DNA methylation-based prediction of response to immune checkpoint inhibition in metastatic melanoma.

Autor:	Filipski K; Neurological Institute (Edinger Institute), University Hospital, Frankfurt am Main, Germany.; German Cancer Consortium (DKTK) Heidelberg, German Cancer Research Center (DKFZ), Heidelberg, Germany.; Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany., Scherer M; Department of Genetics, University of Saarland, Saarbrücken, Germany.; Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, Germany.; Graduate School of Computer Science, Saarland Informatics Campus, Saabrücken, Germany., Zeiner KN; Department of Dermatology, University Hospital, Frankfurt am Main, Germany., Bucher A; Department of Radiology, University Hospital, Frankfurt am Main, Germany., Kleemann J; Department of Dermatology, University Hospital, Frankfurt am Main, Germany., Jurmeister P; Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.; Institute of Pathology, Ludwig Maximilians University Hospital Munich, Munich, Germany., Hartung TI; Neurological Institute (Edinger Institute), University Hospital, Frankfurt am Main, Germany., Meissner M; Department of Dermatology, University Hospital, Frankfurt am Main, Germany., Plate KH; Neurological Institute (Edinger Institute), University Hospital, Frankfurt am Main, Germany.; German Cancer Consortium (DKTK) Heidelberg, German Cancer Research Center (DKFZ), Heidelberg, Germany.; Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany., Fenton TR; School of Biosciences, University of Kent, Kent, UK., Walter J; Department of Genetics, University of Saarland, Saarbrücken, Germany., Tierling S; Department of Genetics, University of Saarland, Saarbrücken, Germany., Schilling B; Department of Dermatology, University Hospital Würzburg, Würzburg, Germany., Zeiner PS; German Cancer Consortium (DKTK) Heidelberg, German Cancer Research Center (DKFZ), Heidelberg, Germany.; Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany.; Dr. Senckenberg Institute of Neurooncology, University Hospital, Frankfurt am Main, Germany., Harter PN; Neurological Institute (Edinger Institute), University Hospital, Frankfurt am Main, Germany patrick.harter@kgu.de.; German Cancer Consortium (DKTK) Heidelberg, German Cancer Research Center (DKFZ), Heidelberg, Germany.; Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany.
Jazyk:	angličtina
Zdroj:	Journal for immunotherapy of cancer [J Immunother Cancer] 2021 Jul; Vol. 9 (7).
DOI:	10.1136/jitc-2020-002226
Abstrakt:	Background: Therapies based on targeting immune checkpoints have revolutionized the treatment of metastatic melanoma in recent years. Still, biomarkers predicting long-term therapy responses are lacking. Methods: A novel approach of reference-free deconvolution of large-scale DNA methylation data enabled us to develop a machine learning classifier based on CpG sites, specific for latent methylation components (LMC), that allowed for patient allocation to prognostic clusters. DNA methylation data were processed using reference-free analyses (MeDeCom) and reference-based computational tumor deconvolution (MethylCIBERSORT, LUMP). Results: We provide evidence that DNA methylation signatures of tumor tissue from cutaneous metastases are predictive for therapy response to immune checkpoint inhibition in patients with stage IV metastatic melanoma. Conclusions: These results demonstrate that LMC-based segregation of large-scale DNA methylation data is a promising tool for classifier development and treatment response estimation in cancer patients under targeted immunotherapy. Competing Interests: Competing interests: None declared. (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Databáze:	MEDLINE
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