Gene expression profiling of 30 cancer cell lines predicts resistance towards 11 anticancer drugs at clinically achieved concentrations

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Abstract
Cancer patients with tumors of similar grading, staging and histogenesis can have markedly different treatment responses to different chemotherapy agents. So far, individual markers have failed to correctly predict resistance against anticancer agents. We tested 30 cancer cell lines for sensitivity to 5‐fluorouracil, cisplatin, cyclophosphamide, doxorubicin, etoposide, methotrexate, mitomycin C, mitoxantrone, paclitaxel, topotecan and vinblastine at drug concentrations that can be systemically achieved in patients. The resistance index was determined to designate the cell lines as sensitive or resistant, and then, the subset of resistant vs. sensitive cell lines for each drug was compared. Gene expression signatures for all cell lines were obtained by interrogating Affymetrix U133A arrays. Prediction Analysis of Microarrays was applied for feature selection. An individual prediction profile for the resistance against each chemotherapy agent was constructed, containing 42–297 genes. The overall accuracy of the predictions in a leave‐one‐out cross validation was 86%. A list of the top 67 multidrug resistance candidate genes that were associated with the resistance against at least 4 anticancer agents was identified. Moreover, the differential expressions of 46 selected genes were also measured by quantitative RT‐PCR using a TaqMan micro fluidic card system. As a single gene can be correlated with resistance against several agents, associations with resistance were detected all together for 76 genes and resistance phenotypes, respectively. This study focuses on the resistance at the in vivo concentrations, making future clinical cancer response prediction feasible. The TaqMan‐validated gene expression patterns provide new gene candidates for multidrug resistance. Supplementary material for this article can be found on the International Journal of Cancer website at http://www.interscience.wiley.com/jpages/0020‐7136/suppmat.