Tumor Response is Predicted by Patient Genetic Profile in Rectal Cancer Patients Treated with Neo-adjuvant Chemo-radiotherapy

The aim of the study was the identification of a pharmacogenetic profile predictive of the tumor regression grade (TRG), considered as tumor response parameter, after neo-adjuvant treatment in rectal cancer patients. A total of 238 rectal cancer patients treated in a neo-adjuvant setting by a fluoropyrimidines-based chemo-radiotherapy (RT) were genotyped for 25 genetic polymorphisms in 16 genes relevant for treatment-associated pathways. Two polymorphisms were associated with TRG in a multivariate analysis: hOGG1-1245C > G, which can affect radiosensitivity and MTHFR-677C > T, which is involved in fluoropyrimidines action. Patients bearing at least one variant allele had a lower chance to get TRG ≤ 2 (OR = 0.46 95% CI 0.23-0.90, P = 0.024; and OR = 0.48 95% CI 0.24-0.96, P = 0.034; respectively). An association trend was observed for ABCB1-3435C > T, which is responsible for the multi-drug resistance (odds ratio (OR) = 1.96, 95% confidence interval (CI) 0.98-3.95, P = 0.057). Exploratory classification and regression tree (CART) analysis highlighted high-order gene-gene and gene-environment interactions and a genetic signature associated with differential response, with hOGG1-1245C > G as the most predictive factor. Other significant variables were: ABCB1-3435C > T, MTHFR-677C > T, ERCC1-8092C > A, ABCC2-1249G > A, XRCC1-28152G > A, XRCC3-4541A > G and patients gender. On the basis of CART results, patients were categorized into three groups according to tumor response probability: intermediate and high profiles had a higher probability to get TRG ≤ 2 as compared with low profiles (OR = 4.12 95% CI 1.46-11.65, P < 0.001 and OR = 12.44, 95% CI 5.52-28.04, P < 0.0001, respectively). This study evidences a major role of hOGG1-1245C > G and MTHFR-677C > T polymorphisms in the tumor response of rectal cancer patients treated with chemo-RT in neo-adjuvant setting, and shows the relevance of gene-gene and gene-environment interactions for complex phenotypes as tumor response.