Joyce, Brian

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.

Abstract Purpose: Hepatocellular Carcinoma (HCC) is the leading cause of cancer-related mortality in Nigeria. HIV and viral hepatitis B (HBV) and C (HCV) co-infection are common in Nigeria that significantly accelerates liver disease progression including HCC. Aging-related DNA methylation signatures obtained in liquid biopsy, such as circulating cell-free DNA (ccfDNA) extracted from serum/plasma are promising minimally-invasive biomarkers that may inform HIV-associated HCC. We examined the epigenetic age acceleration (EpiAgeAccel) in ccfDNA in HCC patients with HIV. Methods: The study included three groups of participants: a) HIV positive with HCC (n=7); b) HIV positive and cancer-free (n=45); and c) HIV negative with HCC (n=33). Epigenetic age was estimated by Horvath's calculator using genome-wide ccfDNA methylation data profiled by Illumina EPIC array. EpiAgeAccel was computed as the residuals of a linear model of epigenetic age on chronological age, namely the unexplained portion of epigenetic age by chronological age. We used multiple linear regression to compare EpiAgeAccel between HIV/HCC groups, adjusting for sex, age, education, alcohol intake, and HBV/HCV infection. Results: Among HIV positive participants, there was a higher percentage of men (57% vs. 22%, p&lt;0.001), HBV infection (29% vs. 11%, p=0.004), and HCV infection (57% vs. 2%, p&lt;0.001) in the HCC group compared to the cancer-free group. EpiAgeAccel was 4.8 years higher in HIV positive patients with HCC compared to cancer-free HIV positives (p=0.02). Among HCC patients, EpiAgeAccel was 2.1 years higher in HIV positives compared to HIV negative but not statistically significant. Conclusion: Epigenetic age in ccfDNA is accelerated in HIV-positive HCC patients. EpiAgeAccel measured in ccfDNA may be developed into a surrogate biomarker for minimally invasive HCC detection among HIV-infected patients in low- and middle-income countries. Citation Format: Yinan Zheng, Claudia Hawkins, Edith Okeke, Mary Duguru, Emuobor Odeghe, Olufunmilayo Lesi, Yishu Qu, Kyeezu Kim, Brian Joyce, Jun Wang, Lewis Roberts, Demirkan Gursel, Abdulkareem Fatimah, Alani Akanmu, Godwin Imade, Jian-Jun Wei, Masha Kocherginsky, Kwang-Youn Kim, Oluwakemi Odukoya, Wasiu Adeyemo, Firas Wehbe, Chad Achenbach, Atiene Sagay, Folasade Ogunsola, Robert Murphy, Lifang Hou. Blood-Based Circulating Cell-Free DNA Epigenetic Age Is Accelerated Among HIV-Infected Patients with Hepatocellular Carcinoma in Nigeria [abstract]. In: Proceedings of the 9th Annual Symposium on Global Cancer Research; Global Cancer Research and Control: Looking Back and Charting a Path Forward; 2021 Mar 10-11. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2021;30(7 Suppl):Abstract nr 83.

Abstract Researchers hypothesized that telomere shortening facilitates carcinogenesis. Previous studies found inconsistent associations between blood leukocyte telomere length (LTL) and cancer. Epigenetic reprogramming of telomere maintenance mechanisms may help explain this inconsistency. We examined associations between DNA methylation in telomere-related genes (TRG) and cancer. We analyzed 475 participants providing 889 samples 1 to 3 times (median follow-up, 10.1 years) from 1999 to 2013 in the Normative Aging Study. All participants were cancer-free at each visit and blood leukocytes profiled using the Illumina 450K array. Of 121 participants who developed cancer, 34 had prostate cancer, 10 melanoma, 34 unknown skin malignancies, and 43 another cancer. We examined 2,651 CpGs from 80 TRGs and applied a combination of Cox and mixed models to identify CpGs prospectively associated with cancer (at FDR &lt; 0.05). We also explored trajectories of DNA methylation, logistic regression stratified by time to diagnosis/censoring, and cross-sectional models of LTL at first blood draw. We identified 30 CpGs on 23 TRGs whose methylation was positively associated with cancer incidence (β = 1.0–6.93) and one protective CpG in MAD1L1 (β = −0.65), of which 87% were located in TRG promoters. Methylation trajectories of 21 CpGs increased in cancer cases relative to controls; at 4 to 8 years prediagnosis/censoring, 17 CpGs were positively associated with cancer. Three CpGs were cross-sectionally associated with LTL. TRG methylation may be a mechanism through which LTL dynamics reflect cancer risk. Future research should confirm these findings and explore potential mechanisms underlying these findings, including telomere maintenance and DNA repair dysfunction. Cancer Prev Res; 11(8); 511–22. ©2018 AACR.