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Comprehensive profiling of immune-related genes in soft tissue sarcoma patients
BACKGROUND: Immune-related genes (IRGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of IRGs and their clinical significance in soft tissue sarcoma (STS) patients is lacking. METHODS: Gene expression files fr...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7465445/ https://www.ncbi.nlm.nih.gov/pubmed/32873319 http://dx.doi.org/10.1186/s12967-020-02512-8 |
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author | Hu, Chuan Chen, Bo Huang, Zhangheng Liu, Chuan Ye, Lin Wang, Cailin Tong, Yuexin Yang, Jiaxin Zhao, Chengliang |
author_facet | Hu, Chuan Chen, Bo Huang, Zhangheng Liu, Chuan Ye, Lin Wang, Cailin Tong, Yuexin Yang, Jiaxin Zhao, Chengliang |
author_sort | Hu, Chuan |
collection | PubMed |
description | BACKGROUND: Immune-related genes (IRGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of IRGs and their clinical significance in soft tissue sarcoma (STS) patients is lacking. METHODS: Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed immune-related genes (DEIRGs) were determined by matching the DEG and ImmPort gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEIRGs was conducted, and associations with prognosis, the tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for progression free survival (PFS), were established and validated in an independent set. Finally, two transcription factor (TF)-IRG regulatory networks were constructed, and a crucial regulatory axis was validated. RESULTS: In total, 364 DEIRGs and four clusters were identified. OS, TME scores, five immune checkpoints, and 12 types of immune cells were found to be significantly different among the four clusters. The two prognostic signatures incorporating 20 DEIRGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.879 (95%CI 0.832 ~ 0.926) and 0.825 (95%CI 0.776 ~ 0.874) for the OS and PFS signatures, respectively. Finally, TF-IRG regulatory networks were established, and the MYH11-ADM regulatory axis was verified in three independent datasets. CONCLUSION: This comprehensive analysis of the IRG landscape in soft tissue sarcoma revealed novel IRGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy. |
format | Online Article Text |
id | pubmed-7465445 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-74654452020-09-02 Comprehensive profiling of immune-related genes in soft tissue sarcoma patients Hu, Chuan Chen, Bo Huang, Zhangheng Liu, Chuan Ye, Lin Wang, Cailin Tong, Yuexin Yang, Jiaxin Zhao, Chengliang J Transl Med Research BACKGROUND: Immune-related genes (IRGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of IRGs and their clinical significance in soft tissue sarcoma (STS) patients is lacking. METHODS: Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed immune-related genes (DEIRGs) were determined by matching the DEG and ImmPort gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEIRGs was conducted, and associations with prognosis, the tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for progression free survival (PFS), were established and validated in an independent set. Finally, two transcription factor (TF)-IRG regulatory networks were constructed, and a crucial regulatory axis was validated. RESULTS: In total, 364 DEIRGs and four clusters were identified. OS, TME scores, five immune checkpoints, and 12 types of immune cells were found to be significantly different among the four clusters. The two prognostic signatures incorporating 20 DEIRGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.879 (95%CI 0.832 ~ 0.926) and 0.825 (95%CI 0.776 ~ 0.874) for the OS and PFS signatures, respectively. Finally, TF-IRG regulatory networks were established, and the MYH11-ADM regulatory axis was verified in three independent datasets. CONCLUSION: This comprehensive analysis of the IRG landscape in soft tissue sarcoma revealed novel IRGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy. BioMed Central 2020-09-01 /pmc/articles/PMC7465445/ /pubmed/32873319 http://dx.doi.org/10.1186/s12967-020-02512-8 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Hu, Chuan Chen, Bo Huang, Zhangheng Liu, Chuan Ye, Lin Wang, Cailin Tong, Yuexin Yang, Jiaxin Zhao, Chengliang Comprehensive profiling of immune-related genes in soft tissue sarcoma patients |
title | Comprehensive profiling of immune-related genes in soft tissue sarcoma patients |
title_full | Comprehensive profiling of immune-related genes in soft tissue sarcoma patients |
title_fullStr | Comprehensive profiling of immune-related genes in soft tissue sarcoma patients |
title_full_unstemmed | Comprehensive profiling of immune-related genes in soft tissue sarcoma patients |
title_short | Comprehensive profiling of immune-related genes in soft tissue sarcoma patients |
title_sort | comprehensive profiling of immune-related genes in soft tissue sarcoma patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7465445/ https://www.ncbi.nlm.nih.gov/pubmed/32873319 http://dx.doi.org/10.1186/s12967-020-02512-8 |
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