Chromosomal breakpoints in primary colon cancer cluster at sites of structural variants in the genome.

Abstract

Genomic aberrations on chromosome 8 are common in colon cancer, and are associated with lymph node and distant metastases as well as with disease susceptibility. This prompted us to generate a high-resolution map of genomic imbalances of chromosome 8 in 51 primary colon carcinomas using a custom-designed genomic array consisting of a tiling path of BAC clones. This analysis confirmed the dominant role of this chromosome. Unexpectedly, the position of the breakpoints suggested colocalization with structural variants in the human genome. In order to map these sites with increased resolution and to extend the analysis to the entire genome, we analyzed a subset of these tumors (n = 32) by comparative genomic hybridization on a 185K oligonucleotide array platform. Our comprehensive map of the colon cancer genome confirmed recurrent and specific low-level copy number changes of chromosomes 7, 8, 13, 18, and 20, and unveiled additional, novel sites of genomic imbalances including amplification of a histone gene cluster on chromosome 6p21.1-21.33 and deletions on chromosome 4q34-35. The systematic comparison of segments of copy number change with gene expression profiles showed that genomic imbalances directly affect average expression levels. Strikingly, we observed a significant association of chromosomal breakpoints with structural variants in the human genome: 41% of all copy number changes occurred at sites of such copy number variants (P < 2.2e(-16)). Such an association has not been previously described and reveals a yet underappreciated plasticity of the colon cancer genome; it also points to potential mechanisms for the induction of chromosomal breakage in cancer cells.

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Chromosomal Breakpoints in Primary Colon Cancer Cluster
at Sites of Structural Variants in the Genome
Jordi Camps,
Amanda B. Hummon,
Michael J. Difilippantonio,
1Marian Grade,
1,3Quang Tri Nguyen,
1Virginia Rodriguez,
1Heinz Becker,
1Patrick Ho ¨rmann,
2Settara Chandrasekharappa,
3B. Michael Ghadimi,
1Sandra Becker,
2Yidong Chen,
3and Thomas Ried
1
1
1
1Genetics Branch, Center for Cancer Research, National Cancer Institute/NIH;
Genome Research Institute/NIH, Bethesda, Maryland; and
Go ¨ttingen, Go ¨ttingen, Germany
2Genome Technology Branch, National Human
3Department of General and Visceral Surgery, University Medicine
Abstract
Genomic aberrations on chromosome 8 are common in colon
cancer, and are associated with lymph node and distant
metastases as well as with disease susceptibility. This
prompted us to generate a high-resolution map of genomic
imbalances of chromosome 8 in 51 primary colon carcinomas
using a custom-designed genomic array consisting of a tiling
path of BAC clones. This analysis confirmed the dominant role
of this chromosome. Unexpectedly, the position of the break-
points suggested colocalization with structural variants in the
human genome. In order to map these sites with increased
resolution and to extend the analysis to the entire genome,
we analyzed a subset of these tumors (n = 32) by comparative
genomic hybridization on a 185K oligonucleotide array
platform. Our comprehensive map of the colon cancer genome
confirmed recurrent and specific low-level copy number
changes of chromosomes 7, 8, 13, 18, and 20, and unveiled
additional, novel sites of genomic imbalances including
amplification of a histone gene cluster on chromosome
6p21.1-21.33 and deletions on chromosome 4q34-35. The
systematic comparison of segments of copy number change
with gene expression profiles showed that genomic imbal-
ances directly affect average expression levels. Strikingly, we
observed a significant association of chromosomal break-
points with structural variants in the human genome: 41% of
all copy number changes occurred at sites of such copy
number variants (P < 2.2e?16). Such an association has not
been previously described and reveals a yet underappreciated
plasticity of the colon cancer genome; it also points to
potential mechanisms for the induction of chromosomal
breakage in cancer cells. [Cancer Res 2008;68(5):1284–95]
Introduction
Colorectal cancer is the second leading cause of cancer death
in Europe and in the United States, with f300,000 new cases
and 200,000 deaths each year (1). Cytogenetic and molecular
cytogenetic studies clearly established that the colorectal cancer
genome is defined by a specific distribution of genomic imbalances,
most prominently, gains of chromosomes and chromosome arms 7,
8q, 13, and 20q as well as losses of chromosomes 4q, 8p, 17p,
and 18q (2).
Within the last decade, microarray technology has been
extensively applied to survey the cellular transcriptome of common
solid tumors, including colorectal cancer, and for colon cancers,
gene expression signatures were subsequently correlated with
clinical outcome (for reviews, see refs. 3–5). However, high-
resolution mapping of chromosomal copy number changes has
only recently been achieved using BAC or cDNA clone-based arrays
(6–10).
Chromosome 8q is one of the most frequently gained
chromosomal arms in colorectal cancers (2), and it is
conceivable that it contains more oncogenes than just the
MYC oncogene, which maps to chromosome band 8q24.21. A
potential role of chromosome 8q for the development of lymph
node metastases has been previously reported (11), and
overexpression of a gene, PRL-3, that maps to chromosome
8q24.3 has been implied in the development of liver metastases
(12). Moreover, the 8q24 locus contains single nucleotide
polymorphisms that are associated with an increased risk for
the development of colon cancer (13–15).
Recently, a new class of genetic variation among humans has
become recognized as a major source of genetic diversity. Termed
structural variations, these polymorphisms can present themselves
as copy number variants (CNV) and segmental duplications,
which could be CNVs, but are not necessarily so (16–19). These
polymorphisms could induce chromosomal rearrangements (20).
One of our previous analyses of chromosomal aberrations in cell
lines established from different carcinomas indicated that genomic
copy number changes could be triggered by jumping trans-
locations, many of which originated in the pericentromeric
heterochromatin of several chromosomes (21). These regions
frequently contain segmental duplications and other structural
variants of the genome (22). Taken together, these data enticed us
to systematically explore the genomic aberration profile and the
potential involvement of structural variants of the human genome
in the genesis of chromosomal aberrations in this common cancer.
We therefore established a high-resolution map of genomic copy
number changes in 51 primary colon carcinomas using compar-
ative genomic hybridization (CGH) on both a BAC-based genomic
tiling array for chromosome 8 and, for a subset of those, using a
185K oligonucleotide platform for whole genome coverage.
Materials and Methods
Patients and Sample Collection
The 51 patients included in this study were diagnosed with primary
adenocarcinomas of the colon, and treated at the Department of General
Note: Supplementary data for this article are available at Cancer Research Online
(http://cancerres.aacrjournals.org/).
Requests for reprints: Thomas Ried, Genetics Branch, Center for Cancer
Research, National Cancer Institute/NIH, Building 50, Room 1408, 50 South Drive,
Bethesda, MD 20892. Phone: 301-594-3118; Fax: 301-435-4428; E-mail: riedt@mail.
nih.gov.
I2008 American Association for Cancer Research.
doi:10.1158/0008-5472.CAN-07-2864
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Surgery, University Medicine Go ¨ttingen, Go ¨ttingen, Germany. All patients
received standardized surgery and histopathologic workup, and tumor
staging was based on WHO criteria (23). Twenty-five tumors were associated
with lymph node metastases [International Union Against Cancer (UICC)-
III], whereas 26 tumors were not (UICC-II). Tumor samples were obtained
immediately after surgery and stored on ice for inspection by an experienced
pathologist. Consistent with standard procedures, only samples with a
tumor cell content of at least 70% were included in this study. Biopsies of
normal adjacent mucosa were collected from some patients when possible.
Table 1 summarizes the clinical data and experimental setup.
