On December 9, 2025 GC Genome, a leading clinical genomics and liquid biopsy company, reported that its study analyzing cell-free DNA (cfDNA) fragmentation patterns in 1,154 healthy individuals has been published in Clinical Chemistry (Impact Factor 6.3, 2025). The findings reveal key physiological factors that can interfere with cancer-associated cfDNA signals, offering a foundation for improving the accuracy of liquid biopsy tests.

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The study, conducted in collaboration with Professor Min-Jung Kwon and her team at Kangbuk Samsung Medical Center, examined correlations between cfDNA fragmentomic profiles and 65 clinical variables, including age and liver function markers. The goal was to identify potential confounders that could influence cfDNA-based cancer detection in individuals without cancer.

Study Overview

Healthy cohort: 1,154 noncancerous individuals who underwent routine health checkups
Clinical variables included: 65 demographic, hematologic, and biochemical parameters
Three fragmentomic features were derived: cfDNA concentration, short-fragment ratio (SFR), and frequency of cancer-enriched motifs(CEMs)
Key Findings

Liver enzymes(including AST, ALP, γ-GTP) and age were identified as major factors altering cfDNA fragmentation patterns.
Elevated AST or age closely resembled cancer-like fragmentomic signatures, blurring the distinction between noncancer and cancer profiles.
AST showed high similarity to fragmentation size patterns seen in lung cancer patients (cosine similarity = 0.98).
Age showed the highest similarity to cancer-like profiles among clinical variables (cosine similarity = 0.52).
Receiver Operating Characteristic (ROC) analysis confirmed that these physiological variables can act as confounders by reducing the specificity of cfDNA-based detection, potentially leading to false-positive results.
These findings demonstrate that non-cancer physiological factors can influence cfDNA signals, underscoring the need for confounder-aware modeling approaches in liquid biopsy development.

A GC Genome spokesperson stated:

"This study is significant because it uses large-scale data from healthy individuals to identify key confounders that influence cfDNA fragmentation patterns. These insights will play an important role in refining our Multi-Cancer Early Detection (MCED) test, ai-CANCERCH, particularly in reducing false-positive rates and improving test specificity."

About ai-CANCERCH

Launched in September 2023, ai-CANCERCH is an AI-based multi-cancer early detection(MCED) test powered by Lc-WGS. Using just 10 mL of blood, the test detects signals associated with multiple cancers. A major upgrade—expanding from 6 detectable cancers to 10 cancers (colorectal, lung, esophageal, liver, ovarian, pancreatic, biliary, breast, gastric, and head-and-neck)—is planned for January 2026.

(Press release, GC Genome, DEC 9, 2025, View Source [SID1234661330])