A genomic approach to identify molecular pathways associated with chemotherapy resistance.

Resistance to chemotherapy in cancer is common. As gene expression profiling has been shown to anticipate chemotherapeutic resistance, we sought to identify cellular pathways associated with resistance to facilitate effective combination therapy. Gene set enrichment analysis was used to associate pathways with resistance in two data sets: the NCI-60 cancer cell lines deemed sensitive and resistant to specific chemotherapeutic agents (Adriamycin, cyclophosphamide, docetaxel, etoposide, 5-fluorouracil, paclitaxel, and topotecan) and a series of 40 lung cancer cell lines for which sensitivity to cisplatin and docetaxel was determined. Candidate pathways were further screened in silico using the Connectivity Map. The lead candidate pathway was functionally validated in vitro. Gene set enrichment analysis associated the matrix metalloproteinase, p53, methionine metabolism, and free pathways with cytotoxic resistance in the NCI-60 cell lines across multiple agents, but no gene set was common to all drugs. Analysis of the lung cancer cell lines identified the bcl-2 pathway to be associated with cisplatin resistance and the AKT pathway enriched in cisplatin- and docetaxel-resistant cell lines. Results from Connectivity Map supported an association between phosphatidylinositol 3-kinase/AKT and docetaxel resistance but did not support the association with cisplatin. Targeted inhibition of the phosphatidylinositol 3-kinase/AKT pathway with LY294002, in combination with docetaxel, resulted in a synergistic effect in previously docetaxel-resistant cell lines but not with cisplatin. These results support the use of a genomic approach to identify drug-specific targets associated with the development of chemotherapy resistance and underscore the importance of disease context in identifying these pathways.