Table 1. Clinical information and experimental setup
Patient codeHistopathologyChromosome 8
BAC microarray
Gene expression
microarray
185K oligonucleotide
microarray
CC-P1
CC-P2
CC-P3
CC-P4
CC-P6
CC-P7
CC-P8
CC-P9
CC-P10
CC-P11
CC-P12
CC-P13
CC-P14
CC-P15
CC-P16
CC-P19
CC-P20
CC-P21
CC-P22
CC-P23
CC-P24
CC-P26
CC-P27
CC-P28
CC-P30
CC-P32
CC-P34
CC-P35
CC-P36
CC-P37
CC-P38
CC-P39
CC-P42
CC-P44
CC-P45
CC-P46
CC-P47
CC-P48
CC-P49
CC-P51
CC-P53
CC-P54
CC-P56
CC-P58
CC-P60
CC-P65
CC-P66
CC-P68
CC-P70
CC-P71
CC-P72
pT3apN0(0/17) M0R0G2
pT3pN0(0/19) M0R0G2
pT3pN0(0/29) M0R0G2
pT3apN0(0/31) M0R0G3
pT4pN0(0/17) M0R0G3
pT3pN0(0/25) M0R0G2
pT3pN0(0/44) M0R0G2
pT3bpN0(0/31) M0R0G1-2
pT3bpN0(0/20) M0R0G2
pT3apN0(0/21) M0R0G2
pT3pN0(0/27) M0R0G2
pT3bpN0(0/39) M0R0G2
pT3pN0(0/23) M0R0G2
pT3pN0(0/31) M0R0G3
pT3pN0(0/15) M0R0G2
pT4pN0(0/57) M0R0G2
pT3bpN0(0/28) M0R0G2
pT3bpN0(0/24) M0R0G2
pT3pN0(0/15) M0R0G2
pT3pN0(0/21) M0R0G3
pT3pN0(0/17) M0R0G2
pT3pN0(0/20) M0R0G2
pT3pN0(0/26) M0R0G2
pT3pN0(0/20) M0R0G2
pT3bpN0(0/35) M0R0G2
pT3apN0(0/23) M0R0G2
pT3pN1(2/17) M0R0G2
pT4pN1(2/51) M0R0G2
pT3pN2(15/42) M0R0G2
pT3pN1(1/25) M0R0G2
pT2pN1(1/23) M0R0G2-3
pT3cpN1(1/28) M0R0G2
pT3apN1(1/2) M0R0G2
pT1-3pN1(2/26) M0R0G2
pT4pN2(4/36) M0R0G2
pT3bpN2(8/16) M0R0G3
pT3pN2(12/13) M0R0G2
pT3apN2(5/23) M0R0G2
pT4pN2(9/21) M0R0G2
pT3cpN2(4/23) M0R0G2
pT4pN2(11/26) M0R0G2
pT3pN1(3/22) M0R0G2
pT3bpN1(2/20) M0R0G2
pT3pN2(1/32) M0R0G2
pT3pN1(2/24) M0R0G2
pT3pN1(2/22) M0R0G2-3
pT2pN2(4/20) M0R0G2
pT3cpN2(12/22) M0R0G3
pT3pN2(12/21) M0R0G2
pT3pN1(1/18) M0R0G3
pT2pN1(2/18) M0R0G3
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NOTE: (?), not included.
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DNA and RNA Isolation
Bioptic material was in the range of 24 to 370 mg, and nucleic acids were
extracted using TRIZOL (Invitrogen) following standard procedures.4
On average, we obtained 200 Ag each of RNA and DNA. Nucleic acid
quantification was determined using the Nanodrop ND-1000 UV-VIS
spectrophotometer (Nanodrop). The quality of the nucleic acids after
preparation was assessed using a 2100 Bioanalyzer (Agilent Technologies).
Array CGH
BAC array CGH platform. The 1,463 BAC clones and DNA used to
construct the chromosome 8 Human-BAC microarray were a subset of
the Human ‘‘32K’’ BAC Re-Array library from the BACPAC Resources
(Children’s Hospital Oakland Research Institute, Oakland, CA).5The
platform and details of the procedure are described in ref. 24.
Genomic DNA was digested using RsaI and AluI (Roche Applied
Science), and the appropriate fragment size was confirmed on an agarose
gel. After protein removal using a phenol-chloroform extraction, 600 ng
of digested DNA were labeled using the Bioprime Labeling Kit (Invitrogen)
to incorporate Cy5-dCTP or Cy3-dCTP (Amersham). Sex-matched tumor
and reference DNA were combined and hybridized to the custom chro-
mosome 8 BAC array in specifically designed hybridization cassettes
(TeleChem International). After overnight hybridization, slides were washed
and scanned on an Axon scanner using GenePixPro (3.0) software (Axon
Instruments).
Oligo array CGH platform. Oligonucleotide array CGH (aCGH) was
performed according to the protocol provided by the manufacturer (Agilent
Oligonucleotide Array-Based CGH for Genomic DNA Analysis, protocol
version 4.0, June 2006; Agilent Technologies), with minor modifications.
Commercially available pooled control DNA (Promega) was used as sex-
matched reference DNA in all hybridizations. Briefly, 3 Ag of genomic DNA
was digested for 2 h with AluI and RsaI (Promega). QIAprep Spin Miniprep
Kit (Qiagen) was used for purifying the digested DNA. Tumor and reference
DNA was labeled with Cy3-dUTP and Cy5-dUTP (Promega), respectively, in
a random priming reaction using Bioprime Array CGH Genomic Labeling
Module (Invitrogen). After 2 h of reaction, unincorporated nucleotides were
removed using Microcon YM-30 columns (Millipore). Cy3 and Cy5-labeled
samples were combined in equal amounts according to the incorporation
of labeled nucleotides as measured using Nanodrop. Hybridization and
washes were performed according to the manufacturer’s protocol. Slides
were scanned using a scanner (G2565BA; Agilent Technologies), and Agilent
Feature Extraction software (version 9.1; Agilent Technologies) was applied
for image analysis. To visualize the aCGH data, we used Agilent CGH
Analytics 3.4 software (Agilent Technologies). The quality of the slides was
assessed using metrics provided by CGH Analytics.
Gene Expression Profiling
Gene expression profiles for all 51 primary colon tumors and 21
associated mucosa samples were established as previously reported (25).
Data Analysis
BAC aCGH platform. In order to compensate for scanner distortion
between the Cy3 and Cy5 channel readings, we applied a 90th inter-
percentile range (90IPR) normalization procedure to equalize the spread
of Cy3 measurement to the spread of Cy5 measurements per array (in
natural scale):
cCy3 ¼ Cy3 ? ð90IPR:Cy5=90IPR:Cy3Þ;
where cCy3 is the corrected Cy3 measurement, and 90IPR.Cy5 and
90IPR.Cy3 are the 95th percentile minus the 5th percentile measurements
in the Cy5 and Cy3 channels, respectively. cCy3 and Cy5 measurements are
then log 2–transformed, and their log 2 (ratio) are median-centralized by
array using the following formula:
log 2ðRÞ ¼ log 2ðcCy3Þ ? log 2ðCy5Þ þ MD:log 2ðCy5Þ ? MD:log 2ðcCy3Þ;
where MD.log 2 (Cy5) and MD.log 2 (cCy3) are the medians of log 2 (Cy5)
and log 2 (cCy3) measurements, respectively. An aCGH segmentation
algorithm developed under MATLAB was applied to all normalized arrays
to extract segmented regions. Consensus gain or loss regions were obtained
as described previously (24).
