Molecular Determinants of the Cytotoxicity of Platinum Compounds: the Contribution of in Silico Research

[CANCER RESEARCH 64, 356–362, January 1, 2004] Molecular Determinants of the Cytotoxicity of Platinum Compounds: The Contribution of in Silico Research

Antoine Vekris,1 Delphine Meynard,2 Marie-Christine Haaz,1 Martine Bayssas,3 Jacques Bonnet,2 and Jacques Robert2 1DiGEM S. A., Bordeaux, France; 2Laboratory of Pharmacology of Anticancer Agents, CNRS FRE 2618 Institut Bergonie´and Universite´Victor Segalen Bordeaux 2, Bordeaux, France; and 3Debiopharm S. A., Lausanne, Switzerland

ABSTRACT compounds presenting no cross-resistance with the original compound. Several hundreds of cisplatin analogs have been synthesized Gene expression profiling of tumors allows the establishment of rela- and screened in various systems, but only very few of them have tionships between gene expression profiles and sensitivity to anticancer shown a clinical interest deserving their introduction in the anticancer drugs. In an attempt to study the molecular determinants of the activity of platinum compounds, we explored the publicly available databases of the armamentarium (4). National Cancer Institute (NCI; http://dtp.nci.nih.gov), which allow access Carboplatin (see structure in Fig. 1), the first analog to be approved to the gene expression profiles of the 60 cell lines for which drug cytotox- for cancer chemotherapy, is now widely used in ovarian and testicular icity patterns already existed. Using this database, we have conducted an cancer as well as in the other indications of cisplatin. In contrast, the in silico research to identify the genes the expression of which was posi- toxicity profile of carboplatin is quite different from that of cisplatin, tively or negatively correlated to the sensitivity to four platinum com- with myelosuppression as the major dose-limiting toxicity. In view of pounds (cisplatin, carboplatin, oxaliplatin and tetraplatin). Important the similarity of their indications and the difference in toxicity targets, similarities were noticed between cisplatin and carboplatin on one hand, the combination of these two platinum compounds has been proposed and tetraplatin and oxaliplatin on the other hand. In the restricted panel as a means of minimizing the toxic symptoms while preserving the of 1416 genes and molecular markers, we identified 204 markers, among which 120 corresponded to identified genes, that significantly correlated antitumor efficiency (5). (P < 0.001) with the cytotoxicity of at least one platinum compound. For Another analog, oxaliplatin (see Fig. 1), is characterized by a example, the functionality of the p53-activated pathway appeared posi- completely different spectrum of activity: its main indication has been tively correlated with the cytotoxicity of all platinum compounds. More found in colorectal cancer, a malignancy that is quite refractory to the specific are the positive correlations between RAS gene mutations and classical platinum compounds. In contrast, no indication of this analog MYC expression and the cellular sensitivity to oxaliplatin. Among the has been found in germ cell tumors or squamous cell carcinomas. parameters already known as related to the sensitivity to platinum com- Oxaliplatin is now included in the classical protocols of treatment of pounds, we identified, in the complete set of 9400 genes, numerous signif- advanced colorectal carcinoma in combination with fluorouracil (6). icant relationships, such as the negative correlations between ERB-B2 and No other platinum compound is currently available in the clinical BCL-XL expressions and the cytotoxicity of the platinum compounds. Public databases mining, therefore, appears to be a valuable tool for the setting, although several have been tested in Phase I and II trials. identification of determinants of anticancer drug activity in tumors. Among them, tetraplatin (ormaplatin, NSC363812; Fig. 1) presents original features but its anticancer spectrum and toxicity pattern have not yet been fully identified (7). INTRODUCTION These four platinum compounds have been extensively studied The discovery and development of platinum compounds has been against in vitro and in vivo models, with a special emphasis on the one of the greatest achievements of cancer chemotherapy in the past 60-cell-line panel of the National Cancer Institute (NCI; Ref. 8). Rixe three decades. Cisplatin was accidentally discovered by Rosenberg in et al. (9) have established the comparative in vitro cytotoxicity pro- 1968 as an antibiotic and very rapidly as a very powerful antiprolif- files of these agents, and have shown a strong similarity between erative agent against tumor cells. It was rapidly introduced in clinical cisplatin and carboplatin on one hand and between oxaliplatin and use, principally for the treatment of germ cell tumors of testis and tetraplatin on the other hand. Using the program COMPARE to assess ovary (1). The spectrum of activity of cisplatin includes, in addition to similarities between cytotoxicity profiles, Rixe et al. found that the germ cell tumors, all types of squamous cell carcinomas but only Pearson correlation coefficients were 0.807 between cisplatin and some adenocarcinomas such as gastric cancer. The clinical use