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Identification of a six-gene prognostic signature for bladder cancer associated macrophage
As major components of the tumor microenvironment (TME), tumor-associated macrophages (TAMs) play an exceedingly complicated role in tumor progression and tumorigenesis. However, few studies have reported the specific TAM gene signature in bladder cancer. Herein, this study focused on developing a T...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582252/ https://www.ncbi.nlm.nih.gov/pubmed/36275756 http://dx.doi.org/10.3389/fimmu.2022.930352 |
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author | Jiang, Yunzhong Qu, Xiaowei Zhang, Mengzhao Zhang, Lu Yang, Tao Ma, Minghai Jing, Minxuan Zhang, Nan Song, Rundong Zhang, Yuanquan Yang, Zezhong Zhang, Yaodong Pu, Yuanchun Fan, Jinhai |
author_facet | Jiang, Yunzhong Qu, Xiaowei Zhang, Mengzhao Zhang, Lu Yang, Tao Ma, Minghai Jing, Minxuan Zhang, Nan Song, Rundong Zhang, Yuanquan Yang, Zezhong Zhang, Yaodong Pu, Yuanchun Fan, Jinhai |
author_sort | Jiang, Yunzhong |
collection | PubMed |
description | As major components of the tumor microenvironment (TME), tumor-associated macrophages (TAMs) play an exceedingly complicated role in tumor progression and tumorigenesis. However, few studies have reported the specific TAM gene signature in bladder cancer. Herein, this study focused on developing a TAM-related prognostic model in bladder cancer patients based on The Cancer Genome Atlas (TCGA) data. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify key genes related to TAM (M2 macrophage). Gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis showed the functional categories of the key genes. Simultaneously, we used the Least Absolute Shrinkage and Selection Operator (LASSO) and univariate and multivariate Cox regressions to establish a TMA-related prognostic model containing six key genes: TBXAS1, GYPC, HPGDS, GAB3, ADORA3, and FOLR2. Subsequently, single-cell sequencing data downloaded from Gene Expression Omnibus (GEO) suggested that the six genes in the prognostic model were expressed in TAM specifically and may be involved in TAM polarization. In summary, our research uncovered six-TAM related genes that may have an effect on risk stratification in bladder cancer patients and could be regarded as potential TAM-related biomarkers. |
format | Online Article Text |
id | pubmed-9582252 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95822522022-10-21 Identification of a six-gene prognostic signature for bladder cancer associated macrophage Jiang, Yunzhong Qu, Xiaowei Zhang, Mengzhao Zhang, Lu Yang, Tao Ma, Minghai Jing, Minxuan Zhang, Nan Song, Rundong Zhang, Yuanquan Yang, Zezhong Zhang, Yaodong Pu, Yuanchun Fan, Jinhai Front Immunol Immunology As major components of the tumor microenvironment (TME), tumor-associated macrophages (TAMs) play an exceedingly complicated role in tumor progression and tumorigenesis. However, few studies have reported the specific TAM gene signature in bladder cancer. Herein, this study focused on developing a TAM-related prognostic model in bladder cancer patients based on The Cancer Genome Atlas (TCGA) data. Weighted Gene Co-Expression Network Analysis (WGCNA) was used to identify key genes related to TAM (M2 macrophage). Gene ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis showed the functional categories of the key genes. Simultaneously, we used the Least Absolute Shrinkage and Selection Operator (LASSO) and univariate and multivariate Cox regressions to establish a TMA-related prognostic model containing six key genes: TBXAS1, GYPC, HPGDS, GAB3, ADORA3, and FOLR2. Subsequently, single-cell sequencing data downloaded from Gene Expression Omnibus (GEO) suggested that the six genes in the prognostic model were expressed in TAM specifically and may be involved in TAM polarization. In summary, our research uncovered six-TAM related genes that may have an effect on risk stratification in bladder cancer patients and could be regarded as potential TAM-related biomarkers. Frontiers Media S.A. 2022-10-06 /pmc/articles/PMC9582252/ /pubmed/36275756 http://dx.doi.org/10.3389/fimmu.2022.930352 Text en Copyright © 2022 Jiang, Qu, Zhang, Zhang, Yang, Ma, Jing, Zhang, Song, Zhang, Yang, Zhang, Pu and Fan https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Jiang, Yunzhong Qu, Xiaowei Zhang, Mengzhao Zhang, Lu Yang, Tao Ma, Minghai Jing, Minxuan Zhang, Nan Song, Rundong Zhang, Yuanquan Yang, Zezhong Zhang, Yaodong Pu, Yuanchun Fan, Jinhai Identification of a six-gene prognostic signature for bladder cancer associated macrophage |
title | Identification of a six-gene prognostic signature for bladder cancer associated macrophage |
title_full | Identification of a six-gene prognostic signature for bladder cancer associated macrophage |
title_fullStr | Identification of a six-gene prognostic signature for bladder cancer associated macrophage |
title_full_unstemmed | Identification of a six-gene prognostic signature for bladder cancer associated macrophage |
title_short | Identification of a six-gene prognostic signature for bladder cancer associated macrophage |
title_sort | identification of a six-gene prognostic signature for bladder cancer associated macrophage |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582252/ https://www.ncbi.nlm.nih.gov/pubmed/36275756 http://dx.doi.org/10.3389/fimmu.2022.930352 |
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