Oligo aCGH platform. The analysis of the aCGH experiments was
performed with in-house developed software based on R version 2.4.16and
the DNA copy package from Bioconductor.7One array that did not pass
the quality control criteria (derivative log ratio spread or DLRSpread > 0.3)
was discarded. We also discarded features with no precise chromosomal
location. The final data set was comprised of 29 arrays and 181,984
features. The data were smoothed using ‘‘smooth.CNA’’ function (with
arguments smooth.region = 1, and smooth.SD.scale = 3), followed by the
generation of chromosome segments using circular binary segmentation
(CBS; ref. 26). We centralized DNA segments to the most common ploidy
per array through an algorithm similar to the one offered in Agilent CGH
Analytics 3.4 software. The cumulative frequency of loss score for each
feature is the percentage of samples for which the segment value is below
the threshold log 2 (5/6) corresponding to a loss of one DNA copy in 30%
of diploid cells. Cumulative frequency is scaled to 100% = 4 (e.g., 25% = 1)
in order to take advantage of the maximum range of the representation in
genome, chromosome, and gene views in Agilent CGH Analytics 3.4.
Likewise, the cumulative frequency of gain score for each feature is the
percentage of samples for which the segment value is above the threshold
log 2 (7/6).
The significance of association of chromosomal breakpoints within CNV
loci was calculated as follows: the statistics for breakpoints in CNV loci is
the m2goodness of fit between the observed fraction of breakpoint in CNV
loci (count of observed breakpoint in CNV loci/total observed breakpoints),
and the fraction of expected breakpoints in CNV loci (total base pair of CNV
areas in array/total base pair covered in array). The significance threshold
for this statistical test was P < a = 0.05 (two-sided).
The correlation between average CGH copy number and average gene
expression was performed using Pearson’s correlation for each CBS segment
with (a) ratio average values (CBS segment mean from this article), as the
X-axis versus (b) average of gene expression [log 2 (ratio); from ref. 25],
as the Y-axis. We excluded gene expression arrays with >30% missing data
points, and to prevent distortion caused by outliers, we excluded segments
containing less than six features for either gene expression or CGH prior to
calculating the correlation, i.e., 10 samples and 314 of 369 segments were
retained. The significance threshold for this statistical test was P < a = 0.05
(two-sided).
Results
CGH using chromosome 8–specific tiling BAC arrays.
Chromosome arm 8q is one of the most common targets of
genomic amplification in colon cancer. It is also associated with
the development of both lymph node and distant metastases, and
contains single nucleotide polymorphisms that predispose to the
development of this malignancy (2, 11, 12, 14, 15). We therefore
aimed to generate a high-resolution map of genomic copy number
changes by analyzing 51 primary colon tumors by CGH using a
BAC clone-based genomic tiling array. Twenty-five of these tumors
were associated with lymph node metastases at the time of surgery
(UICC-III), whereas the remaining patients were free of lymph node
metastases (UICC-II, n = 26). The clinical information is presented
in Table 1.
4http://www.riedlab.nci.nih.gov/protocols.asp
5http://bacpac.chori.org/
6http://www.R-project.org
7http://www.bioconductor.org
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Confirming previous results, 50% of the cases showed aberra-
tions on chromosome 8; 37% had gains on the long arm, and 45%
had losses on 8p. Two regions with the highest copy number
increases mapped to genome locations 105 to 120 Mbp and 127 to
142 Mbp. This includes chromosome band 8q24.21, the genomic
location of the MYC oncogene. Interestingly, in striking difference
from the results suggested by conventional CGH, the short arm of
chromosome 8 was not subject to loss in its entirety: in the
majority of samples with 8p alterations, the loss of this arm did not
include a small region close to the centromere. This region, which
includes 5.5 Mbp of the short arm, was either present in normal
copy number, or in fact gained to the same extent as the long arm.
The summary of this analysis is presented in Fig. 1A and B.
Interestingly, when we then tried to understand why chromosome
8p was prone to chromosomal breaks to such an extent, we noticed
that in 9 out of 14 cases, the breakpoints coincided with sites of
known structural variants identified within the human population,
either CNVs or segmental duplication (Supplementary Table S1).
Figure 1B summarizes the BAC array data of the 8p aberration
patterns in individual cases.
High-resolution genome-wide mapping of DNA copy num-
ber changes. In order to more precisely map these breakpoints
and to investigate whether the observed predilection for chromo-
somal breaks at sites of known structural variants applies to
regions other than 8p, we profiled 31 of the 51 colon cancers
analyzed with the BAC arrays by aCGH on a 185K oligonucleotide,
genome-wide platform (see Table 1 for the respective cases).
Regions of genomic imbalances in these tumors were determined
using CBS (26). Taking the different resolution limits of the
platforms into consideration, we observed an excellent congruence
between the techniques, and the aberration patterns on 8p were
confirmed. Our analyses also confirmed the recurrent low-level
copy number changes of chromosomes 7, 8, 13, 18, and 20, which
are specific for sporadic colorectal cancers (27). However,
attributable to the increased resolution of this platform for aCGH,
additional novel sites of chromosomal gains and deletions could be
identified. Specifically, we detected 393 chromosomal breakpoints
(defined as segments of copy number change) in 31 cases, for an
average of 12.7 breakpoints per case (0–34). One hundred and sixty-
nine breakpoint segments (including those that affected entire
chromosomes) resulted in copy number increases, whereas 202
regions of copy number loss were present. Segments with copy
number increase were recurrently mapped to chromosomes and
chromosome arms 7, 8q, 13, and 20q, whereas losses occurred most
frequently on 1p, 5q, 8p, 14, 15, 17p, 18, 21, and 22. A summary of
these results is presented as cumulative gain or loss in Fig. 1C, and
as a frequency distribution in Supplementary Fig. S1. Gains on
chromosomes 13 and 20 were most commonly observed, and also
revealed the highest level of genomic amplification, followed by
copy number increases of chromosomes 7 and 8q. Chromosome
arms 18q, 17p, and 8p showed the highest degree of genomic loss
(both in terms of cases and actual copy number reduction).
We detected several regions whose recurrent copy number
changes were not appreciated in our previous analyses of colorectal
carcinomas using conventional CGH analysis (28). In addition to
the above-described retention on 8p, we observed a similar pattern
on chromosome 20: the breakpoint that results in copy number
increase resides in the euchromatic region of 20p, and not in the
centromere. In addition, we observed interstitial deletions of
chromosome band 4q34.3-35.2 in three cases (CC-P19, CC-P20, and
CC-P65), and a deletion that included the terminal band of the
short arm of chromosome 11 (11p15.5) in two cases (CC-P23 and
CC-P38). Bands 13q21.32 to 13q31.2 were deleted on this commonly
gained chromosome in CC-P23, and remained in normal copy
number (with the rest of the chromosome gained) in CC-P65. A few
localized high-level amplifications were mapped to chromosome
bands 4q13.2-13.4, 5q32-33.2, and 6p21.1 (CC-P14), and 16q12.2 in
CC-P65. In CC-P23, we observed the genomic amplification of the
ANKRD10 gene, which maps to distal chromosome 13.
Comparison between lymph node–negative and -positive
cancers. The presence of synchronous lymph node metastases
dictates the inclusion of chemotherapy in the treatment of patients
with colon cancer. In order to explore whether lymph node status
could be reflected by specific copy number changes on chromo-
some 8, as previously suggested (11), or elsewhere in the genome,
we compared the distribution of genomic imbalances as deter-
mined in both groups using the oligonucleotide array platform. The
percentage of chromosomal gains and losses was not different
between the lymph node–positive (average, 12.9 per case) and
lymph node–negative (average, 11.7 per case) carcinomas. The
average number of gained or lost segments in the UICC-II tumors
was 6.8 and 6.1, respectively, and for the UICC-III tumors, it was 4.8
and 7.5, respectively. In order to further analyze whether tumors
associated with lymph node metastases carry distinct genomic
aberration profiles, we analyzed the frequency of all CBS units in
the two groups: we could not detect any CBS units that were
uniquely gained or lost in either the UICC-II or UICC-III samples,
nor did we detect a differential distribution of CBS units between
the groups that exceeded a 30% difference threshold. The summary
plots of the UICC-II and UICC-III tumors are displayed in
Supplementary Fig. S2A and B.
