Chromosomal Instability Confers Intrinsic Multidrug Resistance

Cancer Therapeutics, Targets, and Chemical Biology Research

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

Abstract Aneuploidy 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 of multidrug resistance in vitro and heighten risk for tumor relapse in animal models. Identification of distinct therapeutic agents that target tumor karyotypic complexity has important clinical implications. To identify distinct therapeutic approaches to specifically limit the growth of CIN tumors, we focused on a panel of þ colorectal cancer (CRC) cell lines, previously classified as either chromosomally unstable (CIN ) or diploid/near- diploid (CIN ), and treated them individually with a library of kinase inhibitors targeting components of signal þ transduction, cell cycle, and transmembrane receptor signaling pathways. CIN cell lines displayed significant intrinsic multidrug resistance compared with CIN cancer cell lines, and this seemed to be independent of somatic mutation status and proliferation rate. Confirming the association of CIN rather than ploidy status with multidrug resistance, tetraploid isogenic cells that had arisen from diploid cell lines displayed lower drug sensitivity than their diploid parental cells only with increasing chromosomal heterogeneity and isogenic cell þ line models of CIN displayed multidrug resistance relative to their CIN parental cancer cell line derivatives. In þ a meta-analysis of CRC outcome following cytotoxic treatment, CIN predicted worse progression-free or disease-free survival relative to patients with CIN disease. Our results suggest that stratifying tumor responses according to CIN status should be considered within the context of clinical trials to minimize the confounding effects of tumor CIN status on drug sensitivity. Cancer Res; 71(5); 1858–70. 2011 AACR.

Introduction instability (CIN), resulting in ongoing numerical and structural chromosomal aberrations in cancer cells, leading to Colorectal cancer (CRC) is associated with at least 2 intratumoral heterogeneity (2, 3). The less common pattern distinct patterns of genomic instability (1). The more com- is microsatellite instability (MIN) caused by a deficiency in mon form of genomic instability in CRC is chromosomal the mismatch repair apparatus. Because of the accumulation of replication errors, MIN results in length variation of þ microsatellite sequences in DNA. Most MIN CRC cell lines 1 are near-diploid (4, 5) and chromosomally stable (CIN ). In Authors' Affiliations: Translational Cancer Therapeutics Laboratory, þ 2Signal Transduction Laboratory, and 3High Throughput Screening contrast, CIN CRC cell lines are aneuploid and display a Laboratory, Cancer Research UK London Research Institute, London, higher frequency of chromosomal missegregation errors United Kingdom; 4University of Applied Sciences, Mathematics and 5 during each mitosis relative to diploid cells (2). In human Techniques, Remagen, Germany; Molecular and Population Genetics, þ The Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom; CRC, CIN is widely inferred through the measurement of 6 Royal Marsden Hospital, Department of Medicine, Sutton, United King- tumor DNA ploidy (6); normal diploid cells are defined with dom; 7Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark; 8Cancer Genome Project, Wellcome Trust a DNA index of 1.0 (7) and thus an increase in DNA index Sanger Institute, Cambridge, United Kingdom; and 9Children's Hospital infers polyploidy or aneuploidy. Approximately 25% of Informatics Program at the Harvard-MIT Division of Health Sciences and human CRC are both CIN and MIN (6). Technology, Harvard Medical School, Boston, Massachusetts þ Consistent molecular mechanisms responsible for the CIN Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/). phenotype and hence means to target this pattern of genome instability in colorectal and other solid tumors remain poorly A.J.X. Lee and D. Endesfelder contributed equally to the work. defined. Putative mechanisms that may contribute to CIN Corresponding Author: Charles Swanton, Translational Cancer Therapeu- ticsLaboratory, Cancer Research UKLondonResearch Institute,44Lincoln's include weakening of the spindle assembly checkpoint (SAC; Inn Fields, London WC2A 3LY, United Kingdom. Phone: 44-20-7269-3463; refs. 8, 9), defective sister chromatid cohesion (10), merotelic Fax 44-20-7269-3094; E-mail: [email protected] sister chromatid attachments (11), defective cytokinesis (12), doi: 10.1158/0008-5472.CAN-10-3604 centrosome amplification (13), and chromosome breakage– 2011 American Association for Cancer Research. fusion–bridge cycles (14).

1858 Cancer Res; 71(5) March 1, 2011

Increasing evidence suggests that CIN is associated with analysis were present within the CLP database, and a total of poor prognosis in solid tumors (6, 15, 16). It has been sug- 20 of the 61 genes resequenced in the project were found to gested that adverse outcome associated with CIN may be have somatic mutations in at least 1 of those 21 cell lines. related to increased tumor cell heterogeneity, driving the Additional information regarding the somatic mutation status ability of tumors to adapt to environmental stresses (17– of APC, CTNNB1, KRAS, MLH1, PIK3CA, and TP53 were 19). Consistent with a hypothesis whereby CIN may enhance obtained from both published (32–35) and internal laboratory þ tumor adaptation, transient initiation of CIN, following the data. Isogenic HCT116 MAD2 / cell lines (9) and HCT116 brief induction of MAD2 expression in activated KRAS- PTTG1 / cell lines (10) were donated courtesy of Drs. initiated mouse lung tumor models, is associated with a high Benezra and Vogelstein, respectively. To generate tetraploid frequency of tumor recurrence following withdrawal of the HCT116 cells, naturally occurring tetraploid cells were iso- KRAS oncogenic stimulus (20). Preclinical studies have shown lated from the parental cell line and single cell sorted using that CIN is associated with the rapid acquisition of multidrug flow cytometry. Clonal FISH was performed with centromere resistance in cell line systems (21) and intrinsic taxane resis- enumeration probes against centromeres on chromosomes 2 tance in vitro and in vivo (22). Recently, we and others have and 15. proposed the existence of a CIN survival phenotype that þ allows CIN tumor cells to tolerate the impact of excessive Calbiochem Kinase Inhibitor Library and 5-FU screen chromosome gains and losses (22–24) that may in turn impact Calbiochem Kinase Inhibitor Libraries I and II (EMD Bios- upon altered drug sensitivity. ciences) containing 160 inhibitors were used. Comprehensive Determining how CIN might impact upon prognosis and data for these inhibitors including references documenting how this pattern of genomic instability might be specifically target inhibition or downstream signaling cascade inactiva- targeted remains an important research area (23, 25). Evi- tion can be found on the manufacturer's Web site (36). dence in lower eukaryotes has shown that aneuploid Sacchar- Cells were plated into 96-well tissue culture microplates at omyces cerevisiae are dependent on increased glucose an initial seeding density of 4,000 cells per well. After 24 hours, utilization and are more sensitive to both heat shock protein cells were treated with the inhibitors at a final concentration of 90 and proteosome inhibitors (26). Polyploid S. cerevisiae are 10 mmol/L per well. This concentration was selected following dependent upon increased expression of genes involved in drug titration test analysis to give an optimal range of mean sister chromatid cohesion and mitotic spindle function (27). relative surviving cells following inhibitor treatment across all Roschke and Kirsch have shown the existence of anticancer cell lines. After 72 hours of treatment, cell viability was assayed compounds that may specifically target karyotypically com- using the Celltiter-Blue Cell Viability Assay (Promega) accord- plex cancer cells (25). These observations indicate that ing to the manufacturer's instructions. The fluorescent readout karyotypic instability may be specifically targeted in eukar- for each inhibitor treated well was normalized to vehicle yotic organisms and suggest that CIN might be an exploitable control wells. For the HCT116 MAD2 isogenic cell lines, a final and targetable phenotype in cancer. inhibitor concentration of 1 mmol/L per well was used to allow To identify distinct therapeutic approaches to limit the for a larger range of surviving cells across all inhibitors. þ growth of CIN tumors relative to diploid cells, we focused on 5-Fluorouracil (5-FU) was used at both 1 and 10 mmol/L for a panel of CRC cell lines that had previously been classified as a treatment length of 72 hours. The 27 CRC cell lines were þ CIN or CIN and used kinase inhibitor and cytotoxic libraries plated and assayed using the same conditions and methods as to identify agents that might be preferentially lethal toward described earlier. þ þ CIN cells. Both isogenic and nonisogenic CIN cell lines displayed intrinsic multidrug resistance in vitro relative to Biolog Anti-Cancer Agent Microplate screen CIN cell lines. Importantly, consistent with the proposal that Biolog Anti-Cancer Agent Microplates M11–M14 consisting þ CIN is associated with intrinsic multidrug resistance, in a of 92 anticancer agents at 4 increasing concentrations þ meta-analysis of patient outcome in CRC, CIN was asso- between 0.1 and 25 mmol/L per agent were used. Cells were ciated with significantly worse clinical outcome relative to plated at an initial seeding density of 5,000 cells per well. After diploid cancers in both early- and late-stage disease following 72 hours, the number of surviving cells per well was assayed cytotoxic therapy. using Biolog Redox Dye Mix MA according to manufacturer's instructions and normalized to the negative control wells. Materials and Methods Cell proliferation assay Cell lines and FISH analysis We measured the proliferation rate of all 9 CIN and 18 þ 27 CRC cell lines (Table 1; Supplementary Table 1), pre- CIN CRC cell lines, using the IncuCyte Long-term Cell viously characterized for numerical/structural CIN, MIN sta- Imaging System. Cell lines were plated in 96-well plates at tus (2, 28–30), and subject to Affymetrix SNP 6.0 Array analysis an initial plating density of 4,000 cells per well and phase- where available (20/27 cell lines; Wellcome Trust Sanger contrast images were obtained every 2 hours over 70 hours, Institute), were used. allowing measurements of cell monolayer confluence. Outliers We used publicly available somatic mutation data from the were removed manually, and growth curves were fitted by Sanger Institute Cancer Cell Line Project (CLP) and COSMIC splines with the R package grofit (37) with smoothing para- þ database (31). Fifteen CIN and 6 CIN cell lines used in our meter smooth.gc ¼ 0.7.

