Chromosomal Instability Confers Intrinsic Multidrug Resistance · Therapeutics, Targets, and Chemical Biology Chromosomal Instability Confers Intrinsic Multidrug Resistance Alvin

2011;71:1858-1870. Published online March 1, 2011.Cancer Res Alvin J.X. Lee, David Endesfelder, Andrew J. Rowan, et al. ResistanceChromosomal Instability Confers Intrinsic Multidrug

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Therapeutics, Targets, and Chemical Biology

Chromosomal Instability Confers Intrinsic MultidrugResistance

Alvin J.X. Lee1, David Endesfelder1,4, Andrew J. Rowan1, Axel Walther5,6, Nicolai J. Birkbak7,P. Andrew Futreal8, Julian Downward2, Zoltan Szallasi7,9, Ian P.M. Tomlinson5, Michael Howell3,Maik Kschischo4, and Charles Swanton1,6

AbstractAneuploidy is associated with poor prognosis in solid tumors. Spontaneous chromosome missegregation

events in aneuploid cells promote chromosomal instability (CIN) that may contribute to the acquisition ofmultidrug resistance in vitro and heighten risk for tumor relapse in animal models. Identification of distincttherapeutic agents that target tumor karyotypic complexity has important clinical implications. To identifydistinct therapeutic approaches to specifically limit the growth of CIN tumors, we focused on a panel ofcolorectal cancer (CRC) cell lines, previously classified as either chromosomally unstable (CINþ) or diploid/near-diploid (CIN�), and treated them individually with a library of kinase inhibitors targeting components of signaltransduction, cell cycle, and transmembrane receptor signaling pathways. CINþ cell lines displayed significantintrinsic multidrug resistance compared with CIN� cancer cell lines, and this seemed to be independent ofsomatic mutation status and proliferation rate. Confirming the association of CIN rather than ploidy status withmultidrug resistance, tetraploid isogenic cells that had arisen from diploid cell lines displayed lower drugsensitivity than their diploid parental cells only with increasing chromosomal heterogeneity and isogenic cellline models of CINþ displayed multidrug resistance relative to their CIN� parental cancer cell line derivatives. Ina meta-analysis of CRC outcome following cytotoxic treatment, CINþ predicted worse progression-free ordisease-free survival relative to patients with CIN� disease. Our results suggest that stratifying tumor responsesaccording to CIN status should be considered within the context of clinical trials to minimize the confoundingeffects of tumor CIN status on drug sensitivity. Cancer Res; 71(5); 1858–70. �2011 AACR.

Introduction

Colorectal cancer (CRC) is associated with at least 2distinct patterns of genomic instability (1). The more com-mon form of genomic instability in CRC is chromosomal

instability (CIN), resulting in ongoing numerical and struc-tural chromosomal aberrations in cancer cells, leading tointratumoral heterogeneity (2, 3). The less common patternis microsatellite instability (MIN) caused by a deficiency inthe mismatch repair apparatus. Because of the accumulationof replication errors, MIN results in length variation ofmicrosatellite sequences in DNA. Most MINþ CRC cell linesare near-diploid (4, 5) and chromosomally stable (CIN�). Incontrast, CINþ CRC cell lines are aneuploid and display ahigher frequency of chromosomal missegregation errorsduring each mitosis relative to diploid cells (2). In humanCRC, CINþ is widely inferred through the measurement oftumor DNA ploidy (6); normal diploid cells are defined witha DNA index of 1.0 (7) and thus an increase in DNA indexinfers polyploidy or aneuploidy. Approximately 25% ofhuman CRC are both CIN� and MIN� (6).

Consistent molecular mechanisms responsible for the CINþ

phenotype and hence means to target this pattern of genomeinstability in colorectal and other solid tumors remain poorlydefined. Putative mechanisms that may contribute to CINinclude weakening of the spindle assembly checkpoint (SAC;refs. 8, 9), defective sister chromatid cohesion (10), merotelicsister chromatid attachments (11), defective cytokinesis (12),centrosome amplification (13), and chromosome breakage–fusion–bridge cycles (14).

Authors' Affiliations: 1Translational Cancer Therapeutics Laboratory,2Signal Transduction Laboratory, and 3High Throughput ScreeningLaboratory, Cancer Research UK London Research Institute, London,United Kingdom; 4University of Applied Sciences, Mathematics andTechniques, Remagen, Germany; 5Molecular and Population Genetics,The Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom;6Royal Marsden Hospital, Department of Medicine, Sutton, United King-dom; 7Center for Biological Sequence Analysis, Technical University ofDenmark, Lyngby, Denmark; 8Cancer Genome Project, Wellcome TrustSanger Institute, Cambridge, United Kingdom; and 9Children's HospitalInformatics Program at the Harvard-MIT Division of Health Sciences andTechnology, Harvard Medical School, Boston, Massachusetts

Note: Supplementary data for this article are available at Cancer ResearchOnline (http://cancerres.aacrjournals.org/).

A.J.X. Lee and D. Endesfelder contributed equally to the work.

Corresponding Author: Charles Swanton, Translational Cancer Therapeu-ticsLaboratory,CancerResearchUKLondonResearch Institute,44Lincoln'sInn Fields, London WC2A 3LY, United Kingdom. Phone: 44-20-7269-3463;Fax 44-20-7269-3094; E-mail: [email protected]

doi: 10.1158/0008-5472.CAN-10-3604

�2011 American Association for Cancer Research.

CancerResearch

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Increasing evidence suggests that CIN is associated withpoor prognosis in solid tumors (6, 15, 16). It has been sug-gested that adverse outcome associated with CIN may berelated to increased tumor cell heterogeneity, driving theability of tumors to adapt to environmental stresses (17–19). Consistent with a hypothesis whereby CIN may enhancetumor adaptation, transient initiation of CIN, following thebrief induction of MAD2 expression in activated KRAS-initiated mouse lung tumor models, is associated with a highfrequency of tumor recurrence following withdrawal of theKRAS oncogenic stimulus (20). Preclinical studies have shownthat CIN is associated with the rapid acquisition of multidrugresistance in cell line systems (21) and intrinsic taxane resis-tance in vitro and in vivo (22). Recently, we and others haveproposed the existence of a CIN survival phenotype thatallows CINþ tumor cells to tolerate the impact of excessivechromosome gains and losses (22–24) that may in turn impactupon altered drug sensitivity.Determining how CIN might impact upon prognosis and

