Abstract 4074: Non-invasive early detection of cancer-predisposing liver diseases using genome-wide cfDNA fragmentomes

Abstract INTRODUCTION: Liver disease occurs on a continuum from steatosis to fibrosis, cirrhosis and ultimately hepatocellular carcinoma (HCC), with a 30% lifetime risk of HCC among those with cirrhosis (LCr). If identified early, steatosis and fibrosis are potentially reversible, and in LCr, surveillance can reduce cancer morbidity and mortality. Despite these benefits, conventional LCr detection modalities are invasive or have limited performance. We previously demonstrated that cost-effective liquid biopsies of genome-wide cell-free DNA (cfDNA) fragmentomes enable early detection of HCC. Here, we use these technologies to detect liver steatosis, fibrosis, and cirrhosis towards improved pre-cancer intervention and HCC surveillance. METHODS: We performed low-coverage, whole genome sequencing of plasma cfDNA from separate Discovery (n=423) and Validation (n=221) cohorts including individuals with no known liver disease (n=397), chronic liver disease and early fibrosis (n=91) including viral hepatitis and metabolic associated steatotic liver disease, or advanced fibrosis/cirrhosis (n=156). We computed genome-wide fragment length, coverage, and repeat element features (DELFI and ARTEMIS), cross-validated a machine learning classifier for fibrosis and LCr detection in the Discovery Cohort and evaluated the locked model in the Validation Cohort. We then performed whole methylome sequencing (n=28) and cell-type deconvolution to reveal mechanisms of change to cfDNA fragmentomes in LCr. RESULTS: Individuals with early liver disease/fibrosis and advanced fibrosis/cirrhosis were detected with high performance (AUC=0.90, 95% CI=0.86-0.95 and AUC=0.95, 95% CI=0.93-0.98, respectively) in the Discovery Cohort. At an 80% specificity locked cutpoint, Validation Cohort sensitivity was 70.8% (90% CI=52.3%-87.5%) for early liver disease/fibrosis and 90.1% (90% CI=84.4%-94.4%) for advanced fibrosis/cirrhosis. The model displayed low cross-reactivity for other fibrotic origin conditions including benign lung nodules or chronic pancreatitis (median scores 0.087 and 0.068 respectively vs. 0.55 for LCr, p<0.0002). The approach outperformed the existing fibrosis index FIB-4, detecting 5.07x (95% CI=3.03-17.35) and 1.2x (95% CI=1.18-1.32) more cases of early liver disease/fibrosis and advanced fibrosis/cirrhosis in simulations. cfDNA methylome deconvolution revealed increased contributions of liver endothelium (p=0.00016) and blood monocytes (p=5.2x10-5) and decreased contribution of hepatocytes (p=0.00035) with shorter fragment lengths in LCr. CONCLUSIONS: A cfDNA fragmentome biomarker enabled early detection of liver disease including LCr and reflected both liver-derived and immune-cell related changes. These analyses may enable accessible early detection of pre-cancer conditions with potential to improve liver disease management and early detection of HCC. Citation Format: Akshaya Vijaya Annapragada, Zachariah Foda, Hope Orjuela, Carter Norton, Shashi Koul, Noushin Niknafs, Sarah Short, Keerti Boyapati, Adrianna Bartolomucci, Dimitrios Mathios, Michael Noe, Chris Cherry, Jacob Carey, Alessandro Leal, Bryan Chesnick, Nic Dracopoli, Jamie Medina, Nicholas Vulpescu, Daniel Bruhm, Sarah Bacus, Vilmos Adleff, Amy Kim, Steve Baylin, Greg Kirk, Andrei Sorop, Razvan Iacob, Speranta Iacob, Liana Gheorghe, Simona Dima, Katherine McGlynn, Manuel Ramirez-Zea, Claus Feltoft, Julia Johansen, John Groopman, Jillian Phallen, Rob Scharpf, Victor Velculescu. Non-invasive early detection of cancer-predisposing liver diseases using genome-wide cfDNA fragmentomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4074.

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Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-4074
Primary Topic
Cancer Genomics and Diagnostics
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article

Abstract 4074: Non-invasive early detection of cancer-predisposing liver diseases using genome-wide cfDNA fragmentomes

Andrei Sorop, Adrianna L. Bartolomucci, Nicholas A. Vulpescu, Zachariah H. Foda et al.
Cancer Research
Cancer Genomics and Diagnostics
article

Abstract 4074: Non-invasive early detection of cancer-predisposing liver diseases using genome-wide cfDNA fragmentomes

