Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods

Abstract Colorectal cancer (CRC) ranks fourth among the deadliest cancers globally, and the progression is highly affected by the tumor microenvironment (TME). This study explores the relationship between TME and colorectal cancer prognosis and identifies prognostic genes related to the CRC microenv...

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Autores principales:	Yi Liu, Long Cheng, Chao Li, Chen Zhang, Lei Wang, Jiantao Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8dd5c9fc307340788336419e48c46c74
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spelling	oai:doaj.org-article:8dd5c9fc307340788336419e48c46c742021-12-02T17:55:13ZIdentification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods10.1038/s41598-021-94541-62045-2322https://doaj.org/article/8dd5c9fc307340788336419e48c46c742021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-94541-6https://doaj.org/toc/2045-2322Abstract Colorectal cancer (CRC) ranks fourth among the deadliest cancers globally, and the progression is highly affected by the tumor microenvironment (TME). This study explores the relationship between TME and colorectal cancer prognosis and identifies prognostic genes related to the CRC microenvironment. We collected the gene expression data from The Cancer Genome Atlas (TCGA) and calculated the scores of stromal/immune cells and their relations to clinical outcomes in colorectal cancer by the ESTIMATE algorithm. Lower immune scores were significantly related to the malignant progression of CRC (metastasis, p = 0.001). We screened 292 differentially expressed genes (DEGs) by dividing CRC cases into high and low stromal/immune score groups. Functional enrichment analyses and protein–protein interaction (PPI) networks illustrated that these DEGs were closely involved in immune response, cytokine–cytokine receptor interaction, and chemokine signaling pathway. Six DEGs (FABP4, MEOX2, MMP12, ERMN, TNFAIP6, and CHST11) with prognostic value were identified by survival analysis and validated in two independent cohorts (GSE17538 and GSE161158). The six DEGs were significantly related to immune cell infiltration levels based on the Tumor Immune Estimation Resource (TIMER). The results might contribute to discovering new diagnostic and prognostic biomarkers and new treatment targets for colorectal cancer.Yi LiuLong ChengChao LiChen ZhangLei WangJiantao ZhangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yi Liu Long Cheng Chao Li Chen Zhang Lei Wang Jiantao Zhang Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods
description	Abstract Colorectal cancer (CRC) ranks fourth among the deadliest cancers globally, and the progression is highly affected by the tumor microenvironment (TME). This study explores the relationship between TME and colorectal cancer prognosis and identifies prognostic genes related to the CRC microenvironment. We collected the gene expression data from The Cancer Genome Atlas (TCGA) and calculated the scores of stromal/immune cells and their relations to clinical outcomes in colorectal cancer by the ESTIMATE algorithm. Lower immune scores were significantly related to the malignant progression of CRC (metastasis, p = 0.001). We screened 292 differentially expressed genes (DEGs) by dividing CRC cases into high and low stromal/immune score groups. Functional enrichment analyses and protein–protein interaction (PPI) networks illustrated that these DEGs were closely involved in immune response, cytokine–cytokine receptor interaction, and chemokine signaling pathway. Six DEGs (FABP4, MEOX2, MMP12, ERMN, TNFAIP6, and CHST11) with prognostic value were identified by survival analysis and validated in two independent cohorts (GSE17538 and GSE161158). The six DEGs were significantly related to immune cell infiltration levels based on the Tumor Immune Estimation Resource (TIMER). The results might contribute to discovering new diagnostic and prognostic biomarkers and new treatment targets for colorectal cancer.
format	article
author	Yi Liu Long Cheng Chao Li Chen Zhang Lei Wang Jiantao Zhang
author_facet	Yi Liu Long Cheng Chao Li Chen Zhang Lei Wang Jiantao Zhang
author_sort	Yi Liu
title	Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods
title_short	Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods
title_full	Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods
title_fullStr	Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods
title_full_unstemmed	Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods
title_sort	identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/8dd5c9fc307340788336419e48c46c74
work_keys_str_mv	AT yiliu identificationoftumormicroenvironmentrelatedprognosticgenesincolorectalcancerbasedonbioinformaticmethods AT longcheng identificationoftumormicroenvironmentrelatedprognosticgenesincolorectalcancerbasedonbioinformaticmethods AT chaoli identificationoftumormicroenvironmentrelatedprognosticgenesincolorectalcancerbasedonbioinformaticmethods AT chenzhang identificationoftumormicroenvironmentrelatedprognosticgenesincolorectalcancerbasedonbioinformaticmethods AT leiwang identificationoftumormicroenvironmentrelatedprognosticgenesincolorectalcancerbasedonbioinformaticmethods AT jiantaozhang identificationoftumormicroenvironmentrelatedprognosticgenesincolorectalcancerbasedonbioinformaticmethods
_version_	1718379121546887168

Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods

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