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DNA Methylation Profiling at Base-Pair Resolution Reveals Unique Epigenetic Features of Early-Onset Colorectal Cancer in Underrepresented Populations

ABSTRACT: Background. The incidence of early-onset colorectal cancer (EOCRC) has been rising at an alarming rate in the United States, and EOCRC disproportionately affects racial/ethnic minorities. Here, we construct comprehensive profiles of EOCRC DNA methylomes at base-pair resolution for a cohort of Hispanic and African American patients. Results. We show the epigenetic landscape of these EOCRC patients differs from that of late-onset colorectal cancer (LOCRC) patients, and methylation canyons in EOCRC tumor tissue preferentially overlapped genes in cancer-related pathways. Furthermore, we identify epigenetic alterations in metabolic genes that are specific to our racial/ethnic minority EOCRC cohort but not Caucasian patients from TCGA. Top genes differentially methylated between these cohorts included the obesity-protective MFAP2 gene as well as cancer risk susceptibility genes APOL3 and RNASEL. Conclusions. In this study, we provide to the scientific community high-resolution DNA methylomes for a cohort of EOCRC patients from underrepresented populations. Our exploratory findings in this cohort highlight epigenetic mechanisms underlying the pathogenesis of EOCRC and nominate novel biomarkers for EOCRC in underrepresented populations.

ORGANISM(S): Homo sapiens

PROVIDER: GSE284325 | GEO | 2025/01/29

REPOSITORIES: GEO

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Project description:Background: The incidence of colorectal cancer (CRC) has been steadily increasing in younger individuals over the past several decades for reasons that are incompletely defined. Identifying differences in gene expression profiles, or transcriptomes, in early-onset colorectal cancer (EOCRC, < 50 years old) patients versus later-onset colorectal cancer (LOCRC, > 50 years old) patients is one approach to understanding molecular and genetic features that distinguish EOCRC. Methods: We performed RNA-sequencing (RNA-seq) to characterize the transcriptomes of patient-matched tumors and adjacent, uninvolved (normal) colonic segments from EOCRC (n=21) and LOCRC (n=22) patients. The EOCRC and LOCRC cohorts were matched for demographic and clinical characteristics. We used The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) database for validation. We used a series of computational and bioinformatic tools to identify EOCRC-specific differentially expressed genes, molecular pathways, predicted cell populations, differential gene splicing events, and predicted neoantigens. Results: We identified an eight-gene signature in EOCRC comprised of ALDOB, FBXL16, IL1RN, MSLN, RAC3, SLC38A11, WBSCR27 and WNT11, from which we developed a score predictive of overall CRC patient survival. On the entire set of genes identified in normal tissues and tumors, cell type deconvolution analysis predicted a differential abundance of immune and non-immune populations in EOCRC versus LOCRC. Gene set enrichment analysis identified increased expression of splicing machinery in EOCRC. We further found differences in alternative splicing (AS) events, including one within the long non-coding RNA, HOTAIRM1. Additional analysis of AS found seven events specific to EOCRC that encode potential neoantigens. Conclusion: Our transcriptome analyses identified genetic and molecular features specific to EOCRC which may inform future screening, development of prognostic indicators, and novel drug targets.