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Six-lncRNA Immune Prognostic Signature for Cervical Cancer
BACKGROUND: This study searched for immune-related long noncoding RNAs (lncRNAs) to predict the prognosis of patients with cervical cancer. METHOD: We obtained immunologically relevant lncRNA expression profiles and clinical follow-up data from cervical cancer patients from The Cancer Genome Atlas d...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591729/ https://www.ncbi.nlm.nih.gov/pubmed/33173530 http://dx.doi.org/10.3389/fgene.2020.533628 |
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author | Chen, Qian Hu, Lang Huang, Dongping Chen, Kaihua Qiu, Xiaoqiang Qiu, Bingqing |
author_facet | Chen, Qian Hu, Lang Huang, Dongping Chen, Kaihua Qiu, Xiaoqiang Qiu, Bingqing |
author_sort | Chen, Qian |
collection | PubMed |
description | BACKGROUND: This study searched for immune-related long noncoding RNAs (lncRNAs) to predict the prognosis of patients with cervical cancer. METHOD: We obtained immunologically relevant lncRNA expression profiles and clinical follow-up data from cervical cancer patients from The Cancer Genome Atlas database and the Molecular Signatures Database. Cervical cancer patients were randomly divided into a training group, testing group and combined group. The immune prognostic signature was constructed by Least Absolute Shrinkage and Selection Operator Cox regression, prognosis was analyzed by Kaplan–Meier curves between different groups, and the accuracy of the prognostic model was assessed by receiver operating characteristic-area under the curve (ROC-AUC) analysis. RESULTS: A six-lncRNA immune prognostic signature (LIPS) was constructed to predict the prognosis of cervical cancer. The six lncRNAs are as follows: AC009065.8, LINC01871, MIR210HG, GEMIN7-AS1, GAS5-AS1, and DLEU1. A ROC-AUC analysis indicated that the model could predict the prognosis of cervical cancer patients in different subgroups. A Kaplan–Meier analysis showed that patients with high risk scores had a poor prognosis; these results were equally meaningful in the subgroup analyses. Risk scores differed depending on the clinical pathology and tumor grade and were independent risk factors for cervical cancer prognosis. Gene set enrichment analysis revealed an association between the LIPS and the immune response, Wnt signaling pathway, and TGF beta signaling pathway. CONCLUSION: Our study shows that the six-LIPS can predict the prognosis of cervical cancer and contribute to decisions regarding the immunotherapeutic strategy. |
format | Online Article Text |
id | pubmed-7591729 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75917292020-11-09 Six-lncRNA Immune Prognostic Signature for Cervical Cancer Chen, Qian Hu, Lang Huang, Dongping Chen, Kaihua Qiu, Xiaoqiang Qiu, Bingqing Front Genet Genetics BACKGROUND: This study searched for immune-related long noncoding RNAs (lncRNAs) to predict the prognosis of patients with cervical cancer. METHOD: We obtained immunologically relevant lncRNA expression profiles and clinical follow-up data from cervical cancer patients from The Cancer Genome Atlas database and the Molecular Signatures Database. Cervical cancer patients were randomly divided into a training group, testing group and combined group. The immune prognostic signature was constructed by Least Absolute Shrinkage and Selection Operator Cox regression, prognosis was analyzed by Kaplan–Meier curves between different groups, and the accuracy of the prognostic model was assessed by receiver operating characteristic-area under the curve (ROC-AUC) analysis. RESULTS: A six-lncRNA immune prognostic signature (LIPS) was constructed to predict the prognosis of cervical cancer. The six lncRNAs are as follows: AC009065.8, LINC01871, MIR210HG, GEMIN7-AS1, GAS5-AS1, and DLEU1. A ROC-AUC analysis indicated that the model could predict the prognosis of cervical cancer patients in different subgroups. A Kaplan–Meier analysis showed that patients with high risk scores had a poor prognosis; these results were equally meaningful in the subgroup analyses. Risk scores differed depending on the clinical pathology and tumor grade and were independent risk factors for cervical cancer prognosis. Gene set enrichment analysis revealed an association between the LIPS and the immune response, Wnt signaling pathway, and TGF beta signaling pathway. CONCLUSION: Our study shows that the six-LIPS can predict the prognosis of cervical cancer and contribute to decisions regarding the immunotherapeutic strategy. Frontiers Media S.A. 2020-10-14 /pmc/articles/PMC7591729/ /pubmed/33173530 http://dx.doi.org/10.3389/fgene.2020.533628 Text en Copyright © 2020 Chen, Hu, Huang, Chen, Qiu and Qiu. 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 Chen, Qian Hu, Lang Huang, Dongping Chen, Kaihua Qiu, Xiaoqiang Qiu, Bingqing Six-lncRNA Immune Prognostic Signature for Cervical Cancer |
title | Six-lncRNA Immune Prognostic Signature for Cervical Cancer |
title_full | Six-lncRNA Immune Prognostic Signature for Cervical Cancer |
title_fullStr | Six-lncRNA Immune Prognostic Signature for Cervical Cancer |
title_full_unstemmed | Six-lncRNA Immune Prognostic Signature for Cervical Cancer |
title_short | Six-lncRNA Immune Prognostic Signature for Cervical Cancer |
title_sort | six-lncrna immune prognostic signature for cervical cancer |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591729/ https://www.ncbi.nlm.nih.gov/pubmed/33173530 http://dx.doi.org/10.3389/fgene.2020.533628 |
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