Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma

Abstract The present study aimed to improve the understanding of non-uterine leiomyosarcoma (NULMS) prognostic genes through system biology approaches. This cancer is heterogeneous and rare. Moreover, gene interaction networks have not been reported in NULMS yet. The datasets were obtained from the...

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Autores principales:	Mohammad Darzi, Saeid Gorgin, Keivan Majidzadeh-A, Rezvan Esmaeili
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d08c425e9a9143748eacf7d7a53dba8a
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spelling	oai:doaj.org-article:d08c425e9a9143748eacf7d7a53dba8a2021-12-02T14:16:26ZGene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma10.1038/s41598-021-81952-82045-2322https://doaj.org/article/d08c425e9a9143748eacf7d7a53dba8a2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-81952-8https://doaj.org/toc/2045-2322Abstract The present study aimed to improve the understanding of non-uterine leiomyosarcoma (NULMS) prognostic genes through system biology approaches. This cancer is heterogeneous and rare. Moreover, gene interaction networks have not been reported in NULMS yet. The datasets were obtained from the public gene expression databases. Seven co-expression modules were identified from 5000 most connected genes; using weighted gene co-expression network analysis. Using Cox regression, the modules showed favorable (HR = 0.6, 95% CI = 0.4–0.89, P = 0.0125), (HR = 0.65, 95% CI = 0.44–0.98, P = 0.04) and poor (HR = 1.55, 95% CI = 1.06–2.27, P = 0.025) prognosis to the overall survival (OS) (time = 3740 days). The first one was significant in multivariate HR estimates (HR = 0.4, 95% CI = 0.28–0.69, P = 0.0004). Enriched genes through the Database for Annotation, Visualization, and Integrated Discovery (DAVID) revealed significant immune-related pathways; suggesting immune cell infiltration as a favorable prognostic factor. The most significant protective genes were ICAM3, NCR3, KLRB1, and IL18RAP, which were in one of the significant modules. Moreover, genes related to angiogenesis, cell–cell adhesion, protein glycosylation, and protein transport such as PYCR1, SRM, and MDFI negatively affected the OS and were found in the other related module. In conclusion, our analysis suggests that NULMS might be a good candidate for immunotherapy. Moreover, the genes found in this study might be potential candidates for targeted therapy.Mohammad DarziSaeid GorginKeivan Majidzadeh-ARezvan EsmaeiliNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Mohammad Darzi Saeid Gorgin Keivan Majidzadeh-A Rezvan Esmaeili Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma
description	Abstract The present study aimed to improve the understanding of non-uterine leiomyosarcoma (NULMS) prognostic genes through system biology approaches. This cancer is heterogeneous and rare. Moreover, gene interaction networks have not been reported in NULMS yet. The datasets were obtained from the public gene expression databases. Seven co-expression modules were identified from 5000 most connected genes; using weighted gene co-expression network analysis. Using Cox regression, the modules showed favorable (HR = 0.6, 95% CI = 0.4–0.89, P = 0.0125), (HR = 0.65, 95% CI = 0.44–0.98, P = 0.04) and poor (HR = 1.55, 95% CI = 1.06–2.27, P = 0.025) prognosis to the overall survival (OS) (time = 3740 days). The first one was significant in multivariate HR estimates (HR = 0.4, 95% CI = 0.28–0.69, P = 0.0004). Enriched genes through the Database for Annotation, Visualization, and Integrated Discovery (DAVID) revealed significant immune-related pathways; suggesting immune cell infiltration as a favorable prognostic factor. The most significant protective genes were ICAM3, NCR3, KLRB1, and IL18RAP, which were in one of the significant modules. Moreover, genes related to angiogenesis, cell–cell adhesion, protein glycosylation, and protein transport such as PYCR1, SRM, and MDFI negatively affected the OS and were found in the other related module. In conclusion, our analysis suggests that NULMS might be a good candidate for immunotherapy. Moreover, the genes found in this study might be potential candidates for targeted therapy.
format	article
author	Mohammad Darzi Saeid Gorgin Keivan Majidzadeh-A Rezvan Esmaeili
author_facet	Mohammad Darzi Saeid Gorgin Keivan Majidzadeh-A Rezvan Esmaeili
author_sort	Mohammad Darzi
title	Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma
title_short	Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma
title_full	Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma
title_fullStr	Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma
title_full_unstemmed	Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma
title_sort	gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/d08c425e9a9143748eacf7d7a53dba8a
work_keys_str_mv	AT mohammaddarzi genecoexpressionnetworkanalysisrevealsimmunecellinfiltrationasafavorableprognosticmarkerinnonuterineleiomyosarcoma AT saeidgorgin genecoexpressionnetworkanalysisrevealsimmunecellinfiltrationasafavorableprognosticmarkerinnonuterineleiomyosarcoma AT keivanmajidzadeha genecoexpressionnetworkanalysisrevealsimmunecellinfiltrationasafavorableprognosticmarkerinnonuterineleiomyosarcoma AT rezvanesmaeili genecoexpressionnetworkanalysisrevealsimmunecellinfiltrationasafavorableprognosticmarkerinnonuterineleiomyosarcoma
_version_	1718391694558232576

Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma

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