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Ohnmacht, A. ; Rajamani, A.* ; Avar, G. ; Kutkaite, G. ; Gonçalves, E.* ; Saur, D.* ; Menden, M.P.

The pharmacoepigenomic landscape of cancer cell lines reveals the epigenetic component of drug sensitivity.

Comm. Biol. 6:825 (2023)

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Open Access Gold as soon as Publ. Version/Full Text is submitted to ZB.

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Aberrant DNA methylation accompanies genetic alterations during oncogenesis and tumour homeostasis and contributes to the transcriptional deregulation of key signalling pathways in cancer. Despite increasing efforts in DNA methylation profiling of cancer patients, there is still a lack of epigenetic biomarkers to predict treatment efficacy. To address this, we analyse 721 cancer cell lines across 22 cancer types treated with 453 anti-cancer compounds. We systematically detect the predictive component of DNA methylation in the context of transcriptional and mutational patterns, i.e., in total 19 DNA methylation biomarkers across 17 drugs and five cancer types. DNA methylation constitutes drug sensitivity biomarkers by mediating the expression of proximal genes, thereby enhancing biological signals across multi-omics data modalities. Our method reproduces anticipated associations, and in addition, we find that the NEK9 promoter hypermethylation may confer sensitivity to the NEDD8-activating enzyme (NAE) inhibitor pevonedistat in melanoma through downregulation of NEK9. In summary, we envision that epigenomics will refine existing patient stratification, thus empowering the next generation of precision oncology.

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Publication type Article: Journal article

Document type Scientific Article

Corresponding Author

Keywords Island Methylator Phenotype; Dna Methylation; Gene-expression; Hypermethylation; Connectivity; Dacomitinib; Mechanisms; Target

ISSN (print) / ISBN 2399-3642

e-ISSN 2399-3642

Journal Communications Biology

Quellenangaben Volume: 6, Issue: 1, Article Number: 825

Publisher Springer

Publishing Place London

Non-patent literature Publications

Reviewing status Peer reviewed

Institute(s) Institute of Computational Biology (ICB)

Grants European Union's Horizon 2020 research and innovation programme