The role of functional polymorphisms in immune response genes as biomarkers of bacille Calmette-Guérin (BCG) immunotherapy outcome in bladder cancer: establishment of a predictive profile in a Southern Europe population.

Abstract

To evaluate the predictive value of genetic polymorphisms in the context of bacille Calmette-Guérin (BCG) immunotherapy outcome and create a predictive profile that may allow discrimination of the risk of recurrence. In a dataset of 204 patients treated with BCG, we evaluated 42 genetic polymorphisms in 38 genes involved in the BCG mechanism of action, using Sequenom MassARRAY(®) technology. Stepwise multivariate Cox regression was used for data mining. In agreement with previous studies we found that gender, age, tumour multiplicity and treatment scheme were associated with BCG failure. Using stepwise multivariate Cox regression analysis we propose the first predictive profile of BCG immunotherapy outcome and a risk score based on polymorphisms in immune system molecules [single nucleotide polymorphisms in tumour necrosis factor α (TNFA)-1031T/C (rs1799964), interleukin 2 receptor α (IL2RA) rs2104286 T/C, IL17A-197G/A (rs2275913), IL17RA-809A/G (rs4819554), IL18R1 rs3771171 T/C, intercellular adhesion molecule 1 (ICAM-1) K469E (rs5498), Fas ligand (FASL)-844T/C (rs763110) and TNF-related apoptosis-inducing ligand receptor 1 (TRAILR1)-397T/G (rs79037040)] in association with clinicopathological variables. This risk score allows the categorisation of patients into risk groups: patients within the low-risk group have a 90% chance of successful treatment, whereas patients in the high-risk group present a 75% chance of recurrence after BCG treatment. We have established the first predictive score of BCG immunotherapy outcome combining clinicopathological characteristics and a panel of genetic polymorphisms. Further studies using an independent cohort are warranted. Moreover, the inclusion of other biomarkers may help to improve the proposed model.