Identification of genes associated with platinum drug sensitivity and resistance in human ovarian cancer cells

Platinum-based chemotherapeutic regimens are ultimately unsuccessful due to intrinsic or acquired drug resistance. Understanding the molecular basis for platinum drug sensitivity/resistance is necessary for the development of new drugs and therapeutic regimens. In an effort to identify such determinants, we evaluated the expression of approximately 4000 genes using cDNA microarray screening in a panel of 14 unrelated human ovarian cancer cell lines derived from patients who were either untreated or treated with platinum-based chemotherapy. These data were analysed relative to the sensitivities of the cells to four platinum drugs (cis-diamminedichloroplatinum (cisplatin), carboplatin, DACH-(oxalato) platinum (II) (oxaliplatin) and cis-diamminedichloro (2-methylpyridine) platinum (II) (AMD473)) as well as the proliferation rate of the cells. Correlation analysis of the microarray data with respect to drug sensitivity and resistance revealed a significant association of Stat1 expression with decreased sensitivity to cisplatin (r = 0.65) and AMD473 (r = 0.76). These results were confirmed by quantitative RT-PCR and Western blot analyses. To study the functional significance of these findings, the full-length Stat1 cDNA was transfected into drug-sensitive A2780 human ovarian cancer cells. The resulting clones that exhibited increased Stat1 expression were three- to five-fold resistant to cisplatin and AMD473 as compared to the parental cells. The effect of inhibiting Jak/Stat signalling on platinum drug sensitivity was investigated using the Janus kinase inhibitor, AG490. Pretreatment of platinum-resistant cells with AG490 resulted in significant increased sensitivity to AMD473, but not to cisplatin or oxaliplatin. Overall, the results indicate that cDNA microarray analysis may be used successfully to identify determinants of drug sensitivity/resistance and future functional studies of other candidate genes from this database may lead to an increased understanding of the drug resistance phenotype.