of carboplatin and 0.756 between oxaliplatin and tetraplatin but only cisplatin has been considerably hampered by its renal toxicity, which 0.30–0.34 between cisplatin and either oxaliplatin or tetraplatin, and may lead to definitive renal failure and which requires special proce- Ͻ0.1 between carboplatin and either oxaliplatin or tetraplatin (9). dures of administration (2). Neurological toxicity is also a problem, This clear-cut distinction between the two groups of platinum because long-term cisplatin administration may lead to disabling compounds can be interpreted as due to the existence of different peripheral neuropathy. mechanisms of action of the compounds, or at least of mechanisms of A considerable effort has been made by the pharmaceutical industry resistance. This prompted us to explore the molecular determinants of for the discovery of cisplatin analogs. The main goal of this research the activity of these compounds by establishing relationships between was the identification of compounds devoid of the limiting toxicity of gene expression profiles and sensitivity to platinum compounds of cisplatin (3). Also, the emergence of cisplatin-resistant relapsing tu- tumor models. The first step of this exploration can be the mining of mors after initial sensitivity has stimulated the research of active available data in public databases, especially the NCI database. The NCI has recently explored the expression of a panel of 9400 genes in Received 7/24/03; revised 10/3/03; accepted 10/7/03. the 60 cell lines that had been used for 10 years for establishing drug Grant support: Supported by the Ligue Nationale contre le Cancer, comite´de cytotoxicity patterns (10). Using this database, we have conducted an Charente Maritime. The costs of publication of this article were defrayed in part by the payment of page in silico analysis to identify, in the 60 cell lines of the panel and charges. This article must therefore be hereby marked advertisement in accordance with among the 1416 genes or markers that had given the strongest vari- 18 U.S.C. Section 1734 solely to indicate this fact. Requests for reprints: Jacques Robert, Institut Bergonie´, 229 cours de l’Argonne, ation pattern, the genes the expression of which was positively or 33076 Bordeaux-cedex, France. negatively correlated to the sensitivity to each of the platinum com- 356

mining the database of the Gene Ontology Consortium,6 which gathers in a convenient manner all of the information available concerning molecular and cellular functions of the genes products. In a second part of this work, we have explored the literature dealing with the identification of individual genes involved in cell sensitivity or resistance to platinum compounds. This identification originates mainly from studies on cisplatin- or oxaliplatin-resistant cell lines. Using this approach, we identified 18 genes or protein markers; the expression of these individual markers was searched in the whole NCI database, covering not only the original subset of 1376 genes and 40 individual molecular targets but also the complete set of 9400 genes and 255 molecular targets. The coefficients of correlation between the cytotoxicity of the four platinum compounds toward the 60 cell lines and the level of expression of these 18 markers were then calculated as for the exploratory step of 1416 markers. Coefficients of correlation should be used with caution in such studies: a highly significant correlation is in no way indicative of a causal relationship; in addition, a coefficient of correlation can be highly significant without Fig. 1. Structural formulas of the four platinum compounds of the study. showing a gene to be a strong determinant of drug activity. With 58 degrees of freedom, a coefficient of correlation is significant at the P Ͻ 0.001 level from 0.394 and above; this also means that only 16% (0.3942) of the variation is pounds of interest, cisplatin, carboplatin, oxaliplatin and tetraplatin. explained by the correlation. In contrast, a coefficient of correlation of 0.85 We present here the result of this research, which can be considered indicates that 72% of the variation observed can be explained by the correla- as a paradigm of the NCI public database mining. tion. Finally, because a significant coefficient of correlation does not indicate the existence of a linear relationship between two groups of values, and MATERIALS AND METHODS because one or two extreme values can drive a coefficient of correlation to significance, we have first examined the graphs visually as often as possible, We have used for this study the databases of the NCI that are accessible and we have also systematically recalculated the coefficients of correlation through the Internet,4 both for the cytotoxicity data of the four platinum after elimination of the extreme values on both sides. No variations higher than compounds in relation to the 60 cell lines of the panel and for the gene 10% of the r values was found in these conditions. expression data in the same cell lines. A comprehensive review on the access facilities and the generation of matrices has been published by the NCI (10). In a first part of this work, the cytotoxicity data of the four platinum RESULTS compounds in relation to the 60 cell lines were extracted