SNPs associated with colorectal cancer.
Another allele therapy is a method which comprises contacting one or more
cells in the subject or
from the subject with a polypeptide encoded by a nucleic acid having a first
nucleotide sequence.
Genomic DNA in the subject includes a second nucleotide sequence having one or
more SNPs
associated with colorectal cancer. The first and second nucleotide sequences
typically are substantially
identical to one another, and the first nucleotide sequence includes fewer
SNPs associated with
colorectal cancer than the second nucleotide sequence. The first nucleotide
sequence may include a
gene sequence that encodes a full-length polypeptide or a fragment thereof.
The subject is usually a
human.
For antibody-based therapies, antibodies can be generated that are both
specific for target molecules
and that reduce target molecule activity. Such antibodies may be administered
in instances where
antagonizing a target molecule function is appropriate for the treatment of
colorectal cancer.
In circumstances where stimulating antibody production in an animal or a human
subject by injection
with a target molecule is harmful to the subject, it is possible to generate
an immune response against
the target molecule by use of anti-idiotypic antibodies (Herlyn and Birebent,
1999; Bhattacharya-
Chatterjee and Foon, 1998). Introducing an anti-idiotypic antibody to a mammal
or human subject
often stimulates production of anti-anti-idiotypic antibodies, which typically
are specific to the target
molecule. Vaccines directed to colorectal cancer also may be generated in this
fashion.
In instances where the target molecule is intracellular and whole antibodies
are used, internalizing
antibodies often are utilized. Lipofectin or liposomes can be used to deliver
the aritibody or a fragment
of the Fab region that binds to the target antigen into cells. Where fragments
of the antibody are used,
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CA 02548375 2006-06-13
the smallest inhibitory fragment that binds to the target antigen often is
utilized. For example, peptides
having an amino acid sequence corresponding to the Fv region of the antibody
can be used.
Alternatively, single chain neutralizing antibodies that bind to intracellular
target antigens can also be
administered. Such single chain antibodies can be administered, for example,
by expressing nucleotide
sequences encoding single-chain antibodies within the target cell population
(Marasco et al., 1993).
Modulators can be administered to a patient at therapeutically effective doses
to treat colorectal
cancer. A therapeutically effective dose refers to an amount of the modulator
sufficient to result in
amelioration of symptoms of colorectal cancer. Toxicity and therapeutic
efficacy of modulators can be
determined by standard pharmaceutical procedures in cell cultures or
experimental animals, e.g., for
determining the LD50 (the dose lethal to 50% of the population) and the ED50
(the dose therapeutically
effective in 50% of the population). The dose ratio between toxic and
therapeutic effects is the
therapeutic index and it can be expressed as the ratio LD50/EDSO. Modulators
that exhibit large
therapeutic indices often are utilized. While modulators that exhibit toxic
side effects can be used,
care should be taken to design a delivery system that targets such molecules
to the site of affected
tissue in order to minimize potential damage to uninfected cells, thereby
reducing side effects.
Data obtained from cell culture assays and animal studies can be used in
formulating a range of
dosages for use in humans. The dosage of such compounds typically lies within
a range of circulating
concentrations that include the ED50 with little or no toxicity. The dosage
can vary within this range
depending upon the dosage form employed and the route of administration
utilized. The
therapeutically effective dose can be estimated initially from cell culture
assays. A dose can be
formulated in animal models to achieve a circulating plasma concentration
range that includes the IC50
(i.e., the concentration of the test compound that achieves a half-maximal
inhibition of symptoms) as
determined in cell culture. Such information can be used to more accurately
determine useful doses in
humans. Levels in plasma can be measured, for example, by high performance
liquid chromatography.
Another example of effective dose determination for an individual is the
ability to directly assay levels
of "free" and "bound" compound in the serum of the test subject. Such assays
may utilize antibody
mimics and/or "biosensors" that have been created through molecular imprinting
techniques.
Molecules that modulate target molecule activity are used as a template, or
"imprinting molecule", to
spatially organize polymerizable monomers prior to their polymerization with
catalytic reagents. The
subsequent removal of the imprinted molecule leaves a polymer matrix which
contains a repeated
"negative image" of the compound and is able to selectively rebind the
molecule under biological
assay conditions. A detailed review of this technique can be seen in Ansell et
al. (Ansell et al., 1996).
Such "imprinted" affinity matrixes are amenable to ligand-binding assays,
whereby the immobilized
monoclonal antibody component is replaced by an appropriately imprinted
matrix. An example of the
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CA 02548375 2006-06-13
use of such matrixes in this way can be seen in Vlatakis, et al. (Vlatakis et
al., 1993). Through the use
of isotope-labeling, the "free" concentration of compound which modulates
target molecule
expression or activity readily can be monitored and used in calculations of
IC50. Such "imprinted"
affinity matrixes can also be designed to include fluorescent groups whose
photon-emitting properties
measurably change upon local and selective binding of target compound. These
changes readily can
be assayed in real time using appropriate fiberoptic devices, in turn allowing
the dose in a test subject
to be quickly optimized based on its individual ICs0=
The examples set forth below are intended to illustrate but not limit the
invention.
Genomic DNA samples from patients aged 25-74 and patients with both familial
and sporadic CRC
with family and unrelated ethnically matched controls were studied. We
identified CRC-associated
alleles by measuring 99,632 single nucleotide polymorphisms in peripheral
blood DNA from 2475
subjects (1234 cases with colorectal cancer and 1241 age matched individuals
undiseased at the time
of testing), and validating the identified CRC-associated alleles by using
peripheral blood DNA from
a second, different, group of 2194 subjects (1139 cases with colorectal cancer
and 1055 age matched
individuals undiseased at the time of testing). Patients with clinically
documented well characterized
inherited colorectal cancer syndromes such as Familial Adenomatous Polyposis
(FAP) or Hereditary
Non Polyposis Colorectal Cancer were excluded from our analysis. Single
nucleotide polymorphisms
were selected to maximize measurement of genomic variability by choosing these
markers that were
in the greatest degree of linkage disequilibrium with neighboring SNPs. This
was determined by
calculating correlation coefficients (r2) with successive neighboring SNPs at
each site of
polymorphism until an arbitrary cut off of 0.8 was observed. Marker SNPs
selected for measurement
were in linkage disequilibrium with a maximal number of adjacent SNPs, thus
providing an
economical method for measuring diversity over a large portion of the genome.
Single Nucleotide Polymorphisms selected for study were derived from the
International Haplotype
Mapping Project (http://www.hapmap.org) August 2004 release, information about
which is available
from the National Institutes of Health, National Institutes of Health (NIH;
http://www.nih.gov/), 9000
Rockville Pike, Bethesda, Maryland 20892. The SNPs were analyzed on DNA from
our control and
study population using either the Illumina Bead Array system
(http://www.illumina.com; Illumina,
Inc., 9885 Towne Centre Drive, San Diego, CA 92121-1975), the MIP platform
(http://www.affymetrix.com, Affymetrix, Inc., 3380 Central Expressway, Santa
Clara, CA 95051), or
the Affymetrix platform (http://www.affymetrix.com, Affymetrix, Inc., 3380
Central Expressway,
Santa Clara, CA 95051). The SNPs for the Illumina Bead Array system were
selected on the basis of
being associated with genes involved in DNA repair, chromosomal stability or
signal transduction and
expressed in human colon epithelium. The SNPs for the MIP platform were
selected to include most
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CA 02548375 2006-06-13
SNPs that would alter the coding sequence of a protein product. The SNPs for
the Affymetrix
platform were selected as to cover the entire genome, but the SNPs were
preferentially selected in
genic regions present on Xbal or HindIII restriction fragments varying in
length from about 20 base
pairs to about 1000 base pairs. Data was stored and organized using the Nanuq
informatics
environment of the McGill University and Genome Quebec Innovation Centre
(http://www.genomequebec.mcgill.ca/; McGill University and Genome Quebec
Innovation Centre,
740, Docteur Penfield Avenue, Montreal, Qu6bec H3A 1A4). Allele frequencies
found within DNA
from patients with colorectal cancer and those without this disease were
compared using the univariate
Mantel-Haenszel Chi-Square statistic.
The inventors of the present invention have discovered single base pair
polymorphisms that are
present in a highly significant percentage of the genetic DNA of individuals
affected with colorectal
cancer while only present in a smaller percentage of individuals who are not
known to be affected by
the disease.
Example 1
For individuals with colon cancer, the distribution of polymorphic alleles at
position 97159204 of
chromosome 1, found within the PTBP2 gene, was different from those without
colon cancer (Table
1). The trend test for risk associated with carrying the C allele had an
empirical p-value of 0.0008
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.503
(Table 1). These data further suggest that this marker, located within the
PTBP2 gene, is associated
with colon cancer risk and that the C allele at position 97159204 of
chromosome 1 is associated with
an increased risk of developing colon cancer.
Table 1
rs no. 10493889
Chromosome; Position 1; 97159204
Gene Name PTBP2
SEQ ID NO; Position 1120;
Genotype; Pheno e n=C; increased risk
Hard -Weinber 0.799522
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 842 123 5 Trend 0.0008e 1.503
1 2 769 173 6
Table IA indicates SNPs found to be in strong linkage disequilibrium with
rs10493889. To generate
this list, correlation coefficients (r 2) were calculated between the index
SNP and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
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CA 02548375 2006-06-13
Table 1A Linked SNPs
SNP r2 Position on chrl SEQ ID NO
rs17525524 0.667 96911594 1
rs17115733 0.647 96961817 2
rs12024594 0.73 97005044 3
rs11165746 1.0 97141267 4
rs10493889 - 97159204 5
Example 2
For individuals with colon cancer, the distribution of polymorphic alleles at
position 97657313 of
chromosome 1, found within the DPYD gene, was different from those without
colon cancer (Table
2). The trend test for risk associated with carrying the A allele had an
empirical p-value of 0.0845
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.100
(Table 2). These data further suggest that this marker, located within the
DPYD gene, is associated
with colon cancer risk and that the A allele at position 97657313 of
chromosome I is associated with
an increased risk of developing colon cancer.
Table 2
rs no. 945881
Chromosome; Position 1; 97657313
Gene Name DPYD
SEQ ID NO; Position 1121; 441288
Genotype; Phenotype n=A; increased risk
Hardy-Weinberg 0.188
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 246 585 407 Trend 0.0845e 1.100
1 1 196 613 417
Table 2A indicates SNPs found to be in strong linkage disequilibrium with
rs945881. To generate this
list, correlation coefficients (r2) were calculated between the index SNP and
all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 2A Linked SNPs
SNP r 2 Position on chrl SEQ ID NO
rs11165879 0.699 97653506 6
rs945881 - 97657313 7
rs11165881 1.0 97659904 8
Example 3
For individuals with colon cancer, the distribution of polymorphic alleles at
position 115166656 of
chromosome 1, found within the SYCP1 gene, was different from those without
colon cancer (Table
3). The recessive test for risk associated with carrying the A allele had an
empirical p-value of 0.0087
based on permutation analysis, and the corresponding recessive odds ratio is
1.323 (Table 3). These
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CA 02548375 2006-06-13
data further suggest that this marker, located within the SYCP1 gene, is
associated with colon cancer
risk and that the A allele at position 115166656 of chromosome 1 is associated
with an increased risk
of developing colon cancer.
Table 3
rs no. 360659
Chromosome; Position 1; 115166656
Gene Name SYCP 1
SEQ ID NO; Position 1122; 57160
Genotype; Phenotype n=A; increased risk
rg 0.428
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 424 565 208 Recessive 0.0087e 1.323
1 1 376 573 264
Table 3A indicates SNPs found to be in strong linkage disequilibrium with
rs360659. To generate this
list, correlation coefficients (rz) were calculated between the index SNP and
all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 3A Linked SNPs
SNP r2 Position on chrl SEQ ID NO
rs2010899 0.518 114947052 9
rs969273 0.522 114968711 10
rs2007231 0.522 114978348 11
rs2144428 0.569 114981253 12
rs6663115 0.522 114984296 13
rs4140445 0.522 115004020 14
rs3121503 0.966 115071842 15
rs3121506 0.599 115075249 16
rs3121507 0.964 115077252 17
rs6689326 0.583 115081154 18
rs3126216 0.966 115084567 19
rs1286560 0.583 115087972 20
rs869990 0.583 115091656 21
rs360599 0.815 115100040 22
rs360606 0.583 115103811 23
rs360607 0.599 115104443 24
rs360614 1.0 115111982 25
rs360617 0.603 115116141 26
rs360622 1.0 115119103 27
rs360627 1.0 115125087 28
rs360634 0.965 115132157 29
rs360635 0.564 115132560 30
rs360636 1.0 115132947 31
rs360643 1.0 115139005 32
rs360647 1.0 115141772 33
rs360655 0.564 115159909 34
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CA 02548375 2006-06-13
rs360659 - 115166656 35
rs360661 0.62 115167322 36
rs360576 0.546 115171216 37
rs360586 0.564 115179531 38
rs360588 1.0 115180386 39
rs360590 0.504 115182953 40
rs360591 0.809 115183282 41
rs360596 0.815 115185601 42
rs506934 0.51 115200356 43
rs360675 0.583 115202960 44
rs360682 0.815 115209101 45
rs12135023 0.815 115217819 46
rs1591899 0.815 115226640 47
rs12125190 0.815 115234779 48
rs12026343 0.815 115236258 49
rs7416955 0.812 115242333 50
rs4839017 0.815 115242502 51
rs11102859 0.806 115242740 52
rs6698174 0.815 115244057 53
rs7536888 0.815 115261728 54
rs4839399 0.815 115268188 55
rs11102872 0.815 115277042 56
rs7515454 0.815 115278233 57
rs7517739 0.815 115278345 58
rs7541251 0.815 115278448 59
rs6537849 0.815 115278686 60
rs1575070 0.674 115279927 61
rs1575069 0.689 115280070 62
rs12136420 0.689 115281663 63
rs7530810 0.689 115282510 64
rs1321108 0.689 115284407 65
rs11102874 0.749 115285912 66
rs3754363 0.686 115287160 67
rs1321107 0.583 115287345 68
rs7514765 0.612 115289952 69
rs1998008 0.703 115292582 70
rs461 1011 0.633 115298443 71
rs7413646 0.638 115298798 72
rs11102878 0.565 115303040 73
Example 4
For individuals with colon cancer, the distribution of polymorphic alleles at
position 143040559 of
chromosome 1, found within the FLJ25124 gene, was different from those without
colon cancer
(Table 4). The recessive test for risk associated with carrying the G allele
had an empirical p-value of
0.0011 based on permutation analysis, and the corresponding recessive odds
ratio is 1.585 (Table 4).