www.aacrjournals.org Cancer Res; 71(5) March 1, 2011 1859

acrRs 15 ac ,2011 1, March 71(5) Res; Cancer Table 1. Cell lines used in this study al. et Lee Downloaded from cancerres.aacrjournals.org Cancer Research. on September 30, 2021.©2011AmericanAssociation for acrResearch Cancer

NOTE: Black indicates presence of mutation; white indicates absence of mutation; and gray indicates mutation status not known. CIN Confers Intrinsic Multidrug Resistance

Meta-analysis of clinical studies Results Survival data were summarized using a log hazard ratio for þ þ comparison between CIN and CIN groups. Data from Classification of CIN cell lines and relationship with individual studies were extracted using the methods described ploidy status and structural chromosomal complexity þ by Parmar and colleagues (38) and pooled to generate the We selected 9 CIN and 18 CIN CRC cell lines (Table 1). summary statistic and CIs using a fixed-effects model with CIN status for these cell lines had been previously described in inverse variance weighting. All meta-analyses were performed terms of numerical and structural chromosomal aberrations using Stata 10.1 (Stata Corp). (2, 28–30). To confirm the utility of published approaches for defin- Statistical methods ing the CIN status of the cell lines, where SNP Array data All tests were performed as 2-sided unless otherwise men- were available, we estimated the ploidy status of the cell tioned. To remove outliers, drugs resulting in relative number lines by using weighted mean integer copy numbers derived of cells greater than 1.4 were eliminated from analysis. A from the PICNIC (Predicting Integral Copy Numbers In Kolmogorov–Smirnov test was performed to test for overall Cancer) algorithm (ref. 40; Fig. 1A). Ploidy estimates classi- þ differences in the distribution of relative cell numbers follow- fied cells as CIN if they surpassed a threshold of ploidy þ ing inhibitor treatment between CIN and CIN cell lines. greater than 2.2 (corresponding to an estimated DNA index Inhibitors that showed a fraction of surviving cells greater of 1.1). In addition, modal chromosomal number as deter- than 0.8 in more than 75% of the cell lines were excluded from mined previously using high-quality metaphase spreads (28, the analysis. For comparisons of 2 cell lines, drugs resulting in 29) correlated well with ploidy estimates derived from relative number of cells greater than 0.8 in both cell lines were weighted mean PICNIC copy number analysis using the removed from analysis. A Wilcoxon signed-rank test was used SNP Array data [Pearson's correlation coefficient (CC) ¼ þ to test for differences between CIN and CIN cells (for each 0.94, Pearson's correlation test P < 0.0001; Fig. 1B]. These concentration of drug in Biolog microplates). For the Biolog data support the utility of SNP Array data for estimating microplates, each concentration of drug was used in duplicate; cell line ploidy status and are consistent with ploidy esti- therefore, the replicates which showed the least difference in mates by traditional measures, confirming the CIN status of cell number between the 2 cell lines was used for further cell lines used in this analysis. analysis. Next, we addressed the relationship between CIN status and The maximal slope of the growth curve (m) for each cell structural chromosomal complexity, using a summary struc- line was used to test whether the difference in drug sensi- tural chromosomal complexity score (SCCS) derived from the þ tivity between CIN and CIN colorectal cancer cell lines SNP Array data sets. This SCCS was determined by summar- þ was not solely due to different proliferation rates. CIN and izing (i) the number of break points, (ii) LOH events as CIN cell lines with m < 1 were tested with a one-sided predicted using PICNIC (40), and (iii) the Genome Integrity Wilcoxon–Mann–Whitney test. Next, we corrected for the Index (GII; ref. 41) into a single value for each cell line (Fig. 1C). influence of the proliferation rates of each cell line. We There was a highly significant correlation between ploidy estimated a linear regression model for all cell lines with status and the SCCS (Pearson's CC ¼ 0.746, P ¼ 0.0002). m < 1, where m was used as an independent variable and the Taken together, these analyses confirm that cells classified as þ mean fraction of surviving cells over all inhibitors as a CIN have significantly greater ploidy and structural chromo- dependent variable. The residuals of this analysis were somal complexity than CIN cells. þ tested for significant differences between CIN and CIN þ with a one-sided Wilcoxon–Mann–Whitney test (39). An CIN status is associated with intrinsic multidrug analysis of covariance model with interactions was applied, resistance where the mean fraction of surviving cells over all inhibitors Next, we aimed to determine whether a specific kinase þ was used as a dependent variable, m as a linear, independent inhibitor could be identified to selectively target CIN cell variable, and CIN status as a factor variable. The interaction lines. We used a small molecule library (Calbiochem Kinase termwasutilizedtotestforsignificant differences in slopes Inhibitor Library I and II) that included 160 inhibitors to treat þ þ between CIN and CIN cell lines. the 18 CIN and 9 CIN cell lines. Preliminary drug titration þ To test for significant differences in sensitivity to thymi- experiments revealed that the majority of the CIN cell lines dylate synthase inhibitors comparing HCT116 diploid par- were resistant to concentrations up to 1 mmol/L (Supplemen- þ ental and PTTG1 / or MAD2 / cells, we corrected for the tary Fig. 1) and therefore 10 mmol/L was selected as the influence of different concentrations by estimating a linear optimal drug concentration for cell growth inhibition across regression model for near linear correlations between con- the majority of cell lines in order to attempt to identify drugs þ centration and sensitivity or a one-way ANOVA otherwise. In that were specifically active in CIN cells. No specific inhibitor each case, the concentration was used as the independent or inhibitor family was found to be preferentially active in þ variable and the resulting residuals were tested for differ- CIN cell lines compared with CIN cell lines. In contrast, þ þ ences between CIN and CIN cells with a Wilcoxon–Mann– CIN cancer cell lines were significantly more resistant to the Whitney test. inhibitors (Kolmogorov–Smirnov test, P < 0.0001; Fig. 2A–C). All statistical analyses were performed in R and can be Following correction for multiple testing hypotheses, 45 inhi- found in the Supplementary Sweave document. bitors were identified which showed significantly greater

www.aacrjournals.org Cancer Res; 71(5) March 1, 2011 1861

þ activity in CIN cell lines than in CIN cell lines (Supplemen- A tary Table 2). To address whether the variation in drug sensitivity þ between the CIN and CIN cell lines was attributable to differences in proliferation rate, we calculated the maximum þ growth rate (m) for each cell line. We observed that CIN and CIN cell lines show significantly different slopes in regression lines (t test, P ¼ 0.007), with CIN cell lines showing a higher þ proliferation rate than in the CIN cell lines (Wilcoxon– Mann–Whitney test, P ¼ 0.003). These data are consistent with previous studies, suggesting that aneuploidy (42, 43) or chromosomal segregation defects (11, 44) have a negative impact on cellular proliferation rate. We observed a significant

01234 correlation between increased sensitivity to the inhibitors at þ ¼

T84 higher proliferation rates for CIN cell lines (Pearson's CC RKO HT55 GP2D SW48 HCT15 SW948 SW620 SW403 SKCO1 LS1034 LS174T Weighted mean PICNIC copy numbers ¼ HCT116 SW1463 SW1116 SW1417 0.61, P 0.007). In contrast, no such correlation was observed NCIH508 NCIH747 COLO205 COLO678 between proliferation rate and drug sensitivity in CIN cell B lines (Pearson's CC ¼ 0.24, P ¼ 0.55; Supplementary Fig. 2A). CC = 0.94 Neither ploidy index nor the SCCS showed a significant P < 0.0001 correlation with proliferation rate (data not shown). þ NCIH508 We next investigated whether CIN and CIN cell lines with similar proliferation rates displayed differential drug sensitiv- þ ity (cell lines with m < 1; 22/27 cell lines). CIN cell lines remained multidrug resistant compared with CIN cell lines within this group (one-sided Wilcoxon–Mann–Whitney test, P ¼ 0.013). Next, we used a more conservative approach and COLO205 LS1034 SKCO1 corrected for the influence of proliferation rate of each indi- þ HT55 vidual cell line within this group. CIN cell lines remained SW1417 SW403 SW948 significantly more drug resistant than CIN cell lines (one- NCIH747 SW1116 sided Wilcoxon–Mann–Whitney test, P ¼ 0.049; Supplemen- tary Fig. 2B). These data suggest that at similar growth rates, T84 þ COLO678 CIN cell lines remain more drug resistant than CIN cell Modal chromosome number/23 SW620 lines, indicating that proliferation rate is unlikely to be the HCT15GP2DSW48RKO 2.0LS174THCT116 2.5 3.0 3.5 4.0 4.5 main determinant of drug sensitivity. 2.0 2.5 3.0 3.5 4.0 4.5 Weighted mean PICNIC copy numbers Somatic mutation status and drug sensitivity Next, we addressed whether distinct tumor cell line somatic C mutations might be the underlying determinant of drug CC = 0.746 resistance rather than genomic instability status. We investi- P = 0.0002 gated whether the somatic mutation status of 20 genes COLO678 NCIH508 (Table 1) was associated with altered sensitivity either to inhibitors grouped according to target kinase family (Aurora SKCO1 kinase, AKT, CDK, EGFR, FLT-3, GSK-3, JAK3, JNK, MEK, COLO205 PDGFR, PI3K, and SYK) or to all inhibitors combined. We SW1417 addressed whether there was an association of drug sensitivity NCIH747 with somatic mutation status in 13 genes for which cell line SW1463 T84 HT55 group sizes had sufficient statistical power to compare drug SW948 sensitivity in wild-type compared with mutated cell lines. SW620 LS1034 SW403 SW1116

HCT116 Figure 1. A, barplot of the ploidy status of 20 CRC cell lines determined HCT15 LS174TRKO using mean copy number (PICNIC) of SNP Array data. Red line indicates GP2D þ 0.2 0.4 0.6 0.8 1.0 ploidy value threshold of 2.2. CIN cell lines in black text and CIN cell SW48 Structural chromosomal complexity score lines in red text throughout. B, correlation of modal chromosomal numbers and weighted mean copy numbers of the cell lines as determined by 2.0 2.5 3.0 3.5 4.0 4.5 PICNIC. Pearson's CC ¼ 0.94, P < 0.0001. C, correlation of SCCS with Weighted mean PICNIC copy numbers ploidy as determined by weighted mean copy number (PICNIC) of SNP Array data. Pearson's CC ¼ 0.746, P ¼ 0.0002.

