5hmC as a novel liquid biopsy biomarker for colorectal cancer to enable detection and unveil tumor biology.

C Christopher Maher (Washington University School of Medicine, St. Louis, MO) N Netra Navadkar (Washington University in St. Louis, St. Louis, MO) C Ceyda Coruh M Muheng Liao (Washington University in St. Louis, St. Louis, MO) D De'Vana Crutcher (Washington University in St. Louis, St. Louis, MO) J Jacqueline Mudd (Washington University School of Medicine, St. Louis, MO) G Gulfem Dilek Guler (ClearNote Health, San Diego, CA) Y Yuhong Ning (ClearNote Health, San Diego, CA) S Shimul Chowdhury (ClearNote Health, San Diego, CA) A Amy Ly E Emily Rozycki (Washington University in St. Louis, St. Louis, MO) N Nicole White (Washington University School of Medicine, St. Louis, MO) S Samuel Levy (ClearNote Health, San Diego, CA) R Ryan Fields (2Washington University in St. Louis, Department of Surgery, Saint Louis, United States)

Abstract

228 Background: 5-hydroxymethylcytosine (5hmC) is a DNA epigenetic modification which regulates gene expression and is associated with active transcription. 5hmC sequencing in cell-free DNA (cfDNA) enables assessment of gene activity through a liquid biopsy. We profiled 5hmC in plasma cfDNA to assess its potential as a liquid biopsy biomarker for colorectal cancer (CRC). Methods: Genome-wide 5hmC modifications were analyzed with a low-input whole-genome 5hmC sequencing method based on selective chemical labeling using cfDNA from: (i) a discovery cohort of 75 CRC patients and 150 non-cancer blood samples and (ii) a validation cohort of 72 CRC patients and 70 non-cancer blood samples. Differential 5hmC analysis between CRC and non-cancer samples was conducted using DESeq2. Low-pass whole genome sequencing (LP-WGS) was performed on all cfDNA samples. Tumor fraction was estimated using ichorCNA to classify samples into high ct-fraction CRC (ct-fraction ≥0.1) and low ct-fraction CRC (ct-fraction <0.1) groups. Nucleosome profiling analysis using LP-WGS was performed to reveal chromatin accessibility patterns. Elastic Net Regression (ENR) was applied to identify differences in 5hmC levels for classifying samples as cancer or non-cancer. Results: Differential cfDNA 5hmC levels of 319 genes distinguished high ct-fraction CRC and non-cancer samples in the discovery and validation cohorts. Gene set enrichment analysis revealed increased 5hmC in genes associated with colon cancer (i.e., WNT and b-catenin signaling). Next, machine learning was used to develop a 5hmC signature in the discovery cohort which was then independently validated to discriminate between CRC and non-cancer samples (AUC 0.957), irrespective of ct-fraction. Nucleosome profiling analysis using LP-WGS revealed increased chromatin accessibility near the binding sites of active transcriptional drivers. Caudal-related homeobox transcription factor 2 ( CDX2 ), a master transcriptional regulator of intestinal cell fate and cancer, had increased chromatin accessibility near binding sites in CRC patients relative to non-cancer samples in the discovery and validation cohorts. Importantly, CDX2 and its downstream targets had increased cfDNA 5hmC levels in CRC relative to non-cancer samples. Conclusions: Genes with differential 5hmC levels in cfDNA can discriminate between CRC and non-cancer samples. 5hmC signatures identified CRC samples independent of copy number gains or losses, which are typically used to estimate ct-fraction. Differential analysis of 5hmC and LP-WGS data reveal gene activation relevant to disease. In the context of CRC, CDX2 displayed increased chromosome accessibility in the promoters of its target genes which in turn displayed increased 5hmC levels. Further studies will focus on optimizing 5hmC-based biomarkers to monitor patient treatment.

Article Details

Volume / Issue Vol. 44, Issue 2_suppl
Published January 10, 2026
Pages 228-228
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (14)

C

Christopher Maher

Washington University School of Medicine, St. Louis, MO

N

Netra Navadkar

Washington University in St. Louis, St. Louis, MO

C

Ceyda Coruh

M

Muheng Liao

Washington University in St. Louis, St. Louis, MO

D

De'Vana Crutcher

Washington University in St. Louis, St. Louis, MO

J

Jacqueline Mudd

Washington University School of Medicine, St. Louis, MO

G

Gulfem Dilek Guler

ClearNote Health, San Diego, CA

Y

Yuhong Ning

ClearNote Health, San Diego, CA

S

Shimul Chowdhury

ClearNote Health, San Diego, CA

A

Amy Ly

E

Emily Rozycki

Washington University in St. Louis, St. Louis, MO

N

Nicole White

Washington University School of Medicine, St. Louis, MO

S

Samuel Levy

ClearNote Health, San Diego, CA

R

Ryan Fields

2Washington University in St. Louis, Department of Surgery, Saint Louis, United States