how this pattern of genomic instability might be specificallytargeted remains an important research area (23, 25). Evi-dence in lower eukaryotes has shown that aneuploid Sacchar-omyces cerevisiae are dependent on increased glucoseutilization and are more sensitive to both heat shock protein90 and proteosome inhibitors (26). Polyploid S. cerevisiae aredependent upon increased expression of genes involved insister chromatid cohesion and mitotic spindle function (27).Roschke and Kirsch have shown the existence of anticancercompounds that may specifically target karyotypically com-plex cancer cells (25). These observations indicate thatkaryotypic instability may be specifically targeted in eukar-yotic organisms and suggest that CIN might be an exploitableand targetable phenotype in cancer.To identify distinct therapeutic approaches to limit the

growth of CINþ tumors relative to diploid cells, we focused ona panel of CRC cell lines that had previously been classified asCINþ or CIN� and used kinase inhibitor and cytotoxic librariesto identify agents that might be preferentially lethal towardCINþ cells. Both isogenic and nonisogenic CINþ cell linesdisplayed intrinsic multidrug resistance in vitro relative toCIN� cell lines. Importantly, consistent with the proposal thatCINþ is associated with intrinsic multidrug resistance, in ameta-analysis of patient outcome in CRC, CINþ was asso-ciated with significantly worse clinical outcome relative todiploid cancers in both early- and late-stage disease followingcytotoxic therapy.

Materials and Methods

Cell lines and FISH analysis27 CRC cell lines (Table 1; Supplementary Table 1), pre-

viously characterized for numerical/structural CIN, MIN sta-tus (2, 28–30), and subject to Affymetrix SNP 6.0 Array analysiswhere available (20/27 cell lines; Wellcome Trust SangerInstitute), were used.We used publicly available somatic mutation data from the

Sanger Institute Cancer Cell Line Project (CLP) and COSMICdatabase (31). Fifteen CINþ and 6 CIN� cell lines used in our

analysis were present within the CLP database, and a total of20 of the 61 genes resequenced in the project were found tohave somatic mutations in at least 1 of those 21 cell lines.Additional information regarding the somatic mutation statusof APC, CTNNB1, KRAS, MLH1, PIK3CA, and TP53 wereobtained from both published (32–35) and internal laboratorydata. Isogenic HCT116 MAD2þ/� cell lines (9) and HCT116PTTG1�/� cell lines (10) were donated courtesy of Drs.Benezra and Vogelstein, respectively. To generate tetraploidHCT116 cells, naturally occurring tetraploid cells were iso-lated from the parental cell line and single cell sorted usingflow cytometry. Clonal FISH was performed with centromereenumeration probes against centromeres on chromosomes 2and 15.

Calbiochem Kinase Inhibitor Library and 5-FU screenCalbiochem Kinase Inhibitor Libraries I and II (EMD Bios-

ciences) containing 160 inhibitors were used. Comprehensivedata for these inhibitors including references documentingtarget inhibition or downstream signaling cascade inactiva-tion can be found on the manufacturer's Web site (36).

Cells were plated into 96-well tissue culture microplates atan initial seeding density of 4,000 cells per well. After 24 hours,cells were treatedwith the inhibitors at a final concentration of10 mmol/L per well. This concentration was selected followingdrug titration test analysis to give an optimal range of meanrelative surviving cells following inhibitor treatment across allcell lines. After 72 hours of treatment, cell viability was assayedusing the Celltiter-Blue Cell Viability Assay (Promega) accord-ing to themanufacturer's instructions. The fluorescent readoutfor each inhibitor treated well was normalized to vehiclecontrol wells. For the HCT116MAD2 isogenic cell lines, a finalinhibitor concentration of 1 mmol/L per well was used to allowfor a larger range of surviving cells across all inhibitors.

5-Fluorouracil (5-FU) was used at both 1 and 10 mmol/L fora treatment length of 72 hours. The 27 CRC cell lines wereplated and assayed using the same conditions and methods asdescribed earlier.

Biolog Anti-Cancer Agent Microplate screenBiolog Anti-Cancer Agent Microplates M11–M14 consisting

of 92 anticancer agents at 4 increasing concentrationsbetween 0.1 and 25 mmol/L per agent were used. Cells wereplated at an initial seeding density of 5,000 cells per well. After72 hours, the number of surviving cells per well was assayedusing Biolog Redox Dye Mix MA according to manufacturer'sinstructions and normalized to the negative control wells.

Cell proliferation assayWe measured the proliferation rate of all 9 CIN� and 18

CINþ CRC cell lines, using the IncuCyte Long-term CellImaging System. Cell lines were plated in 96-well plates atan initial plating density of 4,000 cells per well and phase-contrast images were obtained every 2 hours over 70 hours,allowing measurements of cell monolayer confluence. Outlierswere removed manually, and growth curves were fitted bysplines with the R package grofit (37) with smoothing para-meter smooth.gc ¼ 0.7.

CIN Confers Intrinsic Multidrug Resistance

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Tab

le1.

Celllines

used

inthis

stud

y

NOTE

:Black

indicates

prese

nceof

mutation;

white

indicates

abse

nceof

mutation;

andgray

indicates

mutationstatus

notkn

own.

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Meta-analysis of clinical studiesSurvival data were summarized using a log hazard ratio for

comparison between CINþ and CIN� groups. Data fromindividual studies were extracted using the methods describedby Parmar and colleagues (38) and pooled to generate thesummary statistic and CIs using a fixed-effects model withinverse variance weighting. All meta-analyses were performedusing Stata 10.1 (Stata Corp).

Statistical methodsAll tests were performed as 2-sided unless otherwise men-

tioned. To remove outliers, drugs resulting in relative numberof cells greater than 1.4 were eliminated from analysis. AKolmogorov–Smirnov test was performed to test for overalldifferences in the distribution of relative cell numbers follow-ing inhibitor treatment between CINþ and CIN� cell lines.Inhibitors that showed a fraction of surviving cells greaterthan 0.8 in more than 75% of the cell lines were excluded fromthe analysis. For comparisons of 2 cell lines, drugs resulting inrelative number of cells greater than 0.8 in both cell lines wereremoved from analysis. A Wilcoxon signed-rank test was usedto test for differences between CINþ and CIN� cells (for eachconcentration of drug in Biolog microplates). For the Biologmicroplates, each concentration of drug was used in duplicate;therefore, the replicates which showed the least difference incell number between the 2 cell lines was used for furtheranalysis.The maximal slope of the growth curve (m) for each cell

line was used to test whether the difference in drug sensi-tivity between CINþ and CIN� colorectal cancer cell lineswas not solely due to different proliferation rates. CINþ andCIN� cell lines with m < 1 were tested with a one-sidedWilcoxon–Mann–Whitney test. Next, we corrected for theinfluence of the proliferation rates of each cell line. Weestimated a linear regression model for all cell lines withm < 1, where m was used as an independent variable and themean fraction of surviving cells over all inhibitors as adependent variable. The residuals of this analysis weretested for significant differences between CINþ and CIN�

with a one-sided Wilcoxon–Mann–Whitney test (39). Ananalysis of covariance model with interactions was applied,where the mean fraction of surviving cells over all inhibitorswas used as a dependent variable, m as a linear, independentvariable, and CIN status as a factor variable. The interactionterm was utilized to test for significant differences in slopesbetween CINþ and CIN� cell lines.To test for significant differences in sensitivity to thymi-

dylate synthase inhibitors comparing HCT116 diploid par-ental and PTTG1�/� or MAD2þ/� cells, we corrected for theinfluence of different concentrations by estimating a linearregression model for near linear correlations between con-centration and sensitivity or a one-way ANOVA otherwise. Ineach case, the concentration was used as the independentvariable and the resulting residuals were tested for differ-ences between CINþ and CIN� cells with a Wilcoxon–Mann–Whitney test.All statistical analyses were performed in R and can be

found in the Supplementary Sweave document.

Results

Classification of CINþ cell lines and relationship withploidy status and structural chromosomal complexity

We selected 9 CIN� and 18 CINþ CRC cell lines (Table 1).CIN status for these cell lines had been previously described interms of numerical and structural chromosomal aberrations(2, 28–30).

To confirm the utility of published approaches for defin-ing the CIN status of the cell lines, where SNP Array datawere available, we estimated the ploidy status of the celllines by using weighted mean integer copy numbers derivedfrom the PICNIC (Predicting Integral Copy Numbers InCancer) algorithm (ref. 40; Fig. 1A). Ploidy estimates classi-fied cells as CINþ if they surpassed a threshold of ploidygreater than 2.2 (corresponding to an estimated DNA indexof 1.1). In addition, modal chromosomal number as deter-mined previously using high-quality metaphase spreads (28,29) correlated well with ploidy estimates derived fromweighted mean PICNIC copy number analysis using theSNP Array data [Pearson's correlation coefficient (CC) ¼0.94, Pearson's correlation test P < 0.0001; Fig. 1B]. Thesedata support the utility of SNP Array data for estimatingcell line ploidy status and are consistent with ploidy esti-mates by traditional measures, confirming the CIN status ofcell lines used in this analysis.

Next, we addressed the relationship between CIN status andstructural chromosomal complexity, using a summary struc-tural chromosomal complexity score (SCCS) derived from theSNP Array data sets. This SCCS was determined by summar-izing (i) the number of break points, (ii) LOH events aspredicted using PICNIC (40), and (iii) the Genome IntegrityIndex (GII; ref. 41) into a single value for each cell line (Fig. 1C).There was a highly significant correlation between ploidystatus and the SCCS (Pearson's CC ¼ 0.746, P ¼ 0.0002).Taken together, these analyses confirm that cells classified asCINþ have significantly greater ploidy and structural chromo-somal complexity than CIN� cells.

CINþ status is associated with intrinsic multidrugresistance

Next, we aimed to determine whether a specific kinaseinhibitor could be identified to selectively target CINþ celllines. We used a small molecule library (Calbiochem KinaseInhibitor Library I and II) that included 160 inhibitors to treatthe 18 CINþ and 9 CIN� cell lines. Preliminary drug titrationexperiments revealed that the majority of the CINþ cell lineswere resistant to concentrations up to 1 mmol/L (Supplemen-tary Fig. 1) and therefore 10 mmol/L was selected as theoptimal drug concentration for cell growth inhibition acrossthe majority of cell lines in order to attempt to identify drugsthat were specifically active in CINþ cells. No specific inhibitoror inhibitor family was found to be preferentially active inCINþ cell lines compared with CIN� cell lines. In contrast,CINþ cancer cell lines were significantly more resistant to theinhibitors (Kolmogorov–Smirnov test, P < 0.0001; Fig. 2A–C).Following correction for multiple testing hypotheses, 45 inhi-bitors were identified which showed significantly greater




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activity in CIN� cell lines than in CINþ cell lines (Supplemen-tary Table 2).

To address whether the variation in drug sensitivitybetween the CINþ and CIN� cell lines was attributable todifferences in proliferation rate, we calculated the maximumgrowth rate (m) for each cell line. We observed that CINþ andCIN� cell lines show significantly different slopes in regressionlines (t test, P ¼ 0.007), with CIN� cell lines showing a higherproliferation rate than in the CINþ cell lines (Wilcoxon–Mann–Whitney test, P ¼ 0.003). These data are consistentwith previous studies, suggesting that aneuploidy (42, 43) orchromosomal segregation defects (11, 44) have a negativeimpact on cellular proliferation rate. We observed a significantcorrelation between increased sensitivity to the inhibitors athigher proliferation rates for CINþ cell lines (Pearson's CC ¼0.61, P¼ 0.007). In contrast, no such correlation was observedbetween proliferation rate and drug sensitivity in CIN� celllines (Pearson's CC ¼ 0.24, P ¼ 0.55; Supplementary Fig. 2A).Neither ploidy index nor the SCCS showed a significantcorrelation with proliferation rate (data not shown).

We next investigated whether CINþ and CIN� cell lines withsimilar proliferation rates displayed differential drug sensitiv-ity (cell lines with m < 1; 22/27 cell lines). CINþ cell linesremained multidrug resistant compared with CIN� cell lineswithin this group (one-sided Wilcoxon–Mann–Whitney test, P¼ 0.013). Next, we used a more conservative approach andcorrected for the influence of proliferation rate of each indi-vidual cell line within this group. CINþ cell lines remainedsignificantly more drug resistant than CIN� cell lines (one-sided Wilcoxon–Mann–Whitney test, P ¼ 0.049; Supplemen-tary Fig. 2B). These data suggest that at similar growth rates,CINþ cell lines remain more drug resistant than CIN� celllines, indicating that proliferation rate is unlikely to be themain determinant of drug sensitivity.

Somatic mutation status and drug sensitivityNext, we addressed whether distinct tumor cell line somatic

mutations might be the underlying determinant of drugresistance rather than genomic instability status. We investi-gated whether the somatic mutation status of 20 genes(Table 1) was associated with altered sensitivity either toinhibitors grouped according to target kinase family (Aurorakinase, AKT, CDK, EGFR, FLT-3, GSK-3, JAK3, JNK, MEK,PDGFR, PI3K, and SYK) or to all inhibitors combined. Weaddressed whether there was an association of drug sensitivitywith somatic mutation status in 13 genes for which cell linegroup sizes had sufficient statistical power to compare drugsensitivity in wild-type compared with mutated cell lines.