Influence of genomic imbalances on gene expression.
Genomic copy number changes are arguably one of the most
recurrent features of solid tumors of epithelial origin. Consequent-
ly, numerous groups attempted to clarify the relationship between
genomic copy number changes and gene expression levels;
however, most of these studies focused either on the effect of
whole chromosomes, or on regional amplicons (25, 29–33). We now
analyzed, for the entire colon cancer genome, this correlation by
plotting the average gene expression values for all CBS units
against their genomic copy number (we only included those 17
cases for which we had gene expression results in both the tumor
and matched normal mucosa, and those CBS segments that
contained more than five genes). The analysis, shown in Fig. 2,
revealed a significant correlation of genomic copy number with
average gene expression levels, therefore suggesting a direct effect
of gene copy on relative message levels (R = 0.66709, P = 2.2e?16).
CNVs. In addition to low level copy number changes, the CBS
analysis revealed numerous recurrent loci of localized high-level
copy number increases or decreases relative to the reference DNA.
Such changes could be indicative of structural variations in the
genome, either germ line or somatic. Structural variations,
including CNVs, have recently emerged as a novel class of DNA
segments that differ from one individual to another (20). The
systematic mapping of CNVs in 270 individuals that constitute the
human HapMap collection (34) suggests that f12% of the human
genome could be subject to copy number variation (20), with as
much as 3% of these regions (f0.3% of the total genome) varying
from one individual to another (35). CNVs therefore contribute
significantly to human sequence variation. Applying the CBS
algorithm, we could identify 120 sites that were suggestive of CNVs
(i.e., sites of high-level copy number increase or decrease of no
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Figure 1. A, summary of the BAC aCGH analysis of chromosome 8 from 51 patients. Chromosome losses (green) and gains (red) are in log 2 ratios. Note the retention
of a portion of the short arm of chromosome 8 from the commonly observed loss of this chromosome arm. Left, genome coordinates and cytogenetic bands.
B, summary of BAC aCGH analysis of individual cases (see patient numbers on top of graph) for those cases that revealed chromosome 8p abnormalities.
Note the varying degrees of retention/amplification of chromosome 8p material (red). DNA copy number losses (green). The red line at 6 Mbp observed in all cases
indicates a novel, common CNV which includes the gene GATA4. The amplicon at 11 Mbp in CC-P1 includes two genes, SOX7 and PINX1. Left, genome coordinates.
C, summary of oligonucleotide aCGH analysis from 31 cases. Copy number increases (red) and decreases (green). Sites suggestive of CNVs are indicated as thin
lines in light green or red. Numbers below the graph refer to chromosomes. Average values are in log 2 ratios.
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more than 200 kbp). The comparison of the variants detected in
our data set derived from 31 tumors with the database on genomic
variation8indicated that 81 of those variants (67.5%) overlapped
with known CNVs, whereas 39 (32.5%) were potentially novel sites
of CNVs. A complete list is provided in Supplementary Table S2.
In order to assess whether these alterations were genomic copy
number changes that emerged de novo in the tumors, i.e., somatic,
or whether they would have to be considered germ line events, we
hybridized tumor DNA from five patients against DNA prepared
from matched normal mucosa tissue. CNVs detectable in such
experiments can be considered bona fide somatic events. The
initial CGH experiments revealed 54 known CNVs in these five
patients (9–13). We now observe that 13 of these CNVs remained
when tumor DNA was hybridized against DNA from matched
normal mucosa (1–4). Based on these observations, we conclude
that 24% of the CNVs are actual variants that emerged in the tumor
tissue, and hence, somatic CNVs. Examples of these variant regions
are shown in Fig. 3A.
Similar to fragile sites, regions of genomic copy number variation
could trigger genomic rearrangements (20, 22). In order to establish
to which extent genomic regions containing CNVs contribute to
the emergence of chromosomal translocations (as deduced from
the presence of segments of genomic copy number change by
CGH), we asked how frequently chromosomal translocations
coincided with the location of previously identified CNVs. Given
the high resolution of our platform (16 kbp), we could manually
annotate the breakpoint sequence for each segment using the
Database of Genomic Variation8in order to search for structural
genomic variants at these genome coordinates. In the 31 cases
analyzed with the oligonucleotide platform, we mapped 393 sites
of genomic copy number change, 161 of which occurred at the site
of known CNVs (Fig. 3C). Taking into account that f18% of the
genome consists of segments identified as CNV, the probability that
41% of all translocations mapped to CNVs by coincidence is
exceedingly low (P < 2.2e?16). This suggests that CNV loci
(including segmental duplications) contribute significantly to the
emergence of chromosomal breaks in colon cancer, and hence,
to the development of genomic imbalances. CNVs that colocalized
to chromosomal breakpoints in our data set are listed in Table 2.
Figure 3B presents an example of a subchromosomal genomic
deletion that eliminates one copy of the tumor suppressor gene
APC and shows the association between the site of the chro-
mosomal break with a known CNV. Figure 4 shows the possible
emergence of genomic copy number changes in CC-P10. In this
tumor, we observed chromosomal breakpoints that coincided
with two segmental duplications, DC3225 on chromosome 17p
and DC2472on chromosome 20p. A sequence homology of
94.51% between these two sites suggests that homologous
recombination events could have contributed to a chromosomal
translocation, which eventually leads to the observed pattern of
DNA gain and loss.
Discussion
Patterns of imbalances. Here, we present a comprehensive
map of genomic imbalances in primary colon carcinomas
generated using high-resolution aCGH on a genomic tiling array
for chromosome 8 and a 185K oligonucleotide platform. The results
are, in general, congruent with previous analyses using chromo-
some banding techniques (2), CGH on metaphase chromosomes
Figure 2. Correlation of genomic copy number of all CBS units with gene expression levels.
8http://projects.tcag.ca/variation/
Chromosomal Breakpoints Cluster at Copy Number Variants
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(28), and aCGH with a genomic BAC platform (6–10). In fact, the
summary pattern of chromosomal gains and losses in our data set
and data sets reported in the literature suggest a striking
conservation of genomic imbalances, and underlines the biological
significance of these recurrent aneuploidies. We observed, however,
a few dissimilarities between the data set presented here and
previously published results. For instance, the short arm of
chromosome 8 is not always lost in its entirety (as suggested by
cytogenetic analyses using chromosome templates), but a mini-
mally retained region that escapes this loss comprises chromosome
band 8p11.1-11.2, which is consistent with previous aCGH analyses
on genomic platforms (9, 36). A similar phenomenon on the short
arm of chromosome 20 was detected. Second, we observed several
regions of subtle copy number changes that were clearly below the
resolution of conventional cytogenetic or CGH analyses. In patient
CC-P9, we observed a localized amplification of chromosome band
6p21.1, which resulted in the significant overexpression of histone
gene HIST1H2BM in this tumor. Other examples include a common
deletion mapped to chromosome band 4q34-35. The most notable
difference between chromosome CGH analysis, the use of an
overlapping BAC array for chromosome 8, and the high-resolution
oligonucleotide platform was the identification of frequent sites of
small, high-level gains and losses, many of which coincided with
loci of known structural variants in the human genome,8which
could only be mapped using the 185K oligonucleotide platform.
This will be discussed separately below.
Correlation of genomic copy number and gene expression
changes. The results presented here underscore the dominant role
of specific and recurrent genomic imbalances, which arguably, are
one of the defining features of genetic insults in colon cancer cells.
