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. 2023 Jul 27;15:119. doi: 10.1186/s13148-023-01518-5

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 1 — Workflow of the study. A multistep analysis to identify cfDNA methylation-based biomarkers for CRC detection in polyp patients. First, starting with genome-wide methylation analysis in primary tissues to discover differentially methylated CpGs and then validated their performance in a larger tissue cohort. Random forest and LASSO models were applied to the training set of tissue validation cohort in order to refine methylation markers. The methylation levels of three hypermethylated markers were measured in the cfDNA validation cohort