Identification of Immune-Related Key Genes in Ovarian Cancer Based on WGCNA

Background: Ovarian cancer (OV) is a fatal gynecologic malignancy and has poor survival rate in women over the age of forty. In our study, we aimed to identify genes related to immune microenvironment regulations and explore genes associated with OV prognosis.Methods: The RNA-seq data of GDC TCGA Ov...

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Autores principales:	Qingli Quan, Xinxin Xiong, Shanyun Wu, Meixing Yu
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	ovarian cancer prognostic biomarkers immune microenvironment immune cells infiltration WGCNA CIBERSORT Genetics QH426-470
Acceso en línea:	https://doaj.org/article/43d205b6dd3449b199034a8178cfbedd
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spelling	oai:doaj.org-article:43d205b6dd3449b199034a8178cfbedd2021-11-15T06:25:50ZIdentification of Immune-Related Key Genes in Ovarian Cancer Based on WGCNA1664-802110.3389/fgene.2021.760225https://doaj.org/article/43d205b6dd3449b199034a8178cfbedd2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fgene.2021.760225/fullhttps://doaj.org/toc/1664-8021Background: Ovarian cancer (OV) is a fatal gynecologic malignancy and has poor survival rate in women over the age of forty. In our study, we aimed to identify genes related to immune microenvironment regulations and explore genes associated with OV prognosis.Methods: The RNA-seq data of GDC TCGA Ovarian Cancer cohort of 376 patients was retrieved from website. Weighted gene co-expression network analysis (WGCNA) and ESTIMATE algorithm were applied to identify the key genes associated with the immune scores. The correlation between key genes and 22 immune cell types were estimated by using CIBERSORT algorithms.Results: WGCNA showed that the pink module was most correlated with the immune score. Seven of 14 key genes (FCRL3, IFNG, KCNA3, LY9, PLA2G2D, THEMIS, and TRAT1) were significantly associated with the OS of OV patients. Correlation analysis showed our key genes positively related to M1 macrophages, CD8 T cells, plasma cells, regulatory T (Treg) cells and activated memory CD4 T cells, and negatively related to naive CD4 T cells, M0 macrophages, activated dendritic cells (DCs) and memory B cells. Kaplan-Meier survival analysis showed that lower abundances of neutrophils and higher abundances of M1 macrophages, plasma cells, T cells gamma delta (γδT) cells and follicular helper T (Tfh) cells predicted better OV prognosis.Conclusion: Forteen key genes related to the immune infiltrating of OV were identified, and seven of them were significantly related to prognosis. These key genes have potential roles in tumor infiltrating immune cells differentiation and proliferation. This study provided potential prognostic markers and immunotherapy targets for OV.Qingli QuanQingli QuanXinxin XiongShanyun WuMeixing YuFrontiers Media S.A.articleovarian cancerprognostic biomarkersimmune microenvironmentimmune cells infiltrationWGCNACIBERSORTGeneticsQH426-470ENFrontiers in Genetics, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	ovarian cancer prognostic biomarkers immune microenvironment immune cells infiltration WGCNA CIBERSORT Genetics QH426-470
spellingShingle	ovarian cancer prognostic biomarkers immune microenvironment immune cells infiltration WGCNA CIBERSORT Genetics QH426-470 Qingli Quan Qingli Quan Xinxin Xiong Shanyun Wu Meixing Yu Identification of Immune-Related Key Genes in Ovarian Cancer Based on WGCNA
description	Background: Ovarian cancer (OV) is a fatal gynecologic malignancy and has poor survival rate in women over the age of forty. In our study, we aimed to identify genes related to immune microenvironment regulations and explore genes associated with OV prognosis.Methods: The RNA-seq data of GDC TCGA Ovarian Cancer cohort of 376 patients was retrieved from website. Weighted gene co-expression network analysis (WGCNA) and ESTIMATE algorithm were applied to identify the key genes associated with the immune scores. The correlation between key genes and 22 immune cell types were estimated by using CIBERSORT algorithms.Results: WGCNA showed that the pink module was most correlated with the immune score. Seven of 14 key genes (FCRL3, IFNG, KCNA3, LY9, PLA2G2D, THEMIS, and TRAT1) were significantly associated with the OS of OV patients. Correlation analysis showed our key genes positively related to M1 macrophages, CD8 T cells, plasma cells, regulatory T (Treg) cells and activated memory CD4 T cells, and negatively related to naive CD4 T cells, M0 macrophages, activated dendritic cells (DCs) and memory B cells. Kaplan-Meier survival analysis showed that lower abundances of neutrophils and higher abundances of M1 macrophages, plasma cells, T cells gamma delta (γδT) cells and follicular helper T (Tfh) cells predicted better OV prognosis.Conclusion: Forteen key genes related to the immune infiltrating of OV were identified, and seven of them were significantly related to prognosis. These key genes have potential roles in tumor infiltrating immune cells differentiation and proliferation. This study provided potential prognostic markers and immunotherapy targets for OV.
format	article
author	Qingli Quan Qingli Quan Xinxin Xiong Shanyun Wu Meixing Yu
author_facet	Qingli Quan Qingli Quan Xinxin Xiong Shanyun Wu Meixing Yu
author_sort	Qingli Quan
title	Identification of Immune-Related Key Genes in Ovarian Cancer Based on WGCNA
title_short	Identification of Immune-Related Key Genes in Ovarian Cancer Based on WGCNA
title_full	Identification of Immune-Related Key Genes in Ovarian Cancer Based on WGCNA
title_fullStr	Identification of Immune-Related Key Genes in Ovarian Cancer Based on WGCNA
title_full_unstemmed	Identification of Immune-Related Key Genes in Ovarian Cancer Based on WGCNA
title_sort	identification of immune-related key genes in ovarian cancer based on wgcna
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/43d205b6dd3449b199034a8178cfbedd
work_keys_str_mv	AT qingliquan identificationofimmunerelatedkeygenesinovariancancerbasedonwgcna AT qingliquan identificationofimmunerelatedkeygenesinovariancancerbasedonwgcna AT xinxinxiong identificationofimmunerelatedkeygenesinovariancancerbasedonwgcna AT shanyunwu identificationofimmunerelatedkeygenesinovariancancerbasedonwgcna AT meixingyu identificationofimmunerelatedkeygenesinovariancancerbasedonwgcna
_version_	1718428548519165952

Identification of Immune-Related Key Genes in Ovarian Cancer Based on WGCNA

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