Potentially functional variants of CYP2A6 and ABHD12 in the arachidonic acid metabolism pathway genes predict the survival of HBV-related hepatocellular carcinoma patients
Year: 2026
Type: article
Study design: Observational Study
Abstract: Arachidonic acid (AA) metabolism plays essential roles in inflammation, tissue regeneration, immune regulation, and tumorigenesis. However, the prognostic significance of genetic variants in AA metabolism genes for hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) remains unclear. We analyzed 56 AA metabolism-related genes in 866 HBV-HCC patients using Cox proportional hazards regression, with Bayesian false discovery probability and false positive report probability for multiple testing correction. Two independent SNPs, CYP2A6 rs28399433 A > C (HR = 1.30, 95% CI = 1.07–1.58, P = 0.008) and ABHD12 rs3827014 C > T (HR = 0.69, 95% CI = 0.52–0.93, P = 0.013), were identified. A genetic score combining protective alleles showed a dose-dependent association with improved overall survival ( P t rend <0.001), with significant multiplicative interactions with smoking ( P interaction =0.016) and alcohol consumption ( P interaction =0.049), and additive interactions for smoking (RERI = 0.65, 95% CI = 0.10–1.19) and BCLC stage B/C (RERI = 1.25, 95% CI = 0.17–2.33). Functional validation with luciferase reporter assays demonstrated allele-specific effects on gene expression ( P < 0.001). Lower CYP2A6 and higher ABHD12 levels in HCC tissues compared to normal were observed in the UALCAN database ( P = 6.43 × 10⁻⁷ for CYP2A6 ; P < 1.00 × 10⁻¹² for ABHD12 ) and in 103 paired tumor/normal tissues. Survival analysis using the KMplot database indicated that decreased CYP2A6 and increased ABHD12 expression were associated with poorer survival ( P < 0.001 and P = 0.008, respectively). These findings suggest that functional variants in CYP2A6 and ABHD12 may serve as novel survival biomarkers for HBV-HCC by regulating gene expression.
Source: BMC Cancer
Authors: Junzheng Peng, Qiuling Lin, Zihan Zhou, Qiuping Wen, Qiuyan Mo, Yanji Jiang, Peiqin Chen, Yingchun Liu, Hongping Yu, Xiaoxia Wei
Language: English
Subfield: Pharmacology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,390
OpenAlex ID: W7162085719
