What is it about?
Stage-specific epigenetic biomarkers have not been previously reported a lot in the literature. Using methylation omics data for colorectal cancer, we have identified novel cancer stage-specific significant differentially methylated biomarkers based on the consensus of a mix of workflows. The work further advances a compact early-stage prognostic panel of epigenetic biomarkers. In brief, a comprehensive computational framework for stage-differentiated epigenomic analysis of colorectal cancer progression is developed, leading to the identification of (i) several novel stage-salient diagnostic biomarkers, (ii) early-stage prognostic panel, and; (iii) a totally novel hyper-methylation driven CIMP-like signature, all of which need experimental corroboration.
Photo by National Cancer Institute on Unsplash
Why is it important?
This publication is important because: (i) Many algorithms exist in the literature for analyzing methylomics data, each with different pros and cons. By synthesizing the consensus among the approaches, we underscore one strategy to arrive at meaningful results. (ii) Differential methylation is one of a handful of processes that drive cancer initiation and progression, and detailed understanding of hyper- and hypo-methylation events in cancer is essential for effective treatment and management. Using a data-driven hypothesis-agnostic approach might sidestep human biases and lead to statistically sound hypotheses for clinical corroboration. (iii) Early-stage biomarkers enable the detection of cancer when it is effectively curable, with high patient response and compliance. Study designs such as ours are aimed at this time-window for cancer treatment.
Read the Original
This page is a summary of: Stage-differentiated ensemble modeling of DNA methylation landscapes uncovers salient biomarkers and prognostic signatures in colorectal cancer progression, PLoS ONE, February 2022, PLOS, DOI: 10.1371/journal.pone.0249151.
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