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Circulating cell-free DNA methylation biomarkers for hepatocellular carcinoma risk prediction in HIV-positive Nigerian population.

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International journal of cancer 📖 저널 OA 48.8% 2022: 0/3 OA 2023: 1/3 OA 2024: 6/16 OA 2025: 32/61 OA 2026: 128/241 OA 2022~2026 2026 Vol.158(5) p. 1281-1291
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출처

Zheng Y, Han J, Qu Y, Wang J, Joyce BT, Okeke E, Davwar PM, Duguru MJ, Nyam DP, Odeghe E, Oyeleke G, Lesi OA, Imade GE, Sulaimon AA, Hawkins C, Abdulkareem FB, Badmos K, Gursel DB, Wei JJ, Silas OA, Kocherginsky M, Kim KA, Sun Z, Achenbach CJ, Zhang X, Yang H, Sagay AS, Ogunsola FT, Murphy RL, Roberts LR, Hou L

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Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality globally, with particularly high burdens among people living with HIV (PLWH) in low-resource settings like Nigeria.

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  • 표본수 (n) 245
  • Sensitivity 80%

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APA Zheng Y, Han J, et al. (2026). Circulating cell-free DNA methylation biomarkers for hepatocellular carcinoma risk prediction in HIV-positive Nigerian population.. International journal of cancer, 158(5), 1281-1291. https://doi.org/10.1002/ijc.70204
MLA Zheng Y, et al.. "Circulating cell-free DNA methylation biomarkers for hepatocellular carcinoma risk prediction in HIV-positive Nigerian population.." International journal of cancer, vol. 158, no. 5, 2026, pp. 1281-1291.
PMID 41129333 ↗
DOI 10.1002/ijc.70204

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality globally, with particularly high burdens among people living with HIV (PLWH) in low-resource settings like Nigeria. Effective early detection remains a major challenge due to limited access to imaging-based surveillance and the low sensitivity of current biomarkers such as alpha-fetoprotein (AFP). We conducted an epigenome-wide association study (EWAS) of circulating cell-free DNA (ccfDNA) methylation in a Nigerian cohort of HIV-positive individuals (n = 245), spanning HCC, cirrhosis (FibroScan ≥12.3 kPa), fibrosis (FibroScan ≥7.6 and <12.3 kPa), and HCC-free without fibrosis (FibroScan <7.6 kPa) groups. Using random forest modeling, we developed and evaluated a ccfDNA methylation classifier (ccfDNAmRF) for HCC risk prediction. We identified 73 CpG sites significantly associated with HCC (false discovery rate <0.01). The ccfDNAmRF model demonstrated strong discriminatory power, achieving 100% sensitivity and 80%-91% specificity for distinguishing HCC from cirrhosis, fibrosis, and HCC-free groups (area under the curve [AUC]: 92%-97%). Combining ccfDNA methylation risk scores with AFP further improved classification accuracy (AUC up to 98.5%). Notably, ccfDNA methylation patterns displayed clear dose-response relationships across the disease spectrum, supporting their utility for early-stage detection and risk stratification. Our findings highlight the promise of ccfDNA methylation biomarkers as a non-invasive, blood-based screening tool for improving early identification of HCC cases among PLWH.

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