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Figure 1. A, barplot of the ploidy status of 20 CRC cell lines determinedusing mean copy number (PICNIC) of SNP Array data. Red line indicatesploidy value threshold of 2.2. CINþ cell lines in black text and CIN� celllines in red text throughout. B, correlation of modal chromosomal numbersand weighted mean copy numbers of the cell lines as determined byPICNIC. Pearson's CC ¼ 0.94, P < 0.0001. C, correlation of SCCS withploidy as determined by weighted mean copy number (PICNIC) of SNPArray data. Pearson's CC ¼ 0.746, P ¼ 0.0002.

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PIK3CA mutation was the only somatic mutationsignificantly associated with altered sensitivity to inhibi-tors grouped according to target kinase families [PIK3CA

mutation associated with increased sensitivity to inhibitorstargeting AKT, Aurora kinase, EGFR, PDGFR, andPI3K, Wilcoxon–Mann–Whitney test, corrected P ¼ 0.003,

A C

Legend

Fraction of survivingcells compared withvehicle control <0.2 0.2 to <0.4 0.4 to <0.6 0.6 to <0.8 >0.8

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P < 0.0001

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Figure 2. Eighteen CINþ and 9 CIN� CRC cell lines were treated with 160 kinase inhibitors at 10 mmol/L for 72 hours. A, a higher fraction of cells surviveinhibitor treatment in CINþ cell lines than in CIN� cell lines (P < 0.0001). B, boxplot of median cell number following inhibitor treatment across all inhibitorsfor all cell lines. The length of the whiskers was limited by maximal ¼ 1.5 times the interquartile range in this boxplot and throughout. C, heatmapshowing the relative numbers of surviving cells following inhibitor treatment across the cell lines (inhibitors that have minimal impact on cell growth defined asa surviving cell fraction of >0.8 in >75% of the cell lines tested have been excluded).




DOI:10.1158/0008-5472.CAN-10-3604



P ¼ 0.038, P ¼ 0.016, P ¼ 0.038, and P ¼ 0.004, respectively;Supplementary Fig. 3B]. We found no evidence for a specificassociation with either PIK3CA exon 9 or 20 mutation statusand drug sensitivity (data not shown). Notably, PIK3CAmutations were more likely to occur in CIN� than in CINþ

cell lines (P ¼ 0.0066, Fisher's exact test).No single somatic mutation was associated with altered

sensitivity to all inhibitors. Next, data for somatic mutationstatus and CIN status were pooled. When corrected for multi-ple testing by the Benjamini–Hochberg method under theassumption that the tests are either positively correlatedor independent (45), CINþ status was the only parametersignificantly associated with multidrug resistance (correctedP ¼ 0.01; Supplementary Fig. 3B). Taken together, these datasuggest that the association of PIK3CA mutation with CIN�

status may confound the interpretation of the associationof PIK3CA mutation status with sensitivity to specific inhibi-tors and may simply reflect the intrinsic drug sensitivity ofCIN� cells.

Isogenic CINþ CRC cell lines display intrinsic multidrugresistance

To support a direct role for the contribution of CIN to themultidrug-resistant phenotype, we assessed whether drugsensitivity was altered in isogenic CRC models of CIN. TheHCT116 MAD2þ/� cell line has one allele of the SAC gene,MAD2, deleted by homologous recombination, resulting innumerical CIN relative to its diploid parental cell line (9). Wetreated the isogenic HCT116 MAD2þ/� cell and its parentaldiploid cell line with the kinase inhibitors and assessed thesurviving cell line fraction after treatment. Consistent with thenonisogenic cell line data presented previously, the MAD2þ/�

cell line was found to be more resistant overall to theinhibitors tested than to the parental diploid cell line (one-sided Wilcoxon signed-rank test, P ¼ 0.001; Fig. 3A and B). Nosingle inhibitor seemed to specifically target the HCT116MAD2þ/� cell line.

To further test the association of CIN with intrinsic drugresistance to drugs other than kinase inhibitors, we challengedthe HCT116 MAD2þ/� and another CINþ isogenic cell line,HCT116 PTTG1�/�, together with their isogenic parentaldiploid HCT116 cell lines with the Biolog cytotoxic librarycontaining 92 anticancer cytotoxic agents. Consistent with thedata from the kinase inhibitors, both the CINþMAD2þ/� andPTTG1�/� cells were significantly more resistant (one-sidedWilcoxon signed-rank test, P < 0.001, except P ¼ 0.035 at thelowest concentration of drug for PTTG1�/�) to a diverse rangeof anticancer agents than to the parental diploid cell lines(Fig. 3C and D).

Importantly, both the HCT116 MAD2þ/� and parentaldiploid cell lines continue to display MINþ (SupplementaryFig. 4), indicating that MIN status is unlikely to sufficientlyexplain the altered drug sensitivity in the CINþ isogenicmodels. These data suggest that CINþ status, initiatedby ongoing chromosome missegregation events driven byloss of 2 distinct proteins controlling mitotic fidelity, isthe dominant phenotype associated with altered drugsensitivity.

CINþ not tetraploidy is associated with drug resistanceCINþ CRC cell lines missegregate chromosomes at a high

rate, in contrast to CIN� CRC cells that have a lower frequencyof mitotic errors (1, 2). In addition, CIN� cells fail to toleratethe propagation of CIN when chromosome segregation errorsare artificially induced by drug treatment (11), suggesting thatsustaining CIN in a cell population may require a specializedsurvival phenotype. The majority of CINþ CRC cell lines usedin this study are triploid or tetraploid. We therefore consid-ered whether altered ploidy status, rather than ongoing CIN,might be associated with enhanced drug resistance. Clonaltetraploid and diploid HCT116 cells were treated with thekinase inhibitors. There was no significant difference in therelative number of surviving cells following drug treatmentbetween HCT116 tetraploid clone 4 (TC4) cell line and diploidclone 8 (DC8) cell line. However, tetraploid clone 9 (TC9) wassignificantly more resistant than the DC8 cell line (Wilcoxonsigned-rank test, P < 0.001; Fig. 4A). Further investigation byclonal FISH (Fig. 4B) revealed that TC9 had a more hetero-geneous karyotype compared with TC4 cell lines, with asignificantly higher proportion of cells that deviated fromthe mode of 4 copies of both chromosomes 2 and 15 (Fisher'sexact test, P ¼ 0.05; Fig. 4C). This implies that karyotypicheterogeneity, rather than increased ploidy, might be respon-sible for increased drug resistance compared with karyotypi-cally stable diploid cells. We cannot formally exclude thepossibility that acquired mutations present in the drug-resis-tant tetraploid clone that may have permitted the sponta-neous tetraploid phenotype may primarily be responsible forincreased drug resistance.

