TNFRSF1A (-135 T>C, rs767455) Polymorphism as a Predictor of Radiation Induced Oral Mucositis and Treatment Response in Locally Advanced Head and Neck Cancer Patients.

Abstract

Head and neck squamous cell carcinoma (HNSCC) is the most common head and neck cancer in India, where intensity-modulated radiation therapy (IMRT) is the standard treatment. Despite therapeutic advances, variability in radiation response and toxicities persists. Genetic factors, including the TNFRSF1A (-135 T>C, rs767455) polymorphism, may influence susceptibility to oral mucositis, dermatitis, and treatment response, but remain insufficiently studied in Indian populations. Functional validation through serum TNF-α profiling and predictive modeling is also lacking. A total of 50 patients with locally advanced HNSCC were treated with IMRT (70 Gy/35 fractions) and weekly cisplatin (40 mg/m²). Pre-treatment blood samples were analyzed for TNFRSF1A genotyping (PCR-RFLP) and serum TNF-α levels (ELISA). Oral mucositis and dermatitis were graded weekly using CTCAE v4.0, and treatment response was evaluated 90 days post-therapy by RECIST 1.1. Statistical analyses included Chi-square/Fisher's exact tests, odds ratios, Kruskal-Wallis ANOVA, and multivariate regression. A Random Forest model was applied for predictive evaluation. Genotype distribution was TT (52.0%), TC (38.0%), and CC (10.0%). Carriers of the C allele (TC/CC) had a significantly higher risk of severe mucositis (OR = 4.58, p = 0.010), while no association was observed with dermatitis. The TT genotype correlated with complete response (OR = 7.00, p = 0.002) and higher median serum TNF-α levels (13.28 pg/mL, p = 0.041). Multivariate analysis confirmed TNFRSF1A genotype as an independent predictor of mucositis and response, while age was protective against dermatitis. The Random Forest model achieved 60% accuracy in predicting treatment response. The TNFRSF1A (-135 T>C) polymorphism influences both toxicity and response in HNSCC, with the C allele predisposing to mucositis and the TT genotype predicting favorable outcomes. It represents a potential biomarker for personalized radiotherapy, meriting validation in larger cohorts.