These data further suggest that this marker, located within the FLJ25124 gene,
is associated with
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CA 02548375 2006-06-13
colon cancer risk and that the G allele at position 143040559 of chromosome 1
is associated with an
increased risk of developing colon cancer.
Table 4
rs no. 10494240
Chromosome; Position 1; 143040559
Gene Name FLJ25124
SEQ ID NO; Position 1123; 2272
Genotype; Phenotype n=G; increased risk
Hardy-Weinberg 0.144192
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 3 438 449 92 Recessive 0.001le 1.585
1 3 416 399 134
Table 4A indicates SNPs found to be in strong linkage disequilibrium with
rs10494240. To generate
this list, correlation coefficients (rz) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 4A Linked SNPs
SNP r2 Position on chrl SEQ ID NO
rs4636400 0.611 142933600 74
rs6688400 0.71 142994415 75
rs872786 0.71 142996870 76
rs2274617 0.898 143024965 77
rs12410298 0.501 143037007 78
rs720899 1.0 143039966 79
rs10494240 - 143040559 80
Example 5
For individuals with colon cancer, the distribution of polymorphic alleles at
position 20254115 of
chromosome 2 was different from those without colon cancer (Table 5). The
trend test for risk
associated with carrying the C allele had an empirical p-value of 0.0028 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.226
(Table 5). These data
further suggest that this marker is associated with colon cancer risk and that
the C allele at position
20254115 of chromosome 2 is associated with an increased risk of developing
colon cancer.
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CA 02548375 2006-06-13
Table 5
rs no. 973128
Chromosome; Position 2; 20254115
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=C; increased risk
Hard -Weinber 0.14711
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 198 485 243 Trend 0.0028e 1.226
1 2 135 490 262
Table 5A indicates SNPs found to be in strong linkage disequilibrium with
rs973 128. To generate this
list, correlation coefficients (r2) were calculated between the index SNP and
all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 5A Linked SNPs
SNP r 2 Position on chr2 SEQ ID NO
rs 17697743 0.755 20250764 81
rs6753830 1.0 20250981 82
rs975951 1.0 20252966 83
rs973128 - 20254115 84
rs875411 1.0 20254650 85
rs875412 1.0 20255588 86
rs6744463 1.0 20256013 87
rs2881879 0.534 20257476 88
rs4666362 0.527 20258973 89
rs6531212 0.522 20259648 90
rs4666364 0.513 20260227 91
Example 6
For individuals with colon cancer, the distribution of polymorphic alleles at
position 186869364 of
chromosome 2 was different from those without colon cancer (Table 6). The
recessive test for risk
associated with carrying the C allele had an asymptotic p-value of 0.00049577,
and the corresponding
recessive odds ratio is 6.624 (Table 6). These data further suggest that this
marker is associated with
colon cancer risk and that the C allele at position 186869364 of chromosome 2
is associated with an
increased risk of developing colon cancer.
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CA 02548375 2006-06-13
Table 6
rs no. 10497667
Chromosome; Position 2; 186869364
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=C; increased risk
Hard -Weinber 0.00834769
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 783 194 3 Recessive 0.00049577a 6.624
1 2 725 160 18
Table 6A indicates SNPs found to be in strong linkage disequilibrium with
rs10497667. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An rz cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 6A Linked SNPs
SNP r 2 Position on chr2 SEQ ID NO
rs7582258 0.611 186729521 92
rs12615770 0.611 186748482 93
rs12998383 0.635 186752544 94
rs16827480 0.63 186753368 95
rs12614513 0.726 186759677 96
rs991084 0.63 186774634 97
rs13005466 0.63 186783677 98
rs6750636 0.61 186788675 99
rs13003934 0.612 186795981 100
rs12999989 0.629 186797056 101
rs13028175 0.59 186797101 102
rs12999474 0.627 186804008 103
rs12373738 0.63 186822924 104
rs6725283 0.891 186849447 105
rs13419562 0.611 186854278 106
rs13394207 0.63 186854406 107
rs13421172 0.63 186856196 108
rs4284795 1.0 186866149 109
rs2887816 0.63 186869233 110
rs10497667 - 186869364 111
rs13388196 0.629 186870116 112
rs2370681 0.63 186873391 113
rs12233005 0.63 186873805 114
rs8179713 1.0 186874321 115
rs13416578 0.63 186876760 116
rs12614595 1.0 186877596 117
rs2370677 1.0 186878043 118
rs4500906 0.908 186883056 119
rs16827554 1.0 186887466 120
rs7584724 1.0 186895423 121
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CA 02548375 2006-06-13
rs16827602 1.0 186898014 122
rs6434164 1.0 186899824 123
rs2370670 1.0 186903194 124
rs16827614 1.0 186905158 125
rs3107174 0.915 186910195 126
rs2887818 0.915 186918660 127
rs3112312 0.901 186933341 128
rs1878754 0.915 186935034 129
rs3112315 0.915 186937617 130
rs2370659 0.915 186938372 131
rs3112316 0.915 186938761 132
rs3107410 0.915 186940537 133
rs3112317 0.915 186942136 134
rs10195099 0.591 186944471 135
rs2370662 0.915 186945120 136
rs10931232 0.915 186950816 137
rs2029085 0.915 187032899 138
rs10497669 0.643 187050892 139
Example 7
For individuals with colon cancer, the distribution of polymorphic alleles at
position 218776751 of
chromosome 2, found within the FLJ46536 gene, was different from those without
colon cancer
(Table 7). The trend test for risk associated with carrying the C allele had
an empirical p-value of
0.0238 based on permutation analysis, and the corresponding Mantel-Haenszel
odds ratio for trend is
1.147 (Table 7). The recessive test for risk associated with carrying the C
allele had an asymptotic p-
value of 0.0021509, and the corresponding recessive odds ratio is 1.395 (Table
7). These data further
suggest that this marker, located within the FLJ46536 gene, is associated with
colon cancer risk and
that the C allele at position 218776751 of chromosome 2 is associated with an
increased risk of
developing colon cancer.
Table 7
rs no. 4133195
Chromosome; Position 2; 218776751
Gene Name FLJ46536
SEQ ID NO; Position 1124; 51535
Genotype; Phenotype n=C; increased risk
Hardy-Weinberg 0.94839
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 284 479 204 Trend 0.0238e 1.147
1 2 252 402 244 Recessive 0.0021509a 1.395
Table 7A indicates SNPs found to be in strong linkage disequilibrium with
rs4133195. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
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CA 02548375 2006-06-13
Table 7A Linked SNPs
SNP r2 Position on chr2 SEQ ID NO
rs4672870 0.647 218767422 140
rs12694425 0.647 218767819 141
rs12694426 0.637 218767857 142
rs10932745 0.669 218768482 143
rs11687200 0.665 218770121 144
rs11676275 0.669 218770314 145
rs12694427 0.669 218770551 146
rs6737563 0.934 218771180 147
rs13013361 0.933 218773021 148
rs4133195 - 218776751 149
rs6726126 1.0 218777739 150
rs10804264 0.819 218781315 151
rs12694428 0.63 218784326 152
rs13035513 0.935 218786186 153
rs13007992 0.792 218789557 154
rs7426289 0.935 218791821 155
rs4674257 0.935 218814280 156
rs4674259 0.935 218816511 157
rs6723449 0.934 218823086 158
rs1126579 0.967 218826240 159
rs4674261 0.625 218830515 160
rs11677534 0.935 218832566 161
rs13009946 0.935 218833258 162
rs7594532 0.918 218833506 163
rs7607437 0.935 218833898 164
rs11676348 0.782 218835652 165
rs1008563 0.625 218852394 166
rs1008562 0.935 218852478 167
rs4674267 0.625 218871943 168
rs13397673 0.641 218873288 169
Example 8
For individuals with colon cancer, the distribution of polymorphic alleles at
position 230825727 of
chromosome 2 was different from those without colon cancer (Table 8). The
trend test for risk
associated with carrying the C allele had an empirical p-value of 0.0021 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.222
(Table 8). These data
further suggest that this marker is associated with colon cancer risk and that
the C allele at position
230825727 of chromosome 2 is associated with an increased risk of developing
colon cancer.
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CA 02548375 2006-06-13
Table 8
rs no. 10498243
Chromosome; Position 2; 230825727
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=C; increased risk
Hard -Weinber 0.0296796
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 472 410 61 Trend 0.0021 e 1.222
1 2 424 414 99
Table 8A indicates SNPs found to be in strong linkage disequilibrium with
rs10498243. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 8A Linked SNPs
SNP r2 Position on chr2 SEQ ID NO
rs12694839 0.52 230822818 170
rs12694840 0.517 230822908 171
rs6706782 1.0 230823742 172
rs6707129 1.0 230824051 173
rs1529377 1.0 230825316 174
rs12694841 1.0 230825613 175
rs10498243 - 230825727 176
rs6715536 1.0 230825877 177
rs1549567 1.0 230827852 178
rs6721137 1.0 230828862 179
rs1365775 1.0 230829298 180
rs10933326 1.0 230830081 181
rs2396713 0.961 230830316 182
rs13004807 1.0 230830886 183
rs10048686 1.0 230832540 184
rs11677105 0.507 230842525 185
Example 9
For individuals with colon cancer, the distribution of polymorphic alleles at
position 25062781 of
chromosome 3 was different from those without colon cancer (Table 9). The
trend test for risk
associated with carrying the A allele had an empirical p-value of 0.0086 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.302
(Table 9). These data
further suggest that this marker is associated with colon cancer risk and that
the A allele at position
25062781 of chromosome 3 is associated with an increased risk of developing
colon cancer.
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CA 02548375 2006-06-13
Table 9
rs no. 4484159
Chromosome; Position 3; 25062781
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=A; increased risk
Hard -Weinber 0.411896
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 22 273 677 Trend 0.0086e 1.302
1 1 21 209 712
Table 9A indicates SNPs found to be in strong linkage disequilibrium with
rs4484159. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 9A Linked SNPs
SNP r2 Position on chr3 SEQ ID NO
rs13067187 0.583 25052936 186
rs6777624 0.854 25054402 187
rs9866836 0.877 25056885 188
rs17015670 1.0 25061156 189
rs4484159 - 25062781 190
rs1604007 0.817 25068060 191
rs988268 0.808 25076452 192
rs6550943 0.778 25084253 193
rs6777955 0.932 25084806 194
rs6766372 0.757 25086476 195
rs994267 0.825 25090198 196
rs1574901 0.825 25090417 197
rs1587430 0.825 25100369 198
rs4858700 0.517 25102693 199
rs11294076 0.788 25105990 200
rs4858703 0.825 25108277 201
rs2036270 0.825 25112900 202
rs972016 0.825 25114656 203
rs1603987 0.825 25115540 204
rs6807196 0.696 25117575 205
rs4858704 0.517 25118394 206
rs1580817 0.825 25121605 207
Example 10
For individuals with colon cancer, the distribution of polymorphic alleles at
position 62952892 of
chromosome 3 was different from those without colon cancer (Table 10). The
recessive test for risk
associated with carrying the C allele had an empirical p-value of 0.0012 based
on permutation
analysis, and the corresponding recessive odds ratio is 2.148 (Table 10).
These data further suggest
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CA 02548375 2006-06-13
that this marker is associated with colon cancer risk and that the C allele at
position 62952892 of
chromosome 3 is associated with an increased risk of developing colon cancer.
Table 10
rs no. 4404442
Chromosome; Position 3; 62952892
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=C; increased risk
Hardy-Weinber 0.910304
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 627 271 28 Recessive 0.0012e 2.148
1 2 600 251 57
Table 10A indicates SNPs found to be in strong linkage disequilibrium with
rs4404442. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 10A Linked SNPs
SNP r 2 Position on chr3 SEQ ID NO
rs9828340 0.51 62937809 208
rs12631618 1.0 62941462 209
rs6807315 1.0 62943033 210
rs4312654 1.0 62943151 211
rs4583651 1.0 62943547 212
rs13072243 1.0 62945427 213
rs4613448 0.948 62949979 214
rs4404442 - 62952892 215
rs13091015 1.0 62955440 216
rs9814898 1.0 62957942 217
rs17067503 1.0 62958060 218
rs10510890 0.948 62959133 219
rs9821058 1.0 62959399 220
rs10510891 1.0 62960430 221
rs4147406 0.95 62962215 222
rs2367590 1.0 62964393 223
rs17067527 0.898 62965607 224
rs12488885 0.948 62966446 225
rs17361212 0.752 62966549 226
rs11130909 0.947 62968123 227
rs13099709 0.948 62968779 228
rs13079904 0.948 62968976 229
rs2367591 0.898 62969677 230
rs9850740 0.947 62970029 231
rs10510892 0.948 62970190 232
rs2367592 0.852 62970589 233
rs11130910 0.887 62971291 234
rs7372226 0.947 62972138 235
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CA 02548375 2006-06-13
rs13061838 0.898 62975188 236
rs6770985 0.528 62981633 237
rs1447443 0.528 62982901 238
rs12637433 0.528 62983787 239
rs4688357 0.555 62985367 240
Example 11
For individuals with colon cancer, the distribution of polymorphic alleles at
position 120037273 of
chromosome 3 was different from those without colon cancer (Table 11). The
trend test for risk
associated with carrying the A allele had an empirical p-value of 0.0016 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.489
(Table 11). These data
further suggest that this marker is associated with colon cancer risk and that
the A allele at position
120037273 of chromosome 3 is associated with an increased risk of developing
colon cancer.