Taken together with the isogenic cell line data sets pre-sented here, where CIN is artificially induced through loss ofone allele of MAD2 or both copies of PTTG1, these resultssupport the contribution of CIN, rather than increased ploidystatus or MIN, in conferring altered drug sensitivity.

Relationship between CIN status and benefit fromcytotoxic therapy in clinical datasets

Published clinical data support the view that CINþ CRCis associated with a worse prognosis compared with CIN�

tumors (6), and data presented here suggest that CINþ celllines display intrinsic multidrug resistance. Conceivably,the poorer prognosis of CINþ disease may relate in partto intrinsic drug resistance of thymidylate synthase inhi-bitors, cytotoxics commonly used in the adjuvant treatmentof CRC. Consistent with this hypothesis, both isogenicCINþ cells are significantly more resistant to the majorityof thymidylate synthase inhibitors tested, including 5-FU,and non-isogenic CINþ cells are more resistant to 5-FU thanto CIN� cell lines, at physiologic concentrations (Supple-mentary Fig. 6A, B).

Next, we asked whether CINþ status might be associatedwith poorer outcome following adjuvant therapy with 5-FU–based regimens. A meta-analysis of studies examining therelationship between CIN and prognosis in locoregional CRC,revealed that CINþ disease (defined as aneuploidy/poly-ploidy determined using flow cytometry) confers a worseoverall survival (30 studies) (Supplementary Fig. 5A) and

Lee et al.



DOI:10.1158/0008-5472.CAN-10-3604



MA

D2 +/–

4'- demethyl epipodophyllotoxin 1 0.32 0.854'- demethyl epipodophyllotoxin 24'- demethyl epipodophyllotoxin 34'- demethyl epipodophyllotoxin 45-fluoro-5'-DeoxyurIdine 35-fluoro-5'-DeoxyurIdine 4 0.76-amino nicotinamide 4Acivicin 2 0.42 0.83Acivicin 3 0.24 0.54Acivicin 4 0.22 0.4Aclarubicin 1Aclarubicin 2Aclarubicin 3Aclarubicin 4Acriflavinium Hydrochloride 2Acriflavinium Hydrochloride 3Acriflavinium Hydrochloride 4Aklavine Hydrochloride 1 0.28 0.87Aklavine Hydrochloride 2 0.28 0.73Aklavine Hydrochloride 3 0.6Aklavine Hydrochloride 4 0.4Aminopterin 1 0.36 0.41Aminopterin 2 0.36 0.54Aminopterin 3 0.44 0.42Aminopterin 4 0.34 0.42Amygdalin 1 0.72 1.01Amygdalin 3 0.64 0.97Amygdalin 4 0.62 0.94Ancitabine Hydrochloride 1 0.79 0.94Ancitabine Hydrochloride 2 0.45 0.94Ancitabine Hydrochloride 3 0.43 0.88Ancitabine Hydrochloride 4 0.33 0.76Azacytidine 2 0.76 1Azaserine 1 0.74 0.98Azathioprine 4 0.72 0.81beta-Peltatin 1 0.31 0.76beta-Peltatin 2 0.65beta-Peltatin 3 0.6beta-Peltatin 4 0.62Camptothecin 1Camptothecin 2Camptothecin 3Camptothecin 4Carboplatin 4 0.79 0.98Carmofur 3 0.63 0.85Carmofur 4 0.33 0.44Chloramphenicol 4 0.51 0.96Colchicine 1 0.17 0.63Colchicine 2 0.3 0.65Colchicine 3 0.22 0.64Colchicine 4 0.16 0.67Cycloheximide 1 0.46 0.75Cycloheximide 2 0.26 0.54Cycloheximide 3 0.15 0.34Cycloheximide 4 0.13 0.26Cytosine-Beta-Darabinofuranoside 1 0.31 0.7Cytosine-Beta-Darabinofuranoside 2 0.29 0.66Cytosine-Beta-Darabinofuranoside 3 0.3 0.69Cytosine-Beta-Darabinofuranoside 4 0.34 0.62Dactinomycin 1 0.1 0.38Dactinomycin 2 0.33 0.53Dactinomycin 3 0.18 0.46Dactinomycin 4 0.15 0.3Daunorubicin Hydrochloride 1 0.24 0.67Daunorubicin Hydrochloride 2 0.17 0.39Daunorubicin Hydrochloride 3 0.12 0.35Daunorubicin Hydrochloride 4 0.06 0.16Doxorubicin Hydrochloride 1 0.28 0.65Doxorubicin Hydrochloride 2 0.06 0.14Doxorubicin Hydrochloride 3 0.17 0.4Doxorubicin Hydrochloride 4 0.14 0.31Ellagic Acid 4 0.63 0.88Emetine 3 0.07 0.25Emetine 4 0.08 0.21Etoposide 2 0.58 0.92Etoposide 3 0.47 0.91Etoposide 4 0.49 0.81Floxuridine 1 0.54 0.86Floxuridine 2 0.38 0.7Floxuridine 3 0.23 0.39Floxuridine 4 0.13 0.28Fluorouracil (5-FU) 3 0.6 0.86Fluorouracil (5-FU) 4 0.32 0.44Gossypol 4 0.29 0.4Juglone 1 0.5 0.8Juglone 2 0.32 0.94Juglone 3 0.34 0.97Juglone 4 0.2 0.71Mercaptopurine 3 0.73 1.02Mercaptopurine 4 0.51 0.72Methotrexate 1 0.31 0.44Methotrexate 2 0.33 0.42Methotrexate 3 0.3 0.43Methotrexate 4 0.33 0.45Mitomycin C 2 0.22 0.61Mitomycin C 3 0.06 0.15Mitomycin C 4 0.05 0.04Mitoxantrone Hydrochloride 1 0.61 0.93Mitoxantrone Hydrochloride 2 0.27 0.78Mitoxantrone Hydrochloride 3 0.07 0.13Mitoxantrone Hydrochloride 4 0.12 0.21Mycophenolic acid 2 0.64 0.87Mycophenolic acid 3 0.45 0.79Mycophenolic acid 4 0.32 0.6Neriifolin 1 0.1 0.14Neriifolin 2 0.09Neriifolin 3 0.07Neriifolin 4 0.07Nocodazole 1 0.15 0.7Nocodazole 2 0.2 0.67Nocodazole 3 0.16 0.69Nocodazole 4 0.18 0.68p-Fluorophenylalanine 3 0.91 0.79Phenethyl caffeate (CAPE) 4 0.54 0.82Picropodophyllotoxin 2 0.45 0.81Picropodophyllotoxin 3 0.3 0.79Picropodophyllotoxin 4 0.3 0.69Podofilox 1 0.21 0.61Podofilox 2 0.2 0.59Podofilox 3 0.18 0.63Podofilox 4 0.18 0.6Puromycin Hydrochloride 1 0.59 0.76Puromycin Hydrochloride 2 0.1 0.05Puromycin Hydrochloride 3 0.08 0.05Puromycin Hydrochloride 4 0.09 0.08Quinacrine Hydrochloride 2 0.21 0.75Quinacrine Hydrochloride 3 0.14 0.48Quinacrine Hydrochloride 4 0.08 0.22Rifaximin 4 0.72 0.99Rotenone 3 0.49 0.85Rotenone 4 0.33 0.72Sanguinarine Sulfate 3 0.77 1.02Sanguinarine Sulfate 4 0.04 0.07Thioguanine 2 0.77 0.93Thioguanine 3 0.58 0.58Thioguanine 4 0.65 0.58Vinblastine Sulfate 1 0.17 0.62Vinblastine Sulfate 2 0.18 0.64Vinblastine Sulfate 3 0.19 0.65Vinblastine Sulfate 4 0.23 0.6

