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m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer
BACKGROUND: N6-methyladenosine (m6A) related long noncoding RNAs (lncRNAs) may have prognostic value in bladder cancer for their key role in tumorigenesis and innate immunity. METHODS: Bladder cancer transcriptome data and the corresponding clinical data were acquired from the Cancer Genome Atlas (T...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617388/ https://www.ncbi.nlm.nih.gov/pubmed/36309694 http://dx.doi.org/10.1186/s12967-022-03711-1 |
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author | Feng, Zi-Hao Liang, Yan-Ping Cen, Jun-Jie Yao, Hao-Hua Lin, Hai-Shan Li, Jia-Ying Liang, Hui Wang, Zhu Deng, Qiong Cao, Jia-Zheng Huang, Yong Wei, Jin-Huan Luo, Jun-Hang Chen, Wei Chen, Zhen-Hua |
author_facet | Feng, Zi-Hao Liang, Yan-Ping Cen, Jun-Jie Yao, Hao-Hua Lin, Hai-Shan Li, Jia-Ying Liang, Hui Wang, Zhu Deng, Qiong Cao, Jia-Zheng Huang, Yong Wei, Jin-Huan Luo, Jun-Hang Chen, Wei Chen, Zhen-Hua |
author_sort | Feng, Zi-Hao |
collection | PubMed |
description | BACKGROUND: N6-methyladenosine (m6A) related long noncoding RNAs (lncRNAs) may have prognostic value in bladder cancer for their key role in tumorigenesis and innate immunity. METHODS: Bladder cancer transcriptome data and the corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. The m6A-immune-related lncRNAs were identified using univariate Cox regression analysis and Pearson correlation analysis. A risk model was established using least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and analyzed using nomogram, time-dependent receiver operating characteristics (ROC) and Kaplan–Meier survival analysis. The differences in infiltration scores, clinical features, and sensitivity to Talazoparib of various immune cells between low- and high-risk groups were investigated. RESULTS: Totally 618 m6A-immune-related lncRNAs and 490 immune-related lncRNAs were identified from TCGA, and 47 lncRNAs of their intersection demonstrated prognostic values. A risk model with 11 lncRNAs was established by Lasso Cox regression, and can predict the prognosis of bladder cancer patients as demonstrated by time-dependent ROC and Kaplan–Meier analysis. Significant correlations were determined between risk score and tumor malignancy or immune cell infiltration. Meanwhile, significant differences were observed in tumor mutation burden and stemness-score between the low-risk group and high-risk group. Moreover, high-risk group patients were more responsive to Talazoparib. CONCLUSIONS: An m6A-immune-related lncRNA risk model was established in this study, which can be applied to predict prognosis, immune landscape and chemotherapeutic response in bladder cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03711-1. |
format | Online Article Text |
id | pubmed-9617388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96173882022-10-30 m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer Feng, Zi-Hao Liang, Yan-Ping Cen, Jun-Jie Yao, Hao-Hua Lin, Hai-Shan Li, Jia-Ying Liang, Hui Wang, Zhu Deng, Qiong Cao, Jia-Zheng Huang, Yong Wei, Jin-Huan Luo, Jun-Hang Chen, Wei Chen, Zhen-Hua J Transl Med Research BACKGROUND: N6-methyladenosine (m6A) related long noncoding RNAs (lncRNAs) may have prognostic value in bladder cancer for their key role in tumorigenesis and innate immunity. METHODS: Bladder cancer transcriptome data and the corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. The m6A-immune-related lncRNAs were identified using univariate Cox regression analysis and Pearson correlation analysis. A risk model was established using least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and analyzed using nomogram, time-dependent receiver operating characteristics (ROC) and Kaplan–Meier survival analysis. The differences in infiltration scores, clinical features, and sensitivity to Talazoparib of various immune cells between low- and high-risk groups were investigated. RESULTS: Totally 618 m6A-immune-related lncRNAs and 490 immune-related lncRNAs were identified from TCGA, and 47 lncRNAs of their intersection demonstrated prognostic values. A risk model with 11 lncRNAs was established by Lasso Cox regression, and can predict the prognosis of bladder cancer patients as demonstrated by time-dependent ROC and Kaplan–Meier analysis. Significant correlations were determined between risk score and tumor malignancy or immune cell infiltration. Meanwhile, significant differences were observed in tumor mutation burden and stemness-score between the low-risk group and high-risk group. Moreover, high-risk group patients were more responsive to Talazoparib. CONCLUSIONS: An m6A-immune-related lncRNA risk model was established in this study, which can be applied to predict prognosis, immune landscape and chemotherapeutic response in bladder cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-022-03711-1. BioMed Central 2022-10-29 /pmc/articles/PMC9617388/ /pubmed/36309694 http://dx.doi.org/10.1186/s12967-022-03711-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Feng, Zi-Hao Liang, Yan-Ping Cen, Jun-Jie Yao, Hao-Hua Lin, Hai-Shan Li, Jia-Ying Liang, Hui Wang, Zhu Deng, Qiong Cao, Jia-Zheng Huang, Yong Wei, Jin-Huan Luo, Jun-Hang Chen, Wei Chen, Zhen-Hua m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
title | m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
title_full | m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
title_fullStr | m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
title_full_unstemmed | m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
title_short | m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer |
title_sort | m6a-immune-related lncrna prognostic signature for predicting immune landscape and prognosis of bladder cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617388/ https://www.ncbi.nlm.nih.gov/pubmed/36309694 http://dx.doi.org/10.1186/s12967-022-03711-1 |
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