Work

Noninvasive Detection and Subtyping of Esophageal Cancer by Circulating Cell‐Free mtDNA Fragmentomics: A Multi‐Center Validation Study

Year: 2026

Type: article

Abstract: ABSTRACT Esophageal cancer (EC) is highly lethal due to late diagnosis, and accurate non‐invasive tools for early detection and subtyping remain lacking. Circulating cell‐free mitochondrial DNA (ccf‐mtDNA) fragmentomics offers a promising biomarker source. In this large multi‐center study enrolling 1,260 participants spanning healthy control (HC), benign esophageal diseases (BED), precancerous lesions and EC patients, we developed two machine learning models based on plasma ccf‐mtDNA fragmentomic profiles: an EC detection (ED) model and a pathological subtyping prediction (PSP) model. The ED model achieved an AUC of 0.9706 (EC vs. non‐EC) in the training cohort, with high performance in internal (0.9762), external (0.9748), and Chinese minority (0.9668, Uyghur and Kazakh) validation cohorts. At the optimal cut‐off, it yielded 92.16% sensitivity for stage I EC in the combined validation cohort and correctly identified 93.10% of early EC cases missed by preoperative biopsy. It also discriminated high‐grade intraepithelial neoplasia from non‐EC with an AUC of 0.9597. The PSP model distinguished ESCC from EAC with 89.71% accuracy, improving to 90.74% after integrating key clinical parameters. In summary, ccf‐mtDNA fragmentomics provides a robust, non‐invasive platform for early EC detection, precancerous risk stratification, and histological subtyping, demonstrating strong potential to transform clinical management.

Source: Advanced Science

DOI: 10.1002/advs.78377