and converted into Ϫ Data Mining in the NCI Database. We first compared the cyto- Microsoft Excel format (A-matrix). We have selected (log GI50)asthe parameter representative of the cytotoxicity of the compounds. Then, the gene toxicity of platinum compounds to gene expression in the 1416-gene expression data of the 60 cell lines were extracted and also converted into data set. The Pearson coefficients of correlation r between drug Microsoft Excel format (T-matrix). As specified by Scherf et al. (10), these cytotoxicity and gene expression ranged between Ϫ0.55 and 0.55. In gene expression data had been obtained at the NCI using glass microarrays. view of the high number of degrees of freedom, a r value of 0.394 They correspond, for each gene, to the log of the ratio of the signal provided or higher is significant at the P Ͻ 0.001 level. In these conditions, 204 by a cell line to the one provided by a pool of 12 cell lines chosen as a genes had their expression level significantly correlated, negatively or reference. As in the study of Scherf et al. (10), the analysis was limited to a positively, with the cytotoxicity of at least one of the four drugs (Table subset of 1376 genes that showed strong patterns of variation among the cell lines and had Ͻ5 of 60 values excluded on the basis of visual quality control 1). In comparison with cisplatin or carboplatin, high numbers of genes or low signal. Besides the available gene markers, 40 other markers corre- had an expression significantly correlated with the cytotoxicities of sponding to protein quantification by Western blotting or functional assays oxaliplatin and tetraplatin. For comparison, the same analysis was were included in the database as carried out by the NCI (10). Because they conducted for drugs of other classes; the numbers of genes having could be relevant for tumor cell characterization, they have been treated as their expression correlated with cytotoxicity was of the same order of gene expression data. magnitude for drugs like doxorubicin, vincristine, paclitaxel, fluorou- For each molecular marker, we calculated the Pearson coefficients of racil, and melphalan (Table 1). When considering two platinum- correlation r between the level of its expression in the 60 cell lines and the containing drugs together, it appeared that the expression of a large degree of cytotoxicity of each of the four compounds. These coefficients of number of markers was significantly correlated to the cytotoxicities of correlation have, therefore, 58 degrees of freedom and are representative of the both oxaliplatin and tetraplatin, whereas a smaller number of markers association between the activity of a drug and the expression of a gene. A significantly positive r value allows one to consider a gene as associated to were correlated to the cytotoxicities of any other group of two drugs drug efficacy, whereas a significantly negative r value allows one to consider (Table 2). For only two markers was the level of expression correlated it as associated to drug resistance. Finally, we calculated the Pearson coeffi- to the degree of cytotoxicity of three drugs together. cients of correlation between the r values obtained for two different drugs, to We then calculated the Pearson coefficients of correlation between evaluate the degree of similarity of the two drugs in terms of the genes the coefficients of correlation, relating cytotoxicity to gene expression associated to drug efficacy or inactivity. These coefficients of correlation have, for each of the four drugs (Table 2). As expected, we obtained very in this case, 1414 degrees of freedom. In all of the analyses, the Pearson high values for the correlations between oxaliplatin and tetraplatin on coefficients of correlation have been considered as significant only for one hand, and carboplatin and cisplatin on the other hand. Much lower Ͻ P 0.001. figures were obtained when comparing oxaliplatin and either carbo- For the genes identified as significantly correlated to the activity of at least platin or cisplatin and when comparing tetraplatin and either carbo- one of the four platinum compounds, we completed the information provided by the NCI database by searching all of the information available in the various platin or cisplatin. Thus, the molecular markers of drug activity are public databases (UniGene, LocusLink).5 Gene functions were identified by very similar for oxaliplatin and tetraplatin, and for cisplatin and carboplatin.

4 Internet address: http://dtp.nci.nih.gov. 5 Internet address: http://www.ncbi.nlm.nih.gov/LocusLink/. 6 Internet address: http://www.godatabase.org/. 357