Table 11
rs no. 1402582
Chromosome; Position 3; 120037273
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=A; increased risk
Hardy-Weinber 0.0111588
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 777 132 0 Trend 0.0016e 1.489
1 1 664 168 0
Table 11A indicates SNPs found to be in strong linkage disequilibrium with
rs1402582. To generate
this list, correlation coefficients (rz) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 11A Linked SNPs
SNP r 2 Position on chr3 SEQ ID NO
rs1081903 0.549 120036240 243
rs1402582 - 120037273 244
rs812824 0.608 120037336 245
rs2936727 0.608 120037804 246
rs1521289 0.608 120039183 247
rs2684320 0.608 120039851 248
rs2649882 0.608 120044441 249
Example 12
For individuals with colon cancer, the distribution of polymorphic alleles at
position 120037336 of
chromosome 3 was different from those without colon cancer (Table 12). The
trend test for risk
associated with carrying the G allele had an empirical p-value of 0.057 based
on permutation analysis,
and the corresponding Mantel-Haenszel odds ratio for trend is 1.122 (Table
12). These data further
-60-
CA 02548375 2006-06-13
suggest that this marker is associated with colon cancer risk and that the G
allele at position
120037336 of chromosome 3 is associated with an increased risk of developing
colon cancer.
Table 12
rs no. 812824
Chromosome; Position 3; 120037336
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=G; increased risk
Hardy-Weinberg 0.0190876
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 3 586 359 34 Trend 0.057e 1.122
1 3 546 340 61
Table 12A indicates SNPs found to be in strong linkage disequilibrium with
rs812824. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 12A Linked SNPs
SNP r2 Position on chr3 SEQ ID NO
rs881603 0.705 120013362 241
rs881604 0.711 120013382 242
rs1081903 0.953 120036240 243
rs1402582 0.608 120037273 244
rs812824 - 120037336 245
rs2936727 1.0 120037804 246
rs1521289 1.0 120039183 247
rs2684320 1.0 120039851 248
rs2649882 1.0 120044441 249
Example 13
For individuals with colon cancer, the distribution of polymorphic alleles at
position 186033203 of
chromosome 3, found within the KIAA0804 gene, was different from those without
colon cancer
(Table 13). The recessive test for risk associated with carrying the A allele
had an empirical p-value
based on permutation analysis of 0.0045, and the corresponding recessive odds
ratio is 1.266 (Table
13). These data further suggest that this marker, located within the KIAA0804
gene, is associated with
colon cancer risk and that the A allele at position 186033203 of chromosome 3
is associated with an
increased risk of developing colon cancer.
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CA 02548375 2006-06-13
Table 13
rs no. 9830734
Chromosome; Position 3; 186033203
Gene Name KIAA0804
SEQ ID NO; Position 1125; 8081
Genotype; Phenotype n=A; increased risk
Hard rg 0.0561279
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 100 526 528 Recessive 0.0045e 1.266
1 1 79 467 583
Table 13A indicates SNPs found to be in strong linkage disequilibrium with
rs9830734. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 13A Linked SNPs
SNP r2 Position on chr3 SEQ ID NO
rs4686769 0.765 186008653 250
rs2377115 0.71 186008673 251
rs725656 0.636 186008910 252
rs7640976 1.0 186012692 253
rs13079793 0.619 186027445 254
rs10513799 0.636 186032241 255
rs9830734 - 186033203 256
rs4432622 0.617 186038166 257
rs11710551 0.643 186041770 258
rs16859344 0.636 186043671 259
rs2305240 0.636 186049741 260
rs11720538 0.623 186052729 261
rs6443999 0.6 186056257 262
rs724273 0.647 186058533 263
rs6809079 0.597 186059022 264
rs7340698 0.636 186060619 265
rs3733165 0.553 186063619 266
rs2377107 0.593 186070576 267
rs7619460 0.597 186070838 268
rs9757458 0.615 186072802 269
rs7628188 0.553 186073295 270
rs7638317 0.557 186076934 271
rs11717139 0.593 186079782 272
rs11714752 0.588 186081364 273
rs9881074 0.593 186083378 274
rs1000270 0.593 186090182 275
rs6762984 0.529 186099834 276
rs4324453 0.593 186104572 277
rs7618180 0.532 186112996 278
rs4686879 0.556 186115949 279
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CA 02548375 2006-06-13
rs7611263 0.597 186117351 280
rs9825856 0.604 186119962 281
rs9290804 0.557 186126928 282
rs10446349 0.597 186131728 283
rs13066369 0.518 186142625 284
rs9870352 0.576 186146360 285
rs4422281 0.518 186148006 286
rs9820111 0.518 186149057 287
rs6784179 0.518 186152026 288
rs7623170 0.512 186156901 289
rs6765821 0.524 186244971 290
rs6783157 0.521 186252104 291
rs12636670 0.526 186267820 292
Example 14
For individuals with colon cancer, the distribution of polymorphic alleles at
position 187873329 of
chromosome 3, found within the HRG gene, was different from those without
colon cancer (Table
14). The trend test for risk associated with carrying the C allele had an
empirical p-value of 0.0504
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.109
(Table 14). These data further suggest that this marker, located within the
HRG gene, is associated
with colon cancer risk and that the C allele at position 187873329 of
chromosome 3 is associated with
an increased risk of developing colon cancer.
Table 14
rs no. 9898
Chromosome; Position 3; 187873329
Gene Name HRG
SEQ ID NO; Position 1126; 6830
Genotype; Phenotype n=C; increased risk
Hard -Weinber 0.0124873
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 168 491 494 Trend 0.0504e 1.109
1 2 119 510 503
Table 14A indicates SNPs found to be in strong linkage disequilibrium with
rs9898. To generate this
list, correlation coefficients (r2) were calculated between the index SNP and
all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 14A Linked SNPs
SNP r 2 Position on chr3 SEQ ID NO
rs3733159 0.8 187843111 293
rs1868154 0.574 187857373 294
rs9898 - 187873329 295
rs1042464 0.547 187878274 296
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CA 02548375 2006-06-13
Example 15
For individuals with colon cancer, the distribution of polymorphic alleles at
position 4862109 of
chromosome 4 was different from those without colon cancer (Table 15). The
trend test for risk
associated with carrying the A allele had an empirical p-value of 0.0017 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.430
(Table 15). The
dominant test for risk associated with carrying the A allele had an empirical
p-value based on
permutation analysis of 0.001, and the corresponding dominant odds ratio is
1.457 (Table 15). These
data further suggest that this marker is associated with colon cancer risk and
that the A allele at
position 4862109 of chromosome 4 is associated with an increased risk of
developing colon cancer.
Table 15
rs no. 10516168
Chromosome; Position 4; 4862109
Gene Name
SEQ ID NO; Position
Geno e; Phenotype n=A; increased risk
Hard -Weinber 1
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 821 156 7 Trend 0.0017e 1.430
1 1 705 196 8 Dominant 0.OOle 1.457
Table 15A indicates SNPs found to be in strong linkage disequilibrium with
rs10516168. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 15A Linked SNPs
SNP r 2 Position on chr4 SEQ ID NO
rs2089781 1.0 4857130 297
rs13149006 0.848 4857759 298
rs10516168 - 4862109 299
rs767564 0.79 4867970 300
Example 16
For individuals with colon cancer, the distribution of polymorphic alleles at
position 73418955 of
chromosome 4, found within the GPR74 gene, was different from those without
colon cancer (Table
16). The trend test for risk associated with carrying the G allele had an
empirical p-value of 0.0583
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.112
(Table 16). These data further suggest that this marker, located within the
GPR74 gene, is associated
with colon cancer risk and that the G allele at position 73418955 of
chromosome 4 is associated with
an increased risk of developing colon cancer.
-64-
CA 02548375 2006-06-13
Table 16
rs no. 10518098
Chromosome; Position 4; 73418955
Gene Name GPR74
SEQ ID NO; Position 1127;
Genotype; Phenotype n=G; increased risk
Hard -Weinber 0.0585416
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 3 411 369 110 Trend 0.0583e 1.112
1 3 386 327 150
Table 16A indicates SNPs found to be in strong linkage disequilibrium with
rs10518098. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 16A Linked SNPs
SNP r 2 Position on chr4 SEQ ID NO
rs11726886 0.533 73187634 301
rs10518093 0.621 73200067 302
rs4129733 0.749 73328055 303
rs4337703 0.749 73346262 304
rs11733404 0.73 73346848 305
rs11737827 0.749 73348223 306
rs12651098 0.738 73357454 307
rs11734943 0.675 73363372 308
rs9790741 0.676 73365920 309
rs11940196 0.925 73368604 310
rs10755169 0.963 73376981 311
rs11729989 0.884 73386336 312
rs4333153 0.963 73387894 313
rs17775363 0.888 73401936 314
rs17718934 0.889 73402263 315
rs885521 0.889 73403367 316
rs2137735 0.889 73409745 317
rs7675397 1.0 73418036 318
rs10518098 - 73418955 319
rs1554016 1.0 73419931 320
rs10938007 0.91 73420592 321
rs4444797 1.0 73420874 322
rs4502651 1.0 73420904 323
rs4301078 1.0 73420954 324
rs7700096 1.0 73421198 325
rs7654146 1.0 73421361 326
rs2056022 1.0 73421626 327
rs2056023 1.0 73421636 328
rs2365795 1.0 73424191 329
rs6840004 0.926 73426574 330
rs1121770 1.0 73428206 331
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CA 02548375 2006-06-13
rs11940139 1.0 73428609 332
rs868028 1.0 73429022 333
rs868026 1.0 73429166 334
rs7673208 1.0 73429961 335
rs4694467 1.0 73430864 336
rs4694468 0.924 73432371 337
rs1398982 1.0 73432662 338
rs10938009 0.926 73433172 339
rs996154 1.0 73435810 340
rs996153 1.0 73435851 341
rs1018283 1.0 73437882 342
rs10805048 0.926 73438096 343
rs957047 1.0 73440758 344
rs957046 1.0 73441001 345
rs957045 1.0 73441029 346
rs10008822 1.0 73442206 347
rs4547769 1.0 73445194 348
rs7674709 0.835 73446950 349
rs10938010 0.888 73448534 350
rs7662481 1.0 73453617 351
rs884511 0.89 73454336 352
rs10029245 0.924 73456969 353
rs970649 1.0 73461203 354
rs10938012 0.925 73461427 355
rs4694120 0.926 73468266 356
rs10518099 0.926 73468802 357
rs10518100 0.89 73469693 358
rs9985540 0.889 73472897 359
rs985302 0.921 73473510 360
rs2117380 0.855 73474331 361
rs1865383 0.816 73475459 362
rs984406 0.842 73476824 363
rs2175830 0.603 73481968 364
rs1554017 0.603 73482388 365
rs10006866 0.603 73484550 366
rs1513894 0.661 73489468 367
rs11729217 0.593 73491229 368
rs6857543 0.662 73491598 369
rs1398980 0.574 73492707 370
rs7681169 0.574 73493192 371
rs10433664 0.574 73493907 372
rs10050160 0.574 73496343 373
rs6446823 0.662 73496916 374
rs7679388 0.574 73501955 375
Example 17
For individuals with colon cancer, the distribution of polymorphic alleles at
position 114720973 of
chromosome 5 was different from those without colon cancer (Table 17). The
recessive test for risk
associated with carrying the A allele had an empirical p-value based on
permutation analysis of
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CA 02548375 2006-06-13
0.0059, and the corresponding recessive odds ratio is 1.325 (Table 17). These
data further suggest that
this marker is associated with colon cancer risk and that the A allele at
position 114720973 of
chromosome 5 is associated with an increased risk of developing colon cancer.
Table 17
rs no. 2963765
Chromosome; Position 5; 114720973
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=A; increased risk
Hardy-Weinber 0.798586
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 251 487 245 Recessive 0.0059e 1.325
1 1 196 470 293
Table 17A indicates SNPs found to be in strong linkage disequilibrium with
rs2963765. To generate
this list, correlation coefficients (rz) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 17A Linked SNPs
SNP r 2 Position on chr5 SEQ ID NO
rs269511 0.677 114716570 376
rs12654556 0.74 114718052 377
rs10519405 0.525 114719100 378
rs10519406 0.525 114719186 379
rs2963765 - 114720973 380
rs2964560 1.0 114721020 381
rs269503 0.525 114724952 382
rs10463669 0.544 114727927 383
rs12657417 0.525 114728598 384
rs2925172 0.935 114729688 385
rs17383755 0.559 114730035 386
rs11241322 0.9 114730402 387
rs11241323 0.501 114731087 388
rs2963749 0.934 114734391 389
rs17383865 0.932 114735264 390
rs2963747 0.934 114735588 391
rs17137667 0.902 114735981 392
rs2925170 0.934 114736503 393
rs7715232 0.505 114739954 394
rs2198712 0.935 114741070 395
rs10477531 0.841 114742706 396
rs7703997 0.615 114743558 397
rs17137708 0.9 114743576 398
rs13162208 0.933 114744950 399
rs751485 0.934 114747047 400
rs897478 0.933 114747337 401
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CA 02548375 2006-06-13
rs2016888 0.964 114747490 402
Example 18
For individuals with colon cancer, the distribution of polymorphic alleles at
position 121110284 of
chromosome 5 was different from those without colon cancer (Table 18). The
recessive test for risk
associated with carrying the T allele had an empirical p-value based on
permutation analysis of
0.0055, and the corresponding recessive odds ratio is 1.451 (Table 18). These
data further suggest that
this marker is associated with colon cancer risk and that the T allele at
position 121110284 of
chromosome 5 is associated with an increased risk of developing colon cancer.
