DNA Methylation Modification Regulator-Mediated Molecular Clusters and Tumor Metabolic Characterization in Prostate Cancer

Background. An increasing number of studies have indicated a close link between DNA methylation and tumor metabolism. However, the overall influence of DNA methylation on tumor metabolic characteristics in prostate cancer (PCa) remains unclear. Methods. We first explored the subtypes of DNA methylat...

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Autores principales:	Yanlong Zhang, Xuezhi Liang, Liyun Zhang, Dongwen Wang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/9d54a55351044500876719a6a97f7043
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spelling	oai:doaj.org-article:9d54a55351044500876719a6a97f70432021-11-22T01:10:49ZDNA Methylation Modification Regulator-Mediated Molecular Clusters and Tumor Metabolic Characterization in Prostate Cancer1687-846910.1155/2021/2408637https://doaj.org/article/9d54a55351044500876719a6a97f70432021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2408637https://doaj.org/toc/1687-8469Background. An increasing number of studies have indicated a close link between DNA methylation and tumor metabolism. However, the overall influence of DNA methylation on tumor metabolic characteristics in prostate cancer (PCa) remains unclear. Methods. We first explored the subtypes of DNA methylation modification regulators and tumor metabolic features of 1,205 PCa samples using clustering analysis and gene set variation analysis based on the mRNA levels of DNA methylation modification regulators. A DNA methylation-related score (DMS) was calculated using principal component analysis and the DNA methylation modification-related gene signatures to quantify DNA methylation characteristics. We then performed a meta-analysis to identify the hazard ratio of DMS in the six cohorts. In addition, a nomogram was drawn using univariate and multivariate Cox analyses based on the DMS and clinical variables. Finally, a drug sensitivity analysis of the DMS was performed based on the genomics of drug sensitivity in cancer datasets. Results. Three PCa clusters showing different DNA methylation modification patterns and tumor metabolic features were identified. A DMS system was established to quantify the characteristics of DNA methylation modification. PCa samples showed a differential metabolic landscape between the high and low DMS groups. The prognostic value of the DMS and nomogram was independently validated in multiple cohorts. A high DMS was associated with increases in the tumor mutation burden, copy number variation, and microsatellite instability; high tumor heterogeneity; and poor prognosis. Finally, DMS was closely related to different types of antitumor treatment. Conclusion. Improving the understanding of tumor metabolism by characterizing DNA methylation modification patterns and using the DMS may help clinicians predict prognosis and aid in more personalized antitumor therapy strategies for PCa.Yanlong ZhangXuezhi LiangLiyun ZhangDongwen WangHindawi LimitedarticleNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENJournal of Oncology, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Yanlong Zhang Xuezhi Liang Liyun Zhang Dongwen Wang DNA Methylation Modification Regulator-Mediated Molecular Clusters and Tumor Metabolic Characterization in Prostate Cancer
description	Background. An increasing number of studies have indicated a close link between DNA methylation and tumor metabolism. However, the overall influence of DNA methylation on tumor metabolic characteristics in prostate cancer (PCa) remains unclear. Methods. We first explored the subtypes of DNA methylation modification regulators and tumor metabolic features of 1,205 PCa samples using clustering analysis and gene set variation analysis based on the mRNA levels of DNA methylation modification regulators. A DNA methylation-related score (DMS) was calculated using principal component analysis and the DNA methylation modification-related gene signatures to quantify DNA methylation characteristics. We then performed a meta-analysis to identify the hazard ratio of DMS in the six cohorts. In addition, a nomogram was drawn using univariate and multivariate Cox analyses based on the DMS and clinical variables. Finally, a drug sensitivity analysis of the DMS was performed based on the genomics of drug sensitivity in cancer datasets. Results. Three PCa clusters showing different DNA methylation modification patterns and tumor metabolic features were identified. A DMS system was established to quantify the characteristics of DNA methylation modification. PCa samples showed a differential metabolic landscape between the high and low DMS groups. The prognostic value of the DMS and nomogram was independently validated in multiple cohorts. A high DMS was associated with increases in the tumor mutation burden, copy number variation, and microsatellite instability; high tumor heterogeneity; and poor prognosis. Finally, DMS was closely related to different types of antitumor treatment. Conclusion. Improving the understanding of tumor metabolism by characterizing DNA methylation modification patterns and using the DMS may help clinicians predict prognosis and aid in more personalized antitumor therapy strategies for PCa.
format	article
author	Yanlong Zhang Xuezhi Liang Liyun Zhang Dongwen Wang
author_facet	Yanlong Zhang Xuezhi Liang Liyun Zhang Dongwen Wang
author_sort	Yanlong Zhang
title	DNA Methylation Modification Regulator-Mediated Molecular Clusters and Tumor Metabolic Characterization in Prostate Cancer
title_short	DNA Methylation Modification Regulator-Mediated Molecular Clusters and Tumor Metabolic Characterization in Prostate Cancer
title_full	DNA Methylation Modification Regulator-Mediated Molecular Clusters and Tumor Metabolic Characterization in Prostate Cancer
title_fullStr	DNA Methylation Modification Regulator-Mediated Molecular Clusters and Tumor Metabolic Characterization in Prostate Cancer
title_full_unstemmed	DNA Methylation Modification Regulator-Mediated Molecular Clusters and Tumor Metabolic Characterization in Prostate Cancer
title_sort	dna methylation modification regulator-mediated molecular clusters and tumor metabolic characterization in prostate cancer
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/9d54a55351044500876719a6a97f7043
work_keys_str_mv	AT yanlongzhang dnamethylationmodificationregulatormediatedmolecularclustersandtumormetaboliccharacterizationinprostatecancer AT xuezhiliang dnamethylationmodificationregulatormediatedmolecularclustersandtumormetaboliccharacterizationinprostatecancer AT liyunzhang dnamethylationmodificationregulatormediatedmolecularclustersandtumormetaboliccharacterizationinprostatecancer AT dongwenwang dnamethylationmodificationregulatormediatedmolecularclustersandtumormetaboliccharacterizationinprostatecancer
_version_	1718418357960572928

DNA Methylation Modification Regulator-Mediated Molecular Clusters and Tumor Metabolic Characterization in Prostate Cancer

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