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5-methylcytosine and 5-hydroxymethylcytosine are synergistic biomarkers for early detection of colorectal cancer

ABSTRACT: Background Early cancer detection has the potential to significantly improve treatment outcomes and survival rates. This study investigates the roles of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) as biomarkers for early-stage colorectal cancer (CRC) detection in cell-free DNA (cfDNA). Methods We analyzed cfDNA from 37 treatment-naive CRC patients and 32 healthy controls using duet evoC 6-base whole genome sequencing (A, C, T, G, 5mC, 5hmC). We then built CRC classifiers using differentially methylated regions identified in stage IV CRC tissue samples. We compared the performance of models using 5mC-only, 5hmC-only, modified cytosine, or 5mC and 5hmC features. Results Here we show that models combining measurements of 5mC and 5hmC significantly enhance diagnostic accuracy (AUC = 0.95) compared to traditional approaches that conflate these markers (modified C, AUC = 0.66). Notably, of all the DMRs considered, almost half show an increase in 5hmC at stage I and a corresponding decrease in 5mC at stage IV, suggesting that 5hmC can effectively track regions undergoing demethylation during tumor development. Conclusions These results support the hypothesis that distinguishing between 5mC and 5hmC improves the sensitivity of liquid biopsy tests for early-stage cancer detection.

ORGANISM(S): Homo sapiens

PROVIDER: GSE311517 | GEO | 2025/12/02

REPOSITORIES: GEO

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Project description:Background: Gastric cancer (GC) remains the third leading cause of cancer death worldwide due to the absence of sensitive and specific biomarkers for its early detection. 5-hydroxymethylcytosine (5hmC)-enriched gene profiles and regions show tissue-specific and tumor specific, and cell-free DNA (cfDNA) 5hmC modification feature sequencing provides a robust tool for gastric cancer detection.Methods: A matched case‒control study design with 50 gastric cancer patients and 50 controls was performed to sequence the 5hmC modification of cfDNA. Significantly differential 5hmC modification genes were identified to construct a gastric cancer diagnostic model. The data set from Gene Expression Omnibus consisted of 61 gastric cancer patients, 90 healthy individuals and 22 benign gastric disease controls was used as an external testing set to test the robustness of the diagnostic model. Results: The vast majority of 5hmC peaks were distributed in the gene body, accounting for more than 90% of the total 5hmC peaks in both the GC and control groups. The diagnostic model was developed based on five different 5hmC modification genes, FBXL7, PDE3A, TPO, SNTG2 and SXBP5. The model could clearly distinguish gastric cancer patients from controls in the training (AUC=0.95, sensitivity=88.6%, specificity=94.3%), validation (AUC=0.87, sensitivity=73.3%, specificity=93.3%) and testing (AUC=0.90, sensitivity=81.9%, specificity=90.2%) sets. The predicted risk scores of the controls were significantly lower than those of GC patients in our own data (P<0.001) or GEO external testing data (P<0.001), but no significant difference was observed between different TNM stage groups (P=0.09 and 0.66). Furthermore, the risk scores of healthy and benign gastric disease controls in the testing set were also not different (P=0.10). Conclusions: The characteristics of 5hmC in cfDNA are specific to GC patients, and the diagnostic model constructed by the 5hmC features of five genes could effectively identify GC patients.

Project description:Purpose: Using the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial samples, we identified cell-free DNA (cfDNA) biomarker candidate genes bearing the epigenetic mark 5-hydroxymethylcytosine (5hmC) that detect occult colorectal cancer (CRC) up to 36 mo prior to clinical diagnosis. Methods: PLCO study subjects were matched by age, race, and sex as cases (n = 201, diagnosed with CRC within 36 mo of blood collection) and controls (n = 402, no cancer diagnosis on follow-up, average 16.3 years after entering the study). Archived plasma samples (300 µL per study subject) were obtained from the National Cancer Institute (NCI), and we employed the sensitive 5hmC-Seal chemical labeling approach on 3 - 8 ng of extracted cfDNA. Following next-generation sequencing (NGS) and genome-wide mapping of 5hmC, we then conducted association studies and machine-learning modeling to analyze the genome-wide 5hmC profiles within training and validation groups that were randomly selected at a 2:1 ratio. Results: Robust genome-wide 5hmC profiles were successfully obtained from these decades-old samples. Association analyses using the Cox proportional hazards models suggested several epigenetic pathways relevant to CRC development distinguishing cases from controls. A weighted Cox model, comprised of 32-associated gene bodies, showed predictive detection value for CRC as early as 24-36 mo prior to overt tumor diagnosis. Furthermore, a trend for increased predictive power was observed for blood samples collected closer to CRC diagnosis. Notably, the 5hmC-based predictive model showed comparable performance regardless of sex and self-reported race/ethnicity, and significantly outperformed risk factors such as age and obesity assessed as BMI (body mass index). Conclusion: An assay and machine learning modeling of 5hmC epigenetic signals on cfDNA revealed candidate biomarkers and a scoring algorithm with the potential to predict CRC occurrence despite the absence of clinical symptoms or the availability of effective predictors. Developing a minimally-invasive clinical assay that detects 5hmC-modified biomarkers holds promise for improving early CRC detection and ultimately patient outcomes. Future investigations to expand this strategy to prospectively collected samples are warranted.

Project description:Background & Aims. Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is growing in incidence but treatment options remain limited, particularly for late stage disease. As liver cirrhosis is the principal risk state for HCC development, markers to detect early HCC within this patient population are urgently needed. Perturbation of epigenetic marks, such as DNA methylation (5mC), is a hallmark of human cancers, including HCC. Identification of regions with consistently altered 5mC levels in circulating cell free DNA (cfDNA) during progression from cirrhosis to HCC could therefore serve as markers for development of minimally-invasive screens of early HCC diagnosis and surveillance. Methods. To discover DNA methylation derived biomarkers of HCC in the background of liver cirrhosis, we profiled genome-wide 5mC landscapes in patient cfDNA using the Infinium HumanMethylation450k BeadChip Array. We further linked these findings to primary tissue data available from TCGA and other public sources. Using biological and statistical frameworks, we selected CpGs that robustly differentiated cirrhosis from HCC in primary tissue and cfDNA followed by validation in an additional independent cohort. Results. We identified CpGs that segregate patients with cirrhosis, from patients with HCC within a cirrhotic liver background, through genome-wide analysis of cfDNA 5mC landscapes. Lasso regression analysis pinpointed a panel of probes in our discovery cohort that were validated in two independent datasets. A panel of five CpGs (cg04645914, cg06215569, cg23663760, cg13781744, and cg07610777) yielded AUROCs of 0.9525, 0.9714, and 0.9528 in cfDNA discovery and tissue validation cohorts 1 and 2, respectively. Conclusions. 5mC markers derived from cfDNA robustly identify HCC within a cirrhotic liver background indicating that further validation is warranted. Our finding that 5mC markers derived from primary tissue did not perform well in cfDNA, compared to those identified directly from cfDNA, reveals potential advantages of starting with cfDNA to discover high performing markers for liquid biopsy development.

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5-methylcytosine and 5-hydroxymethylcytosine are synergistic biomarkers for early detection of colorectal cancer

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