Table 18
rs no. 1988515
Chromosome; Position 5; 121110284
Gene Name
SEQ ID NO; Position
Genotype; Pheno e n=T; increased risk
Hard -Weinber 0.3509
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 11 152 703 Recessive 0.0055e 1.451
1 4 4 108 701
Table 18A indicates SNPs found to be in strong linkage disequilibrium with rs
1988515. To generate
this list, correlation coefficients (rl) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 18A Linked SNPs
SNP r2 Position on chr5 SEQ ID NO
rs11958025 0.693 121091463 403
rs2567820 0.553 121091499 404
rs17148244 0.732 121091674 405
rs7710646 0.553 121092163 406
rs7710680 0.693 121092323 407
rs2174984 0.843 121093100 408
rs17148266 0.744 121093738 409
rs10213700 0.744 121093873 410
rs17148275 0.744 121095213 411
rs1431964 0.948 121096396 412
rs1508809 0.948 121097405 413
rs1828180 0.895 121099073 414
rs1560552 0.948 121099678 415
rs1560551 0.948 121099771 416
rs983441 0.895 121100720 417
rs983440 0.895 121100858 418
rs983439 1.0 121101095 419
rs2567817 0.895 121102610 420
-68-
CA 02548375 2006-06-13
rs2662291 0.71 121102897 421
rs2567816 0.681 121103646 422
rs2136184 1.0 121103950 423
rs2136183 1.0 121104009 424
rs1431963 1.0 121104729 425
rs1431962 0.948 121104747 426
rs1588260 0.897 121105473 427
rs2567803 1.0 121107768 428
rs1156684 1.0 121110035 429
rs1988515 - 121110284 430
rs2662296 1.0 121110706 431
rs1367938 0.948 121114213 432
rs1560553 0.711 121115356 433
rs769365 0.778 121115515 434
rs919651 0.947 121116167 435
rs930180 0.948 121116191 436
rs2406704 0.843 121116332 437
rs2406705 0.855 121116360 438
rs982148 0.744 121119962 439
rs6595320 0.711 121128383 440
rs1431947 0.691 121137238 441
rs2897529 0.711 121153311 442
Example 19
For individuals with colon cancer, the distribution of polymorphic alleles at
position 128145987 of
chromosome 5, found within the SLC27A6 gene, was different from those without
colon cancer
(Table 19). The trend test for risk associated with carrying the A allele had
an empirical p-value of
0.0144 based on permutation analysis, and the corresponding Mantel-Haenszel
odds ratio for trend is
1.172 (Table 19). These data further suggest that this marker, located within
the SLC27A6 gene, is
associated with colon cancer risk and that the A allele at position 128145987
of chromosome 5 is
associated with an increased risk of developing colon cancer.
Table 19
rs no. 10491268
Chromosome; Position 5; 128145987
Gene Name SLC27A6
SEQ ID NO; Position 1128;
Genotype; Phenotype n=A; increased risk
Hard -Weinber 0.928532
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 529 337 55 Trend 0.0144e 1.172
1 1 469 318 85
Table 19A indicates SNPs found to be in strong linkage disequilibrium with
rs10491268. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
-69-
CA 02548375 2006-06-13
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 19A Linked SNPs
SNP r2 Position on chr5 SEQ ID NO
rs247184 0.545 128103463 443
rs247195 0.545 128108152 444
rs247210 0.583 128113997 445
rs247094 0.583 128120050 446
rs10074635 0.503 128134369 447
rs10061806 1.0 128135572 448
rs7449021 1.0 128139763 449
rs17163935 0.56 128141175 450
rs10491268 - 128145987 451
rs17790915 0.512 128146786 452
rs1496344 0.576 128156553 453
rs1019137 0.545 128157693 454
rs7735162 0.961 128160641 455
rs7707454 0.926 128164258 456
rs10066082 0.816 128197696 457
rs10058629 0.778 128206257 458
rs17678073 0.778 128220969 459
rs2214369 0.816 128223084 460
rs6860974 0.778 128227979 461
rs10050439 0.778 128228401 462
rs7723679 0.767 128232311 463
rs7723683 0.777 128232320 464
rs10079808 0.772 128233576 465
rs1363170 0.769 128233727 466
rs13360809 0.778 128234493 467
rs13356389 0.778 128234617 468
rs17678190 0.778 128234806 469
rs17616306 0.778 128235438 470
rs7712212 0.778 128235745 471
rs7712497 0.778 128235767 472
rs7716412 0.778 128236078 473
rs13362019 0.778 128236528 474
rs9327496 0.523 128238639 475
rs13358000 0.778 128240119 476
rs4469239 0.776 128241301 477
rs13360401 0.583 128258653 478
rs6595867 0.578 128260778 479
rs6873372 0.552 128260800 480
rs6880855 0.558 128263313 481
rs1421889 0.61 128265259 482
rs9285913 0.558 128269933 483
rs10478827 0.544 128271956 484
rs9327500 0.591 128273703 485
rs13436689 0.549 128279649 486
rs13156417 0.558 128280539 487
-70-
CA 02548375 2006-06-13
rs10477690 0.555 128287628 488
rs6867677 0.554 128289750 489
rs10042256 0.567 128327389 490
rs11740497 0.556 128340511 491
rs10038006 0.54 128341528 492
rs17617241 0.507 128345166 493
rs10065480 0.516 128346380 494
rs11743701 0.525 128348967 495
rs3886286 0.525 128351543 496
rs7735034 0.524 128352581 497
rs7730969 0.525 128352924 498
rs11749027 0.558 128353107 499
rs17679250 0.525 128355391 500
rs17617329 0.525 128355483 501
rs3851463 0.525 128356081 502
rs6859805 0.642 128358774 503
Example 20
For individuals with colon cancer, the distribution of polymorphic alleles at
position 1032946 of
chromosome 6, found within the LOC285768 gene, was different from those
without colon cancer
(Table 20). The dominant test for risk associated with carrying the A allele
had an asymptotic p-value
of 0.074953, and the corresponding dominant odds ratio is 1.453 (Table 20).
These data further
suggest that this marker, located within the LOC285768 gene, is associated
with colon cancer risk and
that the A allele at position 1032946 of chromosome 6 is associated with an
increased risk of
developing colon cancer.
Table 20
rs no. 9328033
Chromosome; Position 6; 1032946
Gene Name LOC285768
SEQ ID NO; Position 1129; 13622
Genotype; Phenotype n=A; increased risk
Hard erg 0.932075
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 60 370 553 Dominant 0.074953a 1.453
1 1 39 305 567
Table 20A indicates SNPs found to be in strong linkage disequilibrium with
rs9328033. To generate
this list, correlation coefficients (r 2) were calculated between the index
SNP and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 20A Linked SNPs
SNP r 2 Position on chr6 SEQ ID NO
rs9405439 0.795 1026731 504
rs9391899 0.837 1032864 505
-71-
CA 02548375 2006-06-13
rs9328033 - 1032946 506
rs7756730 0.756 1033885 507
rs7770094 0.756 1033964 508
rs10900904 0.75 1034131 509
rs10458112 0.756 1034217 510
rs6596783 0.744 1035056 511
rs6914197 0.72 1035451 512
rs9405441 0.753 1037138 513
rs6911992 0.685 1037761 514
Example 21
For individuals with colon cancer, the distribution of polymorphic alleles at
position 69521107 of
chromosome 6, found within the BAI3 gene, was different from those without
colon cancer (Table
21). The trend test for risk associated with carrying the T allele had an
empirical p-value of 0.0056
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.194
(Table 21). The recessive test for risk associated with carrying the T allele
had an empirical p-value
based on permutation analysis of 0.0983, and the corresponding recessive odds
ratio is 1.180 (Table
21). These data further suggest that this marker, located within the BAI3
gene, is associated with
colon cancer risk and that the T allele at position 69521107 of chromosome 6
is associated with an
increased risk of developing colon cancer.
Table 21
rs no. 10484791
Chromosome; Position 6; 69521107
Gene Name BAI3
SEQ ID NO; Position 1130; 116950
Genotype; Phenotype n=T; increased risk
Hard erg 0.0463995
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 239 453 277 Trend 0.0056e 1.194
1 4 170 442 289 Recessive 0.0983e 1.180
Table 21A indicates SNPs found to be in strong linkage disequilibrium with
rs10484791. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 21A Linked SNPs
SNP r 2 Position on chr6 SEQ ID NO
rs2585614 0.595 69379328 515
rs2246104 0.656 69411039 516
rs2585627 0.656 69414352 517
rs2585626 0.656 69414862 518
rs2802694 0.807 69416925 519
rs2802691 0.739 69420759 520
-72-
CA 02548375 2006-06-13
rs2253759 0.868 69428738 521
rs2253866 0.746 69429357 522
rs2802689 0.865 69429728 523
rs2585622 0.709 69435338 524
rs2585621 0.716 69435377 525
rs2254654 0.837 69435704 526
rs3121775 0.69 69436412 527
rs6931872 0.743 69437088 528
rs2585592 0.656 69437132 529
rs7754835 0.69 69437929 530
rs2746125 0.746 69439747 531
rs2746127 0.746 69440936 532
rs2585597 0.715 69445347 533
rs2746141 0.837 69447873 534
rs2585598 0.69 69449271 535
rs2802684 0.742 69454318 536
rs2802683 0.868 69455343 537
rs2585599 0.733 69461590 538
rs2802680 0.776 69462851 539
rs2585600 0.718 69463179 540
rs2585604 0.776 69469800 541
rs2746132 0.718 69471343 542
rs715294 0.744 69483117 543
rs2802676 0.901 69483590 544
rs12206222 0.717 69486083 545
rs12210045 0.776 69490498 546
rs10945138 0.901 69496298 547
rs7768591 0.901 69497479 548
rs11752837 0.776 69504298 549
rs11752398 0.718 69504487 550
rs10945139 0.775 69511710 551
rs12154008 0.775 69513299 552
rs7745837 0.813 69517615 553
rs12201488 0.813 69518419 554
rs10484791 - 69521107 555
Example 22
For individuals with colon cancer, the distribution of polymorphic alleles at
position 83094274 of
chromosome 6, found within the TPBG gene, was different from those without
colon cancer (Table
22). The recessive test for risk associated with carrying the T allele had an
empirical p-value of 0.0999
based on permutation analysis, and the corresponding recessive odds ratio is
1.291 (Table 22). These
data further suggest that this marker, located within the TPBG gene, is
associated with colon cancer
risk and that the T allele at position 83094274 of chromosome 6 is associated
with an increased risk of
developing colon cancer.
-73-
CA 02548375 2006-06-13
Table 22
rs no. 723142
Chromosome; Position 6; 83094274
Gene Name TPBG
SEQ ID NO; Position 1131;
Genotype; Phenotype n=T; increased risk
Hardy-Weinber 0.0954124
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 496 367 88 Recessive 0.0999e 1.291
1 4 387 380 101
Table 22A indicates SNPs found to be in strong linkage disequilibrium with
rs723142. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 22A Linked SNPs
SNP r 2 Position on chr6 SEQ ID NO
rs2323642 0.621 82950808 556
rs540814 0.553 83037702 557
rs2753211 0.682 83052756 558
rs2753212 0.696 83052893 559
rs9344267 0.797 83059529 560
rs62953 0.768 83059811 561
rs529833 0.754 83063355 562
rs544734 0.959 83065585 563
rs554594 0.959 83065715 564
rs511002 1.0 83066965 565
rs507500 0.921 83067321 566
rs532219 1.0 83079412 567
rs577767 0.959 83086171 568
rs526833 0.958 83086772 569
rs7756828 1.0 83087733 570
rs508106 1.0 83088471 571
rs555844 0.921 83089659 572
rs1923137 1.0 83092525 573
rs1923138 0.958 83092537 574
rs723142 - 83094274 575
rs2180742 1.0 83094499 576
rs1547614 0.959 83094576 577
rs2145368 1.0 83095347 578
rs2180743 1.0 83095565 579
rs7762072 0.956 83095939 580
rs13191698 0.921 83096974 581
rs13207433 0.959 83097004 582
rs1321622 0.879 83097222 583
rs9353066 0.921 83098262 584
rs6907015 0.959 83098329 585
-74-
CA 02548375 2006-06-13
rs6930014 0.959 83098352 586
rs9353067 0.875 83100260 587
rs9353068 1.0 83101000 588
rs2024996 0.879 83103870 589
rs796398 0.959 83113039 590
rs770904 0.916 83114887 591
rs770897 0.786 83120523 592
rs770898 0.755 83122607 593
rs770895 0.778 83127291 594
rs1570140 0.759 83129590 595
rs770911 0.759 83131084 596
rs1275806 0.664 83137358 597
rs770906 0.525 83140060 598
rs932614 0.525 83146661 599
rs9344274 0.517 83147795 600
rs1951006 0.528 83150543 601
rs9449462 0.515 83153296 602
rs9361914 0.514 83155501 603
rs714133 0.528 83162032 604
rs1998204 0.517 83163350 605
rs1853143 0.517 83165082 606
rs4706945 0.528 83165771 607
rs9449469 0.528 83167427 608
rs9449470 0.552 83167802 609
rs4706948 0.514 83168404 610
rs2875128 0.541 83169297 611
rs6912008 0.517 83169493 612
rs9449475 0.631 83170215 613
rs967730 0.562 83170490 614
rs967731 0.552 83170598 615
rs9361923 0.517 83172329 616
Example 23
For individuals with colon cancer, the distribution of polymorphic alleles at
position 9440613 of
chromosome 8, found within the TNKS gene, was different from those without
colon cancer (Table
23). The trend test for risk associated with carrying the A allele had an
empirical p-value of 0.0462
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.148
(Table 23). These data further suggest that this marker, located within the
TNKS gene, is associated
with colon cancer risk and that the A allele at position 9440613 of chromosome
8 is associated with an
increased risk of developing colon cancer.
-75-
CA 02548375 2006-06-13
Table 23
rs no. 6601328
Chromosome; Position 8; 9440613
Gene Name TNKS
SEQ ID NO; Position 1132;
Genotype; Phenotype n=A; increased risk
Hard -Weinber 0.162
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 26 263 950 Trend 0.0462e 1.148
1 1 8 250 968
Table 23A indicates SNPs found to be in strong linkage disequilibrium with
rs6601328. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 23A Linked SNPs
SNP r 2 Position on chr8 SEQ ID NO
rs17150201 0.88 9426711 617
rs1471203 0.803 9431741 618
rs7009486 0.891 9436057 619
rs13261395 1.0 9436101 620
rs4841169 0.891 9436786 621
rs4840423 1.0 9437029 622
rs4841171 1.0 9437099 623
rs11785485 1.0 9439838 624
rs7388554 0.88 9440072 625
rs6601328 - 9440613 626
rs11781665 1.0 9444872 627
rs7013834 1.0 9452052 628
rs13274310 1.0 9458679 629
rs13265363 0.891 9460336 630
rs11784858 0.785 9463104 631
rs13270240 0.847 9468129 632
rs11775432 1.0 9480306 633
rs4551359 1.0 9503674 634
rs11774818 1.0 9523873 635
rs4841186 1.0 9526021 636
rs4840432 1.0 9526193 637
rs11994018 1.0 9531111 638
rs11991547 1.0 9538857 639
rs7839648 0.891 9541393 640
rs4128324 1.0 9546289 641
rs11780274 1.0 9558649 642
rs13250838 1.0 9563755 643
rs13264510 1.0 9568067 644
rs13261385 1.0 9568084 645
rs4570159 1.0 9568712 646
-76-
CA 02548375 2006-06-13
rs13259379 0.891 9640154 647
rs4289816 0.88 9645506 648
rs 17734024 0.891 9673180 649
Example 24
For individuals with colon cancer, the distribution of polymorphic alleles at
position 105447572 of
chromosome 8 was different from those without colon cancer (Table 24). The
dominant test for risk
associated with carrying the G allele had an empirical p-value based on
pertnutation analysis of
0.0432, and the corresponding dominant odds ratio is 1.206 (Table 24). These
data further suggest that
this marker is associated with colon cancer risk and that the G allele at
position 105447572 of
chromosome 8 is associated with an increased risk of developing colon cancer.
