Methylation of CpG Sites as Biomarkers Predictive of Drug-Specific Patient Survival in Cancer

• Type of Material: Article
• Authors: Bridget Neary, Georgia Institute of Technology; Shuting Lin, Georgia Institute of Technology; Peng Qiu, Emory University
• Language: English
• Date: 2022-01-01
• Publisher: SAGE Publications Ltd
• Publication Version: Final Published Version
• Copyright Statement: © The Author(s) 2022
• License: Creative Commons Attribution-NonCommercial 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1177/11769351221131124
• Title of Journal or Parent Work: Cancer Informatics
• Volume: 21
• Start Page: 11769351221131124
• End Page: 11769351221131124
• Grant/Funding Information: This work was supported by funding from the National Science Foundation (CCF2007029).; PQ is an ISAC Marylou Ingram Scholar and a Wallace H. Coulter Distinguished Faculty Fellow. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.; The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article:
• Keywords: methylation-drug interactions; TCGA; drug response biomarkers; precision oncology; survival analysis; pharmacoepigenomics; DNA methylation; drug response prediction; pharmacoepigenetics; epigenomics
• Research Categories: Engineering, Biomedical

Abstract

Background: Though the development of targeted cancer drugs continues to accelerate, doctors still lack reliable methods for predicting patient response to standard-of-care therapies for most cancers. DNA methylation has been implicated in tumor drug response and is a promising source of predictive biomarkers of drug efficacy, yet the relationship between drug efficacy and DNA methylation remains largely unexplored. Method: In this analysis, we performed log-rank survival analyses on patients grouped by cancer and drug exposure to find CpG sites where binary methylation status is associated with differential survival in patients treated with a specific drug but not in patients with the same cancer who were not exposed to that drug. We also clustered these drug-specific CpG sites based on co-methylation among patients to identify broader methylation patterns that may be related to drug efficacy, which we investigated for transcription factor binding site enrichment using gene set enrichment analysis. Results: We identified CpG sites that were drug-specific predictors of survival in 38 cancer-drug patient groups across 15 cancers and 20 drugs. These included 11 CpG sites with similar drug-specific survival effects in multiple cancers. We also identified 76 clusters of CpG sites with stronger associations with patient drug response, many of which contained CpG sites in gene promoters containing transcription factor binding sites. Conclusion: These findings are promising biomarkers of drug response for a variety of drugs and contribute to our understanding of drug-methylation interactions in cancer. Investigation and validation of these results could lead to the development of targeted co-therapies aimed at manipulating methylation in order to improve efficacy of commonly used therapies and could improve patient survival and quality of life by furthering the effort toward drug response prediction.