Cargando…
Integrative Analysis From Multicenter Studies Identifies a WGCNA-Derived Cancer-Associated Fibroblast Signature for Ovarian Cancer
Cancer-associated fibroblasts (CAFs) are a major contributor to tumor stromal crosstalk in the tumor microenvironment (TME) and boost tumor progression by promoting angiogenesis and lymphangiogenesis. This study aimed to identify prognostic genes associated with CAFs that lead to high morbidity and...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9304893/ https://www.ncbi.nlm.nih.gov/pubmed/35874760 http://dx.doi.org/10.3389/fimmu.2022.951582 |
_version_ | 1784752193828552704 |
---|---|
author | Feng, Songwei Xu, Yi Dai, Zhu Yin, Han Zhang, Ke Shen, Yang |
author_facet | Feng, Songwei Xu, Yi Dai, Zhu Yin, Han Zhang, Ke Shen, Yang |
author_sort | Feng, Songwei |
collection | PubMed |
description | Cancer-associated fibroblasts (CAFs) are a major contributor to tumor stromal crosstalk in the tumor microenvironment (TME) and boost tumor progression by promoting angiogenesis and lymphangiogenesis. This study aimed to identify prognostic genes associated with CAFs that lead to high morbidity and mortality in ovarian cancer (OC) patients. We performed bioinformatics analysis in 16 multicenter studies (2,742 patients) and identified CAF-associated hub genes using the weighted gene co-expression network analysis (WGCNA). A machine learning methodology was used to identify COL16A1, COL5A2, GREM1, LUM, SRPX, and TIMP3 and construct a prognostic signature. Subsequently, a series of bioinformatics algorithms indicated risk stratification based on the above signature, suggesting that high-risk patients have a worse prognosis, weaker immune response, and lower tumor mutational burden (TMB) status but may be more sensitive to routine chemotherapeutic agents. Finally, we characterized prognostic markers using cell lines, immunohistochemistry, and single-cell sequencing. In conclusion, these results suggest that the CAF-related signature may be a novel pretreatment guide for anti-CAFs, and prognostic markers in CAFs may be potential therapeutic targets to inhibit OC progression. |
format | Online Article Text |
id | pubmed-9304893 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93048932022-07-23 Integrative Analysis From Multicenter Studies Identifies a WGCNA-Derived Cancer-Associated Fibroblast Signature for Ovarian Cancer Feng, Songwei Xu, Yi Dai, Zhu Yin, Han Zhang, Ke Shen, Yang Front Immunol Immunology Cancer-associated fibroblasts (CAFs) are a major contributor to tumor stromal crosstalk in the tumor microenvironment (TME) and boost tumor progression by promoting angiogenesis and lymphangiogenesis. This study aimed to identify prognostic genes associated with CAFs that lead to high morbidity and mortality in ovarian cancer (OC) patients. We performed bioinformatics analysis in 16 multicenter studies (2,742 patients) and identified CAF-associated hub genes using the weighted gene co-expression network analysis (WGCNA). A machine learning methodology was used to identify COL16A1, COL5A2, GREM1, LUM, SRPX, and TIMP3 and construct a prognostic signature. Subsequently, a series of bioinformatics algorithms indicated risk stratification based on the above signature, suggesting that high-risk patients have a worse prognosis, weaker immune response, and lower tumor mutational burden (TMB) status but may be more sensitive to routine chemotherapeutic agents. Finally, we characterized prognostic markers using cell lines, immunohistochemistry, and single-cell sequencing. In conclusion, these results suggest that the CAF-related signature may be a novel pretreatment guide for anti-CAFs, and prognostic markers in CAFs may be potential therapeutic targets to inhibit OC progression. Frontiers Media S.A. 2022-07-08 /pmc/articles/PMC9304893/ /pubmed/35874760 http://dx.doi.org/10.3389/fimmu.2022.951582 Text en Copyright © 2022 Feng, Xu, Dai, Yin, Zhang and Shen 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 Feng, Songwei Xu, Yi Dai, Zhu Yin, Han Zhang, Ke Shen, Yang Integrative Analysis From Multicenter Studies Identifies a WGCNA-Derived Cancer-Associated Fibroblast Signature for Ovarian Cancer |
title | Integrative Analysis From Multicenter Studies Identifies a WGCNA-Derived Cancer-Associated Fibroblast Signature for Ovarian Cancer |
title_full | Integrative Analysis From Multicenter Studies Identifies a WGCNA-Derived Cancer-Associated Fibroblast Signature for Ovarian Cancer |
title_fullStr | Integrative Analysis From Multicenter Studies Identifies a WGCNA-Derived Cancer-Associated Fibroblast Signature for Ovarian Cancer |
title_full_unstemmed | Integrative Analysis From Multicenter Studies Identifies a WGCNA-Derived Cancer-Associated Fibroblast Signature for Ovarian Cancer |
title_short | Integrative Analysis From Multicenter Studies Identifies a WGCNA-Derived Cancer-Associated Fibroblast Signature for Ovarian Cancer |
title_sort | integrative analysis from multicenter studies identifies a wgcna-derived cancer-associated fibroblast signature for ovarian cancer |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9304893/ https://www.ncbi.nlm.nih.gov/pubmed/35874760 http://dx.doi.org/10.3389/fimmu.2022.951582 |
work_keys_str_mv | AT fengsongwei integrativeanalysisfrommulticenterstudiesidentifiesawgcnaderivedcancerassociatedfibroblastsignatureforovariancancer AT xuyi integrativeanalysisfrommulticenterstudiesidentifiesawgcnaderivedcancerassociatedfibroblastsignatureforovariancancer AT daizhu integrativeanalysisfrommulticenterstudiesidentifiesawgcnaderivedcancerassociatedfibroblastsignatureforovariancancer AT yinhan integrativeanalysisfrommulticenterstudiesidentifiesawgcnaderivedcancerassociatedfibroblastsignatureforovariancancer AT zhangke integrativeanalysisfrommulticenterstudiesidentifiesawgcnaderivedcancerassociatedfibroblastsignatureforovariancancer AT shenyang integrativeanalysisfrommulticenterstudiesidentifiesawgcnaderivedcancerassociatedfibroblastsignatureforovariancancer |