Single nucleotide polymorphism at rs1982073:T869C of the TGFbeta 1 gene is associated with the risk of radiation pneumonitis in patients with non-small-cell lung cancer treated with definitive radiotherapy.
PURPOSE: In search of reliable biologic markers to predict the risk of normal tissue damage by radio(chemo)therapy before treatment, we investigated the association between single nucleotide polymorphisms (SNPs) in the transforming growth factor 1 (TGFbeta1) gene and risk of radiation pneumonitis (RP) in patients with non-small-cell lung cancer (NSCLC). PATIENTS AND METHODS: Using 164 available genomic DNA samples from patients with NSCLC treated with definitive radio(chemo)therapy, we genotyped three SNPs of the TGFbeta1 gene (rs1800469:C-509T, rs1800471:G915C, and rs1982073:T869C) by polymerase chain reaction restriction fragment length polymorphism method. We used Kaplan-Meier cumulative probability to assess the risk of grade > or = 3 RP and Cox proportional hazards analyses to evaluate the effect of TGFbeta1 genotypes on such risk. RESULTS: There were 90 men and 74 women in the study, with median age of 63 years. Radiation doses ranging from 60 to 70 Gy (median = 63 Gy) in 30 to 58 fractions were given to 158 patients (96.3%) and platinum-based chemotherapy to 147 (89.6%). Grade > or = 2 and grade > or = 3 RP were observed in 74 (45.1%) and 36 patients (22.0%), respectively. Multivariate analysis found CT/CC genotypes of TGFbeta1 rs1982073:T869C to be associated with a statistically significantly lower risk of RP grades > or = 2 (hazard ratio [HR] = 0.489; 95% CI, 0.227 to 0.861; P = .013) and grades > or = 3 (HR = 0.390; 95% CI, 0.197 to .774; P = 0.007), respectively, compared with the TT genotype, after adjustment for Karnofsky performance status, smoking status, pulmonary function, and dosimetric parameters. CONCLUSION: Our results showed that CT/CC genotypes of TGFbeta1 rs1982073:T869C gene were associated with lower risk of RP in patients with NSCLC treated with definitive radio(chemo)therapy and thus may serve as a reliable predictor of RP.
Yuan, X; Liao, Z; Liu, Z; Wang, L-E; Tucker, SL; Mao, L; Wang, XS; Martel, M; Komaki, R; Cox, JD; Milas, L; Wei, Q
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