Table 24
rs no. 2853129
Chromosome; Position 8; 105447572
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=G; increased risk
rg 0.127
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 3 941 269 28 Dominant 0.0432e 1.206
1 3 888 314 24
Table 24A indicates SNPs found to be in strong linkage disequilibrium with
rs2853129. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 24A Linked SNPs
SNP r2 Position on chr8 SEQ ID NO
rs2853129 - 105447572 650
Example 25
For individuals with colon cancer, the distribution of polymorphic alleles at
position 138583352 of
chromosome 8 was different from those without colon cancer (Table 25). The
trend test for risk
associated with carrying the C allele had an empirical p-value of 0.0016 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.264
(Table 25). These data
further suggest that this marker is associated with colon cancer risk and that
the C allele at position
138583352 of chromosome 8 is associated with an increased risk of developing
colon cancer.
-77-
CA 02548375 2006-06-13
Table 25
rs no. 1399176
Chromosome; Position 8; 138583352
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=C; increased risk
Hardy-Weinberg 0.0940461
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 693 255 14 Trend 0.0016e 1.264
1 2 634 271 39
Table 25A indicates SNPs found to be in strong linkage disequilibrium with
rs1:399176. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 25A Linked SNPs
SNP r2 Position on chr8 SEQ ID NO
rs4909649 0.835 138448609 651
rs4909652 0.835 138448978 652
rs7000235 0.835 138450507 653
rs7833216 0.835 138450935 654
rs6986763 0.835 138451287 655
rs4265216 0.821 138452272 656
rs4391470 0.835 138452507 657
rs13249389 0.834 138452835 658
rs10102751 0.835 138453471 659
rs4532628 0.835 138454113 660
rs4279630 0.829 138454197 661
rs4474054 0.835 138454235 662
rs4909654 0.835 138454833 663
rs4292724 0.835 138455486 664
rs12541665 0.835 138455728 665
rs4909657 0.82 138456184 666
rs4909367 0.652 138456296 667
rs7820493 0.835 138456395 668
rs7837229 0.835 138457265 669
rs13253269 0.83 138458205 670
rs7014387 0.835 138458287 671
rs7826913 0.835 138458607 672
rs6577786 0.835 138459228 673
rs7835685 0.835 138459736 674
rs4909658 0.833 138460258 675
rs4909659 0.835 138460320 676
rs4909660 0.835 138460491 677
rs6577788 0.835 138461455 678
rs6577789 0.835 138461471 679
rs7845225 0.835 138461926 680
-78-
CA 02548375 2006-06-13
rs7827162 0.835 138462319 681
rs4131207 0.796 138467267 682
rs4131208 0.835 138467277 683
rs7016247 0.835 138467539 684
rs7007938 0.835 138469853 685
rs10875404 0.835 138469883 686
rs6577790 0.835 138472916 687
rs4909665 0.835 138473941 688
rs6577792 0.828 138477490 689
rs4582597 0.835 138481482 690
rs10098545 0.819 138482393 691
rs2943199 0.86 138490184 692
rs2960100 0.835 138498734 693
rs11166725 0.958 138545196 694
rs17629911 0.958 138546484 695
rs10505682 0.837 138551497 696
rs17632067 1.0 138576626 697
rs11786383 1.0 138578139 698
rs11773949 0.628 138580074 699
rs1399176 - 138583352 700
rs10505684 0.628 138585809 701
rs7816962 0.628 138585968 702
rs6577803 0.606 138586498 703
rs6996799 0.606 138588282 704
rs17683816 0.959 138590203 705
rs12677749 0.959 138590751 706
rs6981747 0.957 138594903 707
rs4384013 0.958 138601596 708
rs4625065 0.959 138601771 709
rs11786764 0.959 138603600 710
rs11786786 0.959 138603658 711
rs11776612 0.959 138603708 712
rs1913453 0.959 138604408 713
rs17633935 0.959 138607169 714
rs12677813 0.959 138608732 715
rs11780534 0.959 138610100 716
rs11777429 0.958 138610110 717
rs17634044 0.959 138610517 718
rs11166729 0.959 138611185 719
rs1514199 0.959 138611655 720
rs1514200 0.954 138611699 721
rs1514201 0.953 138611757 722
rs11780105 0.954 138612308 723
rs12375358 0.959 138614096 724
rs10505685 0.958 138614490 725
rs11778762 0.959 138615852 726
rs1514202 0.954 138616621 727
rs1514203 0.959 138616711 728
rs1514204 0.959 138616778 729
Example 26
-79-
CA 02548375 2006-06-13
For individuals with colon cancer, the distribution of polymorphic alleles at
position 138614490 of
chromosome 8 was different from those without colon cancer (Table 26). The
trend test for risk
associated with carrying the C allele had an empirical p-value of 0.0017 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.289
(Table 26). These data
further suggest that this marker is associated with colon cancer risk and that
the C allele at position
138614490 of chromosome 8 is associated with an increased risk of developing
colon cancer.
Table 26
rs no. 10505685
Chromosome; Position 8; 138614490
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=C; increased risk
Hardy-Weinberg 0.2288
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 683 191 19 Trend 0.0017e 1.289
1 2 626 210 42
Table 26A indicates SNPs found to be in strong linkage disequilibrium with
rs10505685. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 26A Linked SNPs
SNP r 2 Position on chr8 SEQ ID NO
rs4909649 0.794 138448609 651
rs4909652 0.794 138448978 652
rs7000235 0.794 138450507 653
rs7833216 0.794 138450935 654
rs6986763 0.794 138451287 655
rs4265216 0.777 138452272 656
rs4391470 0.794 138452507 657
rs13249389 0.793 138452835 658
rs10102751 0.794 138453471 659
rs4532628 0.794 138454113 660
rs4279630 0.788 138454197 661
rs4474054 0.794 138454235 662
rs4909654 0.794 138454833 663
rs4292724 0.794 138455486 664
rs12541665 0.794 138455728 665
rs4909657 0.776 138456184 666
rs4909367 0.641 138456296 667
rs7820493 0.794 138456395 668
rs7837229 0.794 138457265 669
rs13253269 0.789 138458205 670
rs7014387 0.794 138458287 671
rs7826913 0.794 138458607 672
-80-
CA 02548375 2006-06-13
rs6577786 0.794 138459228 673
rs7835685 0.794 138459736 674
rs4909658 0.792 138460258 675
rs4909659 0.794 138460320 676
rs4909660 0.794 138460491 677
rs6577788 0.794 138461455 678
rs6577789 0.794 138461471 679
rs7845225 0.794 138461926 680
rs7827162 0.794 138462319 681
rs4131207 0.755 138467267 682
rs4131208 0.794 138467277 683
rs7016247 0.794 138467539 684
rs7007938 0.794 138469853 685
rs10875404 0.794 138469883 686
rs6577790 0.794 138472916 687
rs4909665 0.794 138473941 688
rs6577792 0.786 138477490 689
rs4582597 0.794 138481482 690
rs10098545 0.774 138482393 691
rs2943199 0.815 138490184 692
rs2960100 0.794 138498734 693
rs11166725 0.916 138545196 694
rs17629911 0.916 138546484 695
rs10505682 0.797 138551497 696
rs17632067 0.957 138576626 697
rs11786383 0.958 138578139 698
rs11773949 0.585 138580074 699
rs1399176 0.958 138583352 700
rs10505684 0.585 138585809 701
rs7816962 0.585 138585968 702
rs6577803 0.626 138586498 703
rs6996799 0.626 138588282 704
rs17683816 1.0 138590203 705
rs 12677749 1.0 13 8590751 706
rs6981747 1.0 138594903 707
rs4384013 0.957 138601596 708
rs4625065 1.0 138601771 709
rs11786764 1.0 138603600 710
rs11786786 1.0 138603658 711
rs11776612 1.0 138603708 712
rs1913453 1.0 138604408 713
rs17633935 1.0 138607169 714
rs12677813 1.0 138608732 715
rs11780534 1.0 138610100 716
rs11777429 1.0 138610110 717
rs17634044 1.0 138610517 718
rs11166729 1.0 138611185 719
rs1514199 1.0 138611655 720
rs1514200 1.0 138611699 721
rs1514201 1.0 138611757 722
-81-
CA 02548375 2006-06-13
rs11780105 1.0 138612308 723
rs12375358 1.0 138614096 724
rs10505685 - 138614490 725
rs11778762 1.0 138615852 726
rs1514202 1.0 138616621 727
rs1514203 1.0 138616711 728
rs1514204 1.0 138616778 729
Example 27
For individuals with colon cancer, the distribution of polymorphic alleles at
position 141587219 of
chromosome 8, found within the CHRACI gene, was different from those without
colon cancer
(Table 27). The dominant test for risk associated with carrying the A allele
had an asymptotic p-value
of 0.04448, and the corresponding dominant odds ratio is 1.697 (Table 27).
These data further suggest
that this marker, located within the CHRAC I gene, is associated with colon
cancer risk and that the A
allele at position 141587219 of chromosome 8 is associated with an increased
risk of developing
colon cancer.
Table 27
rs no. 1057083
Chromosome; Position 8; 141587219
Gene Name CHRAC 1
SEQ ID NO; Position 1133;
Genotype; Phenotype n=C; increased risk
erg 0.012
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 39 288 912 Dominant 0.04448a 1.697
1 1 23 334 867
Table 27A indicates SNPs found to be in strong linkage disequilibrium with
rs1057083. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 27A Linked SNPs
SNP r2 Position on chr8 SEQ ID NO
rs12676904 0.806 141567935 730
rs4961309 1.0 141583366 731
rs1057083 - 141587219 732
rs6578111 1.0 141589763 733
rs4961323 1.0 141595413 734
rs10216653 1.0 141596167 735
rs4610723 0.951 141596488 736
rs7388327 0.521 141597272 737
Example 28
-82-
CA 02548375 2006-06-13
For individuals with colon cancer, the distribution of polymorphic alleles at
position 6355683 of
chromosome 9, found within the NYD-SP25 gene, was different from those without
colon cancer
(Table 28). The trend test for risk associated with carrying the A allele had
an empirical p-value of
0.0039 based on permutation analysis, and the corresponding Mantel-Haenszel
odds ratio for trend is
1.229 (Table 28). These data further suggest that this marker, located within
the NYD-SP25 gene, is
associated with colon cancer risk and that the A allele at position 6355683 of
chromosome 9 is
associated with an increased risk of developing colon cancer.
Table 28
rs no. 719725
Chromosome; Position 9; 6355683
Gene Name NYD-SP25
SEQ ID NO; Position 1134;
Genotype; Phenotype n=A; increased risk
Hardy-Weinberg 0.628649
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 139 437 367 Trend 0.0039e 1.229
1 1 109 355 398
Table 28A indicates SNPs found to be in strong linkage disequilibrium with
rs'719725. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 28A Linked SNPs
SNP r 2 Position on chr9 SEQ ID NO
rs744567 0.509 6282602 738
rs17756142 0.553 6291578 739
rs1322166 0.57 6299862 740
rs4742179 0.518 6314376 741
rs10758764 0.511 6316825 742
rs10491836 0.649 6321421 743
rs16924356 0.615 6321610 744
rs721352 0.518 6322901 745
rs7850988 0.649 6325760 746
rs731585 0.546 6332328 747
rs2169282 0.717 6340235 748
rs16924428 0.624 6341111 749
rs10975552 0.966 6341834 750
rs10975553 1.0 6342819 751
rs7022186 1.0 6349144 752
rs7851246 0.649 6352365 753
rs10975558 0.649 6354449 754
rs7875812 1.0 6354533 755
rs719725 - 6355683 756
rs7860427 0.74 6375637 757
rs7025295 0.965 6385247 758
- 83 -
CA 02548375 2006-06-13
rs7850497 0.782 6385540 759
rs10217561 0.782 6386245 760
rs10815428 0.686 6390030 761
rs7045097 0.816 6392856 762
rs10739097 0.834 6397843 763
rs7865955 0.84 6398247 764
rs7857628 0.966 6399874 765
Example 29
For individuals with colon cancer, the distribution of polymorphic alleles at
position 73642109 of
chromosome 9 was different from those without colon cancer (Table 29). The
trend test for risk
associated with carrying the A allele had an empirical p-value of 0.0034 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.549
(Table 29). The
recessive test for risk associated with carrying the A allele had an empirical
p-value based on
permutation analysis of 0.0054, and the corresponding recessive odds ratio is
1.574 (Table 29). These
data further suggest that this marker is associated with colon cancer risk and
that the A allele at
position 73642109 of chromosome 9 is associated with an increased risk of
developing colon cancer.
Table 29
rs no. 10512028
Chromosome; Position 9; 73642109
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=A; increased risk
Hard -Weinber 0.258618
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 6 109 867 Trend 0.0034e 1.549
1 1 --42 72 878 11 Recessive 0.0054e 1.574
Table 29A indicates SNPs found to be in strong linkage disequilibrium with
rs10512028. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 29A Linked SNPs
SNP r 2 Position on chr9 SEQ ID NO
rs4288438 1.0 73606988 766
rs6560355 1.0 73607164 767
rs1585251 1.0 73607569 768
rs4745250 1.0 73612124 769
rs7044457 1.0 73613027 770
rs2061399 1.0 73614943 771
rs2061398 1.0 73615076 772
rs2061396 1.0 73615232 773
rs2061395 1.0 73616781 774
rs10781152 1.0 73617303 775
-84-
CA 02548375 2006-06-13
rs4745254 1.0 73618675 776
rs2168884 1.0 73619146 777
rs4745255 1.0 73622095 778
rs4745256 1.0 73622395 779
rs4745257 1.0 73622439 780
rs4745258 1.0 73625852 781
rs4745259 1.0 73626601 782
rs4745260 1.0 73626706 783
rs7389572 1.0 73627824 784
rs10746927 1.0 73628740 785
rs7048840 1.0 73629704 786
rs4744695 1.0 73633747 787
rs981197 1.0 73634385 788
rs1458489 1.0 73635467 789
rs1379909 1.0 73635691 790
rs1379910 1.0 73635782 791
rs1902976 1.0 73636447 792
rs1902978 1.0 73636612 793
rs7026566 1.0 73636831 794
rs1379911 1.0 73638980 795
rs7027893 1.0 73639771 796
rs7039655 1.0 73639895 797
rs4468001 1.0 73640222 798
rs10512028 - 73642109 799
rs999791 1.0 73642315 800
rs17059425 1.0 73643177 801
Example 30
For individuals with colon cancer, the distribution of polymorphic alleles at
position 79353007 of
chromosome 9 was different from those without colon cancer (Table 30). The
trend test for risk
associated with carrying the T allele had an empirical p-value of 0.0078 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.699
(Table 30). These data
further suggest that this marker is associated with colon cancer risk and that
the T allele at position
79353007 of chromosome 9 is associated with an increased risk of developing
colon cancer.
