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

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Authors: Akshaya Vijaya Annapragada, Zachariah H. Foda, Hope Orjuela, Carter Norton, Shashi Koul, Noushin Niknafs, Sarah B. Short, Keerti Boyapati, Adrianna L. Bartolomucci, Dimitrios Mathios, Michaël Noë, Chris Cherry
+25 more Jacob L Carey, Alessandro Leal, Bryan Chesnick, Nic Dracopoli, Jamie E. Medina, Nicholas A. Vulpescu, Daniel C. Bruhm, Sarah S. Bacus, Vilmos Adleff, Amy K. Kim, S B Baylin, Greg D. Kirk, Andrei Sorop, Razvan Andrei Iacob, Speranta Iacob, L S Gheorghe, Simona Dima, Katherine A. McGlynn, Manuel Ramirez-Zea, Claus Larsen Feltoft, Julia Sidenius Johansen, John D. Groopman, Jillian A. Phallen, Rob Scharpf, Victor E. Velculescu
Cited by: 1

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

Fields of Study & Subjects

Cancer Genomics and Diagnostics Cancer-related molecular mechanisms research Single-cell and spatial transcriptomics

Publication details

Journal / source
Cancer Research
Publisher
American Association for Cancer Research (AACR)
Volume
86
Issue
7_Supplement
Pages
4074–4074
Publication date
3 April 2026
Language
EN