Figure 3. Regional alterations of CNVs and their prevalence at sites of chromosome breakpoints. A, example of a somatic CNV in patient CC-P42. The hybridization
of matched tumor and normal mucosa DNA revealed a site of a somatic copy number change at the site of a known CNV on chromosome 6q26. B, example
of an aCGH experiment showing the colocalization of a known CNV with a chromosomal breakpoint in patient CC-P24. The breakpoint occurred at genome
coordinate chr5:100699314–100749188. The CNV at this site spans chr5:100,535,625–100,788,621 (18) and is annotated in the Database of Genomic Variants.8
C, genome-wide map of chromosomal breakpoints in colon cancer. Black dots, observed chromosomal breakpoints according to our CBS analysis. Red dots,
breakpoints that coincide with the map location of structural variants of the human genome. Although CNV-induced breakpoints occur throughout the genome,
they cluster near centromeres. The precise genomic coordinates of all CNV-associated breakpoints are provided in Table 2.
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Table 2. Colocalization of chromosomal breakpoints and structural variants in the genome
BP
ID
Cytoband Breakpoint
start
Breakpoint
stop
CNV
locus ID
Segmental
duplications
Interchromosomal/
intrachromosomal
Patient ID
(CC-P no.)
Genes mapping
to the breakpoint
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1p36.33
1p35.2
1p13.2–1p13.1
1p11.2–1p12
1q12
1q21.1–1q12
1q21.1–1q12
1q21.1
1,594,502
31,435,129
113,299,763
120,357,104
120,961,845
143,526,765
145,338,927
146,599,106
1,686,141
31,444,435
113,313,396
120,525,002
141,468,205
143,543,580
145,359,805
146,628,218
0003
0053
0141
0144
0145
0146
0148
0148
DC0021, DC0022Intra
—
—
Intra
Intra
Intra
Inter
Inter
14
14
56
SSU72, CDC2L2
WDR57, ZCCHC17
—
—
—
NBPF11
NBPF15
HIST2H4, H2BE,
HIST2H3C
—
LOC339789
ALMS1
CPS1
—
—
DC0153, DC0154
DC0165
DC0185
DC0206
DC0218
10, 11, 16, 42
20
1, 44, 53, 56, 71
1
1
1.9
2.1
2.2
2.3
3.1
3.2
3.3
3.4
3.5
3.6
4.1
4.2
4.3
4.4
4.5
5.1
5.2
5.3
5.4
5.5
5.6
5.7
5.8
6.1
6.2
6.3
6.4
6.5
6.6
7.1
7.2
7.3
7.4
7.5
7.6
7.7
7.8
8.1
1q23.1
2p25.1
2p13.1
2q34
3p24.3
3p14.2
3p12.3
3q11.2
3q13.11
3q13.33
4p15.31
4q13.2
4q13.3
4q22.3
4q35.1
5p14.3
5p14.3
5p12
5q21.1
5q21.1
5q23.1
5q33.2
5q34
6p21.33–6p22.1
6p21.33
6p21.1
6q12
6q13
6q25.1
7p21.3
7p11.2
7q11.21
7q11.23
7q21.3
7q22.1
7q22.1
7q32.2
8p23.1
154,677,866
8,053,090
73,638,384
211,358,859
20,205,874
60,979,549
74,382,590
95,112,766
105,937,188
121,044,859
20,205,995
69,310,017
71,229,595
94,893,243
184,012,774
20,507,734
20,507,734
45,125,704
99,432,472
100,703,233
115,529,614
153,090,806
165,144,873
29,949,864
30,085,931
46,134,331
65,074,130
73,616,917
149,905,776
7,153,539
55,572,233
62,195,037
76,397,789
97,132,792
101,837,056
101,914,350
130,012,776
7,709,141
154,699,522
8,078,648
73,655,615
211,368,373
20,219,511
60,993,090
74,402,458
95,126,868
105,980,769
121,064,116
20,212,010
69,319,707
71,238,968
94,904,635
184,022,817
20,530,987
20,530,987
45,157,897
99,447,496
100,734,459
115,544,817
153,106,089
165,198,317
29,967,114
30,095,973
46,141,981
65,145,208
73,628,301
149,946,488
7,187,740
55,593,091
62,271,252
76,426,065
97,132,822
101,878,089
101,929,241
130,017,714
7,735,365
— DC0238 Inter
—
—
—
—
—
—
Intra
—
—
—
Intra
—
—
—
—
—
—
1
0278
0354
0485
0544
0597
0612
—
0639
0658
0784
0867
0869
0906
1051
1090
1090
1116
1183
1184
1203
1242
1251
1311
—
1330
1353
1369
—
1491
—
1558
1572
1596
1604
1604
1642
1691
—
—
—
—
—
—
65
14
8
48
53
FHIT
CNTN3
PROS1
—
GSK3B
SLIT2
9
DC0913 47
42—
—
—
8
16
24DC1229
—
—
—
—
—
—
9
9
GRID2
—
—
—
—
—
—
COMMD10
GRIA1
—
—
—
—
—
KCNQ5
C6orf72, PPIL4
C1GALT1
—
—
KIAA1505
ASNS
RASA4, POLR2J2
20
8
19, 24
14
51
24
42
14
DC1732, DC1733Inter, Intra
—
—
—
—
Intra
Intra
—
—
—
Intra
—
Inter
Inter
Intra
Inter
Intra, Inter
Inter
—
Inter
—
—
—
—8
DC1955
DC1958
20
23
—
—
—
8
8, 20
23
48
1, 47
47, 48
65
20, 48
48
48
1, 20
42
48
DC2020
—
DC2177
DC2233
DC2356, DC2357
DC2371
DC2398, DC2399
DC2399
—
DC2508
DEFB106A, DEFB104A,
DEFB105A,
FLJ36980, KIAA1456
8.2
8.3
8.4
8.5
8.6
8.7
8.8
9.1
9.2
9.3
8p22
8p22
8p11.23–8p12
8p11.22–8p11.23
8q11.1
8q11.21
8q22.1
9p21.1
9p13.1
9q12
12,916,574
16,642,931
38,471,875
39,356,595
47,658,706
51,143,041
93,686,213
30,929,344
38,758,232
68,141,956
12,922,059
16,684,703
38,487,158
39,369,686
47,680,223
51,151,309
93,707,355
30,963,839
38,799,072
68,151,359
1698
1704
1733
1734
1742
1749
1811
1931
1944
1945
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
72
48
65
9, 51, 65
10
10
ADAM18
—
SNTG1
—
—
1
14
DC2781, 2806, 2807
DC2382
Intra, Inter
Inter
8, 9, 12, 42, 47, 71
8, 12, 14
KGFLP1, FOXD4L3
(Continued on the following page)
Chromosomal Breakpoints Cluster at Copy Number Variants
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Table 2. Colocalization of chromosomal breakpoints and structural variants in the genome (Cont’d)
BP
ID
CytobandBreakpoint
start
Breakpoint
stop
CNV
locus ID
Segmental
duplications
Interchromosomal/
intrachromosomal
Patient ID
(CC-P no.)