Table 30
rs no. 946807
Chromosome; Position 9; 79353007
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=T; increased risk
rg 0.394131
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 0 75 909 Trend 0.0078e 1.699
1 4 1 43 913
-85-
CA 02548375 2006-06-13
Table 30A indicates SNPs found to be in strong linkage disequilibrium with
rs946807. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 30A Linked SNPs
SNP r2 Position on chr9 SEQ ID NO
rs946807 - 79353007 802
rs7040700 0.59 79353924 803
rs12005727 1.0 79356465 804
rs12347524 1.0 79356737 805
rs10867398 0.536 79359981 806
Example 31
For individuals with colon cancer, the distribution of polymorphic alleles at
position 5766249 of
chromosome 11, found within the OR52N1 gene, was different from those without
colon cancer
(Table 31). The dominant test for risk associated with carrying the C allele
had an empirical p-value of
0.0058 based on permutation analysis, and the corresponding dominant odds
ratio is 1.561 (Table 31).
These data further suggest that this marker, located within the OR52N1 gene,
is associated with colon
cancer risk and that the C allele at position 5766249 of chromosome 11 is
associated with an increased
risk of developing colon cancer.
Table 31
rs no. 10769224
Chromosome; Position 11; 5766249
Gene Name OR52N1
SEQ ID NO; Position 1135; 374
Genotype; Phenotype n=C; increased risk
Hardy-Weinberg 0.0827504
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 120 464 569 Dominant 0.0058e 1.561
1 2 78 500 548
Table 31A indicates SNPs found to be in strong linkage disequilibrium with
rs10769224. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 31A Linked SNPs
SNP r2 Position on chrll SEQ ID NO
rs7948009 0.825 5766124 807
rs10769224 - 5766249 808
rs10742787 1.0 5766322 809
rs7924824 1.0 5768065 810
rs7949986 1.0 5775192 811
-86-
CA 02548375 2006-06-13
rs7940926 1.0 5778275 812
rs10769235 1.0 5779169 813
rs4758099 1.0 5779725 814
rs4758100 0.804 5779774 815
rs7484069 0.826 5780048 816
rs11039085 0.524 5780227 817
rs7937133 1.0 5781044 818
rs1453418 1.0 5781526 819
rs1453417 0.688 5781557 820
rs11039096 0.845 5781753 821
rs10742793 0.672 5782739 822
rs11039102 0.704 5783829 823
rs11607346 0.634 5784028 824
rs6578689 0.71 5784528 825
rs1453415 0.67 5785595 826
rs1840175 0.67 5786072 827
rs4372479 0.67 5792979 828
rs10734554 0.861 5799485 829
rs7938541 1.0 5800361 830
rs4758444 0.524 5802527 831
rs1979197 0.51 5802898 832
Example 32
For individuals with colon cancer, the distribution of polymorphic alleles at
position 43156746 of
chromosome 11 was different from those without colon cancer (Table 32). The
trend test for risk
associated with carrying the T allele had an empirical p-value of 0.0141 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.213
(Table 32). The
dominant test for risk associated with carrying the T allele had an empirical
p-value based on
permutation analysis of 0.0812, and the corresponding dominant odds ratio is
1.211 (Table 32). These
data further suggest that this marker is associated with colon cancer risk and
that the T allele at
position 43156746 of chromosome 11 is associated with an increased risk of
developing colon cancer.
Table 32
rs no. 890248
Chromosome; Position 11; 43156746
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=T; increased risk
Hard -Weinber 0.536552
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 714 200 11 Trend 0.0141 e 1.213
1 4 637 200 28 Dominant 0.0812e 1211
Table 32A indicates SNPs found to be in strong linkage disequilibrium with
rs890248. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
-87-
CA 02548375 2006-06-13
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 32A Linked SNPs
SNP r 2 Position on chrll SEQ ID NO
rs11601828 0.646 43124098 833
rs11037302 0.704 43145953 834
rs7940185 0.669 43149399 835
rs6485403 0.715 43151108 836
rs2114089 0.688 43153254 837
rs1025168 1.0 43155303 838
rs1353463 1.0 43156052 839
rs890249 0.715 43156514 840
rs890248 - 43156746 841
rs890246 0.748 43156937 842
rs7935140 0.715 43158142 843
rs7938445 1.0 43158508 844
rs977439 1.0 43159402 845
rs7943295 1.0 43160243 846
rs2068405 1.0 43160762 847
rs7933421 0.715 43160895 848
rs959648 1.0 43160975 849
rs959647 0.715 43161066 850
rs10838055 0.715 43161471 851
rs10838056 1.0 43161777 852
rs7129867 1.0 43161927 853
rs7950242 1.0 43167395 854
rs7950144 0.715 43167433 855
rs1318986 1.0 43169005 856
rs1025166 1.0 43169462 857
rs1425857 1.0 43170570 858
rs10768938 1.0 43171231 859
Example 33
For individuals with colon cancer, the distribution of polymorphic alleles at
position 73972614 of
chromosome 11, found within the POLD3 gene, was different from those without
colon cancer (Table
33). The trend test for risk associated with carrying the A allele had an
empirical p-value of 0.0129
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.153
(Table 33). The recessive test for risk associated with carrying the A allele
had an empirical p-value
based on permutation analysis of 0.0286, and the corresponding recessive odds
ratio is 1.223 (Table
33). These data further suggest that this marker, located within the POLD3
gene, is associated with
colon cancer risk and that the A allele at position 73972614 of chromosome 11
is associated with an
increased risk of developing colon cancer.
-88-
CA 02548375 2006-06-13
Table 33
rs no. 11236164
Chromosome; Position 11; 73972614
Gene Name POLD3
SEQ ID NO; Position 1136;
Genotype; Phenotype n=A; increased risk
Hard rg 0.518
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 312 632 295 Trend 0.0129e 1.153
1 1 270 617 339 Recessive 0.0286e 1.223
Table 33A indicates SNPs found to be in strong linkage disequilibrium with rsl
1236164. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 33A Linked SNPs
SNP r2 Position on chrll SEQ ID NO
rs10899009 1.0 73953815 860
rs10793093 0.832 73968600 861
rs11236164 - 73972614 862
rs7940880 0.966 73995062 867
rs10219203 0.96 74002571 868
rs10793094 1.0 74013473 873
rs2117222 0.966 74015333 874
rs2155935 0.966 74017225 876
rs2298792 0.966 74017844 877
rs11236178 0.966 74018984 878
rs3824999 0.966 74023198 879
rs7932922 0.68 74037678 885
rs1944933 0.923 74039262 886
rs11236185 0.928 74040179 887
rs4145954 0.669 74040814 888
rs6421715 0.966 74052598 889
rs11236203 0.966 74055648 890
rs11825804 0.964 74056519 891
rs6592590 0.649 74058677 892
rs11822234 0.631 74062794 893
rs11602237 0.604 74063339 894
rs7104802 0.572 74064448 895
rs17244949 0.632 74067429 897
Example 34
For individuals with colon cancer, the distribution of polymorphic alleles at
position 73982157 of
chromosome 11, found within the POLD3 gene, was different from those without
colon cancer (Table
34). The trend test for risk associated with carrying the C allele had an
empirical p-value of 0.0396
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.177
-89-
CA 02548375 2006-06-13
(Table 34). The recessive test for risk associated with carrying the C allele
had an empirical p-value
based on permutation analysis of 0.0531, and the corresponding recessive odds
ratio is 1.193 (Table
34). These data further suggest that this marker, located within the POLD3
gene, is associated with
colon cancer risk and that the C allele at position 73982157 of chromosome 11
is associated with an
increased risk of developing colon cancer.
Table 34
rs no. 7939226
Chromosome; Position 11; 73982157
Gene Name POLD3
SEQ ID NO; Position 1136; 881
Genotype; Phenotype n=C; increased risk
rg 0.724
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 34 330 875 Trend 0.0396e 1.177
1 2 25 292 909 Recessive 0.0531e 1.193
Table 34A indicates SNPs found to be in strong linkage disequilibrium with
rs7939226. To generate
this list, correlation coefficients (rZ) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 34A Linked SNPs
SNP r 2 Position on chrll SEQ ID NO
rs7944514 0.516 73978840 863
rs7939226 - 73982157 864
rs10899013 0.543 73987190 865
rs6592573 0.543 73990610 866
rs4944051 0.673 74002983 869
rs4145953 0.66 74009527 872
rs1433970 0.673 74016841 875
rs3741127 1.0 74024581 880
rs1051058 0.673 74029849 881
rs7123887 0.636 74033737 882
rs4944922 0.635 74034353 883
rs4944925 0.636 74037177 884
rs12789086 0.747 74067075 896
rs11236208 0.727 74067969 898
rs12282262 0.707 74071586 899
Example 35
For individuals with colon cancer, the distribution of polymorphic alleles at
position 74002983 of
chromosome 11, found within the POLD3 gene, was different from those without
colon cancer (Table
35). The trend test for risk associated with carrying the T allele had an
empirical p-value of 0.0222
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.166
-90-
CA 02548375 2006-06-13
(Table 35). The dominant test for risk associated with carrying the T allele
had an asymptotic p-value
of 0.092236, and the corresponding dominant odds ratio is 1.365 (Table 35).
These data further
suggest that this marker, located within the POLD3 gene, is associated with
colon cancer risk and that
the T allele at position 74002983 of chromosome 11 is associated with an
increased risk of developing
colon cancer.
Table 35
rs no. 4944051
Chromosome; Position 11; 74002983
Gene Name POLD3
SEQ ID NO; Position 1136; 21707
Genotype; Phenotype n=T; increased risk
erg 0.232
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 72 420 747 Trend 0.0222e 1.166
1 4 53 385 788 Dominant 0.092236a 1.365
Table 35A indicates SNPs found to be in strong linkage disequilibrium with
rs494405 1. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 35A Linked SNPs
SNP r 2 Position on chril SEQ ID NO
rs7939226 0.673 73982157 864
rs4944051 - 74002983 869
rs7943085 0.582 74007856 870
rs10501417 0.582 74008628 871
rs4145953 1.0 74009527 872
rs1433970 1.0 74016841 875
rs3741127 0.659 74024581 880
rs1051058 1.0 74029849 881
rs7123887 0.945 74033737 882
rs4944922 0.945 74034353 883
rs4944925 0.945 74037177 884
Example 36
For individuals with colon cancer, the distribution of polymorphic alleles at
position 83565887 of
chromosome 11, found within the DLG2 gene, was different from those without
colon cancer (Table
36). The recessive test for risk associated with carrying the T allele had an
empirical p-value based on
permutation analysis of 0.002, and the corresponding recessive odds ratio is
1.443 (Table 36). These
data further suggest that this marker, located within the DLG2 gene, is
associated with colon cancer
risk and that the T allele at position 83565887 of chromosome 11 is associated
with an increased risk
of developing colon cancer.
-91-
CA 02548375 2006-06-13
Table 36
rs no. 1454027
Chromosome; Position 11; 83565887
Gene Name DLG2
SEQ ID NO; Position 1137; 746200
Genotype; Phenotype n=T; increased risk
Hard -Weinber 0.0879631
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 8 197 626 Recessive 0.002e 1.443
1 4 12 143 683
Table 36A indicates SNPs found to be in strong linkage disequilibrium with
rs1454027. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 36A Linked SNPs
SNP r 2 Position on chrll SEQ ID NO
rs790367 0.536 83325571 900
rs790368 0.536 83325870 901
rs1599914 0.535 83326348 902
rs790372 0.536 83331489 903
rs1471687 0.607 83333982 904
rs790351 0.536 83338726 905
rs2449592 0.536 83346857 906
rs2449594 0.536 83359180 907
rs2514171 0.536 83378990 908
rs2449575 0.536 83383578 909
rs1817515 0.536 83385447 910
rs7933909 0.534 83386501 911
rs1483387 0.536 83387013 912
rs1586143 0.536 83389630 913
rs1118277 0.508 83389983 914
rs1304480 0.536 83390829 915
rs2170707 0.536 83400665 916
rs1483388 0.536 83402660 917
rs2514167 0.536 83403491 918
rs2514166 0.536 83403720 919
rs10751101 0.536 83404929 920
rs2853026 0.536 83418135 921
rs1601094 0.536 83420693 922
rs1160818 0.536 83430317 923
rs7114261 0.773 83504794 924
rs7108582 0.773 83508907 925
rs1945824 0.749 83523059 926
rs10501555 0.773 83525615 927
rs1014066 0.773 83527163 928
rs2000961 0.773 83532440 929
rs1584854 0.536 83540697 930
-92-
CA 02548375 2006-06-13
rs1598073 0.536 83542042 931
rs1454019 0.773 83548041 932
rs1869472 1.0 83555723 933
rs1454027 - 83565887 934
rs970226 1.0 83569470 935
rs1670685 0.536 83570172 936
rs7943267 0.891 83572107 937
rs988322 1.0 83574800 938
rs1377746 1.0 83576676 939
rs7941004 0.881 83594342 940
rs4944472 0.784 83599752 941
rs10751109 0.773 83601427 942
Example 37
For individuals with colon cancer, the distribution of polymorphic alleles at
position 31141128 of
chromosome 12, found within the DDXI 1 gene, was different from those without
colon cancer (Table
37). The dominant test for risk associated with carrying the G allele had an
asymptotic p-value of
0.023884, and the corresponding dominant odds ratio is 1.222 (Table 37). These
data further suggest
that this marker, located within the DDX11 gene, is associated with colon
cancer risk and that the G
allele at position 31141128 of chromosome 12 is associated with an increased
risk of developing
colon cancer.