1862 Cancer Res; 71(5) March 1, 2011 Cancer Research

Legend

Fraction of surviving A C cells compared with

vehicle control <0.2 0.2 to <0.4 0.4 to <0.6 0.6 to <0.8 >0.8 S

DLD1 SW1222 H747 NCI- SW837 SW1116 C 15 HCT GP2D RKO VACO5 LS174T HCA7 SW48 116 HCT 55 HT SW620 SW948 COLO678 LS1034 COLO205 SKCO1 T84 H508 NCI- C32 SW403 HDC57 SW1463 W

P < 0.0001 1

4 1 + 7 CIN – CIN AG 1478 111 1 1 011 1110 1 1 11110 11111111 AGL 2043 1 1 0 1 1 2 1 11111 1111111 11111111 Akt Inhibitor IV 00000 001 000 0 0000 00001011111 Akt Inhibitor V Tric iribine 110 1 0 1 1 111 2 1 11111 1 1 111111 11 Akt Inhibitor VIII Isozyme-Selec tive Akti-1/2 000 000 111 0 1 0 1 1111111 1 111 1 11 Akt Inhibitor X 0 1 0 00001 1 1 1 1 0 0 0 1 1 0 1 0 1 1 11112 Aloisine A RP107 0 0 1111 1 101111 1 1111111111111 Aloisine RP106 1 0 1111 1 11111111111111111111 Alsterpaullone 0001 002 1 00000001 1110111 1111 Alsterpaullone, 2-Cyanoethyl 0 00001 0 1 00000000101 0 1 1 11111 Aminopurvalanol A 00000 0 0 1 0 0000 0 0 1 10001111111 AMPK Inhibitor, Compound C 0 0 1 0 0 001101 1 1 0 1111111 111112 ATM Kinase Inhibitor 1 110001 1111 1112111111111111 ATM/ATR Kinase Inhibitor 0 0 0000 0 1 0000000 1 1010 111 1 111 Aurora Kinase Inhibitor II 1 0 0000011 1 00110 1 1111 1111111 Aurora Kinase Inhibitor III 000 0000110001 001 1000 1111111 Aurora Kinase Inhibitor III 0 0 0 0 0001 1 0001 001111 0 1111111 Aurora Kinase/Cdk Inhibitor 0 00000000 00000011110 1 111 111 BAY 11-7082 000001 001 0000 1 0 1 0000101 1 111 Bisindolylmaleimide I 0 0 000 0 0 111 1 1101 1 1 1 111 1 11111 number after inhibitor treatment BPIQ- I 1 1 11121 211 11111 111 0 11111111 111 111 111112111110 21111 2 1 11

0.0 0.2 0.4 0.6 0.8 1.0 Casein Kinase I Inhibitor, D4476 Cumulative distribution of relative cell Cdc2-Like Kinase Inhibitor, TG003 1111211111 111 1 1 111 1 0 11111 11 0.0 0.5 1.0 1.5 Cdk/Crk Inhibitor 00000001 000 000 0 000 1 0 1 1111 11 Cdk1 Inhibitor 000000000000100 1 00101 1 11111 Cdk1 Inhibitor, CGP74514A 00000000000 0000001 0 1 1 1 1 1 111 Relative number of cells Cdk1/2 Inhibitor III 0 0000000 0 0 0 0000001 1 1 1 111 111 Cdk2 Inhibitor III 0 1 0 0 000100001 0001 0 1 0 1 1 1 1 1 11 Cdk2 Inhibitor IV, NU6140 001 0001 1 110 11101 11111 111112 Cdk4 Inhibitor 0 0 0 0 0 001 00000 0 1010 1 0 11111 11 Cdk4 Inhibitor III 000000 0 1 00000000 0 1 0 1 111 1 1 1 1 Chelerythrine Chloride 00000001 1 0 0 0 0000000010111 11 Chk2 Inhibitor II 1 11111111111 1 111 111111111 11 Compound 52 0 1111 011 111 1 1 11110 1111 111 11 Compound 56 0 1 0 1 1 10111 1 11111 1 1 0 11111111 EGFR Inhibitor 00000 0 0 1 0 0001 0 0101001111111 EGFR/ErbB-2 Inhibitor 111 11001 1 0 211 111 111 11111111 EGFR/ErbB-2/ErbB-4 Inhibitor 00000 2 0 100000001 11001111111 ERK Inhibitor II, FR180204 1 1 111111 111111 1110 1 0 111 1 1 11 Fascaplysin Synthetic 0 1 000001 000 0 0000 0 1 0 1 101 1 1 1 1 Flt-3 Inhibitor II 001110 0 1 0 1 0 1 1 1111 1 111111111 Flt-3 Inhibitor III 00000 001 1 0001 001 002 0 1 1 111 11 Gö 6976 00011 0 0 1 0 0 0 0 00010 111 111 1111 Gö 6983 1 0 0 00001 1 1 1 111 111 11111111 11 B GSK-3 Inhibitor IX 00000001 00000000 0 1 1 1 111 1 1 1 1 GSK- 3 Inhibit or X 000 00001 0000001 1 0 1 1 2 1 1 1 1 1 1 1 GSK-3 Inhibitor XIII 0 0 1 0 0 001 00000 00110 0 0 1 1 111 11 GSK- 3b Inhibit or I 00111111 1 0 0 1 1 1 0 1 111 1 1 1 11111 GSK-3b Inhibitor VIII 1 1 111111 1 111 111 1 111 11111111 GSK- 3b Inhibit or XI 11111111 1112111110 1 0 111 1 1 11 GSK3b Inhibitor XII, TWS119 0 0 0 0 000 1000 1 1 0 1 111 1 0 1 1111 11 Herbimycin A, Streptomyces sp. 00000001 1 0000001 1 0 1 0 1 1 1 1111 IC261 0 0 0 0000 1 0 0 0 1110 1 1 110 1 1 1 1111 IGF-1R Inhibitor II 0 1111 111 1 1 00101 011 111111 111 IKK- 2 Inhibit or IV 00010001100 11000111 1 111 1 111 Indirubin Derivative E804 000 0000 1 0 0 0 0000101 0011 1 1111 Indirubin-3’-monoxime 001 1 110 1110 1 0 1 11111 1 1 111111 Isogranulatimide 1 1 1111 1 1 1 1 0 1111 1 1 010 1 1 1 1 1 11 JAK Inhibitor I 0 0 1 1 001 1 1100110 1 1 1 111 111111 JAK3 Inhibitor II 011 1110 1 1 1 1 1 1 1 1 111111111111 JAK3 Inhibitor IV 0 1 111 22111 110 1 1 1 1 1121111111 JAK3 Inhibitor VI 000 0 0001 00001001 1 0 1 0 1 111111 JNK Inhibitor 1 1111111 1 1 1 1 1 1 1111111111111 JNK Inhibitor II 0 0 1 11111 1 1 1 1 1 1 111111 1111111 JNK Inhibitor IX 0000000 1 0 001 1 0 0 1111111111 11 JNK Inhibitor V 0 0 1 0 111 1100100001110 1 1111 11 K-252a, Nocardiopsis sp. 00000001 0 000000001 0 1 111 1 1 1 1 Kenpaullone 0 0 0 00111 00000001 1 0 1 0 1 1 11111 KN- 93 0 1 1110 1111 0 111111111 1 1 1 1 111 Lck Inhibitor 1 11111 1 111 111111111 11111111 LY 294002 11001 0 1 1 1 1 1 0 1 1 1 1 1 11111 11111 MEK Inhibitor I 11112121 1 1 111 11111221111111 MEK Inhibitor II 0 0 11111111 1 1 0 1 0 1 111 11111111 MEK1/2 Inhibitor 1 1 1 1 0 1 1 1 1 101 11111111 1111111 Met Kinase Inhibitor 001 0 1 0 1110001 001 0 1111111 111 MK2a Inhibitor 0000 0 1 0 1 110 1 1 1 0 1 1 1 111111111 MNK1 Inhibitor 0 1 1111 11111 1 1 1 1 1 111 1 1111112 NF-kB Activation Inhibitor 1 1111 1 1 1 1 1 11111 1 112111 11112 0 1 1 110 0 1 1111 1 111 111 11111111 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 PD 158780 PD 169316 11111111 1 1 1 111 1 111111111111 Relative cell number after inhibitor treatment PD 98059 1 1 111111111 1 11111110 1111111 T84 C32 0000001 1 0 000 1 1 111 0111 111111 RKO PDGF Receptor Tyrosine Kinase Inhibitor III HT55 DLD1 HCA7 SW48 GP2D 00000 001 0 0000 0 0 1 10001 1111 11

