TY - JOUR
T1 - Prediagnostic Plasma Metabolites Are Associated with Incident Hepatocellular Carcinoma
T2 - A Prospective Analysis
AU - Wilechansky, Robert M.
AU - Challa, Prasanna K.
AU - Han, Xijing
AU - Hua, Xinwei
AU - Manning, Alisa K.
AU - Corey, Kathleen E.
AU - Chung, Raymond T.
AU - Zheng, Wei
AU - Chan, Andrew T.
AU - Simon, Tracey G.
N1 - Publisher Copyright:
©2025 American Association for Cancer Research.
PY - 2025/4/1
Y1 - 2025/4/1
N2 - Despite increasing incidence of hepatocellular carcinoma (HCC) in vulnerable populations, accurate early detection tools are lacking. We aimed to investigate the associations between prediagnostic plasma metabolites and incident HCC in a diverse population. In a prospective, nested case–control study within the Southern Community Cohort Study, we conducted prediagnostic LC/MS metabolomic profiling in 150 incident HCC cases (median time to diagnosis, 7.9 years) and 100 controls with cirrhosis. Logistic regression assessed metabolite associations with HCC risk. Metabolite set enrichment analysis identified enriched pathways, and a random forest classifier was used for risk classification models. Candidate metabolites were validated in the UK Biobank (N = 12 incident HCC cases and 24 cirrhosis controls). In logistic regression analysis, seven metabolites were associated with incident HCC (Meff P < 0.0004), including N-acetylmethionine (OR = 0.46; 95% confidence interval, 0.31–0.66). Multiple pathways were enriched in HCC, including histidine and CoA metabolism (FDR P < 0.001). The random forest classifier identified 10 metabolites for inclusion in HCC risk classification models, which improved HCC risk classification compared with clinical covariates alone (AUC = 0.66 for covariates vs. 0.88 for 10 metabolites plus covariates; P < 0.0001). Findings were consistent in the UK Biobank (AUC = 0.72 for covariates vs. 0.88 for four analogous metabolites plus covariates; P = 0.04), assessed via nuclear magnetic resonance spectroscopy. Prediagnostic metabolites, primarily amino acid and sphingolipid derivatives, are associated with HCC risk and improve HCC risk classification beyond clinical covariates. These metabolite profiles, detectable years before diagnosis, could serve as early biomarkers for HCC detection and risk stratification if validated in larger studies.
AB - Despite increasing incidence of hepatocellular carcinoma (HCC) in vulnerable populations, accurate early detection tools are lacking. We aimed to investigate the associations between prediagnostic plasma metabolites and incident HCC in a diverse population. In a prospective, nested case–control study within the Southern Community Cohort Study, we conducted prediagnostic LC/MS metabolomic profiling in 150 incident HCC cases (median time to diagnosis, 7.9 years) and 100 controls with cirrhosis. Logistic regression assessed metabolite associations with HCC risk. Metabolite set enrichment analysis identified enriched pathways, and a random forest classifier was used for risk classification models. Candidate metabolites were validated in the UK Biobank (N = 12 incident HCC cases and 24 cirrhosis controls). In logistic regression analysis, seven metabolites were associated with incident HCC (Meff P < 0.0004), including N-acetylmethionine (OR = 0.46; 95% confidence interval, 0.31–0.66). Multiple pathways were enriched in HCC, including histidine and CoA metabolism (FDR P < 0.001). The random forest classifier identified 10 metabolites for inclusion in HCC risk classification models, which improved HCC risk classification compared with clinical covariates alone (AUC = 0.66 for covariates vs. 0.88 for 10 metabolites plus covariates; P < 0.0001). Findings were consistent in the UK Biobank (AUC = 0.72 for covariates vs. 0.88 for four analogous metabolites plus covariates; P = 0.04), assessed via nuclear magnetic resonance spectroscopy. Prediagnostic metabolites, primarily amino acid and sphingolipid derivatives, are associated with HCC risk and improve HCC risk classification beyond clinical covariates. These metabolite profiles, detectable years before diagnosis, could serve as early biomarkers for HCC detection and risk stratification if validated in larger studies.
UR - https://www.scopus.com/pages/publications/105002581534
U2 - 10.1158/1940-6207.CAPR-24-0440
DO - 10.1158/1940-6207.CAPR-24-0440
M3 - Article
C2 - 39916630
AN - SCOPUS:105002581534
SN - 1940-6207
VL - 18
SP - 179
EP - 188
JO - Cancer Prevention Research
JF - Cancer Prevention Research
IS - 4
ER -