Abstract 6426: Cell-free DNA fragmentomes enable early identification of liver cirrhosis to facilitate cancer surveillance
Authors: Akshaya V. Annapragada, Zachariah H. Foda, Noushin Niknafs, Sarah Short, Dimitrios Mathios, Shashikant Koul, Keerti Boyapati, Adrianna Bartolomucci, Jamie E. Medina, Nicholas A. Vulpescu, Chris Cherry, Daniel C. Bruhm, Vilmos Adleff, Amy Kim, Andrei Sorop, Razvan Iacob, Speranta Iacob, Liana Gheorghe, Simona Dima, Katherine A. McGlynn, Manuel Ramirez-Zea, John Groopman, Jillian Phallen, Robert B. Scharpf, Victor E. Velculescu
Journal: Cancer Research (2025)

Introduction: 80% of adults in the US have metabolic risk factors for Liver Cirrhosis (LCr), but LCr diagnosis is challenging. Elastography and blood-based fibrosis indices have limited performance, and biopsies are invasive. The lifetime risk of hepatocellular carcinoma (HCC) in individuals with LCr is ∼30%, yet &amp;lt;20% of individuals undergo any HCC surveillance. We previously demonstrated that genome-wide cell-free DNA (cfDNA) fragmentomes can detect HCC in the blood. Here, we expand these approaches to pre-neoplasia, for LCr detection to facilitate management and HCC surveillance. Methods: We evaluated cfDNA fragmentomes in separate Discovery (n=465) and External Validation (n=279) Cohorts. These cohorts comprised individuals with LCr (n=132), at high-risk for LCr with viral hepatitis (n=26), metabolic associated steatotic liver disease (MASLD) and/or non-cirrhotic fibrosis (n=44), or aflatoxin exposure (n=10), or from healthy screening populations (n=532, including 126 with metabolic risk factors). For all individuals, we extracted cfDNA from plasma, performed low coverage (1-2x) whole genome sequencing, and computed genome-wide fragment length, coverage and repeat element features (DELFI and ARTEMIS). We cross-validated a machine learning model with these features for detection of LCr in the Discovery Cohort and evaluated the locked model in the Validation Cohort. Results: In the Discovery Cohort, individuals with LCr were detected with high performance (AUC=0.97, 95% CI 0.94-1.0 and AUC=0.95, 95% CI=0.92-0.98, for individuals with and without metabolic risk factors). Scores were higher in LCr than in healthy populations and increased with cirrhosis severity (p&amp;lt;3.2x10-6 for Child-Pugh A, B and C). In the Validation Cohort, the locked model achieved 78% sensitivity and 92% specificity when locked at a threshold of 90% specificity and 90% sensitivity in the Discovery Cohort (AUC=0.95, 95% CI=0.91-0.99, and AUC=0.93, 95% CI=0.89-0.97, for individuals with and without metabolic risk factors), outperforming common fibrosis indices APRI and FIB-4. Among high-risk individuals without LCr but with aflatoxin exposure, MASLD, or fibrosis, scores were higher than in healthy individuals (p&amp;lt;6.0x10-16), but remained lower than for individuals with LCr (p&amp;lt;2.2x10-16). Fragmentomic analyses of transcription factor binding sites and single nucleotide variants revealed molecular alterations linked to both liver-tissue derived and inflammatory changes of cirrhosis. Conclusions: cfDNA fragmentomes enable detection of LCr, a pre-cancer condition that increases HCC risk. HCC surveillance in high-risk populations is critical, but accessibility and adherence remain low. A facile, effective screening approach for LCr may enable early identification towards improved management and initiation of HCC surveillance. Citation Format: Akshaya V. Annapragada, Zachariah H. Foda, Noushin Niknafs, Sarah Short, Dimitrios Mathios, Shashikant Koul, Keerti Boyapati, Adrianna Bartolomucci, Jamie E. Medina, Nicholas A. Vulpescu, Chris Cherry, Daniel C. Bruhm, Vilmos Adleff, Amy Kim, Andrei Sorop, Razvan Iacob, Speranta Iacob, Liana Gheorghe, Simona Dima, Katherine A. McGlynn, Manuel Ramirez-Zea, John Groopman, Jillian Phallen, Robert B. Scharpf, Victor E. Velculescu. Cell-free DNA fragmentomes enable early identification of liver cirrhosis to facilitate cancer surveillance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6426.