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Identification of vital prognostic genes related to tumor microenvironment in pheochromocytoma and paraganglioma based on weighted gene co-expression network analysis

Pheochromocytoma and paraganglioma (PCPG) is a rare neuroendocrine tumor. This study aims to identify vital prognostic genes which were associated with PCPG tumor microenvironment (TME). We downloaded transcriptome data of PCPG from TCGA database and calculated the immune scores and stromal scores b...

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Autores principales: Chen, Chun-Xian, Chen, Dong-Ning, Sun, Xiong-Lin, Ke, Zhi-Bin, Lin, Fei, Chen, Hang, Tao, Xuan, Huang, Fei, Wei, Yong, Xu, Ning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064173/
https://www.ncbi.nlm.nih.gov/pubmed/33795528
http://dx.doi.org/10.18632/aging.202754
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author Chen, Chun-Xian
Chen, Dong-Ning
Sun, Xiong-Lin
Ke, Zhi-Bin
Lin, Fei
Chen, Hang
Tao, Xuan
Huang, Fei
Wei, Yong
Xu, Ning
author_facet Chen, Chun-Xian
Chen, Dong-Ning
Sun, Xiong-Lin
Ke, Zhi-Bin
Lin, Fei
Chen, Hang
Tao, Xuan
Huang, Fei
Wei, Yong
Xu, Ning
author_sort Chen, Chun-Xian
collection PubMed
description Pheochromocytoma and paraganglioma (PCPG) is a rare neuroendocrine tumor. This study aims to identify vital prognostic genes which were associated with PCPG tumor microenvironment (TME). We downloaded transcriptome data of PCPG from TCGA database and calculated the immune scores and stromal scores by using the ESTIMATE algorithm. DEGs related to TMB were then identified. We conducted WGCNA to further extract the TME-related modules. GO, KEGG pathway analysis, and PPI network were performed. Survival analysis was conducted to identify the hub genes associated with the prognosis of PCPG. A total of 150 PCPG samples were included in this study. We obtained 1507 and 2067 DEGs based on immune scores and stromal scores, respectively. WGCNA analysis identified the red module and brown module were correlated with immune sores while the turquoise module and red module were significantly associated with stromal scores. Functional enrichments analysis revealed that 307 TME-related genes were correlated with the inflammation or immune response. Survival analysis showed that three TME-relate genes (ADGRE1, CCL18, and LILRA6) were associated with PCPG prognosis. These three hub genes including ADGRE1, CCL18, and LILRA6 might be involved in the progression of PCPG and could serve as potential biomarkers and novel therapeutic targets.
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spelling pubmed-80641732021-04-26 Identification of vital prognostic genes related to tumor microenvironment in pheochromocytoma and paraganglioma based on weighted gene co-expression network analysis Chen, Chun-Xian Chen, Dong-Ning Sun, Xiong-Lin Ke, Zhi-Bin Lin, Fei Chen, Hang Tao, Xuan Huang, Fei Wei, Yong Xu, Ning Aging (Albany NY) Research Paper Pheochromocytoma and paraganglioma (PCPG) is a rare neuroendocrine tumor. This study aims to identify vital prognostic genes which were associated with PCPG tumor microenvironment (TME). We downloaded transcriptome data of PCPG from TCGA database and calculated the immune scores and stromal scores by using the ESTIMATE algorithm. DEGs related to TMB were then identified. We conducted WGCNA to further extract the TME-related modules. GO, KEGG pathway analysis, and PPI network were performed. Survival analysis was conducted to identify the hub genes associated with the prognosis of PCPG. A total of 150 PCPG samples were included in this study. We obtained 1507 and 2067 DEGs based on immune scores and stromal scores, respectively. WGCNA analysis identified the red module and brown module were correlated with immune sores while the turquoise module and red module were significantly associated with stromal scores. Functional enrichments analysis revealed that 307 TME-related genes were correlated with the inflammation or immune response. Survival analysis showed that three TME-relate genes (ADGRE1, CCL18, and LILRA6) were associated with PCPG prognosis. These three hub genes including ADGRE1, CCL18, and LILRA6 might be involved in the progression of PCPG and could serve as potential biomarkers and novel therapeutic targets. Impact Journals 2021-03-26 /pmc/articles/PMC8064173/ /pubmed/33795528 http://dx.doi.org/10.18632/aging.202754 Text en Copyright: © 2021 Chen et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Chen, Chun-Xian
Chen, Dong-Ning
Sun, Xiong-Lin
Ke, Zhi-Bin
Lin, Fei
Chen, Hang
Tao, Xuan
Huang, Fei
Wei, Yong
Xu, Ning
Identification of vital prognostic genes related to tumor microenvironment in pheochromocytoma and paraganglioma based on weighted gene co-expression network analysis
title Identification of vital prognostic genes related to tumor microenvironment in pheochromocytoma and paraganglioma based on weighted gene co-expression network analysis
title_full Identification of vital prognostic genes related to tumor microenvironment in pheochromocytoma and paraganglioma based on weighted gene co-expression network analysis
title_fullStr Identification of vital prognostic genes related to tumor microenvironment in pheochromocytoma and paraganglioma based on weighted gene co-expression network analysis
title_full_unstemmed Identification of vital prognostic genes related to tumor microenvironment in pheochromocytoma and paraganglioma based on weighted gene co-expression network analysis
title_short Identification of vital prognostic genes related to tumor microenvironment in pheochromocytoma and paraganglioma based on weighted gene co-expression network analysis
title_sort identification of vital prognostic genes related to tumor microenvironment in pheochromocytoma and paraganglioma based on weighted gene co-expression network analysis
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8064173/
https://www.ncbi.nlm.nih.gov/pubmed/33795528
http://dx.doi.org/10.18632/aging.202754
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