Table 1 Numbers of genes whose expression is significantly correlated (P Ͻ 0.001) to able complexes. We present in Fig. 2 the diagrams showing some the cytotoxicity of the four platinum analogs and of five other drugs significant relationships between molecular markers and the cytotox- Positively Negatively icity of selected platinum compounds. correlated correlated r Ͼ 0.394 r ϽϪ0.394 When considering the genes associated with the activity of drugs of other classes (doxorubicin, vincristine, paclitaxel, fluorouracil, and Cisplatin 8 10 Carboplatin 15 9 melphalan), we observed that numerous genes were shared by drugs Oxaliplatin 13 132 having no mechanistic relationship: 4 identified genes were signifi- Tetraplatin 8 76 Ͻ Any of the platinum-containing drugs 34 170 cantly (P 0.001) related to both doxorubicin and cisplatin or carboplatin activity, and 13 to both doxorubicin and oxaliplatin or Doxorubicin 2 31 Vincristine 1 8 tetraplatin activity. The corresponding figures were 0 and 11 for Fluorouracil 14 20 paclitaxel, 0 and 7 for fluorouracil, 6 and 33 for paclitaxel. No gene Paclitaxel 3 58 was shared by vincristine and any platinum compound. Melphalan 17 79 Literature Mining in Relation to the NCI Database. The second part of this work was based on literature analysis. From numerous studies performed with cell lines selected for resistance to cisplatin, Among the 204 markers significantly correlated with the cytotox- several genes have already been associated with the acquired resist- icity of at least one of the four platinum compounds, 4 of them have ance to this compound (13–14): this is the case for mismatch repair been detected from individual protein assays. Among the 200 remain- proteins MLH-1 and MSH-2 and for high-mobility group proteins, ing probes, 33 were not correctly identified in the NCI database, with which have been found to be deficient in cisplatin-resistant cells (15). the UniGene accession numbers corresponding to another gene than This is also the case for the detoxification systems involving gluta- the description provided. Among the remaining 167 nucleic acid thione or metallothionein, the levels of which have been found to be probes, a large amount of expressed sequence tags were used on the increased in cisplatin-resistant cell lines (16–18). Consequently, the NCI glass microarrays; 46 of them are not described, whereas 37 glutathione conjugate export pump, MRP1, appears overexpressed in received an official gene symbol and name by the HUGO Gene cisplatin-resistant cell lines (19). Some early-response genes encoding Nomenclature Committee.7 In some cases, different probes corre- transcription factors such as c-MYC,c-FOS,orc-JUN are also over- sponded to the same gene, with very similar expression patterns, expressed in cell lines selected for resistance to cisplatin (20–22). which, finally, limited to 116 the total number of identified genes for Finally, a number of genes involved in the cellular response to DNA which expression was significantly correlated to the activity of any of damage, such as TP53, BAX, BCL-2, and BCL-XL, have been shown the platinum drugs. A complete list of these 116 identified genes to interfere with cisplatin sensitivity (23–25). For instance, transfec- markers and 4 individual protein markers is given on Table 3. A total tion of the antiapoptotic gene BCL-2 confers resistance to cisplatin in of 191 different functions have been attributed to these 116 probes by the ovarian cell line A2780 (23). Concerning oxaliplatin, some deter- the Gene Ontology Consortium. Among the functions or groups of minants of its activity, either in cell lines or in human tumors, have functions, the most represented are the following: cytoskeleton-related been described previously (26–30). In particular, the DNA nucleotide protein activities (actin, myosin, kinesin, cell motility, and so forth; 22 excision repair (NER) has been shown to be involved in the repair of genes); signal transduction-related proteins (16 genes); cell adhesion- oxaliplatin-induced lesions, and the expression of the ERCC1 gene related proteins (16 genes); cell proliferation control (15 genes); negatively correlated with oxaliplatin activity (29, 30). extracellular matrix proteins (14 genes); and transcription factors and We have thus identified 18 markers among those available in the related proteins (12 genes). complete NCI database (9400 genes and 255 molecular markers) as Some features apparent in Table 3 are especially worth the men- potentially related to cisplatin or oxaliplatin sensitivity or resistance tioning. First, the activity of all platinum compounds was positively from the data available in the literature. We have indicated in Table 4 ␥ correlated with the -ray inducibility of the MDM2 protein or of G1 the coefficients of correlation that were obtained between the cyto- arrest, two p53-dependent events requiring integrity of the p53 path- toxicity of the four platinum compounds and the level of expression of way (11). Second, the activity of oxaliplatin was significantly higher these markers. No significant relationship was found between the in cell lines with a mutation in one of the RAS genes, whereas there cytotoxicity of any platinum compound and the level of p53 protein, was no correlation between RAS mutations and the activity of the evaluated by Western blotting; however, there was a relationship other platinum compounds. This is in contrast to the observation that between the presence of a TP53 mutation in a cell line and its transfection with mutated Ha-RAS gene induced cisplatin resistance in sensitivity to most platinum compounds, although with a relatively NIH 3T3 cells (12). It is worth remembering that cisplatin is partic- low significance level (0.01ϽP Ͻ 0.05). This explains the important ularly effective against ovarian and testicular tumors, which have a role of the p53-dependent events such as the radiation inducibility of