HCT15 PDGF Receptor Tyrosine Kinase Inhibitor IV HDC57 SW948 SW620 SW403 SW837 VACO5 SKCO1 LS1034 LS174T HCT116 SW1222 SW1417 SW1116 SW1463 PDGF RTK Inhibitor 0 0 1 1 111111 001 11111111111112 NCIH508 NCIH747 COLO205 COLO678 PDK1/Akt/Flt Dual Pathway Inhibitor 00000 001 000 0 0000 000011111 1 1 PI 3-Kg Inhibitor 1 1 1101111121 11111 11111 11112 PI-103 0 0 0 001 0 1 00001 0 1 1 1 1 1 0 1111111 PKCb Inhibitor 1 110 1 1 1 1 1121111111 111111112 PKR Inhibitor 00000001 0000 00001 0 0 0 1 111111 PP1 Analog II 1NM-PP1 1 1 1 1 121111111 12111211111111 Purvalanol A 000000011 00001011111 111 1111 Rapamyc in 0 1 0 1 1 1 1111 1 0 1 1111 1 1 11111111 Rho Kinase Inhibitor IV 1 0 11001111 001 10111111111111 SB 202190 1111 0 111 1 1 2111 1 1 11111111111 SB 218078 00110001 1 0 0 1 0 1 1 1 1 1 1 1 111 1 111 SB220025 1 0 10001 1100 11001121 1 1 111111 SKF-86002 1 11111 1 1 1 1 111 111111 11111111 Sphingosine Kinase Inhibitor 0 11111111 1 1 1111111111 111 111 Src Kinase Inhibitor I 1 1 0 1 1 0 0 1 1 1 21111111 1 11111111 Staurosporine N-benzoyl- 000000010000100 1 1 110 2 1 1 1 112 Staurosporine, Streptomyces sp. 00000001 000 0 0001 1 0001111111 Staurosporine, Streptomyces sp. 00000001 0000000001 0 1 111 1 111 STO-609 111111111111111110 1 0 111 1 1 11 SU11652 00000001 000 0 00000000 10111 1 1 SU6656 0 0 1 111 1 111 0 1110111111111112 SU9516 0 0 0 00001 000010 0 1 1 0 111111111 Syk Inhibitor 1 1 1 111 1 1 111 1 111111 111111111 Syk Inhibitor II 1 1 1 002 111 11111 1 1 1 1 1 1 1111111 Syk Inhibitor III 0 1 000001 0 0 0 0 1 1 0 1 1 1101 1 11111 TGF-b RI Inhibitor III 1 0 1 112111 0001 1 0 1 1 1 11111 1111 Tpl2 Kinase Inhibitor 0 1 1111 1 1 1 0 111 1 1 1 111 11111111

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 survive inhibitor treatment in CINþ cell lines than in CIN cell lines (P < 0.0001). B, boxplot of median cell number following inhibitor treatment across all inhibitors for 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, heatmap showing the relative numbers of surviving cells following inhibitor treatment across the cell lines (inhibitors that have minimal impact on cell growth defined as a surviving cell fraction of >0.8 in >75% of the cell lines tested have been excluded).

PIK3CA mutation was the only somatic mutation mutation associated with increased sensitivity to inhibitors significantly associated with altered sensitivity to inhibi- targeting AKT, Aurora kinase, EGFR, PDGFR, and tors grouped according to target kinase families [PIK3CA PI3K, Wilcoxon–Mann–Whitney test, corrected P ¼ 0.003,

www.aacrjournals.org Cancer Res; 71(5) March 1, 2011 1863

þ P ¼ 0.038, P ¼ 0.016, P ¼ 0.038, and P ¼ 0.004, respectively; CIN not tetraploidy is associated with drug resistance þ Supplementary Fig. 3B]. We found no evidence for a specific CIN CRC cell lines missegregate chromosomes at a high association with either PIK3CA exon9or20mutationstatus rate, in contrast to CIN CRC cells that have a lower frequency and drug sensitivity (data not shown). Notably, PIK3CA of mitotic errors (1, 2). In addition, CIN cells fail to tolerate þ mutations were more likely to occur in CIN than in CIN the propagation of CIN when chromosome segregation errors cell lines (P ¼ 0.0066, Fisher's exact test). are artificially induced by drug treatment (11), suggesting that No single somatic mutation was associated with altered sustaining CIN in a cell population may require a specialized þ sensitivity to all inhibitors. Next, data for somatic mutation survival phenotype. The majority of CIN CRC cell lines used status and CIN status were pooled. When corrected for multi- in this study are triploid or tetraploid. We therefore consid- ple testing by the Benjamini–Hochberg method under the ered whether altered ploidy status, rather than ongoing CIN, assumption that the tests are either positively correlated might be associated with enhanced drug resistance. Clonal þ or independent (45), CIN status was the only parameter tetraploid and diploid HCT116 cells were treated with the significantly associated with multidrug resistance (corrected kinase inhibitors. There was no significant difference in the P ¼ 0.01; Supplementary Fig. 3B). Taken together, these data relative number of surviving cells following drug treatment suggest that the association of PIK3CA mutation with CIN between HCT116 tetraploid clone 4 (TC4) cell line and diploid status may confound the interpretation of the association clone 8 (DC8) cell line. However, tetraploid clone 9 (TC9) was of PIK3CA mutation status with sensitivity to specific inhibi- significantly more resistant than the DC8 cell line (Wilcoxon tors and may simply reflect the intrinsic drug sensitivity of signed-rank test, P < 0.001; Fig. 4A). Further investigation by CIN cells. clonal FISH (Fig. 4B) revealed that TC9 had a more hetero- geneous karyotype compared with TC4 cell lines, with a þ Isogenic CIN CRC cell lines display intrinsic multidrug significantly higher proportion of cells that deviated from resistance the mode of 4 copies of both chromosomes 2 and 15 (Fisher's To support a direct role for the contribution of CIN to the exact test, P ¼ 0.05; Fig. 4C). This implies that karyotypic multidrug-resistant phenotype, we assessed whether drug heterogeneity, rather than increased ploidy, might be respon- sensitivity was altered in isogenic CRC models of CIN. The sible for increased drug resistance compared with karyotypi- þ HCT116 MAD2 / cell line has one allele of the SAC gene, cally stable diploid cells. We cannot formally exclude the MAD2, deleted by homologous recombination, resulting in possibility that acquired mutations present in the drug-resis- numerical CIN relative to its diploid parental cell line (9). We tant tetraploid clone that may have permitted the sponta- þ treated the isogenic HCT116 MAD2 / cell and its parental neous tetraploid phenotype may primarily be responsible for diploid cell line with the kinase inhibitors and assessed the increased drug resistance. surviving cell line fraction after treatment. Consistent with the Taken together with the isogenic cell line data sets pre- þ nonisogenic cell line data presented previously, the MAD2 / sented here, where CIN is artificially induced through loss of cell line was found to be more resistant overall to the one allele of MAD2 or both copies of PTTG1, these results inhibitors tested than to the parental diploid cell line (one- support the contribution of CIN, rather than increased ploidy sided Wilcoxon signed-rank test, P ¼ 0.001; Fig. 3A and B). No status or MIN, in conferring altered drug sensitivity. single inhibitor seemed to specifically target the HCT116 þ MAD2 / cell line. Relationship between CIN status and benefit from To further test the association of CIN with intrinsic drug cytotoxic therapy in clinical datasets þ resistance to drugs other than kinase inhibitors, we challenged Published clinical data support the view that CIN CRC þ þ the HCT116 MAD2 / and another CIN isogenic cell line, is associated with a worse prognosis compared with CIN þ HCT116 PTTG1 / , together with their isogenic parental tumors (6), and data presented here suggest that CIN cell diploid HCT116 cell lines with the Biolog cytotoxic library lines display intrinsic multidrug resistance. Conceivably, þ containing 92 anticancer cytotoxic agents. Consistent with the the poorer prognosis of CIN disease may relate in part þ þ data from the kinase inhibitors, both the CIN MAD2 / and to intrinsic drug resistance of thymidylate synthase inhi- PTTG1 / cells were significantly more resistant (one-sided bitors, cytotoxics commonly used in the adjuvant treatment Wilcoxon signed-rank test, P < 0.001, except P ¼ 0.035 at the of CRC. Consistent with this hypothesis, both isogenic þ lowest concentration of drug for PTTG1 / ) to a diverse range CIN cells are significantly more resistant to the majority of anticancer agents than to the parental diploid cell lines of thymidylate synthase inhibitors tested, including 5-FU, þ (Fig. 3C and D). and non-isogenic CIN cells are more resistant to 5-FU than þ Importantly, both the HCT116 MAD2 / and parental to CIN cell lines, at physiologic concentrations (Supple- þ diploid cell lines continue to display MIN (Supplementary mentary Fig. 6A, B). þ Fig. 4), indicating that MIN status is unlikely to sufficiently Next, we asked whether CIN status might be associated þ explain the altered drug sensitivity in the CIN isogenic with poorer outcome following adjuvant therapy with 5-FU– þ models. These data suggest that CIN status, initiated based regimens. A meta-analysis of studies examining the by ongoing chromosome missegregation events driven by relationship between CIN and prognosis in locoregional CRC, þ loss of 2 distinct proteins controlling mitotic fidelity, is revealed that CIN disease (defined as aneuploidy/poly- the dominant phenotype associated with altered drug ploidy determined using flow cytometry) confers a worse sensitivity. overall survival (30 studies) (Supplementary Fig. 5A) and

