Metabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer

Abstract Tumor metabolism patterns have been reported to be associated with the prognosis of many cancers. However, the metabolic mechanisms underlying prostate cancer (PCa) remain unknown. This study aimed to explore the metabolic characteristics of PCa. First, we downloaded mRNA expression data an...

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Autores principales:	Yanlong Zhang, Xuezhi Liang, Liyun Zhang, Dongwen Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/dd52ed7d0e3c429e8124dfa227e7017c
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spelling	oai:doaj.org-article:dd52ed7d0e3c429e8124dfa227e7017c2021-11-21T12:20:13ZMetabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer10.1038/s41598-021-01140-62045-2322https://doaj.org/article/dd52ed7d0e3c429e8124dfa227e7017c2021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-01140-6https://doaj.org/toc/2045-2322Abstract Tumor metabolism patterns have been reported to be associated with the prognosis of many cancers. However, the metabolic mechanisms underlying prostate cancer (PCa) remain unknown. This study aimed to explore the metabolic characteristics of PCa. First, we downloaded mRNA expression data and clinical information of PCa samples from multiple databases and quantified the metabolic pathway activity level using single-sample gene set enrichment analysis (ssGSEA). Through unsupervised clustering and principal component analyses, we explored metabolic characteristics and constructed a metabolic score for PCa. Then, we independently validated the prognostic value of our metabolic score and the nomogram based on the metabolic score in multiple databases. Next, we found the metabolic score to be closely related to the tumor microenvironment and DNA mutation using multi-omics data and ssGSEA. Finally, we found different features of drug sensitivity in PCa patients in the high/low metabolic score groups. In total, 1232 samples were analyzed in the present study. Overall, an improved understanding of tumor metabolism through the characterization of metabolic clusters and metabolic score may help clinicians predict prognosis and aid the development of more personalized anti-tumor therapeutic strategies for PCa.Yanlong ZhangXuezhi LiangLiyun ZhangDongwen WangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yanlong Zhang Xuezhi Liang Liyun Zhang Dongwen Wang Metabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer
description	Abstract Tumor metabolism patterns have been reported to be associated with the prognosis of many cancers. However, the metabolic mechanisms underlying prostate cancer (PCa) remain unknown. This study aimed to explore the metabolic characteristics of PCa. First, we downloaded mRNA expression data and clinical information of PCa samples from multiple databases and quantified the metabolic pathway activity level using single-sample gene set enrichment analysis (ssGSEA). Through unsupervised clustering and principal component analyses, we explored metabolic characteristics and constructed a metabolic score for PCa. Then, we independently validated the prognostic value of our metabolic score and the nomogram based on the metabolic score in multiple databases. Next, we found the metabolic score to be closely related to the tumor microenvironment and DNA mutation using multi-omics data and ssGSEA. Finally, we found different features of drug sensitivity in PCa patients in the high/low metabolic score groups. In total, 1232 samples were analyzed in the present study. Overall, an improved understanding of tumor metabolism through the characterization of metabolic clusters and metabolic score may help clinicians predict prognosis and aid the development of more personalized anti-tumor therapeutic 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	Metabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer
title_short	Metabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer
title_full	Metabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer
title_fullStr	Metabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer
title_full_unstemmed	Metabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer
title_sort	metabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/dd52ed7d0e3c429e8124dfa227e7017c
work_keys_str_mv	AT yanlongzhang metaboliccharacterizationandmetabolismscoreoftumortopredicttheprognosisinprostatecancer AT xuezhiliang metaboliccharacterizationandmetabolismscoreoftumortopredicttheprognosisinprostatecancer AT liyunzhang metaboliccharacterizationandmetabolismscoreoftumortopredicttheprognosisinprostatecancer AT dongwenwang metaboliccharacterizationandmetabolismscoreoftumortopredicttheprognosisinprostatecancer
_version_	1718419097410076672

Metabolic characterization and metabolism-score of tumor to predict the prognosis in prostate cancer

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