low frequency of mutated RAS alleles, and that oxaliplatin is rather MDM2 and G1 arrest, which were found to be correlated with the active against colon cancers, which frequently exhibit a RAS mutation. cytotoxicity of most platinum analogs in the previous step. The This may justify the experimentation of this drug in pancreatic cancer, ERB-B2 oncogene, which had been mentioned as overexpressed in in which RAS mutations are especially frequent. And third, the activity cisplatin-resistant cell lines (31), was found negatively correlated to of oxaliplatin and that of tetraplatin were positively correlated to the expression of the MYC oncogene: there again, this may suggest that the tumors that overexpress this oncogene could be particularly sen- Table 2 Pearson coefficients of correlation between the r values relating cytotoxicity sitive to these platinum analogs. The activity of tetraplatin was highly to gene expression for each of the four drugs, and (in parentheses) number of genes the expression of which is significantly correlated (P Ͻ 0.001) to the cytotoxicity of correlated with the level of topoisomerase II; this result can be two platinum analogs simultaneously interpreted as a mere relationship between cytotoxicity and cell pro- Cisplatin Carboplatin Oxaliplatin Tetraplatin liferation, and it may also signify that tetraplatin-induced DNA dam- Cisplatin 0.858 (8) 0.360 (4) 0.197 (2) age preferentially occurs at the level of DNA–topoisomerase II cleav- Carboplatin 0.152 (1) Ϫ0.006 (0) Oxaliplatin 0.848 (54) 7 Internet address: http://www.gene.ucl.ac.uk/nomenclature. Tetraplatin 358

Table 3 List of the identified genes and molecular markers whose expression is significantly correlated to the cytotoxicity of at least one of the four platinum compounds Gene locus number, gene symbol and gene description are those indicated in the Locus Link database (http://www.ncbi.nlm.nih.gov/LocusLink/); gene function is the main function associated with this gene in the Gene Ontology database (http://www.godatabase.org/). Genes have been listed in decreasing order of relation with the activity of any platinum drug, evaluated as the sum of the absolute values of the coefficients of correlation relating drug cytotoxicity and gene expression. The four molecular markers present in the dataset have been listed first. Coefficient of correlation with the cytotoxicity of: Locus Gene No. link no. symbol Gene description Functions cisplat carbo tetra oxali ␥ 1. G1 arrest (12.6 Gy of rays) 0.414 0.402 0.402 2. X-ray induction of mdm2 0.466 0.455 3. Topoisomerase II ␣ 0.537 4. Activated ras oncogene 0.501 5. 928 CD9 CD9 antigen (p24) Integral to plasma membrane Ϫ0.400 Ϫ0.431 Ϫ0.435 6. 7057 THBS1 Thrombospondin 1 Signal transduction Ϫ0.545 Ϫ0.542 7. 65059 ALS2CR9 Amyotrophic lateral sclerosis 2 (juvenile), candidate 9 Not in Gene Ontology Ϫ0.478 Ϫ0.561 8. 6002 RGS12 Regulator of G-protein signaling 12 Regulation of G protein-linked receptor Ϫ0.471 Ϫ0.565 protein signaling pathway 9. 1282 COL4A1 Collagen, type IV, ␣1 Extracellular matrix Ϫ0.512 Ϫ0.522 10. 87 ACTN1 Actinin, ␣1 Actin binding Ϫ0.450 Ϫ0.567 11. 3091 HIF1A Hypoxia-inducible factor 1, ␣ subunit (basic DNA-dependent regulation of Ϫ0.511 Ϫ0.475 transcription factor) transcription 12. 1266 CNN3 Calponin 3, acidic Actin-binding activity Ϫ0.503 Ϫ0.477 13. 2152 F3 Coagulation factor III (thromboplastin, tissue factor) Blood coagulation factor Ϫ0.495 Ϫ0.472 14. 95 ACY1 Aminoacylase 1 Aminoacid metabolism Ϫ0.423 Ϫ0.539 15. 4634 MYL3 Myosin, light polypeptide 3, alkali Calcium ion binding 0.455 0.503 16. 26064 RAI14 Retinoic acid induced 14 Not in Gene Ontology Ϫ0.448 Ϫ0.507 17. 64801 ARV1 Likely ortholog of yeast ARV1 Not in Gene Ontology Ϫ0.469 Ϫ0.485 18. 4609 MYC Myelocytomatosis viral oncogene Cell proliferation; transcription factor 0.432 0.520 19. 10360 NPM3 Nucleophosmin/nucleoplasmin, 33 Chaperone activity 0.484 0.463 20. 9260 ENIGMA Enigma (LIM domain protein) Receptor-mediated endocytosis Ϫ0.489 Ϫ0.455 21. 8829 NRP1 Neuropilin 1 Positive control of cell proliferation Ϫ0.508 Ϫ0.431 22. 1284 COL4A2 Collagen, type IV, ␣2 Extracellular matrix Ϫ0.509 Ϫ0.429 23. 7414 VCL Vinculin Intercellular junction Ϫ0.450 Ϫ0.480 24. 23365 ARHGEF12 Rho guanine nucleotide exchange factor (GEF) 12 Signal transduction Ϫ0.475 Ϫ0.452 25. 55970 GNG12 Guanine nucleotide binding protein (G protein), ␥12 Signal transduction Ϫ0.399 Ϫ0.507 26. 51159 CCRP Colon carcinoma related protein Not in Gene Ontology Ϫ0.465 Ϫ0.441 27. 389 ARH9 Ras homolog gene family, member C RHO small monomeric GTPase activity Ϫ0.481 Ϫ0.421 28. 51765 MST4 Mst3 and SOK1-related kinase Not in Gene Ontology 0.451 0.435 29. 3693 ITGB5 Integrin, ␤5 Cell adhesion Ϫ0.423 Ϫ0.461 30. 11098 SPUVE Serine protease 23 Proteolysis and peptidolysis Ϫ0.420 Ϫ0.440 31. 54443 ANLN Anillin, actin-binding protein Actin binding Ϫ0.436 Ϫ0.424 32. 1073 CFL2 Cofilin 2 (muscle) Actin binding activity Ϫ0.397 Ϫ0.454 33. 1495 CTNNA1 Catenin (cadherin-associated protein), ␣1 Cell adhesion Ϫ0.398 Ϫ0.450 34. 1364 CLDN4 Claudin 4 Tight junction Ϫ0.426 Ϫ0.422 35. 10039 ADPRTL3 ADP-ribosyltransferase (NADϩ; poly (ADP-ribose) DNA repair Ϫ0.407 Ϫ0.437 polymerase)-like 3 36. 8853 DDEF2 Development and differentiation enhancing factor 2 DNA binding Ϫ0.394 Ϫ0.449 37. 