Genes mapping
to the breakpoint
9.4
9.5
10.1 10p11.21
10.2 10p11.21
10.3 10q11.21
10.4 10q11.21
10.5 10q11.22
10.6 10q21.1
10.7 10q21.3
11.1 11p15.5
11.2 11p15.4
11.3 11q24.2
12.1 12p13.31
12.2 12p13.2
12.3 12p13.2
9q21.33–9q22.1
9q31.1
87,362,045
104,443,646
37,523,207
37,561,205
42,066,866
42,676,347
45,489,352
58,591,323
66,455,837
1,341,557
3,625,683
124,745,557
8,908,348
11,040,946
11,113,176
87,376,119
104,448,713
37,536,450
37,573,675
42,097,773
42,724,171
45,507,880
58,643,177
66,527,887
1,478,016
3,638,563
124,758,015
8,909,373
11,045,834
11,274,374
1960
1980
2086
2086
2093
2093
2095
2111
2124
2201
2204
2349
2370
2374
2374
—
—
—
—
8
8
DAPK1
OR13C2
ANKRD30A
ANKRD30A
DC3033Inter
—
Inter
Inter
Intra
—
—
—
—
—
—
—
Intra
71
—8
DC3061, DC6062
DC3077, DC3078
DC3091
—
—
—
—
—
—
—
DC3675
71
8
14, 49—
—
—
8
14
38
38
HCCA2, BRSK2
ART1
PKNOX2
—
TAS2R49
TAS2R46, TAS2R43,
TAS2R44
—
EFHA1
—
—
—
RP11-54H7.1
—
CHD8
MIA2
—
—
KIAA0125
C15ORF43
FAM86A
—
—
—
GPR56
LOC348174
GLG1
DRG2
SLC5A10
—
8
8
42
45
12.4 12q13.11
13.1 13q12.11
13.2 13q21.31
13.3 13q21.33
13.4 13q31.3
13.5 13q33.3
13.6 13q34
14.1 14q11.2
14.2 14q21.1
14.3 14q21.1
14.4 14q21.2
14.5 14q32.33
15.1 15q21.1
16.1 16p13.3
16.2 16p12.1
16.3 16p11.2
16.4 16p11.2
16.5 16q13
16.6 16q22.1
16.7 16q22.3
17.1 17p11.2
17.2 17p11.2
17.3 17p11.2
47,046,663
21,020,530
62,773,029
70,415,095
89,088,605
108,193,190
111,053,779
20,923,484
38,759,886
40,612,280
43,688,550
105,881,961
43,050,880
5,085,210
22,578,173
28,141,539
32,181,810
56,228,731
68,534,408
73,128,535
17,935,146
18,823,700
21,471,897
47,074,456
21,029,004
62,811,083
70,460,603
89,156,716
108,202,800
111,083,506
20,941,004
38,773,059
40,647,692
43,723,219
105,902,383
43,057,665
5,132,553
22,625,780
28,154,008
32,206,373
56,242,451
68,575,859
73,148,905
17,945,526
18,845,631
21,627,596
2418
2540
2578
2590
2615
2631
2633
2641
2668
2671
2676
2747
2772
2870
2893
2899
2905
2924
2935
2940
2998
3001
3005
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
49
20
65
47
23
47
47
42
19
51
9
9
DC3877
DC3528
Intra
Inter
—
—
Inter
—
Inter
Intra
—
—
Inter
53
20
—
—
45, 65
20
14
47
45
45
71
51
10, 48, 72
DC3586
—
DC3625
DC3635
—
—
DC3225, DC3226,
DC3227
DC3241, DC3242,
DC3243
—
—
DC2923, DC2924,
DC2925
—
—
—
—
—
—
—
—
DC2471, DC2472
DC2479, DC2480
—
—
17.4 17p11.222,324,326 22,367,302 3006Intra, Inter1, 16, 20, 24, 42,
45, 53, 56, 71
56
56
—
17.5 17q21.2
17.6 17q21.2
18.1 18p11.21
35,991,941
37,142,507
14,968,075
36,017,353
37,148,208
15,042,839
3020
3021
3109
—
—
—
HAP1
—Inter1
18.2 18q11.2
19.1 19q13.12
19.2 19q13.32
20.1 20p13
20.2 20p13
20.3 20p12.1
20.4 20p12.1
20.5 20p11.22
20.6 20p11.1
20.7 20q11.1
20.8 20q13.33
20.9 20q13.33
18,905,068
42,671,304
53,178,403
98,836
1,546,858
14,802,986
15,234,450
22,297,096
26,023,784
28,209,786
58,950,616
62,234,272
18,910,922
42,678,874
53,192,305
111,637
1,557,784
14,816,751
15,249,882
22,316,323
26,096,870
28,225,117
59,000,615
62,235,717
3112
3252
3271
3294
3300
3327
3330
3347
3352
3353
3414
3419
—
—
—
—
—
—
—
—
1—
— 42
71
47
47
ELSPBP1
—
SIRPB1
C20orf133
C20orf133
—
—
—
—
—
9, 44
1, 9, 47
65
10, 42, 49Inter
Inter
—
—
12, 14, 16, 20, 44, 48, 53, 71
39
39
(Continued on the following page)
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We and others have therefore tried to understand the consequen-
ces of such genomic imbalances on the cancer transcriptome
(25, 29–33). In general, the data are consistent with the
interpretation that genomic copy number is positively correlated
to transcript levels. The data set generated here now affords us the
possibility to interrogate the relationship of genomic imbalances,
as detected by segments of copy number change based on the CBS
analysis (185K oligonucleotide arrays), with the expression levels of
resident genes for the entire genome (Fig. 2). The data show that
there is indeed a general, and statistically significant correlation of
genomic copy number and gene expression levels and thus provide
further evidence that these imbalances exert a direct effect on the
cancer transcriptome, and hence, result in a massive and complex
deregulation of the transcriptional equilibrium of malignant
epithelial cells. This observation underlines the importance of the
question as to which extent such rather global gene expression
changes contribute to tumorigenesis vis-a `-vis the targeted
deregulation of specific genes by mutation, deletion, amplification,
or epigenetic deregulation.
CNVs and potential mechanisms of induction of chromo-
some breakage. CNVs constitute a subset of structural variants
that represent a substantial amount of interindividual genetic
variation (20). The most comprehensive catalogue of structural
variants in the human genome can be found at http://projects.
tcag.ca/variation/. The data summarized there was generated by
analyzing the genomes of 270 individuals from the human HapMap
consortium using both aCGH and genome-wide single nucleotide
polymorphism platforms. These variants are rather ubiquitous,
comprising f12% of the human genome. Some of them have been
shown to be associated with a particular phenotype and with
disease (20). Based on a comprehensive evaluation of chromosomal
breakpoints and associated genomic copy number changes in cell
lines derived from solid tumors (i.e., bladder, prostate, cervix,
pancreas, and breast), we could previously show that a consider-
able fraction of chromosomal translocations (in that case referred
to as jumping translocations) originated in the pericentromeric
heterochromatin of several chromosomes (21). Such heterochro-
matin is enriched for segmental duplications, and these show a
6:1 ratio of interchromosomal to intrachromosomal duplications.
These regions can also vary in copy number between individuals,
and if so, could be classified as CNVs (22). We were therefore
curious as to which extent chromosomal breakpoints (as defined
by sites of genomic copy number change using aCGH) colocalize
with such structural variants in the genome of primary colon
cancers. Surprisingly, f41% of all translocations resided at sites of
known CNVs, including segmental duplications (Fig. 3; Table 2).
Such an association is highly significant (P < 2.2e?16). Figure 4
suggests a possible scenario on how the observed pattern of
genomic gain and loss could be explained in one of the tumors
analyzed here (CC-P10). It is, however, not possible to perform
cytogenetic analysis on this very sample, and therefore, one cannot
formally prove that the observed pattern of imbalance is indeed
caused by translocations between chromosomes 17 and 20 despite
the high degree of homology (95%) between the segmental
duplications that colocalize with these breakpoints. Alternatively,
CNVs and segmental duplications are simply regions more prone to
chromosome breakage, which can result in loss of genomic
segments due to the lack of a centromere, or translocation with
other regions in the genome without homology. The difference in
copy number of these regions between individuals, however, is
perhaps an indication that they are particularly susceptible to
homology-mediated recombination, i.e., formation of chiasmata, in
meiotic cells. In cells experiencing DNA damage, one could easily
envision that aberrant homology-mediated repair of segmentally
duplicated regions might also lead to chromosome aberrations in
somatic cells, such as deletions, inversions, and translocations.