Andrei Sorop, Adrianna L. Bartolomucci, Nicholas A. Vulpescu, Zachariah H. Foda, Shashi Koul, Simona Dima, Jamie E. Medina, Sarah Bacus, Răzvan Iacob, Greg Kirk, Dimitrios Mathios, Rob Scharpf, Amy K. Kim, Carter Norton, Julia S. Johansen, Bryan Chesnick, Daniel C. Bruhm, Alessandro Leal, Jacob Carey, Vilmos Adleff, Jillian Phallen, John D. Groopman, Keerti Boyapati, Noushin Niknafs, Claus Larsen Feltoft, Hope Orjuela, Sarah Short, Steve Baylin, L S Gheorghe, Chris Cherry, Katherine A. McGlynn, Victor E. Velculescu, Manuel Ramirez-Zea, Nic Dracopoli, Michael Noe, Speranta Iacob, Akshaya Vijaya Annapragada
article en

Abstract

Abstract INTRODUCTION: Liver disease occurs on a continuum from steatosis to fibrosis, cirrhosis and ultimately hepatocellular carcinoma (HCC), with a 30% lifetime risk of HCC among those with cirrhosis (LCr). If identified early, steatosis and fibrosis are potentially reversible, and in LCr, surveillance can reduce cancer morbidity and mortality. Despite these benefits, conventional LCr detection modalities are invasive or have limited performance. We previously demonstrated that cost-effective liquid biopsies of genome-wide cell-free DNA (cfDNA) fragmentomes enable early detection of HCC. Here, we use these technologies to detect liver steatosis, fibrosis, and cirrhosis towards improved pre-cancer intervention and HCC surveillance. METHODS: We performed low-coverage, whole genome sequencing of plasma cfDNA from separate Discovery (n=423) and Validation (n=221) cohorts including individuals with no known liver disease (n=397), chronic liver disease and early fibrosis (n=91) including viral hepatitis and metabolic associated steatotic liver disease, or advanced fibrosis/cirrhosis (n=156). We computed genome-wide fragment length, coverage, and repeat element features (DELFI and ARTEMIS), cross-validated a machine learning classifier for fibrosis and LCr detection in the Discovery Cohort and evaluated the locked model in the Validation Cohort. We then performed whole methylome sequencing (n=28) and cell-type deconvolution to reveal mechanisms of change to cfDNA fragmentomes in LCr. RESULTS: Individuals with early liver disease/fibrosis and advanced fibrosis/cirrhosis were detected with high performance (AUC=0.90, 95% CI=0.86-0.95 and AUC=0.95, 95% CI=0.93-0.98, respectively) in the Discovery Cohort. At an 80% specificity locked cutpoint, Validation Cohort sensitivity was 70.8% (90% CI=52.3%-87.5%) for early liver disease/fibrosis and 90.1% (90% CI=84.4%-94.4%) for advanced fibrosis/cirrhosis. The model displayed low cross-reactivity for other fibrotic origin conditions including benign lung nodules or chronic pancreatitis (median scores 0.087 and 0.068 respectively vs. 0.55 for LCr, p<0.0002). The approach outperformed the existing fibrosis index FIB-4, detecting 5.07x (95% CI=3.03-17.35) and 1.2x (95% CI=1.18-1.32) more cases of early liver disease/fibrosis and advanced fibrosis/cirrhosis in simulations. cfDNA methylome deconvolution revealed increased contributions of liver endothelium (p=0.00016) and blood monocytes (p=5.2x10-5) and decreased contribution of hepatocytes (p=0.00035) with shorter fragment lengths in LCr. CONCLUSIONS: A cfDNA fragmentome biomarker enabled early detection of liver disease including LCr and reflected both liver-derived and immune-cell related changes. These analyses may enable accessible early detection of pre-cancer conditions with potential to improve liver disease management and early detection of HCC. Citation Format: Akshaya Vijaya Annapragada, Zachariah Foda, Hope Orjuela, Carter Norton, Shashi Koul, Noushin Niknafs, Sarah Short, Keerti Boyapati, Adrianna Bartolomucci, Dimitrios Mathios, Michael Noe, Chris Cherry, Jacob Carey, Alessandro Leal, Bryan Chesnick, Nic Dracopoli, Jamie Medina, Nicholas Vulpescu, Daniel Bruhm, Sarah Bacus, Vilmos Adleff, Amy Kim, Steve Baylin, Greg Kirk, Andrei Sorop, Razvan Iacob, Speranta Iacob, Liana Gheorghe, Simona Dima, Katherine McGlynn, Manuel Ramirez-Zea, Claus Feltoft, Julia Johansen, John Groopman, Jillian Phallen, Rob Scharpf, Victor Velculescu. Non-invasive early detection of cancer-predisposing liver diseases using genome-wide cfDNA fragmentomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4074.

Cancer ResearchVol. 86(7_Supplement)
Johns Hopkins University (US), Washington University in St. Louis (US), CCC Diagnostics (United States) (US), Institute of Nutrition of Central America and Panama (GT), National Cancer Institute (US), Centre de Géomatique du Québec (CA), ScienceScope (United Kingdom) (GB), Institutul Clinic Fundeni (RO), University of Baltimore (US)
Good health and well-being
Openalex Percentile: Top 32%
Cancer Genomics and Diagnostics
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