PTTG1 –/–

4'- demethyl epipodophyllotoxin 24'- demethyl epipodophyllotoxin 34'- demethyl epipodophyllotoxin 45-fluoro-5'-DeoxyurIdine 3 0.35 0.645-fluoro-5'-DeoxyurIdine 4 0.19 0.366-amino nicotinamide 4 0.62 0.7Acivicin 2 0.39 0.73Acivicin 3 0.23 0.21Acivicin 4 0.11 0.13Aclarubicin 1 0.03 0.43Aclarubicin 2 0.04 0.52Aclarubicin 3 0.17 0.17Aclarubicin 4 0.16 0.21Acriflavinium Hydrochloride 2 0.62 0.99Acriflavinium Hydrochloride 3 0.13 1.05Acriflavinium Hydrochloride 4 0.05 1.14Aklavine Hydrochloride 1 0.3 0.44Aklavine Hydrochloride 2 0.26 1.13Aklavine Hydrochloride 3 0.2 0.56Aklavine Hydrochloride 4 0.22 0.28Aminopterin 1 0.1 0.24Aminopterin 2 0.1 0.64Aminopterin 3 0.09 0.26Aminopterin 4 0.1 0.32Amygdalin 3 0.49 0.64Amygdalin 4 0.38 0.6Ancitabine Hydrochloride 1 0.52 0.55Ancitabine Hydrochloride 2 0.38 0.5Ancitabine Hydrochloride 3 0.32 0.53Ancitabine Hydrochloride 4 0.27 0.41Azacytidine 4 0.77 0.65Azathioprine 4 0.53 0.71beta-Peltatin 1 0.18 0.45beta-Peltatin 2 0.13 0.29beta-Peltatin 3 0.13 0.21beta-Peltatin 4 0.14 0.51Camptothecin 1 0.1 0.28Camptothecin 2 0.07 0.21Camptothecin 3 0.08 0.92Camptothecin 4 0.15 0.94Carmofur 2 0.76 0.87Carmofur 3 0.43 0.49Carmofur 4 0.2 0.31Cepharanthine 4 0.46 0.31Chloramphenicol 4 0.51 0.55Colchicine 1 0.11 0.26Colchicine 2 0.12 0.17Colchicine 3 0.13 0.28Colchicine 4 0.14 1.22Cycloheximide 1 0.45 0.64Cycloheximide 2 0.28 0.61Cycloheximide 3 0.16 0.32Cycloheximide 4 0.1 0.48Cytosine-Beta-Darabinofuranoside 1 0.3 0.34Cytosine-Beta-Darabinofuranoside 2 0.23 0.34Cytosine-Beta-Darabinofuranoside 3 0.21 0.58Cytosine-Beta-Darabinofuranoside 4 0.2 0.25Dactinomycin 1 0.13 1.21Dactinomycin 2 0.26 0.83Dactinomycin 3 0.27 0.29Dactinomycin 4 0.2 0.21Daunorubicin Hydrochloride 1 0.16 0.3Daunorubicin Hydrochloride 2 0.18 0.24Daunorubicin Hydrochloride 3 0.18 1.25Daunorubicin Hydrochloride 4 0.05 1.16Doxorubicin Hydrochloride 1 0.12 0.66Doxorubicin Hydrochloride 2 0.15 1.26Doxorubicin Hydrochloride 3 0.17 1Doxorubicin Hydrochloride 4 0.14 0.15Ellagic Acid 4 0.6 0.69Emetine 3 0.09 0.76Emetine 4 0.1 1.13Etoposide 2 0.75 0.51Etoposide 3 0.41 1.23Etoposide 4 0.34 0.51Floxuridine 1 0.39 0.39Floxuridine 2 0.22 0.25Floxuridine 3 0.1 0.14Floxuridine 4 0.08 0.12Fluorouracil (5-FU) 2 0.76 0.97Fluorouracil (5-FU) 3 0.49 0.76Fluorouracil (5-FU) 4 0.27 0.31Gossypol 4 0.14 0.15Juglone 1 0.24 0.36Juglone 2 0.35 0.73Juglone 3 0.32 0.63Juglone 4 0.25 1.21Mercaptopurine 4 0.33 0.52Methotrexate 1 0.11 0.27Methotrexate 2 0.12 0.26Methotrexate 3 0.11 0.43Methotrexate 4 0.11 0.46Mitomycin C 1 0.9 0.71Mitomycin C 2 0.17 0.18Mitomycin C 3 0.05 0.06Mitomycin C 4 0.03 0.03Mitoxantrone Hydrochloride 1 0.42 1.23Mitoxantrone Hydrochloride 2 0.17 0.69Mitoxantrone Hydrochloride 3 0.05 0.08Mitoxantrone Hydrochloride 4 0.17 0.8Mycophenolic acid 2 0.56 0.64Mycophenolic acid 3 0.31 0.43Mycophenolic acid 4 0.26 0.29Neriifolin 1 0.09 0.12Neriifolin 2 0.09 0.11Neriifolin 3 0.07 0.19Neriifolin 4 0.06 0.06Nocodazole 1 0.11 0.19Nocodazole 2 0.1 0.32Nocodazole 3 0.1 0.17Nocodazole 4 0.11 0.23Phenethyl caffeate (CAPE) 4 0.6 0.94Picropodophyllotoxin 2 0.24 0.56Picropodophyllotoxin 3 0.14 0.39Picropodophyllotoxin 4 0.14 0.44Podofilox 1 0.13 0.23Podofilox 2 0.13 0.41Podofilox 3 0.13 0.29Podofilox 4 0.14 0.97Puromycin Hydrochloride 1 0.7 0.59Puromycin Hydrochloride 2 0.02 0.11Puromycin Hydrochloride 3 0.03 0.04Puromycin Hydrochloride 4 0.04 0.93Quinacrine Hydrochloride 2 0.54 0.97Quinacrine Hydrochloride 3 0.14 0.71Quinacrine Hydrochloride 4 0.05 0.17Rapamycin 3 0.86 0.8Rotenone 3 0.54 0.55Rotenone 4 0.3 0.51Sanguinarine Sulfate 1 0.41 1.02Sanguinarine Sulfate 4 0.07 1.13Tamoxifen Citrate 4 0.79 1.06Thioguanine 2 0.63 0.94Thioguanine 3 0.32 0.48Thioguanine 4 0.24 0.37Urethane 4Vinblastine Sulfate 1Vinblastine Sulfate 2Vinblastine Sulfate 3Vinblastine Sulfate 4