1864 Cancer Res; 71(5) March 1, 2011 Cancer Research

Downloaded from cancerres.aacrjournals.org on September 30, 2021. © 2011 American Association for Cancer Research. 1865 mol/L) cell line m d. 25 þ/ – values suggest P MAD2 1 0.3 0.8 0.8 0.6 0.5 0.69 1.13 0.71 0.32 0.94 0.59 0.51 0.44 0.56 0.24 0.64 0.32 0.28 0.31 0.48 0.25 0.21 0.24 1.25 1.16 0.66 1.26 0.76 0.51 1.23 0.51 0.97 0.76 0.73 0.63 1.21 0.52 0.27 0.26 0.43 0.46 1.23 0.69 0.64 0.43 0.23 0.56 0.39 0.44 0.23 0.41 0.29 0.97 0.93 0.97 0.71 1.02 1.13 1.06 0.94 0.48 PTTG1 –/– 0.64 0.36 0.73 0.43 0.52 0.21 0.99 1.05 1.14 1.13 0.26 0.64 0.53 0.41 0.71 0.45 0.29 0.21 0.51 0.21 0.92 0.94 0.87 0.31 0.26 0.28 1.22 0.64 0.61 0.32 0.58 1.21 0.83 >0.8 0.6 0.1 0.1 0.14 0.9 0.1 0.1 0.170.6 0.7 0.3 Diploid 0.3 0.2 0.1 0.1 0.1 0.1 0.2 0.1 0.3 0.34 0.2 0.2 0.16 0.18 0.18 0.05 0.12 0.15 0.17 0.14 0.150.09 0.75 0.41 0.34 0.390.22 0.39 0.250.080.76 0.120.49 0.270.14 0.310.24 0.150.35 0.360.32 0.25 0.33 0.11 0.12 0.11 0.11 0.170.05 0.180.03 0.060.42 0.030.17 0.050.17 0.080.56 0.31 0.260.09 0.290.09 0.120.07 0.110.06 0.190.11 0.06 0.19 0.11 0.24 0.14 0.14 0.13 0.13 0.13 0.14 0.020.03 0.110.04 0.040.54 0.14 0.050.86 0.170.54 0.550.41 0.07 0.79 0.63 0.32 0.24 0.37 0.35 0.19 0.620.39 0.23 0.7 0.11 0.210.03 0.130.04 0.170.16 0.170.62 0.13 0.05 0.26 0.22 0.28 0.09 0.49 0.38 0.520.38 0.550.32 0.27 0.770.53 0.650.18 0.13 0.13 0.14 0.07 0.08 0.15 0.76 0.43 0.490.46 0.510.11 0.550.120.13 0.170.14 0.45 0.28 0.16 0.230.21 0.34 0.13 0.26 0.27 0.29 Parental 0.6 to <0.8 Cancer Res; 71(5) March 1, 2011 0.4 to <0.6 Daunorubicin Hydrochloride 1 Daunorubicin Hydrochloride 2 Daunorubicin Hydrochloride 3 Daunorubicin Hydrochloride 4 Doxorubicin Hydrochloride 1 Doxorubicin Hydrochloride 2 Doxorubicin Hydrochloride 3 Doxorubicin Hydrochloride 4 Ellagic Acid 4 Emetine 3 Emetine 4 Etoposide 2 Etoposide 3 Etoposide 4 Floxuridine 1 Floxuridine 2 Floxuridine 3 Floxuridine 4 2 (5-FU) Fluorouracil 3 (5-FU) Fluorouracil 4 (5-FU) Fluorouracil 4 Gossypol Juglone 1 Juglone 2 Juglone 3 Juglone 4 Mercaptopurine 4 Methotrexate 1 Methotrexate 2 Methotrexate 3 Methotrexate 4 1 C Mitomycin 2 C Mitomycin 3 C Mitomycin 4 C Mitomycin Mitoxantrone Hydrochloride 1 Mitoxantrone Hydrochloride 2 Mitoxantrone Hydrochloride 3 Mitoxantrone Hydrochloride 4 Mycophenolic acid 2 Mycophenolic acid 3 Mycophenolic acid 4 Neriifolin 1 Neriifolin 2 Neriifolin 3 Neriifolin 4 Nocodazole 1 Nocodazole 2 Nocodazole 3 Nocodazole 4 Phenethyl caffeate (CAPE) 4 Picropodophyllotoxin 2 Picropodophyllotoxin 3 Picropodophyllotoxin 4 Podofilox 1 Podofilox 2 Podofilox 3 Podofilox 4 Puromycin Hydrochloride 1 Puromycin Hydrochloride 2 Puromycin Hydrochloride 3 Puromycin Hydrochloride 4 Quinacrine Hydrochloride 2 Quinacrine Hydrochloride 3 Quinacrine Hydrochloride 4 Rapamycin 3 Rotenone 3 Rotenone 4 Sanguinarine Sulfate 1 Sanguinarine Sulfate 4 Tamoxifen Citrate 4 2 Thioguanine 3 Thioguanine 4 Thioguanine Urethane 4 1 Sulfate Vinblastine 2 Sulfate Vinblastine 3 Sulfate Vinblastine 4 Sulfate Vinblastine 4'- demethyl4'- epipodophyllotoxin 2 demethyl4'- epipodophyllotoxin 3 demethyl4'- epipodophyllotoxin 4 5-fluoro-5'-DeoxyurIdine 3 5-fluoro-5'-DeoxyurIdine 4 6-amino nicotinamide 4 2 Acivicin 3 Acivicin 4 Acivicin 1 Aclarubicin 2 Aclarubicin 3 Aclarubicin 4 Aclarubicin Acriflavinium Hydrochloride 2 Acriflavinium Hydrochloride 3 Acriflavinium Hydrochloride 4 Aklavine Hydrochloride 1 Aklavine Hydrochloride 2 Aklavine Hydrochloride 3 Aklavine Hydrochloride 4 Aminopterin 1 Aminopterin 2 Aminopterin 3 Aminopterin 4 Amygdalin 3 Amygdalin 4 Ancitabine Hydrochloride 1 Ancitabine Hydrochloride 2 Ancitabine Hydrochloride 3 Ancitabine Hydrochloride 4 4 Azacytidine Azathioprine 4 beta-Peltatin 1 beta-Peltatin 2 beta-Peltatin 3 beta-Peltatin 4 1 Camptothecin 2 Camptothecin 3 Camptothecin 4 Camptothecin 2 Carmofur 3 Carmofur 4 Carmofur Cepharanthine 4 Chloramphenicol 4 Colchicine 1 Colchicine 2 Colchicine 3 Colchicine 4 1 Cycloheximide 2 Cycloheximide 3 Cycloheximide 4 Cycloheximide Cytosine-Beta-Darabinofuranoside 1 Cytosine-Beta-Darabinofuranoside 2 Cytosine-Beta-Darabinofuranoside 3 Cytosine-Beta-Darabinofuranoside 4 1 Dactinomycin 2 Dactinomycin 3 Dactinomycin 4 Dactinomycin 0.2 to <0.4 CIN Confers Intrinsic Multidrug Resistance 1 0.8 0.3 0.4 0.7 0.6 0.7 0.6 0.6 0.7 0.7 0.6 0.4 0.6 0.86 0.71 0.43 0.67 0.79 0.69 0.59 0.65 0.69 0.38 0.67 0.39 0.35 0.65 0.31 0.88 0.25 0.21 0.92 0.91 0.81 0.86 0.28 0.44 0.94 0.97 1.02 0.72 0.44 0.42 0.45 0.61 0.93 0.78 0.21 0.87 0.79 0.69 0.68 0.79 0.82 0.81 0.61 0.63 0.76 0.75 0.48 0.22 0.99 0.85 0.72 1.02 0.93 0.58 0.62 0.64 0.65 0.85 0.83 0.54 0.87 0.73 0.41 0.54 0.42 1.01 0.97 0.94 0.94 0.94 0.88 0.76 0.98 0.81 0.76 0.98 0.85 0.44 0.96 0.63 0.64 0.67 0.75 0.54 0.34 0.26 0.66 0.62 0.53 0.46 MAD2 +/– 0.65 0.62 0.6 0.5 0.2 0.3 0.1 0.14 0.2 0.3 0.3 0.2 0.1 0.05 0.3 0.3 0.1 0.15 0.24 0.17 0.12 0.060.28 0.160.060.17 0.140.14 0.63 0.07 0.08 0.58 0.47 0.49 0.54 0.38 0.230.13 0.39 0.32 0.290.32 0.4 0.34 0.73 0.51 0.31 0.33 0.33 0.22 0.060.05 0.150.61 0.040.27 0.070.12 0.130.64 0.45 0.32 0.09 0.07 0.07 0.15 0.16 0.18 0.91 0.54 0.45 0.21 0.18 0.18 0.59 0.080.09 0.050.21 0.080.14 0.08 0.72 0.49 0.33 0.77 0.040.77 0.070.580.65 0.580.17 0.18 0.19 0.23 Diploid 0.32 0.42 0.24 0.22 0.4 0.28 0.28 0.36 0.36 0.440.34 0.420.72 0.64 0.62 0.79 0.45 0.43 0.33 0.76 0.74 0.72 0.31 0.79 0.63 0.33 0.51 0.17 0.22 0.16 0.46 0.26 0.15 0.13 0.31 0.29 0.34 0.33 0.18 <0.2 Parental and parental diploid cell lines (inhibitors that show a surviving cell þ/ Legend Fraction of surviving cells compared with vehicle control cells to their specific isogenic parental cells. Significant MAD2 / D Dactinomycin 4 Dactinomycin Daunorubicin Hydrochloride 1 Daunorubicin Hydrochloride 2 Daunorubicin Hydrochloride 3 Daunorubicin Hydrochloride 4 Doxorubicin Hydrochloride 1 Doxorubicin Hydrochloride 2 Doxorubicin Hydrochloride 3 Doxorubicin Hydrochloride 4 Ellagic Acid 4 Emetine 3 Emetine 4 Etoposide 2 Etoposide 3 Etoposide 4 Floxuridine 1 Floxuridine 2 Floxuridine 3 Floxuridine 4 Fluorouracil (5-FU) 3 Fluorouracil (5-FU)4 4 Gossypol Juglone 1 Juglone 2 Juglone 3 Juglone 4 Mercaptopurine 3 Mercaptopurine 4 1 Methotrexate 2 Methotrexate 3 Methotrexate 4 Methotrexate 2 C Mitomycin 3 C Mitomycin 4 C Mitomycin Mitoxantrone Hydrochloride 1 Mitoxantrone Hydrochloride 2 Mitoxantrone Hydrochloride 3 Mitoxantrone Hydrochloride 4 Mycophenolic acid 2 Mycophenolic acid 3 Mycophenolic acid 4 1 Neriifolin 2 Neriifolin 3 Neriifolin 4 Neriifolin Nocodazole 1 Nocodazole 2 Nocodazole 3 Nocodazole 4 p-Fluorophenylalanine 3 Phenethyl caffeate (CAPE) 4 Picropodophyllotoxin 2 Picropodophyllotoxin 3 Picropodophyllotoxin 4 1 Podofilox 2 Podofilox 3 Podofilox 4 Podofilox Puromycin Hydrochloride 1 Puromycin Hydrochloride 2 Puromycin Hydrochloride 3 Puromycin Hydrochloride 4 Quinacrine Hydrochloride 2 Quinacrine Hydrochloride 3 Quinacrine Hydrochloride 4 Rifaximin 4 Rotenone 3 Rotenone 4 Sanguinarine Sulfate 3 Sanguinarine Sulfate 4 2 Thioguanine 3 Thioguanine 4 Thioguanine 1 Sulfate Vinblastine 2 Sulfate Vinblastine 3 Sulfate Vinblastine 4 Sulfate Vinblastine 4'- demethyl4'- epipodophyllotoxin 1 demethyl4'- epipodophyllotoxin 2 demethyl4'- epipodophyllotoxin 3 demethyl4'- epipodophyllotoxin 4 5-fluoro-5'-DeoxyurIdine 3 5-fluoro-5'-DeoxyurIdine 4 6-amino nicotinamide 4 2 Acivicin 3 Acivicin 4 Acivicin 1 Aclarubicin 2 Aclarubicin 3 Aclarubicin 4 Aclarubicin Acriflavinium Hydrochloride 2 Acriflavinium Hydrochloride 3 Acriflavinium Hydrochloride 4 Aklavine Hydrochloride 1 Aklavine Hydrochloride 2 Aklavine Hydrochloride 3 Aklavine Hydrochloride 4 Aminopterin 1 Aminopterin 2 Aminopterin 3 Aminopterin 4 Amygdalin 1 Amygdalin 3 Amygdalin 4 Ancitabine Hydrochloride 1 Ancitabine Hydrochloride 2 Ancitabine Hydrochloride 3 Ancitabine Hydrochloride 4 2 Azacytidine Azaserine 1 Azathioprine 4 1 beta-Peltatin 2 beta-Peltatin 3 beta-Peltatin 4 beta-Peltatin 1 Camptothecin 2 Camptothecin 3 Camptothecin 4 Camptothecin Carboplatin 4 3 Carmofur 4 Carmofur Chloramphenicol 4 Colchicine 1 Colchicine 2 Colchicine 3 Colchicine 4 Cycloheximide 1 Cycloheximide 2 Cycloheximide 3 Cycloheximide 4 Cytosine-Beta-Darabinofuranoside 1 Cytosine-Beta-Darabinofuranoside 2 Cytosine-Beta-Darabinofuranoside 3 Cytosine-Beta-Darabinofuranoside 4 1 Dactinomycin 2 Dactinomycin 3 Dactinomycin PTTG1 on September 30, 2021. © 2011 American Association for and M14 drug microplates were used at 4 increasing concentrations per drug (0.1 >0.8 – Cancer Research. þ/

