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Identification of a Six-Immune-Related Long Non-coding RNA Signature for Predicting Survival and Immune Infiltrating Status in Breast Cancer
Long non-coding RNAs (lncRNAs) play critical roles in tumor immunity; however, the functional roles of immune-related lncRNAs in breast cancer (BC) remain elusive. To further explore the immune−related lncRNAs in BC, whole genomic expression data and corresponding clinical information were obtained...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7358358/ https://www.ncbi.nlm.nih.gov/pubmed/32733537 http://dx.doi.org/10.3389/fgene.2020.00680 |
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author | Li, Zheng Li, Yaming Wang, Xiaolong Yang, Qifeng |
author_facet | Li, Zheng Li, Yaming Wang, Xiaolong Yang, Qifeng |
author_sort | Li, Zheng |
collection | PubMed |
description | Long non-coding RNAs (lncRNAs) play critical roles in tumor immunity; however, the functional roles of immune-related lncRNAs in breast cancer (BC) remain elusive. To further explore the immune−related lncRNAs in BC, whole genomic expression data and corresponding clinical information were obtained from multiple BC datasets. Based on correlation with the immune-related genes within the training set, we screened out the most promising immune-related lncRNAs. Subsequently, Lasso penalized Cox regression analysis followed by stepwise multivariate Cox regression analysis identified six survival-related lncRNAs (AC116366.1, AC244502.1, AC100810.1, MIAT, AC093297.2, and AL356417.2) and constructed a prognostic signature. The cohorts in the high−risk group had significantly poor survival time compared to those in the low−risk group. In addition, a nomogram integrated with clinical features and the prognostic signature was developed on the basis of the training set. Importantly, all the findings had a similar performance in three validated datasets. In the following studies, our integrative analyses indicated that the infiltration of CD8-positive (CD8) T cells associated with a good prognosis was strikingly activated in the low−risk group. To further provide an interpretation of biological mechanisms for the prognostic signature, we performed weighted gene co−expression network analysis (WGCNA) followed by KEGG pathway-enrichment analysis. Our results showed that the antigen presentation pathway involved in protein processing in endoplasmic reticulum and antigen processing and presentation was markedly altered in the high-risk group, which might promote tumor immune evasion and associate with poor clinical outcomes in BC patients with high risk scores. In conclusion, we aimed to take advantage of bioinformatics analyses to explore immune−related lncRNAs, which could function as prognostic indicators and promising therapeutic targets for BC patients. |
format | Online Article Text |
id | pubmed-7358358 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73583582020-07-29 Identification of a Six-Immune-Related Long Non-coding RNA Signature for Predicting Survival and Immune Infiltrating Status in Breast Cancer Li, Zheng Li, Yaming Wang, Xiaolong Yang, Qifeng Front Genet Genetics Long non-coding RNAs (lncRNAs) play critical roles in tumor immunity; however, the functional roles of immune-related lncRNAs in breast cancer (BC) remain elusive. To further explore the immune−related lncRNAs in BC, whole genomic expression data and corresponding clinical information were obtained from multiple BC datasets. Based on correlation with the immune-related genes within the training set, we screened out the most promising immune-related lncRNAs. Subsequently, Lasso penalized Cox regression analysis followed by stepwise multivariate Cox regression analysis identified six survival-related lncRNAs (AC116366.1, AC244502.1, AC100810.1, MIAT, AC093297.2, and AL356417.2) and constructed a prognostic signature. The cohorts in the high−risk group had significantly poor survival time compared to those in the low−risk group. In addition, a nomogram integrated with clinical features and the prognostic signature was developed on the basis of the training set. Importantly, all the findings had a similar performance in three validated datasets. In the following studies, our integrative analyses indicated that the infiltration of CD8-positive (CD8) T cells associated with a good prognosis was strikingly activated in the low−risk group. To further provide an interpretation of biological mechanisms for the prognostic signature, we performed weighted gene co−expression network analysis (WGCNA) followed by KEGG pathway-enrichment analysis. Our results showed that the antigen presentation pathway involved in protein processing in endoplasmic reticulum and antigen processing and presentation was markedly altered in the high-risk group, which might promote tumor immune evasion and associate with poor clinical outcomes in BC patients with high risk scores. In conclusion, we aimed to take advantage of bioinformatics analyses to explore immune−related lncRNAs, which could function as prognostic indicators and promising therapeutic targets for BC patients. Frontiers Media S.A. 2020-07-07 /pmc/articles/PMC7358358/ /pubmed/32733537 http://dx.doi.org/10.3389/fgene.2020.00680 Text en Copyright © 2020 Li, Li, Wang and Yang. http://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 | Genetics Li, Zheng Li, Yaming Wang, Xiaolong Yang, Qifeng Identification of a Six-Immune-Related Long Non-coding RNA Signature for Predicting Survival and Immune Infiltrating Status in Breast Cancer |
title | Identification of a Six-Immune-Related Long Non-coding RNA Signature for Predicting Survival and Immune Infiltrating Status in Breast Cancer |
title_full | Identification of a Six-Immune-Related Long Non-coding RNA Signature for Predicting Survival and Immune Infiltrating Status in Breast Cancer |
title_fullStr | Identification of a Six-Immune-Related Long Non-coding RNA Signature for Predicting Survival and Immune Infiltrating Status in Breast Cancer |
title_full_unstemmed | Identification of a Six-Immune-Related Long Non-coding RNA Signature for Predicting Survival and Immune Infiltrating Status in Breast Cancer |
title_short | Identification of a Six-Immune-Related Long Non-coding RNA Signature for Predicting Survival and Immune Infiltrating Status in Breast Cancer |
title_sort | identification of a six-immune-related long non-coding rna signature for predicting survival and immune infiltrating status in breast cancer |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7358358/ https://www.ncbi.nlm.nih.gov/pubmed/32733537 http://dx.doi.org/10.3389/fgene.2020.00680 |
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