Such analyses will have to be conducted using cell lines established
from primary tumors. The mere fact that homologous chromo-
somes in an interphase nucleus rarely tend to be in the same
topographical neighborhood (37) makes it more likely that a
homology search will identify a duplicated region on
a different chromosome. This may explain the relatively high
frequency of whole chromosome arm gains and losses in aneuploid
tumors. Why might these regions be more susceptible to DNA
damage? First, CNVs are often found in association with gene
coding regions and therefore might be expected to be in an open
configuration, making them more susceptible to DNA damage. Alu
sequences, satellite repeats, and regions with hallmarks of DNA
fragility are found to be enriched at the boundaries of these
regions, supporting the hypothesis that these areas are preferential
sites of DNA double-strand breaks, making them ideal substrates
for repair pathways with the potential for causing increased copy
number or rearrangements. Gorgoulis et al. (38) and Bartkova et al.
(39) observed an early activation of DNA damage response
pathways in precancerous lesions. Serrano and colleagues showed
that high expression of oncogenes triggers a permanent block in
replication, termed oncogene-induced senescence (40). Oncogene-
induced senescence has recently been shown to induce a DNA
damage response in tissue culture models (41, 42) as well as in vivo
during the development of thymocytes (43), and is able to restrict
the growth of human and murine precancerous tissues (44–48).
These early incidents set the stage for the events outlined above.
Further progression to more advanced dysplastic lesions and to
invasive carcinomas was associated with p53 inactivation and
reduction of apoptosis. Interestingly, allelic loss of loci prone to
DNA double-strand break formation, i.e., fragile sites was common.
The authors put forward a model in which, at early stages
of tumorigenesis, replicative stress triggers the formation of
Table 2. Colocalization of chromosomal breakpoints and structural variants in the genome (Cont’d)
BP
ID
CytobandBreakpoint
start
Breakpoint
stop
CNV
locus ID
Segmental
duplications
Interchromosomal/
intrachromosomal
Patient ID
(CC-P no.)
Genes mapping
to the breakpoint
21.1
21.2
X.1
X.2
X.3
21q21.1
21q21.2
Xp11.22
Xq21.31
Xq22.1
21,148,687
24,275,094
52,775,986
91,052,975
101,404,534
21,166,248
24,312,332
52,782,545
91,151,194
101,556,005
3430
3435
—
—
—
—
—
—
—
44
14
42
71
NCAM2
—
GAGED4
PCDH11X
NXF2
DC1465
DC1550, DC1551
DC1569
Intra
Inter
Intra8
Chromosomal Breakpoints Cluster at Copy Number Variants
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Cancer Res 2008; 68: (5). March 1, 2008

Page 11

double-strand breaks, which in turn results in genomic instability,
and through that to inhibition of apoptosis and cell cycle arrest.
One could therefore reasonably speculate that CNV-induced
double-strand breaks are among the earliest gross chromosomal
aberrations in cancer genomes. The resulting unbalanced trans-
locations could then, in addition to aneuploidies of entire
chromosomes (which are also observed in premalignant, early
dysplastic lesions), contribute to the emergence of patterns of
genomic imbalances that define different tumors of epithelial
origin. These speculations are potentially substantiated by our
observation that f24% of the observed CNVs are actually de novo
events, i.e., are detectable when tumor DNA was compared with
DNA prepared from matched normal mucosa tissue. These data
suggest that regions of copy number variation observed in the
normal population continue to be subject to hypervariability and
are foci of genomic instability in the tumor.
Itremainstobeseenwhetherthestrikingcolocalizationofsitesof
structural variants in the genome and cancer-associated chromo-
somal breakpoints that we observed here in colon carcinomas
occurs in other epithelial neoplasms as well. It will be equally
interesting to determine whether the distribution and frequency of
specific CNVs is associated with population-based cancer risk.
Acknowledgments
Received 7/26/2007; revised 10/11/2007; accepted 1/20/2008.
Grant support: Intramural Research Program of the NIH, National Cancer
Institute, the Deutsche Forschungsgemeinschaft (KFO 179), and a stipend from the
Deutsche Krebshilfe (M. Grade).
The costs of publication of this article were defrayed in part by the payment of page
charges. This article must therefore be hereby marked advertisement in accordance
with 18 U.S.C. Section 1734 solely to indicate this fact.
The authors thank Hesed M. Padilla-Nash, Buddy Chen, Joseph Cheng, and Jessica
Eggert for helpful discussion, technical, and editorial assistance.
Figure 4. Structural variation-mediated translocation resulting in genomic imbalance. Interchromosomal segmental duplications with high sequence homology are
found on chromosomes 17 (green) and 20 (red) in their pericentromeric regions (white boxes). In the example illustrated above, a single-strand break occurring in one
segmental duplication on chromosome 17p finds homology with a segmental duplication with inverted orientation on chromosome 20p (first inset). The strand
invasion at the site of homology (black text and lines) results in the formation of a Holliday junction and branch migration. One resolution of the Holliday junction occurs
through single-strand breaks of the uninvolved DNA strands and rotation of the structure resulting in a chromosome translocation of 17p to 20p and 17q to 20q.
The former structure lacks a centromere whereas the latter is a dicentric chromosome. Spindle attachment and chromosome segregation during mitosis could result in
one daughter cell containing a genomic imbalance due to loss of the acentric t(17;20). Duplication of the t(17;20)(q;q) in subsequent cell divisions would result
in the genomic imbalances observed in the tumor of patient CC-P10.
References
1. Midgley R, Kerr D. Colorectal cancer. Lancet 1999;353:
391–9.
2. Heim S, Mitelman F. Cancer cytogenetics. 2nd ed. New
York: Wiley-Liss; 1995.
3. Shih W, Chetty R, Tsao MS. Expression profiling by
microarrays in colorectal cancer (review). Oncol Rep
2005;13:517–24.
4. Bustin SA, Dorudi S. Gene expression profiling for
molecular staging and prognosis prediction in colorectal
cancer. Expert Rev Mol Diagn 2004;4:599–607.
5. Augenlicht LH, Velcich A, Klampfer L, et al. Applica-
tion of gene expression profiling to colon cell matura-
tion, transformation and chemoprevention. J Nutr 2003;
133:2410–6S.
6. Lassmann S, Weis R, Makowiec F, et al. Array CGH
identifies distinct DNA copy number profiles of
oncogenes and tumor suppressor genes in chromosom-
al- and microsatellite-unstable sporadic colorectal
carcinomas. J Mol Med 2007;85:289–300.
7. Kim MY, Yim SH, Kwon MS, et al. Recurrent genomic
alterations with impact on survival in colorectal cancer
identified by genome-wide array comparative genomic
hybridization. Gastroenterology 2006;131:1913–24.
8. Gaasenbeek M, Howarth K, Rowan AJ, et al. Combined
array-comparative genomic hybridization and single-
nucleotide polymorphism-loss of heterozygosity analysis
reveals complex changes and multiple forms of
chromosomal instability in colorectal cancers. Cancer
Res 2006;66:3471–9.
9. Nakao K, Mehta KR, Fridlyand J, et al. High-resolution
analysis of DNA copy number alterations in colorectal
cancer by array-based comparative genomic hybridiza-
tion. Carcinogenesis 2004;25:1345–57.
10. Camps J, Armengol G, del Rey J, et al. Genome-wide
differences between microsatellite stable and unstable
colorectal tumors. Carcinogenesis 2006;27:419–28.