390 ARHE Ras homolog gene family, member E Rho small monomeric GTPase activity Ϫ0.396 Ϫ0.447 38. 858 CAV2 Caveolin 2 Integral to membrane Ϫ0.424 Ϫ0.408 39. 9828 P164RHOGEF Rho-specific guanine-nucleotide exchange factor Not in Gene Ontology Ϫ0.428 Ϫ0.398 40. 11031 RAB31 RAB31, member RAS oncogene family Small monomeric GTPase activity Ϫ0.398 Ϫ0.425 41. 54741 HSOBRGRP Leptin receptor gene-related protein Integral to plasma membrane Ϫ0.403 Ϫ0.416 42. 7003 TEAD1 TEA domain family member 1 (SV40 transcriptional DNA-dependent regulation of Ϫ0.401 Ϫ0.412 enhancer factor) transcription 43. 2289 FKBP5 FK506 binding protein 5 Cyclophilin-type cis-trans isomerase 0.588 activity 44. 23677 SH3BP4 SH3-domain binding protein 4 Signal transduction Ϫ0.542 45. 3912 LAMB1 Laminin, ␤1 Cell adhesion; kinesin complex Ϫ0.540 46. 1605 DAG1 Dystroglycan 1 (dystrophin-associated glycoprotein 1) Cell adhesion receptor activity Ϫ0.533 47. 64114 PP1201 PP1201 protein Not in Gene Ontology Ϫ0.530 48. 3936 LCP1 Lymphocyte cytosolic protein 1 (L-plastin) Actin-binding activity 0.525 49. 23047 AS3 Androgen-induced proliferation inhibitor Negative control of cell proliferation Ϫ0.523 50. 8565 YARS Tyrosyl-tRNA synthetase Tyrosyl-tRNA biosynthesis 0.519 51. 51454 CED-6 Phosphotyrosine-binding domain adaptor protein Signal transduction Ϫ0.517 52. 5445 PON2 Paraoxonase 2 Arylesterase activity Ϫ0.511 53. 1509 CTSD Cathepsin D (lysosomal aspartyl protease) Proteolysis and peptidolysis Ϫ0.509 54. 4651 MYO10 Myosin X Not in Gene Ontology Ϫ0.496 55. 10184 LHFPL2 Lipoma HMGIC fusion partner-like 2 Not in Gene Ontology Ϫ0.496 56. 10457 GPNMB Glycoprotein (transmembrane) nmb Negative control of cell proliferation 0.495 57. 308 ANXA5 Annexin A5 Calcium ion binding activity Ϫ0.488 58. 5536 PPP5C Protein phosphatase 5, catalytic subunit Protein serine/threonine phosphatase 0.485 59. 51573 MIR16 Membrane interacting protein of RGS16 Not in Gene Ontology Ϫ0.483 60. 1975 EIF4B Eukaryotic translation initiation factor 4B Translation initiation 0.483 61. 5829 PXN Paxillin Cell matrix adhesion Ϫ0.481 62. 7105 TM4SF6 Transmembrane 4 superfamily member 6 Cell adhesion Ϫ0.477 63. 10783 NEK6 NIMA (never in mitosis gene a)-related kinase 6 Not in Gene Ontology Ϫ0.476 64. 11151 CORO1A Coronin, actin-binding protein, 1A Actin-binding activity 0.473 65. 2050 EPHB4 Ephrin-B4 Transmembrane protein tyrosine kinase Ϫ0.472 receptor 66. 22836 RHOBTB3 Rho-related BTB domain containing 3 Rho small monomeric GTPase activity Ϫ0.470 67. 2059 EPS8 Epidermal growth factor receptor pathway substrate 8 EGF receptor signaling pathway Ϫ0.468 68. 114876 OSBPL1A Oxysterol binding protein-like 1A Not in Gene Ontology Ϫ0.465

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Table 3 continued Coefficient of correlation with the cytotoxicity of: Locus Gene No. link no. symbol Gene description Functions cisplat carbo tetra oxali 69. 5236 PGM1 Phosphoglucomutase 1 Glucose metabolism Ϫ0.462 70. 7319 UBE2A Ubiquitin-conjugating enzyme E2A (RAD6 homolog) Ubiquitin-dependent protein Ϫ0.461 degradation 71. 1371 CPO Coproporphyrinogen oxidase Mitochondrion/oxidoreductase activity 0.461 72. 25937 TAZ Transcriptional co-activator with PDZ-binding motif Regulation of transcription, DNA- Ϫ0.458 dependent 73. 857 CAV1 Caveolin 1 Integral to plasma membrane Ϫ0.458 74. 7042 TGFB2 Transforming growth factor, ␤2 Cell proliferation; signal transduction Ϫ0.457 75. 4775 NFATC3 Nuclear factor of activated T-cells, calcineurin-dependent 3 Transcription activating factor 0.451 76. 29994 BAZ2B Bromodomain adjacent to zinc finger domain, 2B DNA-dependent regulation of 0.451 transcription 77. 347 APOD Apolipoprotein D High-density lipoprotein binding Ϫ0.450 78. 10544 PROCR Protein C receptor, endothelial Integral plasma membrane protein Ϫ0.449 79. 529 ATP6E Atpase, Hϩ transporting, lysosomal 31 kda, V1 subunit E Proton-transporting ATP synthase Ϫ0.448 isoform 1 complex 80. 8412 BCAR3 Breast cancer anti-estrogen resistance 3 Signal transduction Ϫ0.445 81. 51164 DCTN Dynactin 4 (p62) Centrosome 0.445 82. 55353 LAPTM4B Lysosomal-associated protein transmembrane 4␤ Membrane integral protein Ϫ0.443 83. 2778 GNAS Guanine nucleotide ␣-stimulating complex locus Heterotrimeric G protein GTPase, ␣ Ϫ0.443 subunit 84. 5768 QSCN6 Quiescin Q6 Negative control of cell proliferation Ϫ0.441 85. 1718 DHCR24 24-dehydrocholesterol reductase Cholesterol biosynthesis Ϫ0.437 86. 203 AK1 Adenylate kinase 1 Adenylate kinase activity Ϫ0.434 87. 3491 CYR61 Cysteine-rich, angiogenic inducer, 61 Cell proliferation Ϫ0.432 88. 81551 STMN4 Stathmin-like 4 Kinesin complex Ϫ0.431 89. 2274 FHL2 Four and a half LIM domains 2 Oncogenesis Ϫ0.431 90. 6385 SDC4 Syndecan 4 (amphiglycan, ryudocan) Cytoskeletal protein binding activity Ϫ0.430 91. 1727 D1A1 Diaphorase (NADH: cytochrome b-5 reductase) Cytochrome b5-reductase activity Ϫ0.430 92. 1022 CDK7 Cyclin-dependent kinase 7 Regulation of CDK activity Ϫ0.430 93. 1490 CTGF Connective tissue growth factor Cell growth and maintenance Ϫ0.429 94. 79666 LEKHF2 Pleckstrin homology domain containing, family F member 2 Zinc ion binding Ϫ0.427 95. 9444 QKI Quaking homolog, KH domain RNA-binding Signal transduction 0.420 96. 7082 TJP1 Tight junction protein 1 Tight junction Ϫ0.416 97. 