MAD2+/– MAD2

0.6 to <0.8 Diploid Parental +/- 0.4 to <0.6 P - values P - values P < 0.001 Drug concentration Drug Concentration cells than in their parental diploid cells. D, heatmap of surviving fraction of cells compared with negative control in and their parental diploid cell lines for 72 hours. The boxplot shows difference in relative surviving cell number HCT116 MAD2 vs. diploid parental 0.2 to <0.4 / 0.001) following treatment with each equivalent inhibitor. B, heatmap showing the relative numbers of surviving cells

/ 0.035 <0.001 <0.001 <0.001

<0.001 <0.001 <0.001 <0.001

020002040.6 0.4 0.2 0.0 −0.2 1.0 0.8 020002040.6 0.4 0.2 0.0 −0.2 1.0 0.8 cancerres.aacrjournals.org

<0.2 0200020.4 0.2 0.0 −0.2

diploid parental diploid

diploid parental diploid PTTG1

MAD2 MAD2 HCT116 between

and PTTG1 PTTG1 HCT116 between and

–/– +/–

parental after inhibitor treatment inhibitor after parental or , and their parental diploid cell lines treated with Biolog drug microplates at 4 increasing concentrations per drug (1-4, 1 being

Difference in surviving cell fraction cell surviving in Difference

MAD2 HCT116 between and diploid and

+/− Akt Inhibitor IV Alsterpaullone 2-Cyanoethyl Alsterpaullone Aurora Kinase/Cdk Inhibitor TG003 Cdc2-Like Inhibitor Kinase Inhibitor Cdk/Crk InhibitorCdk2 IV NU6140 52 Compound Inhibitor EGFR InhibitorERK II Negative c ontrol 6976 Go GSK- 3 Inhibit orGSK- X 3b Inhibit 1077 DihydrochlorideHA or Fasudil XI A Streptomyces sp. Herbimycin IKK-2 Inhibitor IV Indirubin-3'-monoxime Isogranulatimide VI Inhibitor JAK3 Inhibitor IX JNK K-252a Nocardiopsis sp. Inhibitor MK2a 169316 PD ReceptorPDGF IV Tyrosine Inhibitor Kinase PDK1/Akt /FltPI-103 Dual Pat hwaySB220025 Inhibit or Streptomyces sp. Staurosporine Streptomyces sp. Staurosporine and

/ þ/ Difference in mean relative cell number cell relative mean in Difference þ/ MAD2 PTTG1 Legend Fraction of surviving cells compared with vehicle control , B A C MAD2 þ/ Downloaded from 0.8 in both cell lines have been excluded). C, Biolog M11 > A, boxplot showing that following treatment with kinase inhibitors, there seemed to be a higher surviving fraction of cells in the HCT116 MAD2 HCT116 www.aacrjournals.org Figure 3. across all drugs at each of the 4 concentrations, comparing the lowest). Drugs resulting in a surviving cellular fraction of more than 0.8 compared with negative control in both isogenic cell lines were exclude to treat HCT116 fraction of than in its parental diploid cell line ( following the inhibitor treatments compared with vehicle control across the HCT116 higher resistance in Lee et al.

A C Histogram of copies of chromosome 2 per cell in TC 4 P - values 150

0.078 <0.001 100

Frequency 50

0 12345678 Copies of chromosome 2 per cell

Histogram of copies of chromosome 2 per cell in TC 9 150

−0.5 0.0 0.5 100 Difference in mean relative cell number after inhibitor treatment

Frequency 50 TC4 vs. DC8 TC9 vs. DC8

0 12345678 Copies of chromosome 2 per cell

B Histogram of copies of chromosome 15 per cell in TC 4 150

100

Frequency 50

0 123456789 Copies of chromosome 15 per cell

Histogram of copies of chromosome 15 per cell in TC 9 150

TCTC4 4 100

Frequency 50

0 123456789 Copies of chromosome 15 per cell

% Cells with % Cells with 4 copies of number of copies ≠4 both Chr 2 and 15 of either Chr 2 or Chr 15

TC4 37 63 TC9 TC9 28 72

Fisher’s exact test, P = 0.05

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 was significantly more resistant than DC8 (P < 0.001). The difference in drug sensitivity between TC4 and DC8 was not significant (P ¼ 0.078). B, representative FISH images for TC4 and TC9. Probes against chromosome 15 in green. C, histogram showing distribution of number of markers per cell corresponding to chromosome 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 of both chromosomes 2 and 15 (P ¼ 0.05) than that in TC4.