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Akt Inhibitor IVAlsterpaulloneAlsterpaullone 2-CyanoethylAurora Kinase/Cdk InhibitorCdc2-Like Kinase Inhibitor TG003Cdk/Crk InhibitorCdk2 Inhibitor IV NU6140Compound 52EGFR InhibitorERK Inhibitor II Negative controlGo 6976 GSK-3 Inhibitor XGSK-3b Inhibitor XIHA 1077 Dihydrochloride FasudilHerbimycin A Streptomyces sp.IKK-2 Inhibitor IVIndirubin-3'-monoximeIsogranulatimideJAK3 Inhibitor VIJNK Inhibitor IXK-252a Nocardiopsis sp. MK2a InhibitorPD 169316PDGF Receptor Tyrosine Kinase Inhibitor IVPDK1/Akt/Flt Dual Pathway InhibitorPI-103SB220025Staurosporine Streptomyces sp.Staurosporine Streptomyces sp.

P - values

Diff

eren

ce in

sur

vivi

ng c

ell f

ract

ion

betw

een

HC

T11

6 M

AD

2 +

/– a

nddi

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d pa

rent

al−

0.2

0.0

0.2

0.4

Diff

eren

ce in

mea

n re

lativ

e ce

ll nu

mbe

rbe

twee

n H

CT

116

MA

D2+

/− a

nd d

iplo

idpa

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al a

fter

inhi

bito

r tr

eatm

ent

P < 0.001

−0.

20.

00.

20.

40.

60.

81.

0

<0.001 <0.001 <0.001 <0.001

−0.

20.

00.

20.

40.

60.

81.

0

0.035 <0.001 <0.001 <0.001

Legend

Fraction of survivingcells compared withvehicle control

0.2 to <0.4 0.4 to <0.6 0.6 to <0.8 >0.8<0.2

Drug Concentration

Diploid

Parental

Diploid

Parental

Legend

Fraction of survivingcells compared withvehicle control

0.2 to <0.4 0.4 to <0.6 0.6 to <0.8 >0.8<0.2

HCT116 MAD2+/-

vs. diploid parental

Drug concentration

Figure 3. A, boxplot showing that following treatmentwith kinase inhibitors, there seemed to bea higher surviving fractionof cells in theHCT116MAD2þ/� cell linethan in its parental diploid cell line (P < 0.001) following treatment with each equivalent inhibitor. B, heatmap showing the relative numbers of surviving cellsfollowing the inhibitor treatments compared with vehicle control across the HCT116MAD2þ/� and parental diploid cell lines (inhibitors that show a surviving cellfraction of >0.8 in both cell lines have been excluded). C, Biolog M11–M14 drug microplates were used at 4 increasing concentrations per drug (0.1–25 mmol/L)to treat HCT116 MAD2þ/� and PTTG1�/� and their parental diploid cell lines for 72 hours. The boxplot shows difference in relative surviving cell numberacross all drugs at each of the 4 concentrations, comparingMAD2þ/� and PTTG1�/� cells to their specific isogenic parental cells. Significant P values suggesthigher resistance in MAD2þ/� or PTTG1�/� cells than in their parental diploid cells. D, heatmap of surviving fraction of cells compared with negative control inHCT116 MAD2þ/�, PTTG1�/�, and their parental diploid cell lines treated with Biolog drug microplates at 4 increasing concentrations per drug (1-4, 1 beingthe lowest). Drugs resulting in a surviving cellular fraction of more than 0.8 compared with negative control in both isogenic cell lines were excluded.




DOI:10.1158/0008-5472.CAN-10-3604



A C

TC4 vs. DC8 TC9 vs. DC8

P - values

0.078 <0.001

−0.

50.

00.

5

Histogram of copies of chromosome 2 per cellin TC 4

1 2 3 4 5 6 7 80

50

100

150

Copies of chromosome 2 per cell

Fre

quen

cy

1 2 3 4 5 6 7 80

50

100

150

B

TC 4

TC9

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Fre

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1 2 3 4 5 6 7 8 90

50

100

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Fre

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1 2 3 4 5 6 7 8 90

50

100

150



Fre

quen

cy

% Cells with4 copies of

both Chr 2 and 15

% Cells withnumber of copies ≠4

of either Chr 2 or Chr 15

TC4 37 63

TC9 28 72

Fisher’s exact test, P = 0.05

TC4

Figure 4. A, boxplot of relative surviving cell numbers comparing HCT116 TC4 and DC8 cell lines and TC9 with DC8 cell lines. The TC9 cell line wassignificantly more resistant than DC8 (P < 0.001). The difference in drug sensitivity between TC4 and DC8 was not significant (P ¼ 0.078). B, representativeFISH images for TC4 and TC9. Probes against chromosome 15 in green. C, histogram showing distribution of number of markers per cell corresponding tochromosome 2 (top two) and 15 (bottom two) in TC4 and TC9. TC9 had a statistically significant higher proportion of cells that deviated from having 4 copies ofboth chromosomes 2 and 15 (P ¼ 0.05) than that in TC4.

Lee et al.



