plasmaCHORD: A Machine Learning Approach to Distinguish Clonal Hematopoiesis-Derived Variants in Liquid Biopsies from Patients with Solid Tumors.

doi:10.1158/1078-0432.CCR-25-0976

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plasmaCHORD: A Machine Learning Approach to Distinguish Clonal Hematopoiesis-Derived Variants in Liquid Biopsies from Patients with Solid Tumors.

Clinical cancer research : an official journal of the American Association for Cancer Research - 1 May 2026

Canzoniero Jenna V, Rabizadeh Daniel, Ziakas Ilias, Wehr Jaime, Balan Archana, Jamali Amna, Landon Blair V, Sivapalan Lavanya, Scott Susan, Pereira Gavin, Lam Vincent K, Hann Christine L, Lovly Christine M, Tao Jessica, Forde Patrick M, Murray Joseph C, Sausen Mark, Meijer Gerrit A, Vink Geraldine R, Fijneman Remond J A, Velculescu Victor E, Phallen Jillian, Scharpf Robert B, Anagnostou Valsamo

Abstract excerpt

PURPOSE: Targeted next-generation sequencing (NGS) of cell-free DNA (cfDNA) enables comprehensive molecular profiling and can guide the selection of genotype-targeted therapies. However, the detection of variants derived from clonal hematopoiesis (CH) is a significant confounder in liquid biopsies. EXPERIMENTAL DESIGN: Using a training cohort of 426 variants identified in cfDNA NGS from 225 patients with stage I...

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Identifiers

PMID: 42001480
DOI: 10.1158/1078-0432.CCR-25-0976
PMCID: PMC13133610

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