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Genetic biomarkers for hepatocellular cancer risk in a caucasian population
AIM: To uncover novel genetic markers that could contribute to predicting hepatocellular carcinoma (HCC) susceptibility in Caucasians. METHODS: The present retrospective case-control study compared genotype frequencies between a cohort of HCC cases and two, independent, HCC-free, age/sex-matched con...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5643288/ https://www.ncbi.nlm.nih.gov/pubmed/29085212 http://dx.doi.org/10.3748/wjg.v23.i36.6674 |
Sumario: | AIM: To uncover novel genetic markers that could contribute to predicting hepatocellular carcinoma (HCC) susceptibility in Caucasians. METHODS: The present retrospective case-control study compared genotype frequencies between a cohort of HCC cases and two, independent, HCC-free, age/sex-matched control groups. The HCC cohort comprised 192 homogeneous patients that had undergone orthotopic liver transplantation. The first control group comprised 167 patients that were matched to the HCC cohort for the percentage of hepatitis B (HBV) and/or hepatitis C (HCV) infections. A second control group included 192 virus-free, healthy individuals that were used to evaluate the generalizability of the identified predictive markers. All cases and controls were Caucasian. The three study populations were characterized with a panel of 31 markers derived from 21 genes that encoded key proteins involved in hepatocarcinogenesis-related pathways. The study end-point was to assess the association between genetic variants and HCC onset. RESULTS: Five genetic markers were identified as risk factors for HCC in high-risk patients infected with HBV/HCV. According to a dominant model, reduced HCC risk was associated with three polymorphisms: ERCC1 rs3212986 (OR = 0.46, 95%CI: 0.30-0.71, P = 0.0005), GST-P1 rs1138272 (OR = 0.41, 95%CI: 0.21-0.81, P = 0.0097), and CYP17A1 rs743572 (OR = 0.50, 95%CI: 0.31-0.79, P = 0.0032). Conversely, according to a recessive model, increased HCC risk was associated with two polymorphisms: XRCC3 rs1799794 (OR = 3.70, 95%CI: 1.02-13.39, P = 0.0461) and ABCB1 rs1128503 (OR = 2.06, 95%CI: 1.18-3.61, P = 0.0111). These associations remained significant in a subgroup analysis, where patients were stratified according to viral status (HBV- or HCV-positive serology). Two variants exhibited a serology-specific effect: ABCB1 rs1128503 (OR = 4.18, 95%CI: 1.55-11.29, P = 0.0048) showed an effect in the HBV-positive subgroup; and ERCC1 rs3212986 (OR = 0.33, 95%CI: 0.18-0.60, P = 0.0003) showed an effect in the HCV-positive subgroup. Among the five markers identified, ERCC1 rs3212986 (OR = 0.43, P < 0.0001) and CYP17A1 rs743572 (OR = 0.73, P = 0.0310) had a different distribution in patients with HCC compared to healthy individuals. With a recursive partitioning approach, we also demonstrated that significant gene-gene interactions between ERCC1 rs3212986, CYP17A1 rs743572, GST-P1 rs1138272, and the previously described UGT1A7*3 predictive marker, played a role in the complex trait of HCC susceptibility. CONCLUSION: We identified five polymorphisms and interactions that contributed crucially to predicting HCC risk. These findings represented an important step towards improving HCC diagnosis and management. |
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