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Abstract

Hepatitis B virus (HBV) mutations and signal transducer and activator of transcription 3 (STAT3) activation are closely associated with hepatocellular carcinoma (HCC). However, single nucleotide polymorphisms (SNPs) of STAT3 have not been implicated in HCC susceptibility. This study was designed to evaluate the effect of STAT3 SNPs and their interactions with HBV mutations on HCC risk. A total of 2,011 HBV-infected subjects (including 1,021 HCC patients) and 1,012 healthy controls were involved in this study. SNPs rs4796793 (−1697, C>G), rs2293152 (intron 11, C>G), and rs1053004 (3′ untranslated region, T>C) were genotyped using quantitative polymerase chain reaction. HBV mutations were determined via direct sequencing. It was found that rs2293152 (GG versus CC) was significantly associated with HCC risk compared with the subjects without HCC, adjusting for age and sex (adjusted odds ratio [AOR], 1.30; 95% confidence interval [CI], 1.04-1.62). The impact of rs2293152 was greater in women compared with men. Compared with HCC-free HBV-infected subjects, rs2293152 GG was solely associated with HCC in women (AOR, 2.04; 95% CI, 1.15-3.61). rs2293152 GG was significantly associated with high viral load (≥1 × 104 copies/mL) (AOR, 1.37; 95%, CI 1.01-1.88) and increased frequencies of T1674C/G (AOR, 1.61; 95% CI, 1.06-2.46) and A1762T/G1764A (AOR, 1.64; 95% CI, 1.14-2.35). In multivariate regression analyses, multiplicative interaction of rs1053004 with T1674C/G significantly increased HCC risk, whereas rs2293152 and A1726C interaction reduced it, adjusting for covariates including HBV mutations in the enhancer II/basal core promoter/precore region; the interaction of rs4796793 with preS2 start codon mutation significantly increased HCC risk, adjusting for covariates including HBV mutations in the preS region. Conclusion: STAT3 SNPs appear to predispose the host with HBV mutations to hepatocarcinogenesis, and this effect may differ in men versus women. STAT3 SNPs may have applicability in future HCC surveillance algorithms. (Hepatology 2013;57:2369–2377)