1866 Cancer Res; 71(5) March 1, 2011 Cancer Research

Figure 5. A, impact of CINþ on disease-free survival, overall survival, and those receiving adjuvant chemotherapy in locoregional CRC. Overall CINþ seems to confer a worse prognosis compared with diploid. B, benefit derived from adjuvant 5-FU in patients with (near) diploid (top) and CINþ (middle) CRC. Patients with diploid CRC seem to benefit more from chemotherapy than patients with CINþ tumors. Combined analysis of CINþ and diploid patients shows similar magnitude of benefit as would be expected from literature (bottom; ref. 49).

progression-free survival (15 studies) (Supplementary 1.16, P ¼ 0.250; I2 ¼ 0%, P ¼ 0.932). The combined analysis Fig. 5B) compared with patients with diploid CRC. Similarly, of all patients suggests a benefit following 5-FU treatment if only patients who received chemotherapy are included comparable with that reported in the literature for genetically þ (2 studies; ref. 46, 47), CIN tumors are associated with a unselected patients (49). While these studies are limited, þ worse overall survival (Fig. 5A). they are consistent with the view that patients with CIN Two studies explore the predictive value of CIN (46, 48) in CRC derive less benefit from 5-FU–based adjuvant cytotoxic patients with locoregional CRC who received either adjuvant chemotherapy than patients with diploid CRC. Prospective þ chemotherapy or no chemotherapy following surgery (Fig. 5B). evaluation of the association of CIN disease with the efficacy Patients with diploid CRC seem to benefit from 5-FU–based of combination regimens (e.g., 5-FU/oxaliplatin) in stage 3 and therapy (N ¼ 262, HR ¼ 0.61; 95% CI ¼ 0.40–0.94, P ¼ 0.024; 5-FU/oxaliplatin and irinotecan in stage 4 disease might be I2 ¼ 0%, P ¼ 0.467) compared with untreated diploid controls, considered to assess whether clinical outcome following whereas there was no significant difference between treated these more recent regimens has a similar association with þ and untreated CIN CRCs (N ¼ 303, HR ¼ 0.81; 95% CI ¼ 0.57– CIN status.

www.aacrjournals.org Cancer Res; 71(5) March 1, 2011 1867

þ Discussion somatic mutation status and CIN status, CIN status was the only parameter significantly associated with resistance þ In this analysis, we have provided evidence that CIN to these inhibitors. CRC cell lines display intrinsic multidrug resistance com- Therefore, evidence exists for the coordination of apop- paredwithCIN cell lines. No specific kinase inhibitor totic/cell death pathways following chromosome mis- þ was identified that displayed greater activity in CIN cell segregation events. Conceivably, common molecular lines. We cannot exclude the potential for off-target effects pathways regulating cell death following a chromosome þ at the concentrations of kinase inhibitors used in this missegregation event may become disrupted in CIN cells, analysis; however, the same conditions were applied to simultaneously triggering tolerance of chromosome reas- the CIN cells and therefore off-target phenomena are sortments and, as an indirect consequence, resistance to unlikely to change the conclusions of this work. Further- drug exposure. þ more, in the isogenic systems, we observed significant drug The observations that CIN cancer cell lines seem to be þ resistance in the CIN cell lines relative to their isogenic less sensitive to a range of anticancer agents than to diploid parental CIN pairs at all concentrations of cytotoxics cells and that poorer patient outcome follows cytotoxic þ tested (ranging from 0.1 to 25 mmol/L). Intriguingly, the treatment of CIN tumors compared with diploid counter- þ isogenic CIN and tetraploid cell line systems suggest that parts strongly suggest the need to consider tumor strati- the primary association is between multidrug resistance and fication according to CIN status in the design of clinical þ CIN rather than tetraploidy. It has been previously shown trials testing novel anticancer agents in CRC. This is that aneuploid cell lines can acquire multidrug resistance particularly relevant to the advanced CRC setting where þ at an accelerated rate (50) that may be driven by cancer the incidence of CIN is greater than in early-stage disease. cell heterogeneity resulting from multiple chromosomal Stratifying drug response according to CIN status may limit reassortments in aneuploid cells. The short time course the risk of early drug attrition and heighten the chance of of our experiments in comparison with this study suggests identifying responder populations in patients with diploid that multidrug resistance is likely to be an intrinsic pro- tumors. Importantly, these data indicate that specifically þ þ perty of CIN cells rather than a process that is acquired targeting cancer cells with CIN status, using currently in our cell systems over multiple generations. What might available kinase inhibitors, seems challenging. An improved contribute to this intrinsic multidrug resistance pheno- understanding of the mechanisms associated with the þ þ type in CIN cells? We speculate that either basal popula- generation and survival of CIN CRC will be important þ tion heterogeneity in CIN cell lines is sufficiently diverse to drive the development of new therapeutic approaches in to confer a cell viability advantage following drug exposure order to improve patient outcome in this high-risk disease þ or there is a specific CIN survival phenotype that initiates a subtype. tolerance of ongoing chromosomal rearrangements that is also associated with multidrug resistance. þ Disclosure of Potential Conflicts of Interest There is increasing evidence in support of a CIN survival phenotype and putative molecular coordinators of this No potential conflicts of interest were disclosed. property. Cell death after mitotic arrest may result from transcriptional inhibition due to condensed chromatin, Acknowledgments precipitating the degradation of short-lived mRNA encod- þ þ ing prosurvival proteins (51). CIN cells may overexpress We thank Robert Benezra for the donation of the isogenic HCT116 MAD2 / / these prosurvival genes compared with diploid cells (22) cell lines and Bert Vogelstein for the donation of the isogenic HCT116 PTTG1 þ cell lines. that may drive the resistance of CIN cells to a mitotic arrest triggered by taxanes. Jeganathan and colleagues have shown that tolerance of chromosome missegregation Grant Support events can be conferred by a hypomorphic BUB1 allele C. Swanton is a senior Medical Research Council clinical research fellow and in mouse embryonic fibroblasts(24).Recently,Thompson is funded by both Cancer Research UK (CRUK) and the Medical Research and Compton have shown that chromosome missegregra- Council. A.J.X. Lee is funded by CRUK. I.P.M. Tomlinson is supported by the Oxford Biomedical Research Centre and CRUK. tion in diploid human cells triggers an increase in nuclear The costs of publication of this article were defrayed in part by the p53andthatp53nullcellsareabletotoleratechromosome payment of page charges. This article must therefore be hereby marked missegregation events, enabling the propagation of aneu- advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this þ fact. ploid genomes (52). A higher proportion of the CIN cell lines used in our study have mutant p53 in comparison with Received October 6, 2010; revised December 23, 2010; accepted January 8, the CIN cell lines. However, when we pooled data for 2011; published OnlineFirst March 1, 2011.

References 1. Lengauer C, Kinzler KW, Vogelstein B. Genetic instabilities in human 2. Lengauer C, Kinzler KW, Vogelstein B. Genetic instability in colorectal cancers. Nature 1998;396:643–9. cancers. Nature 1997;386:623–7.