11. Ghadimi BM, Grade M, Liersch T, et al. Gain of
chromosome 8q23–24 is a predictive marker for lymph
node positivity in colorectal cancer. Clin Cancer Res
2003;9:1808–14.
12. Saha S, Bardelli A, Buckhaults P, et al. A phosphatase
associated with metastasis of colorectal cancer. Science
2001;294:1343–6.
13. Haiman CA, Le Marchand L, Yamamato J, et al. A
common genetic risk factor for colorectal and prostate
cancer. Nat Genet 2007;39:954–6.
14. Tomlinson I, Webb E, Carvajal-Carmona L, et al. A
genome-wide association scan of tag SNPs identifies a
susceptibility variant for colorectal cancer at 8q24.21.
Nat Genet 2007;39:984–8.
15. Zanke BW, Greenwood CM, Rangrej J, et al. Genome-
wide association scan identifies a colorectal cancer
susceptibility locus on chromosome 8q24. Nat Genet
2007;39:989–94.
16. Sebat J, Lakshmi B, Troge J, et al. Large-scale copy
Cancer Research
Cancer Res 2008; 68: (5). March 1, 2008
1294
www.aacrjournals.org

Page 12

number polymorphism in the human genome. Science
2004;305:525–8.
17. Iafrate AJ, Feuk L, Rivera MN, et al. Detection of
large-scale variation in the human genome. Nat Genet
2004;36:949–51.
18. Redon R, Ishikawa S, Fitch KR, et al. Global variation
in copy number in the human genome. Nature 2006;444:
444–54.
19. Stranger BE, Forrest MS, Dunning M, et al. Relative
impact of nucleotide and copy number variation on
gene expression phenotypes. Science 2007;315:848–53.
20. Feuk L, Carson AR, Scherer SW. Structural variation
in the human genome. Nat Rev Genet 2006;7:85–97.
21. Padilla-Nash HM, Heselmeyer-Haddad K, Wangsa D,
et al. Jumping translocations are common in solid
tumor cell lines and result in recurrent fusions of whole
chromosome arms. Genes Chromosomes Cancer 2001;
30:349–63.
22. Bailey JA, Eichler EE. Primate segmental duplica-
tions: crucibles of evolution, diversity and disease. Nat
Rev Genet 2006;7:552–64.
23. Sobin LH, Wittekind C. UICC: TNM classification of
malignant tumors. 6th ed. New York: Wiley-Liss; 2002.
24. Rodriguez V, Chen Y, Elkahloun A, Dutra A, Pak E,
Chandrasekharappa S. Chromosome 8 BAC array
comparative genomic hybridization and expression
analysis identify amplification and overexpression of
TRMT12 in breast cancer. Genes Chromosomes Cancer
2007;46:694–707.
25. Grade M, Ho ¨rmann P, Becker S, et al. Gene
expression profiling reveals a massive, aneuploidy-
dependent transcriptional deregulation and distinct
differences between lymph node-negative and lymph
node-positive colon carcinomas. Cancer Res 2007;67:
41–56.
26. Olshen AB, Venkatraman ES, Lucito R, Wigler M.
Circular binary segmentation for the analysis of array-
based DNA copy number data. Biostatistics 2004;5:
557–72.
27. Ried T, Knutzen R, Steinbeck R, et al. Comparative
genomic hybridization reveals a specific pattern of
chromosomal gains and losses during the genesis of
colorectal tumors. Genes Chromosomes Cancer 1996;15:
234–45.
28. Grade M, Becker H, Liersch T, Ried T, Ghadimi BM.
Molecular cytogenetics: Genomic imbalances in colo-
rectal cancer and their clinical impact. Cell Oncol 2006;
28:71–84.
29. Upender MB, Habermann JK, McShane LM, et al.
Chromosome transfer induced aneuploidy results in
complex dysregulation of the cellular transcriptome in
immortalized and cancer cells. Cancer Res 2004;64:
6941–9.
30. Monni O, Barlund M, Mousses S, et al. Comprehen-
sive copy number and gene expression profiling of the
17q23 amplicon in human breast cancer. Proc Natl Acad
Sci U S A 2001;98:5711–6.
31. Pollack JR, Sorlie T, Perou CM, et al. Microarray
analysis reveals a major direct role of DNA copy
number alteration in the transcriptional program of
human breast tumors. Proc Natl Acad Sci U S A 2002;
99:12963–8.
32. Tsafrir D, Bacolod M, Selvanayagam Z, et al.
Relationship of gene expression and chromosomal
abnormalities in colorectal cancer. Cancer Res 2006;66:
2129–37.
33. Grade M, Ghadimi BM, Varma S, et al. Aneuploidy-
dependent massive deregulation of the cellular tran-
scriptome and apparent divergence of the Wnt/h-
catenin signaling pathway in human rectal carcinomas.
Cancer Res 2006;66:267–82.
34. The International HapMap Consortium. A haplotype
map of the human genome. Nature 2005;437:1299–320.
35. Wong KK, de Leeuw RJ, Dosanjh NS, et al. A
comprehensive analysis of common copy-number var-
iations in the human genome. Am J Hum Genet 2007;80:
91–104.
36. Pole JC, Courtay-Cahen C, Garcia MJ, et al. High-
resolution analysis of chromosome rearrangements on
8p in breast, colon and pancreatic cancer reveals a
complex pattern of loss, gain and translocation.
Oncogene 2006;25:5693–706.
37. Cremer T, Cremer C. Chromosome territories,
nuclear architecture and gene regulation in mammalian
cells. Nat Rev Genet 2001;2:292–301.
38. Gorgoulis VG, Vassiliou LV, Karakaidos P, et al.
Activation of the DNA damage checkpoint and genomic
instability in human precancerous lesions. Nature 2005;
434:907–13.
39. Bartkova J, Horejsi Z, Koed K, et al. DNA damage
response as a candidate anti-cancer barrier in early
human tumorigenesis. Nature 2005;434:864–70.
40. Serrano M, Lin AW, McCurrach ME, Beach D, Lowe
SW. Oncogenic ras provokes premature cell senescence
associated with accumulation of p53 and p16INK4a. Cell
1997;88:593–602.
41. Di Micco R, Fumagalli M, Cicalese A, et al. Oncogene-
induced senescence is a DNA damage response
triggered by DNA hyper-replication. Nature 2006;444:
638–42.
42. Bartkova J, Rezaei N, Liontos M, et al. Oncogene-
induced senescence is part of the tumorigenesis barrier
imposed by DNA damage checkpoints. Nature 2006;444:
633–7.
43. Xu M, Yu Q, Subrahmanyam R, et al. B–Catenin
expression results in p53-independent DNA damage
and oncogene-induced-senescence in pre-lymph-
omagenic thymocytes in vivo. Mol Cell Bio. In press
2008.
44. Braig M, Lee S, Loddenkemper C, et al. Oncogene-
induced senescence as an initial barrier in lymphoma
development. Nature 2005;436:660–5.
45. Chen Z, Trotman LC, Shaffer D, et al. Crucial role
of p53-dependent cellular senescence in suppression
of Pten-deficient tumorigenesis. Nature 2005;436:
725–30.
46. Collado M, Gil J, Efeyan A, et al. Tumour biology:
senescenceinpremalignanttumours. Nature 2005;436:642.
47. Michaloglou C, Vredeveld LC, Soengas MS, et al.
BRAFE600-associated senescence-like cell cycle arrest of
human naevi. Nature 2005;436:720–4.
48. Sharpless NE, DePinho RA. Cancer: crime and
punishment. Nature 2005;436:636–7.
Chromosomal Breakpoints Cluster at Copy Number Variants
www.aacrjournals.org
1295
Cancer Res 2008; 68: (5). March 1, 2008