DOI:10.1158/0008-5472.CAN-10-3604



progression-free survival (15 studies) (SupplementaryFig. 5B) compared with patients with diploid CRC. Similarly,if only patients who received chemotherapy are included(2 studies; ref. 46, 47), CINþ tumors are associated with aworse overall survival (Fig. 5A).Two studies explore the predictive value of CIN (46, 48) in

patients with locoregional CRC who received either adjuvantchemotherapy or no chemotherapy following surgery (Fig. 5B).Patients with diploid CRC seem to benefit from 5-FU–basedtherapy (N ¼ 262, HR ¼ 0.61; 95% CI ¼ 0.40–0.94, P ¼ 0.024;I2 ¼ 0%, P¼ 0.467) compared with untreated diploid controls,whereas there was no significant difference between treatedand untreated CINþ CRCs (N¼ 303, HR¼ 0.81; 95% CI¼ 0.57–

1.16, P ¼ 0.250; I2 ¼ 0%, P ¼ 0.932). The combined analysisof all patients suggests a benefit following 5-FU treatmentcomparable with that reported in the literature for geneticallyunselected patients (49). While these studies are limited,they are consistent with the view that patients with CINþ

CRC derive less benefit from 5-FU–based adjuvant cytotoxicchemotherapy than patients with diploid CRC. Prospectiveevaluation of the association of CINþ disease with the efficacyof combination regimens (e.g., 5-FU/oxaliplatin) in stage 3 and5-FU/oxaliplatin and irinotecan in stage 4 disease might beconsidered to assess whether clinical outcome followingthese more recent regimens has a similar association withCIN status.

Figure 5. A, impact of CINþ ondisease-free survival, overallsurvival, and those receivingadjuvant chemotherapy inlocoregional CRC. Overall CINþ

seems to confer a worseprognosis compared with diploid.B, benefit derived from adjuvant5-FU in patients with (near) diploid(top) and CINþ (middle) CRC.Patients with diploid CRC seem tobenefit more from chemotherapythan patients with CINþ tumors.Combined analysis of CINþ anddiploid patients shows similarmagnitude of benefit as would beexpected from literature (bottom;ref. 49).




DOI:10.1158/0008-5472.CAN-10-3604



Discussion

In this analysis, we have provided evidence that CINþ

CRC cell lines display intrinsic multidrug resistance com-pared with CIN� cell lines. No specific kinase inhibitorwas identified that displayed greater activity in CINþ celllines. We cannot exclude the potential for off-target effectsat the concentrations of kinase inhibitors used in thisanalysis; however, the same conditions were applied tothe CIN� cells and therefore off-target phenomena areunlikely to change the conclusions of this work. Further-more, in the isogenic systems, we observed significant drugresistance in the CINþ cell lines relative to their isogenicparental CIN� pairs at all concentrations of cytotoxicstested (ranging from 0.1 to 25 mmol/L). Intriguingly, theisogenic CINþ and tetraploid cell line systems suggest thatthe primary association is between multidrug resistance andCINþ rather than tetraploidy. It has been previously shownthat aneuploid cell lines can acquire multidrug resistanceat an accelerated rate (50) that may be driven by cancercell heterogeneity resulting from multiple chromosomalreassortments in aneuploid cells. The short time courseof our experiments in comparison with this study suggeststhat multidrug resistance is likely to be an intrinsic pro-perty of CINþ cells rather than a process that is acquiredin our cell systems over multiple generations. What mightcontribute to this intrinsic multidrug resistance pheno-type in CINþ cells? We speculate that either basal popula-tion heterogeneity in CINþ cell lines is sufficiently diverseto confer a cell viability advantage following drug exposureor there is a specific CINþ survival phenotype that initiates atolerance of ongoing chromosomal rearrangements that isalso associated with multidrug resistance.

There is increasing evidence in support of a CINþ survivalphenotype and putative molecular coordinators of thisproperty. Cell death after mitotic arrest may result fromtranscriptional inhibition due to condensed chromatin,precipitating the degradation of short-lived mRNA encod-ing prosurvival proteins (51). CINþ cells may overexpressthese prosurvival genes compared with diploid cells (22)that may drive the resistance of CINþ cells to a mitoticarrest triggered by taxanes. Jeganathan and colleagueshave shown that tolerance of chromosome missegregationevents can be conferred by a hypomorphic BUB1 allelein mouse embryonic fibroblasts (24). Recently, Thompsonand Compton have shown that chromosome missegregra-tion in diploid human cells triggers an increase in nuclearp53 and that p53 null cells are able to tolerate chromosomemissegregation events, enabling the propagation of aneu-ploid genomes (52). A higher proportion of the CINþ celllines used in our study have mutant p53 in comparison withthe CIN� cell lines. However, when we pooled data for

somatic mutation status and CIN status, CINþ status wasthe only parameter significantly associated with resistanceto these inhibitors.

Therefore, evidence exists for the coordination of apop-totic/cell death pathways following chromosome mis-segregation events. Conceivably, common molecularpathways regulating cell death following a chromosomemissegregation event may become disrupted in CINþ cells,simultaneously triggering tolerance of chromosome reas-sortments and, as an indirect consequence, resistance todrug exposure.

The observations that CINþ cancer cell lines seem to beless sensitive to a range of anticancer agents than to diploidcells and that poorer patient outcome follows cytotoxictreatment of CINþ tumors compared with diploid counter-parts strongly suggest the need to consider tumor strati-fication according to CIN status in the design of clinicaltrials testing novel anticancer agents in CRC. This isparticularly relevant to the advanced CRC setting wherethe incidence of CINþ is greater than in early-stage disease.Stratifying drug response according to CIN status may limitthe risk of early drug attrition and heighten the chance ofidentifying responder populations in patients with diploidtumors. Importantly, these data indicate that specificallytargeting cancer cells with CINþ status, using currentlyavailable kinase inhibitors, seems challenging. An improvedunderstanding of the mechanisms associated with thegeneration and survival of CINþ CRC will be importantto drive the development of new therapeutic approaches inorder to improve patient outcome in this high-risk diseasesubtype.

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Acknowledgments

We thank Robert Benezra for the donation of the isogenic HCT116MAD2þ/�

cell lines and Bert Vogelstein for the donation of the isogenic HCT116 PTTG1�/�

cell lines.

Grant Support

C. Swanton is a senior Medical Research Council clinical research fellow andis funded by both Cancer Research UK (CRUK) and the Medical ResearchCouncil. A.J.X. Lee is funded by CRUK. I.P.M. Tomlinson is supported by theOxford Biomedical Research Centre and CRUK.

The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby markedadvertisement in accordance with 18 U.S.C. Section 1734 solely to indicate thisfact.

Received October 6, 2010; revised December 23, 2010; accepted January 8,2011; published OnlineFirst March 1, 2011.

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