Victor Velculescu, Co-Director of Cancer Genetics and Epigenetics at the Sidney Kimmel Comprehesive Cancer Center, shared on LinkedIn:
“Can an AI-enabled, cfDNA fragmentome – based blood test provide a high – performing, accessible approach to detecting liver cancer across diverse populations and disease etiologies?
Our latest study in Cell Press Blue shows it can.
Across 377 individuals from geographically distinct cohorts in Guatemala and Romania, we found that a previously developed, locked cfDNA fragmentome classifier detected hepatocellular carcinoma across stages and etiologies and outperformed AFP. Combining fragmentomics with AFP and clinical risk factors further improved detection, including for early – stage disease.
Using our new tissue – of – origin approach, MethID, we also found that circulating DNA signals reflect not only tumor and liver cells, but also vascular and immune responses to cancer.
These findings highlight the potential of the cfDNA fragmentome for both early cancer detection and understanding disease biology.
Congratulations to Hope Orjuela, Carter Norton, Shashikant Koul, John Groopman, Zachariah Foda, and our many collaborators at Johns Hopkins Medicine, National Cancer Institute (NCI), DELFI Diagnostics, and in Guatemala and Romania who made this work possible.”
Title: Detection and characterization of hepatocellular carcinoma using cfDNA fragmentomes
Authors: Hope Orjuela, Carter Norton, Shashikant Koul, Daniel C. Bruhm, Akshaya V. Annapragada, Jason Zavras, Sarah Short, Keerti Boyapati, Adrianna Bartolomucci, Vilmos Adleff, Nicholas A. Vulpescu, Kaui Patricio Lebarbenchon, Jacob Carey, Carter Portwood, Andrei Sorop, Razvan Iacob, Speranta Iacob, Liana Gheorghe, Simona Dima, Manuel Ramírez-Zea, Katherine A. McGlynn, Jillian Phallen, Robert B. Scharpf, John Groopman, Victor E. Velculescu, Zachariah H. Foda
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