Cargando…

Tumor microenvironment characterization in triple-negative breast cancer identifies prognostic gene signature

We aimed to elucidate the landscape of tumor microenvironment (TME) in triple-negative breast cancer (TNBC). Cohorts from Gene Expression Omnibus database (N = 107) and METABRIC (N = 299) were used as the training set and validation set, respectively. TME was evaluated via single-sample gene set enr...

Descripción completa

Detalles Bibliográficos
Autores principales: Qin, Yan, Deng, Jiehua, Zhang, Lihua, Yuan, Jiaxing, Yang, Huawei, Li, Qiuyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7950290/
https://www.ncbi.nlm.nih.gov/pubmed/33536349
http://dx.doi.org/10.18632/aging.202478
_version_ 1783663558384418816
author Qin, Yan
Deng, Jiehua
Zhang, Lihua
Yuan, Jiaxing
Yang, Huawei
Li, Qiuyun
author_facet Qin, Yan
Deng, Jiehua
Zhang, Lihua
Yuan, Jiaxing
Yang, Huawei
Li, Qiuyun
author_sort Qin, Yan
collection PubMed
description We aimed to elucidate the landscape of tumor microenvironment (TME) in triple-negative breast cancer (TNBC). Cohorts from Gene Expression Omnibus database (N = 107) and METABRIC (N = 299) were used as the training set and validation set, respectively. TME was evaluated via single-sample gene set enrichment analysis, and unsupervised clustering was used for cluster identification. Consequently, TNBC was classified into two distinct TME clusters (Cluster 1 and Cluster 2) according to predefined immune-related terms. Cluster 1 was characterized by low immune infiltration with poor prognosis; whereas, Cluster 2 was characterized by high immune infiltration with better survival probability. Further, Cluster 1 had larger tumor volumes, while Cluster 2 had smaller tumor volumes. Finally, a TME signature for prognosis stratification in TNBC was developed and validated. In summary, we comprehensively evaluated the TME of TNBC and constructed a TME signature that correlated with prognosis. Our results provide new insights for the immunotherapy of TNBC.
format Online
Article
Text
id pubmed-7950290
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Impact Journals
record_format MEDLINE/PubMed
spelling pubmed-79502902021-03-23 Tumor microenvironment characterization in triple-negative breast cancer identifies prognostic gene signature Qin, Yan Deng, Jiehua Zhang, Lihua Yuan, Jiaxing Yang, Huawei Li, Qiuyun Aging (Albany NY) Research Paper We aimed to elucidate the landscape of tumor microenvironment (TME) in triple-negative breast cancer (TNBC). Cohorts from Gene Expression Omnibus database (N = 107) and METABRIC (N = 299) were used as the training set and validation set, respectively. TME was evaluated via single-sample gene set enrichment analysis, and unsupervised clustering was used for cluster identification. Consequently, TNBC was classified into two distinct TME clusters (Cluster 1 and Cluster 2) according to predefined immune-related terms. Cluster 1 was characterized by low immune infiltration with poor prognosis; whereas, Cluster 2 was characterized by high immune infiltration with better survival probability. Further, Cluster 1 had larger tumor volumes, while Cluster 2 had smaller tumor volumes. Finally, a TME signature for prognosis stratification in TNBC was developed and validated. In summary, we comprehensively evaluated the TME of TNBC and constructed a TME signature that correlated with prognosis. Our results provide new insights for the immunotherapy of TNBC. Impact Journals 2021-02-01 /pmc/articles/PMC7950290/ /pubmed/33536349 http://dx.doi.org/10.18632/aging.202478 Text en Copyright: © 2021 Qin 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
Qin, Yan
Deng, Jiehua
Zhang, Lihua
Yuan, Jiaxing
Yang, Huawei
Li, Qiuyun
Tumor microenvironment characterization in triple-negative breast cancer identifies prognostic gene signature
title Tumor microenvironment characterization in triple-negative breast cancer identifies prognostic gene signature
title_full Tumor microenvironment characterization in triple-negative breast cancer identifies prognostic gene signature
title_fullStr Tumor microenvironment characterization in triple-negative breast cancer identifies prognostic gene signature
title_full_unstemmed Tumor microenvironment characterization in triple-negative breast cancer identifies prognostic gene signature
title_short Tumor microenvironment characterization in triple-negative breast cancer identifies prognostic gene signature
title_sort tumor microenvironment characterization in triple-negative breast cancer identifies prognostic gene signature
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7950290/
https://www.ncbi.nlm.nih.gov/pubmed/33536349
http://dx.doi.org/10.18632/aging.202478
work_keys_str_mv AT qinyan tumormicroenvironmentcharacterizationintriplenegativebreastcanceridentifiesprognosticgenesignature
AT dengjiehua tumormicroenvironmentcharacterizationintriplenegativebreastcanceridentifiesprognosticgenesignature
AT zhanglihua tumormicroenvironmentcharacterizationintriplenegativebreastcanceridentifiesprognosticgenesignature
AT yuanjiaxing tumormicroenvironmentcharacterizationintriplenegativebreastcanceridentifiesprognosticgenesignature
AT yanghuawei tumormicroenvironmentcharacterizationintriplenegativebreastcanceridentifiesprognosticgenesignature
AT liqiuyun tumormicroenvironmentcharacterizationintriplenegativebreastcanceridentifiesprognosticgenesignature