1868 Cancer Res; 71(5) March 1, 2011 Cancer Research

3. Roschke AV, Tonon G, Gehlhaus KS, McTyre N, Bussey KJ, Lababidi 24. Jeganathan K, Malureanu L, Baker DJ, Abraham SC, van Deursen JM. S, et al. Karyotypic complexity of the NCI-60 drug-screening panel. Bub1 mediates cell death in response to chromosome missegregation Cancer Res 2003;63:8634–47. and acts to suppress spontaneous tumorigenesis. J Cell Biol 4. Lothe RA, Peltomaki€ P, Meling GI, Aaltonen LA, Nystrom-Lahti€ M, 2007;179:255–67. Pylkkanen€ L, et al. Genomic instability in colorectal cancer: relation- 25. Roschke AV, Kirsch IR. Targeting cancer cells by exploiting karyotypic ship to clinicopathological variables and family history. Cancer Res complexity and chromosomal instability. Cell Cycle 2005;4:679–82. 1993;53:5849–52. 26. Torres EM, Sokolsky T, Tucker CM, Chan LY, Boselli M, Dunham MJ, 5. Thibodeau SN, French AJ, Cunningham JM, Tester D, Burgart LJ, et al. Effects of aneuploidy on cellular physiology and cell division in Roche PC, et al. Microsatellite instability in colorectal cancer: different haploid yeast. Science 2007;317:916–24. mutator phenotypes and the principal involvement of hMLH1. Cancer 27. Storchova Z, Breneman A, Cande J, Dunn J, Burbank K, O'Toole E, Res 1998;58:1713–8. et al. Genome-wide genetic analysis of polyploidy in yeast. Nature 6. Walther A, Houlston R, Tomlinson I. Association between chromo- 2006;443:541–7. somal instability and prognosis in colorectal cancer: a meta-analysis. 28. Woodford-Richens KL, Rowan AJ, Gorman P, Halford S, Bicknell DC, Gut 2008;57:941–50. Wasan HS, et al. SMAD4 mutations in colorectal cancer probably 7. Hiddemann W, Schumann J, Andreef M, Barlogie B, Herman CJ, Leif occur before chromosomal instability, but after divergence of the RC, et al. Convention on nomenclature for DNA cytometry. Cancer microsatellite instability pathway. Proc Natl Acad Sci U S A Genet Cytogenet 1984;13:181–3. 2001;98:9719–23. 8. Cahill DP, Lengauer C, Yu J, Riggins GJ, Willson JK, Markowitz SD, 29. Gaasenbeek M, Howarth K, Rowan AJ, Gorman PA, Jones A, Chaplin et al. Mutations of mitotic checkpoint genes in human cancers. Nature T, et al. Combined Array-comparative genomic hybridization and 1998;392:300–3. single-nucleotide polymorphism-loss of heterozygosity analysis 9. Michel LS, Liberal V, Chatterjee A, Kirchwegger R, Pasche B, Gerald reveals complex changes and multiple forms of chromosomal instabil- W, et al. MAD2 haplo-insufficiency causes premature anaphase ity in colorectal cancers. Cancer Res 2006;66:3471–9. and chromosome instability in mammalian cells. Nature 2001; 30. Abdel-Rahman WM, Katsura K, Rens W, Gorman PA, Sheer D, 409:355–9. Bicknell D, et al. Spectral karyotyping suggests additional subsets 10. Jallepalli PV, Waizenegger IC, Bunz F, Langer S, Speicher MR, Peters of colorectal cancers characterized by pattern of chromosome rear- JM, et al. Securin is required for chromosomal stability in human cells. rangement. Proc Natl Acad Sci U S A 2001;98:2538–43. Cell 2001;105:445–57. 31. Cancer Genome Project. [Internet]Cambridge, UK: Wellcome Trust 11. Thompson SL, Compton DA. Examining the link between chromo- Sanger Institute; 2010[updated 2010 Dec 20; cited 2010 Dec 23]. somal instability and aneuploidy in human cells. J Cell Biol Available from:http://www.sanger.ac.uk/genetics/CGP. 2008;180:665–72. 32. Liu Y, Bodmer WF. Analysis of P53 mutations and their expression in 56 12. Fukasawa K, Vande Woude G. Synergy between the Mos/mitogen- colorectal cancer cell lines. Proc Natl Acad Sci U S A 2006;103:976–81. activated protein kinase pathway and loss of p53 function in 33. Rowan AJ, Lamlum H, Ilyas M, Wheeler J, Straub J, Papadopoulou A, transformation and chromosome instability. Mol Cell Biol 1997; et al. APC mutations in sporadic colorectal tumors: a mutational 17:506–18. "hotspot" and interdependence of the "two hits". Proc Natl Acad 13. Pihan GA, Purohit A, Wallace J, Malhotra R, Liotta L, Doxsey SJ. Sci U S A 2000;97:3352–7. Centrosome defects can account for cellular and genetic changes 34. Ilyas M, Tomlinson IPM, Rowan A, Pignatelli M, Bodmer WF. Beta- that characterize prostate cancer progression. Cancer Res 2001; catenin mutations in cell lines established from human colorectal 61:2212–9. cancers. Proc Natl Acad Sci U S A 1997;94:10330–4. 14. Gisselsson D, Pettersson L, Hoglund M, Heidenblad M, Gorunova L, 35. Samuels Y, Diaz LA Jr, Schmidt-Kittler O, Cummins JM, Delong L, Wiegant J, et al. Chromosomal breakage-fusion-bridge events cause Cheong I, et al. Mutant PIK3CA promotes cell growth and invasion of genetic intratumor heterogeneity. Proc Natl Acad Sci U S A human cancer cells. Cancer Cell 2005;7:561–73. 2000;97:5357–62. 36. Inhibitor Libraries and Pathway Panels. [Internet]Darmstadt, Germany: 15. Carter SL, Eklund AC, Kohane IS, Harris LN, Szallasi Z. A signature of Merck KGaA; 2010[cited 2010 Dec 23]. Available from:http://www. chromosomal instability inferred from gene expression profiles pre- emdchemicals.com/life-science-research/inhibitor-libraries-and- dicts clinical outcome in multiple human cancers. Nat Genet pathway-panels/c_bKSb.s1O9nQAAAEitTV5hDHD#docs. 2006;38:1043–8. 37. Kahm M, Hasenbrink G, Lichtenberg-Frate H, Ludwig J, Kschischo M. 16. Sheffer M, Bacolod MD, Zuk O, Giardina SF, Pincas H, Barany F, et al. grofit: fitting biological growth curves with R. J Stat Software Association of survival and disease progression with chromosomal 2010;33:1–21. instability: A genomic exploration of colorectal cancer. Proc Natl Acad 38. Parmar MK, Torri V, Stewart L. Extracting summary statistics to Sci U S A 2009;106:7131–6. perform meta-analyses of the published literature for survival end- 17. Cahill DP, Kinzler KW, Vogelstein B, Lengauer C. Genetic inst- points. Stat Med 1998;17:2815–34. ability and Darwinian selection in tumours. Trends Cell Biol 39. Anderson MJ. Permutation tests for univariate or multivariate analysis 1999;9:M57–60. of variance and regression. Can J Fish Aquat Sci 2001;58:626–39. 18. Nicholson JM, Duesberg P. On the karyotypic origin and evolution of 40. Greenman CD, Bignell G, Butler A, Edkins S, Hinton J, Beare D, et al. cancer cells. Cancer Genet Cytogenet 2009;194:96–110. PICNIC: an algorithm to predict absolute allelic copy number variation 19. Chandhok NS, Pellman D. A little CIN may cost a lot: revisiting with microarray cancer data. Biostatistics 2010;11:164–75. aneuploidy and cancer. Curr Opin Genet Dev 2009;19:74–81. 41. Chin S, Teschendorff A, Marioni J, Wang Y, Barbosa-Morais NL, 20. Sotillo R, Schvartzman J-M, Socci ND, Benezra R. Mad2-induced Thorne NP, et al. High-resolution aCGH and expression profiling chromosome instability leads to lung tumour relapse after oncogene identifies a novel genomic subtype of ER negative breast cancer. withdrawal. Nature 2010;464:436–40. Genome Biol 2007;8:R215. 21. Duesberg P, Stindl R, Hehlmann R. Explaining the high mutation rates 42. Williams BR, Prabhu VR, Hunter KE, Glazier CM, Whittaker CA, of cancer cells to drug and multidrug resistance by chromosome Housman DE, et al. Aneuploidy Affects proliferation and spontaneous reassortments that are catalyzed by aneuploidy. Proc Natl Acad Sci U immortalization in mammalian cells. Science 2008;322:703–9. S A 2000;97:14295–300. 43. Segal DJ, McCoy EE. Studies on Down's syndrome in tissue culture. I. 22. Swanton C, Nicke B, Schuett M, Eklund AC, Ng C, Li Q, et al. Growth rates protein contents of fibroblast cultures. J Cell Physiol Chromosomal instability determines taxane response. Proc Natl Acad 1974;83:85–90. Sci U S A 2009;106:8671–6. 44. Baker DJ, Jeganathan KB, Cameron JD, Thompson M, Juneja S, 23. McClelland SE, Burrell RA, Swanton C. Chromosomal instability: a Kopecka A, et al. BubR1 insufficiency causes early onset of aging- composite phenotype that influences sensitivity to chemotherapy. associated phenotypes and infertility in mice. Nat Genet 2004; Cell Cycle 2009;8:3262–6. 36:744–9.

www.aacrjournals.org Cancer Res; 71(5) March 1, 2011 1869

45. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a 49. Gill S, Loprinzi CL, Sargent DJ, Thome SD, Alberts SR, Haller DG, et al. practical and powerful approach to multiple testing. J R Stat Soc Pooled analysis of fluorouracil-based adjuvant therapy for stage II and Ser B 1995;57:289–300. III colon cancer: who benefits and by how much?J Clin Oncol 46. Barratt PL, Seymour MT, Stenning SP, Georgiades I, Walker C, 2004;22:1797–806. Birbeck K, et al. DNA markers predicting benefit from adjuvant 50. Duesberg P, Stindl R, Hehlmann R. Origin of multidrug resistance in fluorouracil in patients with colon cancer: a molecular study. Lancet cells with and without multidrug resistance genes: Chromosome 2002;360:1381–91. reassortments catalyzed by aneuploidy. Proc Natl Acad Sci U S A 47. Sinicrope FA, Rego RL, Halling KC, Foster N, Sargent DJ, La Plant B, 2001;98:11283–8. et al. Prognostic impact of microsatellite instability and DNA ploidy in 51. Blagosklonny MV. Mitotic arrest and cell fate: why and how mitotic human colon carcinoma patients. Gastroenterology 2006;131:729–37. inhibition of transcription drives mutually exclusive events. Cell Cycle 48. Ahnen DJ, Feigl P, Quan G, Fenoglio-Preiser C, Lovato LC, Bunn PA 2007;6:70–4. Jr, et al. Ki-ras mutation and p53 overexpression predict the clinical 52. Thompson SL, Compton DA. Proliferation of aneuploid human behavior of colorectal cancer: a Southwest Oncology Group study. cells is limited by a p53-dependent mechanism. J Cell Biol 2010; Cancer Res 1998;58:1149–58. 188:369–81.

1870 Cancer Res; 71(5) March 1, 2011 Cancer Research

Alvin J.X. Lee, David Endesfelder, Andrew J. Rowan, et al.

Cancer Res 2011;71:1858-1870.

Updated version Access the most recent version of this article at: http://cancerres.aacrjournals.org/content/71/5/1858

Supplementary Access the most recent supplemental material at: Material http://cancerres.aacrjournals.org/content/suppl/2011/02/28/71.5.1858.DC1

Cited articles This article cites 50 articles, 24 of which you can access for free at: http://cancerres.aacrjournals.org/content/71/5/1858.full#ref-list-1

Citing articles This article has been cited by 57 HighWire-hosted articles. Access the articles at: http://cancerres.aacrjournals.org/content/71/5/1858.full#related-urls

E-mail alerts Sign up to receive free email-alerts related to this article or journal.

Reprints and To order reprints of this article or to subscribe to the journal, contact the AACR Publications Subscriptions Department at [email protected].

Permissions To request permission to re-use all or part of this article, use this link http://cancerres.aacrjournals.org/content/71/5/1858. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC) Rightslink site.