Clinical-pharmacogenetic models for personalized cancer treatment: application to malignant mesothelioma

Large interindividual differences in treatment outcome are observed in cancer patients undergoing chemotherapy. Our aim was to develop and validate clinical-pharmacogenetic prediction models of gemcitabine/cisplatin or pemetrexed/cisplatin treatment outcome and develop an algorithm for genotype-based treatment recommendations in malignant mesothelioma (MM). We genotyped 189 MM patients for polymorphisms in gemcitabine, pemetrexed and cisplatin metabolism, transport and drug target genes and DNA repair pathways. To build respective clinical-pharmacogenetic models, pharmacogenetic scores were assigned by rounding regression coefficients. Gemcitabine/cisplatin model was based on training group of 71 patients and included CRP, histological type, performance status, RRM1 rs1042927, ERCC2 rs13181, ERCC1 rs3212986, and XRCC1 rs25487. Patients with higher score had shorter progression-free (PFS) and overall survival (P < 0.001). This model's sensitivity was 0.615 and specificity 0.812. In independent validation group of 66 patients the sensitivity and specificity were 0.667 and 0.641, respectively. Pemetrexed/cisplatin model was based on 57 patients and included CRP, MTHFD1 rs2236225, and ABCC2 rs2273697. Patients with higher score had worse response and shorter PFS (P < 0.001). This model's sensitivity was 0.750 and specificity 0.607. In independent validation group of 20 patients the sensitivity and specificity were 0.889 and 0.500, respectively. The proposed algorithm based on these models could enable the choice of the most effective chemotherapy for 85.5% of patients and lead to improved treatment outcome in MM.