8974 P4HA2 Procollagen-proline, 2-oxoglutarate 4-dioxygenase (proline Protein prolyl hydroxylation Ϫ0.414 4-hydroxylase), ␣ polypeptide II 98. 7980 TFP12 Tissue factor pathway inhibitor 2 Extracellular matrix Ϫ0.413 99. 800 CALD1 Caldesmon 1 Actin binding activity Ϫ0.412 100. 1381 CRABP1 Cellular retinoic acid-binding protein 1 Retinoid binding activity Ϫ0.410 101. 7048 TGFBR2 Transforming growth factor, ␤ receptor II Cell proliferation; signal transduction Ϫ0.408 102. 10965 ZAP128 Peroxisomal long-chain acyl-coa thioesterase Acyl-coa metabolism Ϫ0.407 103. 7070 THY1 Thy-1 cell surface antigen Integral to plasma membrane 0.407 104. 5747 PTK2 Protein tyrosine kinase 2 Signal transduction Ϫ0.406 105. 2202 EFEMP1 EGF-containing fibulin-like extracellular matrix protein 1 Calcium binding activity Ϫ0.406 106. 409 ARRB2 Arrestin, ␤2 Signal transduction 0.405 107. 752 FMNL Formin-like protein Not in Gene Ontology 0.404 108. 50863 HNT Neurotrimin Cell adhesion 0.404 109. 11328 FKBP9 FK506 binding protein 9 Cyclophilin-type cis-trans isomerase Ϫ0.403 activity 110. 2013 EMP2 Epithelial membrane protein 2 Cell death Ϫ0.403 111. 10171 RNAC RNA cyclase homolog RNA-3Ј-phosphate cyclase activity 0.403 112. 84962 JUB Ajuba homolog Cell adhesion Ϫ0.402 113. 5859 QARS Glutaminyl-tRNA synthetase Glutaminyl-tRNA biosynthesis Ϫ0.402 114. 1015 CDH17 Cadherin 17, LI cadherin (liver-intestine) Calcium-dependent cell adhesion Ϫ0.401 115. 6282 S100A11 S100 calcium binding protein A11 (calgizzarin) Negative control of cell proliferation Ϫ0.399 116. 8682 PEA15 Phosphoprotein enriched in astrocytes 15 Small molecule transport Ϫ0.398 117. 4794 NFKBIE Nuclear factor of ␬ light polypeptide gene enhancer in B- Transcription factor binding Ϫ0.397 cells inhibitor, ⑀ 118. 3945 LDHB Lactate dehydrogenase B L-lactate dehydrogenase activity Ϫ0.397 119. 3151 HMG17 High-mobility group nucleosomal-binding domain 2 Not in Gene Ontology Ϫ0.394 120. 2200 FBN1 Fibrillin 1 (Marfan syndrome) Calcium ion binding 0.394 the cytotoxicity of tetraplatin and oxaliplatin (P Ͻ 0.001) and, to a Finally, the platinum detoxification systems involving glutathione or lesser extent, to that of cisplatin and carboplatin (P Ͻ 0.05). In the metallothionein were weakly correlated to the cytotoxicity of plati-

BCL-2 family, the expression of the antiapoptotic gene BCL-XL was num compounds: only the mRNA expression of the ATP-binding the only one to be (negatively) correlated with the cytotoxicity of the cassette pump MRP1 seemed correlated to the resistance to tetraplatin platinum compounds, especially cisplatin and carboplatin. Concerning (P Ͻ 0.001) and to oxaliplatin (P Ͻ 0.05). In addition, metallothio- the DNA mismatch repair proteins MLH1 and MSH2, which have nein seemed paradoxically correlated to the sensitivity to tetraplatin. been found to be deficient in cisplatin-resistant cell lines (15), we obtained positive coefficients of correlation between the level of their DISCUSSION expression and the cytotoxicity of tetraplatin and oxaliplatin, but much below the level of significance (P Ͼ 0.05). Unfortunately, the In this study, we have explored the public databases of the NCI to nucleotide excision repair proteins ERRC1 and XPA were not present identify the molecular markers associated with cell sensitivity and in the NCI database, which prevented the establishment of relation- resistance to four platinum compounds of clinical interest. A total of ships between the level of their expression and oxaliplatin resistance. 204 marker genes have been found, which are associated with a high 360

There are, however, several limitations to the type of study that we have developed and the reader should be aware of them: 1. The evaluation of gene expression was performed on a subset of 1416 genes and molecular markers, which represents a relatively small fraction of the total transcriptome, because ϳ30,000 genes are present in the human genome, 10,000 of which are thought to be expressed in a single cell. The original glass arrays concerned a total of 9400 genes (nearly one-third of the genome), but the results had not been obtained on a sufficient number of cell lines of the panel to be included in the database (10). As a consequence, not included in the database are many genes that may play an important role in deter- mining cell sensitivity to the drugs. The existence of other databases including the expression levels of larger sets of genes in the NCI cell line panel will allow the extension of this type of in silico research to the complete genome (34). 