Identifying gene expression patterns associated with drug-specific survival in cancer patients

Abstract The ability to predict the efficacy of cancer treatments is a longstanding goal of precision medicine that requires improved understanding of molecular interactions with drugs and the discovery of biomarkers of drug response. Identifying genes whose expression influences drug sensitivity ca...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Bridget Neary, Jie Zhou, Peng Qiu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3a996745202d46b795526e4e3a7d6fe7
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:3a996745202d46b795526e4e3a7d6fe7
record_format	dspace
spelling	oai:doaj.org-article:3a996745202d46b795526e4e3a7d6fe72021-12-02T15:54:09ZIdentifying gene expression patterns associated with drug-specific survival in cancer patients10.1038/s41598-021-84211-y2045-2322https://doaj.org/article/3a996745202d46b795526e4e3a7d6fe72021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-84211-yhttps://doaj.org/toc/2045-2322Abstract The ability to predict the efficacy of cancer treatments is a longstanding goal of precision medicine that requires improved understanding of molecular interactions with drugs and the discovery of biomarkers of drug response. Identifying genes whose expression influences drug sensitivity can help address both of these needs, elucidating the molecular pathways involved in drug efficacy and providing potential ways to predict new patients’ response to available therapies. In this study, we integrated cancer type, drug treatment, and survival data with RNA-seq gene expression data from The Cancer Genome Atlas to identify genes and gene sets whose expression levels in patient tumor biopsies are associated with drug-specific patient survival using a log-rank test comparing survival of patients with low vs. high expression for each gene. This analysis was successful in identifying thousands of such gene–drug relationships across 20 drugs in 14 cancers, several of which have been previously implicated in the respective drug’s efficacy. We then clustered significant genes based on their expression patterns across patients and defined gene sets that are more robust predictors of patient outcome, many of which were significantly enriched for target genes of one or more transcription factors, indicating several upstream regulatory mechanisms that may be involved in drug efficacy. We identified a large number of genes and gene sets that were potentially useful as transcript-level biomarkers for predicting drug-specific patient survival outcome. Our gene sets were robust predictors of drug-specific survival and our results included both novel and previously reported findings, suggesting that the drug-specific survival marker genes reported herein warrant further investigation for insights into drug mechanisms and for validation as biomarkers to aid cancer therapy decisions.Bridget NearyJie ZhouPeng QiuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Bridget Neary Jie Zhou Peng Qiu Identifying gene expression patterns associated with drug-specific survival in cancer patients
description	Abstract The ability to predict the efficacy of cancer treatments is a longstanding goal of precision medicine that requires improved understanding of molecular interactions with drugs and the discovery of biomarkers of drug response. Identifying genes whose expression influences drug sensitivity can help address both of these needs, elucidating the molecular pathways involved in drug efficacy and providing potential ways to predict new patients’ response to available therapies. In this study, we integrated cancer type, drug treatment, and survival data with RNA-seq gene expression data from The Cancer Genome Atlas to identify genes and gene sets whose expression levels in patient tumor biopsies are associated with drug-specific patient survival using a log-rank test comparing survival of patients with low vs. high expression for each gene. This analysis was successful in identifying thousands of such gene–drug relationships across 20 drugs in 14 cancers, several of which have been previously implicated in the respective drug’s efficacy. We then clustered significant genes based on their expression patterns across patients and defined gene sets that are more robust predictors of patient outcome, many of which were significantly enriched for target genes of one or more transcription factors, indicating several upstream regulatory mechanisms that may be involved in drug efficacy. We identified a large number of genes and gene sets that were potentially useful as transcript-level biomarkers for predicting drug-specific patient survival outcome. Our gene sets were robust predictors of drug-specific survival and our results included both novel and previously reported findings, suggesting that the drug-specific survival marker genes reported herein warrant further investigation for insights into drug mechanisms and for validation as biomarkers to aid cancer therapy decisions.
format	article
author	Bridget Neary Jie Zhou Peng Qiu
author_facet	Bridget Neary Jie Zhou Peng Qiu
author_sort	Bridget Neary
title	Identifying gene expression patterns associated with drug-specific survival in cancer patients
title_short	Identifying gene expression patterns associated with drug-specific survival in cancer patients
title_full	Identifying gene expression patterns associated with drug-specific survival in cancer patients
title_fullStr	Identifying gene expression patterns associated with drug-specific survival in cancer patients
title_full_unstemmed	Identifying gene expression patterns associated with drug-specific survival in cancer patients
title_sort	identifying gene expression patterns associated with drug-specific survival in cancer patients
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/3a996745202d46b795526e4e3a7d6fe7
work_keys_str_mv	AT bridgetneary identifyinggeneexpressionpatternsassociatedwithdrugspecificsurvivalincancerpatients AT jiezhou identifyinggeneexpressionpatternsassociatedwithdrugspecificsurvivalincancerpatients AT pengqiu identifyinggeneexpressionpatternsassociatedwithdrugspecificsurvivalincancerpatients
_version_	1718385442455289856

Identifying gene expression patterns associated with drug-specific survival in cancer patients

Ejemplares similares