Table 37
rs no. 2075322
Chromosome; Position 12; 31141128
Gene Name DDX 11
SEQ ID NO; Position 1138; 23052
Genotype; Phenotype n=G; increased risk
Hard -Weinber 0.438
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 3 386 595 252 Dominant 0.023884a 1.222
1 3 333 619 274
Table 37A indicates SNPs found to be in strong linkage disequilibrium with
rs2075322. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 37A Linked SNPs
SNP r2 Position on chrl2 SEQ ID NO
rs2075322 - 31141128 945
Example 38
For individuals with colon cancer, the distribution of polymorphic alleles at
position 31157554 of
chromosome 12, found within the DDX11 gene, was different from those without
colon cancer (Table
-93-
CA 02548375 2006-06-13
38). The trend test for risk associated with carrying the A allele had an
empirical p-value of 0.0363
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.138
(Table 38). The dominant test for risk associated with carrying the A allele
had an empirical p-value
based on permutation analysis of 0.0451, and the corresponding dominant odds
ratio is 1.179 (Table
38). These data further suggest that this marker, located within the DDX11
gene, is associated with
colon cancer risk and that the A allele at position 31157554 of chromosome 12
is associated with an
increased risk of developing colon cancer.
Table 38
rs no. 4931434
Chromosome; Position 12; 31157554
Gene Name DDX 11
SEQ ID NO; Position 1138;
Genotype; Phenotype n=A; increased risk
Hard rg 0.928
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 548 554 137 Trend 0.0363e 1.138
1 1 493 577 156 Dominant 0.0451 e 1,.179
Table 38A indicates SNPs found to be in strong linkage disequilibrium with
rs4931434. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 38A Linked SNPs
SNP r2 Position on chr12 SEQ ID NO
rs11051239 0.534 31132974 943
rs1808348 0.515 31136113 944
rs4931432 0.588 31144153 946
rs11219 0.588 31148962 947
rs1974752 0.588 31149995 948
rs2111770 0.581 31152638 949
rs2005900 0.588 31152965 950
rs1053552 0.588 31156037 951
rs4931434 - 31157554 952
rs4244856 0.581 31157580 953
Example 39
For individuals with colon cancer, the distribution of polymorphic alleles at
position 21875373 of
chromosome 13 was different from those without colon cancer (Table 39). The
trend test for risk
associated with carrying the G allele had an empirical p-value of 0.0071 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.722
(Table 39). These data
further suggest that this marker is associated with colon cancer risk and that
the G allele at position
21875373 of chromosome 13 is associated with an increased risk of developing
colon cancer.
-94-
CA 02548375 2006-06-13
Table 39
rs no. 10507308
Chromosome; Position 13; 21875373
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=G; increased risk
Hardy-Weinberg 0.361024
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 3 941 40 1 Trend 0.0071 e 1.722
1 3 843 63 1
Table 39A indicates SNPs found to be in strong linkage disequilibrium with
rs10507308. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An rZ cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 39A Linked SNPs
SNP r 2 Position on chr13 SEQ ID NO
rs9506845 0.66 21846344 954
rs2038713 1.0 21860220 955
rs692783 0.59 21868669 956
rs573671 0.589 21868693 957
rs1886088 0.59 21870958 958
rs9316962 0.59 21873258 959
rs10507308 - 21875373 960
Example 40
For individuals with colon cancer, the distribution of polymorphic alleles at
position 32659011 of
chromosome 13, found within the STARD13 gene, was different from those without
colon cancer
(Table 40). The recessive test for risk associated with carrying the A allele
had an empirical p-value
based on permutation analysis of 0.0023, and the corresponding recessive odds
ratio is 1.316 (Table
40). These data further suggest that this marker, located within the STARDI3
gene, is associated with
colon cancer risk and that the A allele at position 32659011 of chromosome 13
is associated with an
increased risk of developing colon cancer.
Table 40
rs no. 797206
Chromosome; Position 13; 32659011
Gene Name STARD 13
SEQ ID NO; Position 1139; 98882
Genotype; Phenotype n=A; increased risk
Hard -Weinber 0.752433
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 1 75 401 507 Recessive 0.0023e 1.316
1 1 58 340 558
-95-
CA 02548375 2006-06-13
Table 40A indicates SNPs found to be in strong linkage disequilibrium with
rs797206. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 40A Linked SNPs
SNP r2 Position on chrl3 SEQ ID NO
rs797227 0.68 32643593 961
rs797211 0.636 32655052 962
rs797208 0.951 32658737 963
rs797206 - 32659011 964
rs797201 0.904 32665137 965
Example 41
For individuals with colon cancer, the distribution of polymorphic alleles at
position 45440577 of
chromosome 13, found within the KIAA0853 gene, was different from those
without colon cancer
(Table 41). The trend test for risk associated with carrying the G allele had
an empirical p-value of
0.0962 based on permutation analysis, and the corresponding Mantel-Haenszel
odds ratio for trend is
1.110 (Table 41). These data further suggest that this marker, located within
the KIAA0853 gene, is
associated with colon cancer risk and that the G allele at position 45440577
of chromosome 13 is
associated with an increased risk of developing colon cancer.
Table 41
rs no. 4941537
Chromosome; Position 13; 45440577
Gene Name KIAA0853
SEQ ID NO; Position 1140; 84319
Genotype; Phenotype n=G; increased risk
Hardy-Weinberg 0.145
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 3 484 560 194 Trend 0.0962e 1.110
1 3 427 602 197
Table 41A indicates SNPs found to be in strong linkage disequilibrium with
rs4941537. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 41A Linked SNPs
SNP r2 Position on chrl3 SEQ ID NO
rs7325308 1.0 45412663 966
rs2075427 1.0 45413606 967
rs1080107 0.733 45414960 968
rs6561274 1.0 45416097 969
rs9534258 1.0 45418874 970
-96-
CA 02548375 2006-06-13
rs4460970 1.0 45438294 971
rs4941537 - 45440577 972
rs9534265 1.0 45445023 973
rs4942460 1.0 45448444 974
rs9316177 0.962 45459812 975
rs9534272 1.0 45464824 976
rs4941538 1.0 45484610 977
rs1409436 0.926 45512651 978
rs3783200 0.744 45514463 979
rs1087 0.636 45525440 980
rs9534304 0.568 45538603 981
rs9526136 0.642 45539148 982
rs9316179 0.578 45539467 983
rs9316180 0.578 45539686 984
rs9562635 0.591 45540993 986
rs7988836 0.655 45541374 987
rs7993537 0.578 45541562 988
rs9316181 0.578 45543741 989
rs1409434 0.578 45544445 990
rs3742264 0.601 45546095 991
rs9567615 0.607 45549081 992
rs9567618 0.578 45549309 993
rs1326398 0.523 45550691 994
rs723391 0.555 45553450 995
rs9534322 0.509 45568003 996
rs1952187 0.524 45572910 997
Example 42
For individuals with colon cancer, the distribution of polymorphic alleles at
position 45525440 of
chromosome 13, found within the CPB2 gene, was different from those without
colon cancer (Table
42). The trend test for risk associated with carrying the T allele had an
empirical p-value of 0.0119
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.167
(Table 42). These data further suggest that this marker, located within the
CPB2 gene, is associated
with colon cancer risk and that the T allele at position 45525440 of
chromosome 13 is associated with
an increased risk of developing colon cancer.
Table 42
rs no. 1087
Chromosome; Position 13; 45525440
Gene Name CPB2
SEQ ID NO; Position 1141; 51730
Genotype; Phenotype n=T; increased risk
Hardy-Weinberg 0.478
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 576 529 134 Trend 0.0119e 1.167
1 4 510 558 157
-97-
CA 02548375 2006-06-13
Table 42A indicates SNPs found to be in strong linkage disequilibrium with
rs1087. To generate this
list, correlation coefficients (r2) were calculated between the index SNP and
all neighboring SNPs
cited in the January 2006 HapMap data set release. An rZ cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 42A Linked SNPs
SNP r2 Position on chrl3 SEQ ID NO
rs7325308 0.636 45412663 966
rs2075427 0.636 45413606 967
rs6561274 0.697 45416097 969
rs9534258 0.636 45418874 970
rs4460970 0.666 45438294 971
rs4941537 0.636 45440577 972
rs9534265 0.613 45445023 973
rs4942460 0.636 45448444 974
rs9316177 0.607 45459812 975
rs9534272 0.634 45464824 976
rs4941538 0.636 45484610 977
rs1409436 0.577 45512651 978
rs3783200 0.744 45514463 979
rs1087 - 45525440 980
rs9534304 0.96 45538603 981
rs9526136 0.957 45539148 982
rs9316179 0.961 45539467 983
rs9316180 0.961 45539686 984
rs9534305 0.724 45540157 985
rs9562635 0.958 45540993 986
rs7988836 0.917 45541374 987
rs7993537 0.961 45541562 988
rs9316181 0.961 45543741 989
rs1409434 0.961 45544445 990
rs3742264 0.961 45546095 991
rs9567615 0.956 45549081 992
rs9567618 0.961 45549309 993
rs1326398 0.885 45550691 994
rs723391 0.85 45553450 995
rs1952187 0.811 45572910 997
Example 43
For individuals with colon cancer, the distribution of polymorphic alleles at
position 46146164 of
chromosome 15 was different from those without colon cancer (Table 43). The
dominant test for risk
associated with carrying the C allele had an asymptotic p-value of 0.0017368,
and the corresponding
dominant odds ratio is 1.516 (Table 43). These data further suggest that this
marker is associated with
colon cancer risk and that the C allele at position 46146164 of chromosome 15
is associated with an
increased risk of developing colon cancer.
-98-
CA 02548375 2006-06-13
Table 43
rs no. 2469583
Chromosome; Position 15; 46146164
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=C; increased risk
Hardy-Weinber 0.0967368
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 161 486 293 Dominant 0.0017368a 1.516
1 2 110 467 340
Table 43A indicates SNPs found to be in strong linkage disequilibrium with
rs2469583. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 43A Linked SNPs
SNP r2 Position on chr15 SEQ ID NO
rs17423970 0.706 46089356 998
rs2081619 0.964 46101819 999
rs17424213 0.965 46103228 1000
rs11070622 0.965 46108382 1001
rs1869453 0.965 46111620 1002
rs17340116 0.965 46114858 1003
rs1453857 0.965 46116200 1004
rs1453856 0.965 46116311 1005
rsl2324567 0.965 46116717 1006
rs748848 0.965 46118326 1007
rs930016 0.962 46118529 1008
rs930017 0.965 46118841 1009
rs1453855 0.965 46120302 1010
rs1025199 1.0 46126798 1011
rs11070623 1.0 46136739 1012
rs2433363 1.0 46139544 1013
rs1426655 0.964 46145643 1014
rs2469583 - 46146164 1015
rs2469581 0.964 46149357 1016
Example 44
For individuals with colon cancer, the distribution of polymorphic alleles at
position 93233505 of
chromosome 15 was different from those without colon cancer (Table 44). The
dominant test for risk
associated with carrying the C allele had an empirical p-value of 0.021 based
on permutation analysis,
and the corresponding dominant odds ratio is 1.649 (Table 44). These data
further suggest that this
marker is associated with colon cancer risk and that the C allele at position
93233505 of chromosome
is associated with an increased risk of developing colon cancer.
-99-
CA 02548375 2006-06-13
Table 44
rs no. 4372639
Chromosome; Position 15; 93233505
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=C; increased risk
rg 0.48238
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 61 343 547 Dominant 0.021e 1.649
1 2 35 287 555
Table 44A indicates SNPs found to be in strong linkage disequilibrium with
rs4372639. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 44A Linked SNPs
SNP r 2 Position on chrl5 SEQ ID NO
rs6496053 0.795 93195638 1017
rs12439498 0.681 93202040 1018
rs4984579 1.0 93217814 1019
rs4489958 1.0 93221398 1020
rs6416529 1.0 93222123 1021
rs4247091 0.919 93226669 1022
rs6496059 1.0 93229804 1023
rs6496060 1.0 93231817 1024
rs6496061 1.0 93232312 1025
rs4372639 - 93233505 1026
rs766233 0.742 93238457 1027
rs12440481 1.0 93261273 1028
rs4306453 0.947 93263139 1029
rs4247087 1.0 93264699 1030
rs1562628 1.0 93265029 1031
rs6496067 1.0 93266435 1032
rs6496068 1.0 93266453 1033
rs11630913 1.0 93267466 1034
rs9920787 0.649 93277598 1035
rs6416531 0.569 93279847 1036
Example 45
For individuals with colon cancer, the distribution of polymorphic alleles at
position 97282996 of
chromosome 15, found within the IGF1R gene, was different from those without
colon cancer (Table
45). The trend test for risk associated with carrying the C allele had an
asymptotic p-value of
0.099586, and the corresponding Mantel-Haenszel odds ratio for trend is 1.300
(Table 45). The
recessive test for risk associated with carrying the C allele had an
asymptotic p-value of 0.049715, and
the corresponding recessive odds ratio is 1.321 (Table 45). These data further
suggest that this marker,
- 100 -
CA 02548375 2006-06-13
located within the IGF1R gene, is associated with colon cancer risk and that
the C allele at position
97282996 of chromosome 15 is associated with an increased risk of developing
colon cancer.
Table 45
rs no. 3743262
Chromosome; Position 15; 97282996
Gene Name IGF 1 R
SEQ ID NO; Position 1142; 272709
Genotype; Phenotype n=C; increased risk
Hardy-Weinberg 1
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 2 3 122 1114 Trend 0.099586- 1.300
1 2 6 90 1130 Recessive 0.049715a 1.321
Table 45A indicates SNPs found to be in strong linkage disequilibrium with
rs3743262. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 45A Linked SNPs
SNP r2 Position on chr15 SEQ ID NO
rs3743262 - 97282996 1037
Example 46
For individuals with colon cancer, the distribution of polymorphic alleles at
position 99773203 of
chromosome 15, found within the PCSK6 gene, was different from those without
colon cancer (Table
46). The trend test for risk associated with carrying the T allele had an
empirical p-value of 0.0095
based on permutation analysis, and the corresponding Mantel-Haenszel odds
ratio for trend is 1.181
(Table 46). The dominant test for risk associated with carrying the T allele
had an empirical p-value of
0.0041 based on permutation analysis, and the corresponding dominant odds
ratio is 1.667 (Table 46).