2. The level of expression of the 1416 molecular markers was deter- mined with a technique that was still under development and not fully validated. Nothing is known on the accuracy of the gene expression data Fig. 2. Some highly significant relationships between molecular markers or gene expres- provided in the database. In particular, the lack of reproducibility of the sion levels and the cytotoxicity of platinum compounds, as extracted from the National Cancer Institute databases: relationship between RAS gene status and oxaliplatin cytotoxicity; rela- crucial reverse-transcription step is a relatively important cause of error. tionship between c-MYC gene expression and oxaliplatin cytotoxicity; relationship between A recent study comparing the gene expression data obtained for the 60 topoisomerase II expression (estimated by Western blotting) and tetraplatin cytotoxicity; cell lines of the NCI panel by three different laboratories evidenced not relationship between actinin ␣1 gene expression and oxaliplatin cytotoxicity. more than 36% of statistically significant results for those markers present in the three data sets (35). In the NCI data set that we have used, the level level of significance to drug activity, but only 120 of them could be of expression of the 1376 genes in the 60 cell lines is normalized to the identified with certainty. In a first approach, we can consider these mean expression of these genes in a subset of 12 cell lines (10). These molecular markers as involved in the cellular response to the drugs. A levels of expression are, therefore, only relative to an arbitrary standard large number of the markers that were identified as associated with the and this may introduce an important bias, especially for the genes that are activity of the drugs correspond to genes involved in cell proliferation, expressed at a low level. in cell adhesion, in the cytoskeleton, and in transcriptional control. If 3. The criterion for drug cytotoxicity that has been retained by the NCI one considers that chemotherapy should be prescribed in the future as is the 50% growth inhibitory concentration (GI50) and not cell kill. There a function of the molecular characteristics of the tumor, and not only has been much controversy about the relevance of growth inhibition to as a function of its localization, the identification of the molecular evaluate drug cytotoxicity (36). For instance, growth inhibition by any determinants of drug action is a crucial enterprise. In this respect, the drug is clearly related to the p53 status of a cell line, whereas clonogenic availability of large databases relating drug activity to gene expression survival is not (37). Therefore, one can wonder whether the GI50 used by profiles constitutes a powerful tool to identify the tumor characteris- the NCI is the ultimate test to evaluate drug activity. Indeed, an obser- tics that will allow the optimal choice of the anticancer drug on an vation made in the NCI database raises the problem of the relevance of individual basis. The NCI has implemented such a tool that allows a this parameter: when considering not only the four platinum compounds, multitude of possible minings such as the one we have performed. but the 121 active drugs of the NCI core database, the coefficients of Other databases have recently been constituted and made available correlation between the r values relating drugs and gene expression are in (32, 33) with the same purpose. Starting from the clues given by in majority highly significant; when comparing each of the 121 drugs to the silico research, one can validate in clinical studies the set of markers 120 other ones, the correlation is significantly positive at the 0.001 level that appear, simultaneously, the most significantly predictive of drug in 80% of the possible cases. In other words, the levels of gene expression action and the easiest to detect in routine pathology laboratories. are correlated to a general drug sensitivity phenotype, independently of

Table 4 Coefficients of correlation between sensitivity to a platinum compound and the expression of a gene or a protein potentially involved in platinum cytotoxicitya cisplatin carboplatin tetraplatin oxaliplatin c-MYC (mRNA) Overexpressed in cisplatin-resistant cells (21) 0.070 Ϫ0.088 0.315** 0.429*** p53 (protein) Overexpression associated with mutations Ϫ0.233* Ϫ0.194 Ϫ0.073 Ϫ0.020 TP53 mutation (0 ϭ mutant) Associated with cisplatin resistance (23, 25) 0.320** 0.314** 0.276* 0.177 ERB-B2 (mRNA) Overexpressed in cisplatin-resistant cells (26) Ϫ0.270* Ϫ0.281* Ϫ0.443*** Ϫ0.538*** BCL-2 (mRNA) Overexpressed in cisplatin-resistant cells (24) 0.181 0.111 Ϫ0.097 0.080 Ϫ Ϫ Ϫ Ϫ BCL-XL (mRNA) Analogous to BCL-2 0.517*** 0.385** 0.235* 0.204 BAD (protein) Antagonistic to BCL proteins Ϫ0.016 Ϫ0.003 0.040 Ϫ0.152 BAX (mRNA) Deficient in cisplatin-resistant cells (25) 0.042 0.190 Ϫ0.060 0.007 MLH1 (protein) Deficient in cisplatin-resistant cells (15) 0.101 Ϫ0.061 0.192 0.154 MSH2 (protein) Deficient in cisplatin-resistant cells (15) Ϫ0.008 Ϫ0.015 0.132 0.138 Glutathione Elevated in cisplatin-resistant cells Ϫ0.187 Ϫ0.288* Ϫ0.024 Ϫ0.056 Glutathione synthase (mRNA) Overexpressed in cisplatin-resistant cells (16) Ϫ0.165 Ϫ0.254* 0.079 0.032 ␥-Glu-transpeptidase (mRNA) Overexpressed in cisplatin-resistant cells (16) 0.117 0.160 Ϫ0.064 Ϫ0.045 Glutathione S-transferase ␣ (mRNA) Overexpressed in cisplatin-resistant cells (17) Ϫ0.144 Ϫ0.023 Ϫ0.203 Ϫ0.302** Glutathione S-transferase ␮ (mRNA) Overexpressed in cisplatin-resistant cells (17) 0.263* 0.246* 0.053 0.176 Glutathione S-transferase ␲ (mRNA) Overexpressed in cisplatin-resistant cells (17) Ϫ0.171 0.018 0.044 0.093 Multidrug resistance protein 1 (mRNA) Overexpressed in cisplatin-resistant cells (19) 0.021 Ϫ0.023 Ϫ0.444*** Ϫ0.218* Metallothionein (protein) Elevated in cisplatin-resistant cells (18) 0.081 Ϫ0.001 0.232* 0.169 .P Ͻ 0.001 ,ءءء ;P Ͻ 0.01 ,ءء ;P Ͻ 0.05 ,ء :(a The significance of the coefficients of correlation is as follows (58 degrees of freedom 361

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