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A robust immune-related lncRNA signature for the prognosis of human colorectal cancer
Background: Colorectal cancer (CRC) is one of the most prevalent malignant cancers worldwide. Immune-related long non-coding RNAs (IRlncRNAs) are proved to be essential in the development and progression of carcinoma. The purpose of the present study was to develop and validate a prognostic IRlncRNA...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9301293/ https://www.ncbi.nlm.nih.gov/pubmed/35506372 http://dx.doi.org/10.1042/BSR20220078 |
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author | Zhu, Gongmin Pei, Lijiao Yang, Fan Zhang, Chenliang |
author_facet | Zhu, Gongmin Pei, Lijiao Yang, Fan Zhang, Chenliang |
author_sort | Zhu, Gongmin |
collection | PubMed |
description | Background: Colorectal cancer (CRC) is one of the most prevalent malignant cancers worldwide. Immune-related long non-coding RNAs (IRlncRNAs) are proved to be essential in the development and progression of carcinoma. The purpose of the present study was to develop and validate a prognostic IRlncRNA signature for CRC patients. Methods: Gene expression profiles of CRC samples were downloaded from The Cancer Genome Atlas (TCGA) database. Immune-related genes were obtained from the ImmPort database and were used to identify IRlncRNA by correlation analysis. Through LASSO Cox regression analyses, a prognostic signature was constructed. Functional enrichment analysis was performed by gene set enrichment analysis (GSEA). TIMER2.0 web server and tumor immune dysfunction and exclusion (TIDE) algorithm were employed to analyze the association between our model and tumor-infiltrating immune cells and immunotherapy response. The expression levels of IRlncRNAs in cell lines were detected by quantitative real-time PCR (qPCR). Results: A 9-IRlncRNA signature was developed by a LASSO Cox proportional regression model. Based on the signature, CRC patients were divided into high- and low-risk groups with different prognoses. GSEA results indicated that patients in high-risk group were associated with cancer-related pathways. In addition, patients in low-risk group were found to have more infiltration of anti-tumor immune cells and might show a favorable response to immunotherapy. Finally, the result of qPCR revealed that most IRlncRNAs were differently expressed between normal and tumor cell lines. Conclusion: The constructed 9-IRlncRNA signature has potential to predict the prognosis of CRC patients and may be helpful to guide personalized immunotherapy. |
format | Online Article Text |
id | pubmed-9301293 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93012932022-08-03 A robust immune-related lncRNA signature for the prognosis of human colorectal cancer Zhu, Gongmin Pei, Lijiao Yang, Fan Zhang, Chenliang Biosci Rep Bioinformatics Background: Colorectal cancer (CRC) is one of the most prevalent malignant cancers worldwide. Immune-related long non-coding RNAs (IRlncRNAs) are proved to be essential in the development and progression of carcinoma. The purpose of the present study was to develop and validate a prognostic IRlncRNA signature for CRC patients. Methods: Gene expression profiles of CRC samples were downloaded from The Cancer Genome Atlas (TCGA) database. Immune-related genes were obtained from the ImmPort database and were used to identify IRlncRNA by correlation analysis. Through LASSO Cox regression analyses, a prognostic signature was constructed. Functional enrichment analysis was performed by gene set enrichment analysis (GSEA). TIMER2.0 web server and tumor immune dysfunction and exclusion (TIDE) algorithm were employed to analyze the association between our model and tumor-infiltrating immune cells and immunotherapy response. The expression levels of IRlncRNAs in cell lines were detected by quantitative real-time PCR (qPCR). Results: A 9-IRlncRNA signature was developed by a LASSO Cox proportional regression model. Based on the signature, CRC patients were divided into high- and low-risk groups with different prognoses. GSEA results indicated that patients in high-risk group were associated with cancer-related pathways. In addition, patients in low-risk group were found to have more infiltration of anti-tumor immune cells and might show a favorable response to immunotherapy. Finally, the result of qPCR revealed that most IRlncRNAs were differently expressed between normal and tumor cell lines. Conclusion: The constructed 9-IRlncRNA signature has potential to predict the prognosis of CRC patients and may be helpful to guide personalized immunotherapy. Portland Press Ltd. 2022-07-20 /pmc/articles/PMC9301293/ /pubmed/35506372 http://dx.doi.org/10.1042/BSR20220078 Text en © 2022 The Author(s). https://creativecommons.org/licenses/by/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Bioinformatics Zhu, Gongmin Pei, Lijiao Yang, Fan Zhang, Chenliang A robust immune-related lncRNA signature for the prognosis of human colorectal cancer |
title | A robust immune-related lncRNA signature for the prognosis of human colorectal cancer |
title_full | A robust immune-related lncRNA signature for the prognosis of human colorectal cancer |
title_fullStr | A robust immune-related lncRNA signature for the prognosis of human colorectal cancer |
title_full_unstemmed | A robust immune-related lncRNA signature for the prognosis of human colorectal cancer |
title_short | A robust immune-related lncRNA signature for the prognosis of human colorectal cancer |
title_sort | robust immune-related lncrna signature for the prognosis of human colorectal cancer |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9301293/ https://www.ncbi.nlm.nih.gov/pubmed/35506372 http://dx.doi.org/10.1042/BSR20220078 |
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