These data further suggest that this marker, located within the PCSK6 gene, is
associated with colon
cancer risk and that the T allele at position 99773203 of chromosome 15 is
associated with an
increased risk of developing colon cancer.
Table 46
rs no. 1994967
Chromosome; Position 15; 99773203
Gene Name PCSK6
SEQ ID NO; Position 1143; 74508
Genotype; Phenotype n=T; increased risk
Hard -Weinber 0.0688478
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 90 366 493 Trend 0.0095e 1.181
1 4 55 355 520 Dominant 0.0041e 1.667
- 101 -
CA 02548375 2006-06-13
Table 46A indicates SNPs found to be in strong linkage disequilibrium with
rs1994967. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 46A Linked SNPs
SNP r 2 Position on chr15 SEQ ID NO
rs1532364 0.81 99768367 1038
rs1108993 0.81 99768718 1039
rs7172235 1.0 99772560 1040
rs12437488 1.0 99772834 1041
rs12912500 1.0 99773041 1042
rs1994967 - 99773203 1043
rs1994968 0.554 99773242 1044
rs4965856 1.0 99775105 1045
rs4965857 1.0 99775156 1046
rs12911482 1.0 99775985 1047
rs2277585 0.515 99785607 1048
Example 47
For individuals with colon cancer, the distribution of polymorphic alleles at
position 23619426 of
chromosome 16, found within the LOC388226 gene, was different from those
without colon cancer
(Table 47). The trend test for risk associated with carrying the G allele had
an empirical p-value of
0.0021 based on permutation analysis, and the corresponding Mantel-Haenszel
odds ratio for trend is
1.234 (Table 47). These data further suggest that this marker, located within
the LOC388226 gene, is
associated with colon cancer risk and that the G allele at position 23619426
of chromosome 16 is
associated with an increased risk of developing colon cancer.
Table 47
rs no. 26764
Chromosome; Position 16; 23619426
Gene Name LOC388226
SEQ ID NO; Position 1144; 12897
Genotype; Phenotype n=G; increased risk
Hardy-Weinberg 0.678458
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 3 650 397 65 Trend 0.0021e 1.234
1 3 566 425 87
Table 47A indicates SNPs found to be in strong linkage disequilibrium with
rs26764. To generate this
list, correlation coefficients (rz) were calculated between the index SNP and
all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
- 102 -
CA 02548375 2006-06-13
Table 47A Linked SNPs
SNP r2 Position on chr16 SEQ ID NO
rs249856 0.638 23566477 1049
rs249870 0.638 23573679 1050
rs249869 0.566 23574058 1051
rs249867 0.638 23576069 1052
rs34514 0.638 23578098 1053
rs34513 0.551 23579493 1054
rs35586 0.638 23584507 1055
rs7588 0.638 23588666 1056
rs40076 0.767 23599906 1057
rs42873 0.637 23602233 1058
rs35634 0.638 23605180 1059
rs26767 0.766 23605958 1060
rs27770 0.638 23609039 1061
rs35633 0.591 23611506 1062
rs26764 - 23619426 1063
rs26763 1.0 23619684 1064
rs26762 1.0 23619949 1065
rs11074570 0.857 23620229 1066
Example 48
For individuals with colon cancer, the distribution of polymorphic alleles at
position 13110425 of
chromosome 17 was different from those without colon cancer (Table 48). The
trend test for risk
associated with carrying the G allele had an empirical p-value of 0.0418 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.132
(Table 48). These data
further suggest that this marker is associated with colon cancer risk and that
the G allele at position
13110425 of chromosome 17 is associated with an increased risk of developing
colon cancer.
Table 48
rs no. 1963296
Chromosome; Position 17; 13110425
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=G; increased risk
Hardy-Weinberg 0.423012
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 3 80 378 510 Trend 0.0418e 1.132
1 3 43 361 495
Table 48A indicates SNPs found to be in strong linkage disequilibrium with
rs1963296. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
-103-
CA 02548375 2006-06-13
Table 48A Linked SNPs
SNP r2 Position on chr17 SEQ ID NO
rs1963296 - 13110425 1067
rs3886341 1.0 13112831 1068
rs11869275 0.956 13114370 1069
rs7212267 0.955 13117081 1070
rs2188894 0.831 13117504 1071
rs2214260 0.831 13117537 1072
Example 49
For individuals with colon cancer, the distribution of polymorphic alleles at
position 34299961 of
chromosome 18 was different from those without colon cancer (Table 49). The
trend test for risk
associated with carrying the T allele had an empirical p-value of 0.0015 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 1.331
(Table 49). These data
further suggest that this marker is associated with colon cancer risk and that
the T allele at position
34299961 of chromosome 18 is associated with an increased risk of developing
colon cancer.
Table 49
rs no. 10502694
Chromosome; Position 18; 34299961
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=T; increased risk
Hard -Weinber 0.785918
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 625 220 17 Trend 0.0015e 1.331
1 4 548 251 31
Table 49A indicates SNPs found to be in strong linkage disequilibrium with rs
10502694. To generate
this list, correlation coefficients (r 2) were calculated between the index
SNP and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 49A Linked SNPs
SNP r 2 Position on chr18 SEQ ID NO
rs10502692 1.0 34294350 1073
rs12373278 1.0 34294807 1074
rs9954810 1.0 34297013 1075
rs10502694 - 34299961 1076
Example 50
For individuals with colon cancer, the distribution of polymorphic alleles at
position 64600521 of
chromosome 18 was different from those without colon cancer (Table 50). The
trend test for risk
associated with carrying the G allele had an empirical p-value of 0.0038 based
on permutation
analysis, and the corresponding Mantel-Haenszel odds ratio for trend is 2.064
(Table 50). The
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CA 02548375 2006-06-13
recessive test for risk associated with carrying the G allele had an empirical
p-value based on
permutation analysis of 0.0038, and the corresponding recessive odds ratio is
2.064 (Table 50). These
data further suggest that this marker is associated with colon cancer risk and
that the G allele at
position 64600521 of chromosome 18 is associated with an increased risk of
developing colon cancer.
Table 50
rs no. 10503122
Chromosome; Position 18; 64600521
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=G; increased risk
Hardy-Weinber 1
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 3 0 50 931 Trend 0.0038e 2.064
1 3 0 23 884 Recessive 0.0038e 2.064
Table 50A indicates SNPs found to be in strong linkage disequilibrium with
rs10503122. To generate
this list, correlation coefficients (rz) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r 2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 50A Linked SNPs
SNP r2 Position on chr18 SEQ ID NO
rs646985 1.0 64574312 1077
rs17079646 1.0 64575303 1078
rs631470 1.0 64575455 1079
rs1676846 1.0 64577169 1080
rs12458298 1.0 64577779 1081
rs17079657 1.0 64578874 1082
rs679650 1.0 64579596 1083
rs12604145 1.0 64580779 1084
rs17079677 1.0 64584139 1085
rs491835 1.0 64586668 1086
rs12457185 1.0 64588166 1087
rs12454555 1.0 64588368 1088
rs12455204 1.0 64589299 1089
rs12607604 1.0 64591510 1090
rs595015 1.0 64592428 1091
rs607696 1.0 64592919 1092
rs12454311 1.0 64593139 1093
rs11151464 1.0 64595151 1094
rs17079696 1.0 64595371 1095
rs677592 1.0 64596256 1096
rs11151465 1.0 64596392 1097
rs499881 1.0 64596771 1098
rs1676853 1.0 64600350 1099
rs10503122 - 64600521 1100
rs656681 1.0 64601827 1101
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rs17079705 1.0 64602989 1102
rs8092610 1.0 64612870 1103
rs17079717 1.0 64618545 1104
Example 51
For individuals with colon cancer, the distribution of polymorphic alleles at
position 20272988 of
chromosome 21 was different from those without colon cancer (Table 51). The
recessive test for risk
associated with carrying the T allele had an empirical p-value of 0.0012 based
on permutation
analysis, and the corresponding recessive odds ratio is 1.425 (Table 51).
These data ftirther suggest
that this marker is associated with colon cancer risk and that the T allele at
position 20272988 of
chromosome 21 is associated with an increased risk of developing colon cancer.
Table 51
rs no. 377685
Chromosome; Position 21; 20272988
Gene Name
SEQ ID NO; Position
Genotype; Phenotype n=T; increased risk
Hard -Weinberg 0.337514
Case Flag Allele B AA AB BB Model p-Value Odds Ratio
0 4 259 506 217 Recessive 0.0012e 1.425
1 4 235 413 262
Table 51A indicates SNPs found to be in strong linkage disequilibrium with
rs377685. To generate
this list, correlation coefficients (r2) were calculated between the index SNP
and all neighboring SNPs
cited in the January 2006 HapMap data set release. An r2 cut off of 0.50 was
selected for inclusion as
evidence for strong genetic linkage.
Table 51A Linked SNPs
SNP r2 Position on chr2l SEQ ID NO
rs2825896 0.564 20218657 1105
rs2825899 0.571 20222308 1106
rs2825905 0.561 20226492 1107
rs2825910 0.591 20228734 1108
rs12482291 0.591 20232506 1109
rs2825922 0.714 20243479 1110
rs2205470 0.714 20251093 1111
rs13047152 0.714 20257959 1112
rs12482827 0.714 20261725 1113
rs377685 - 20272988 1114
rs7281221 0.51 20274521 1115
rs2825928 0.522 20274865 1116
rs2825930 1.0 20279236 1117
rs12482714 1.0 20282727 1118
rs2825941 0.966 20308050 1119
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CA 02548375 2006-06-13
Another aspect of the invention is a method of diagnosing colorectal cancer in
an individual, or
determining whether the individual is at altered risk for colorectal cancer,
by detecting polymorphism
in a subject by treating a tissue sample from the subject with an antibody to
a polymorphic genetic
variant of the present invention and detecting binding of said antibody. A
person of skill in the art
would know how to produce such an antibody (see, for instance, Harlow, E. and
Lane, eds., 1988,
"Antibodies: A Laboratory Manual", Cold Spring Harbor Press, Cold Spring
Harbor). Such antibodies
may include, but are not limited to polyclonal antibodies, monoclonal
antibodies (mAbs), humanized
or chimeric antibodies, single chain antibodies, Fab fragments, F(ab')2
fragments, fragments produced
by a Fab expression library, anti-idiotypic (anti-Id) antibodies, and epitope-
binding fragments of any
of the above. The present invention also provides an animal model to study
colorectal cancer and
susceptibility to colorectal cancer. Such studies can be performed using
transgenic animals. For
example, one can produce transgenic mice, which contain a specific allelic
variant of a containing any
of the SNPs disclosed herein. These mice can be created, e.g., by replacing
their wild-type gene with
an allele containing a SNP disclosed herein, or of the corresponding human
gene containing such a
SNP.
In a preferred embodiment, the present invention provides a transgenic
mammalian animal, said
animal having cells incorporating a recombinant expression system adapted to
express a gene
containing a SNP disclosed herein (preferably the human gene containing a SNP
disclosed herein).
Generally, the recombinant expression system will be stably integrated into
the genome of the
transgenic animal and will thus be heritable so that the offspring of such a
transgenic animal may
themselves contain the transgene. Transgenic animals can be engineered by
introducing the a nucleic
acid molecule containing only the coding portion of the gene into the genome
of animals of interest,
using standard techniques for producing transgenic animals. Animals that can
serve as a target for
transgenic manipulation include, without limitation, mice, rats, rabbits,
guinea pigs, sheep, goats, pigs,
and non-human primates, e.g. baboons, chimpanzees and monkeys. Techniques
known in the art to
introduce a transgene into such animals include pronucleic microinjection
(U.S. Pat. No. 4,873,191);
retrovirus-mediated gene transfer into germ lines (e.g. Van der Putten et al.
1985, Proc. Natl. Acad.
Sci. USA 82: 6148-6152); gene targeting in embryonic stem cells (Thompson et
al., Cell 56 (1989),
313-321); electroporation of embryos and sperm-mediated gene transfer (for a
review, see for
example, U.S. Pat. No. 4,736,866). For the purpose of the present invention,
transgenic animals
include those that carry the recombinant molecule only in part of their cells
("mosaic animals"). The
molecule can be integrated either as a single transgene, or in concatamers.
Selective introduction of a
nucleic acid molecule into a particular cell type is also possible by
following, for example, the
technique of Lasko et al., Proc. Natl. Acad. Sci. USA 89 (1992): 6232-6236.
Particular cells could
also be targeted for molecular incorporation with tissue-specific enhancers.
The expression of the
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CA 02548375 2006-06-13
integrated molecule can be monitored by standard techniques such as in situ
hybridization, Northern
Blot analysis, PCR or immunocytochemistry. Transgenic animals that include a
copy of such a nucleic
acid molecule introduced into the germ line of the animal at an embryonic
stage can be used to
examine the effect of increased expression of DNA encoding the corresponding
protein. In accordance
with this facet of the invention, an animal is treated with the reagent and a
reduceci incidence of the
pathological condition, compared to untreated animals bearing the transgene,
would indicate a
potential therapeutic intervention for the pathological condition.
The present invention has been described in detail by way of illustration and
example in order to
acquaint others skilled in the art with the invention, its principles and its
practical application.
Particular formulations and processes of the present invention are not limited
to the descriptions of the
specific embodiments presented, but rather the descriptions and examples
should be viewed in terms
of the claims that follow and their equivalents. While some of the examples
and descriptions above
include some conclusions about the way the invention may function, the
inventors do not intend to be
bound by those conclusions and functions, but put them forth only as possible
explanations.
It is to be further understood that the specific embodiments of the present
invention as set forth are not
intended as being exhaustive or limiting of the invention, and that many
alternatives, modifications
and variations will be apparent to those of ordinary skill in the art in light
of the foregoing examples
and detailed description. Accordingly, this invention is intended to embrace
all such alternatives,
modifications and variations that fall within the spirit and scope of the
following claims.
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CA 02548375 2006-06-13
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