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A New Prognostic Signature Constructed with Necroptosis-Related lncRNA in Bladder Cancer

BACKGROUND: Bladder cancer (BC) accounts for the most common urologic malignancy, leading to a heavy social burden over the world. We aim to search for a novel prognostic biomarker with necroptosis-related lncRNAs of bladder cancer in this study. METHODS: We download the RNA-sequencing data and corr...

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Detalles Bibliográficos
Autores principales: Yu, Zuhu, Lu, Bin, Gao, Hong, Liang, Rongfang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681547/
https://www.ncbi.nlm.nih.gov/pubmed/36425941
http://dx.doi.org/10.1155/2022/5643496
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author Yu, Zuhu
Lu, Bin
Gao, Hong
Liang, Rongfang
author_facet Yu, Zuhu
Lu, Bin
Gao, Hong
Liang, Rongfang
author_sort Yu, Zuhu
collection PubMed
description BACKGROUND: Bladder cancer (BC) accounts for the most common urologic malignancy, leading to a heavy social burden over the world. We aim to search for a novel prognostic biomarker with necroptosis-related lncRNAs of bladder cancer in this study. METHODS: We download the RNA-sequencing data and corresponding clinical information of BC patients from TCGA. We performed Pearson correlation analysis to identify necroptosis-related lncRNAs (NRlncRNAs). Then, we used univariate Cox regression, Lasso Cox analysis, and multivariate Cox regression to construct the optimal prognostic model. Next, we used Kaplan–Meier curves, Cox regression, receiver operating characteristic (ROC) curves, nomogram, and stratified survival analysis to evaluate the capacity of the prognostic signature. Furthermore, gene set enrichments in the signature and the correlation between prognostic signature and necroptosis genes, tumor microenvironment, immune infiltration, and immune checkpoints of BC were also explored. RESULTS: A 7-NRlncRNAs signature comprising FKBP14-AS1, AL731567.1, LINC02178, AC011503.2, LINC02195, AC068196.1, and AL136084.2 was constructed to predict the prognosis of BC in this research. Cox regression analysis showed that the signature could be an independent prognostic factor for BC patients (P < 0.001). Compared to other clinicopathological characteristics, this signature displayed a better capacity of prediction with the area under the curve (AUC) of 0.745. Stratified analysis using various clinical variables demonstrated that the prognostic signature has good clinical fitness. GSEA showed that focal adhesion and the WNT signaling pathway were enriched in the high-risk group. Immune infiltration analysis indicated that the signature was significantly inversely correlated with infiltration of CD8(+) T cells and CD4(+) T cells while positively correlated with macrophages and cancer associated fibroblasts. Immune checkpoint analysis revealed that the expressions of protective factors were significantly lower in the high-risk group, while expressions of cancer promotors were significantly higher in this group. The gene expression analysis displayed that necroptosis genes such as FADD, FAS, MYC, STAT3, PLK1, LEF1, EGFR, RIPK3, CASP8, BRAF, ID1, GATA3, MYCN, CD40, and TNFRSF21 were significantly different between the two groups. CONCLUSIONS: The 7-NRlncRNAs signature can predict the overall survival of BC and may provide help for the individualized treatment of BC patients.
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spelling pubmed-96815472022-11-23 A New Prognostic Signature Constructed with Necroptosis-Related lncRNA in Bladder Cancer Yu, Zuhu Lu, Bin Gao, Hong Liang, Rongfang J Oncol Research Article BACKGROUND: Bladder cancer (BC) accounts for the most common urologic malignancy, leading to a heavy social burden over the world. We aim to search for a novel prognostic biomarker with necroptosis-related lncRNAs of bladder cancer in this study. METHODS: We download the RNA-sequencing data and corresponding clinical information of BC patients from TCGA. We performed Pearson correlation analysis to identify necroptosis-related lncRNAs (NRlncRNAs). Then, we used univariate Cox regression, Lasso Cox analysis, and multivariate Cox regression to construct the optimal prognostic model. Next, we used Kaplan–Meier curves, Cox regression, receiver operating characteristic (ROC) curves, nomogram, and stratified survival analysis to evaluate the capacity of the prognostic signature. Furthermore, gene set enrichments in the signature and the correlation between prognostic signature and necroptosis genes, tumor microenvironment, immune infiltration, and immune checkpoints of BC were also explored. RESULTS: A 7-NRlncRNAs signature comprising FKBP14-AS1, AL731567.1, LINC02178, AC011503.2, LINC02195, AC068196.1, and AL136084.2 was constructed to predict the prognosis of BC in this research. Cox regression analysis showed that the signature could be an independent prognostic factor for BC patients (P < 0.001). Compared to other clinicopathological characteristics, this signature displayed a better capacity of prediction with the area under the curve (AUC) of 0.745. Stratified analysis using various clinical variables demonstrated that the prognostic signature has good clinical fitness. GSEA showed that focal adhesion and the WNT signaling pathway were enriched in the high-risk group. Immune infiltration analysis indicated that the signature was significantly inversely correlated with infiltration of CD8(+) T cells and CD4(+) T cells while positively correlated with macrophages and cancer associated fibroblasts. Immune checkpoint analysis revealed that the expressions of protective factors were significantly lower in the high-risk group, while expressions of cancer promotors were significantly higher in this group. The gene expression analysis displayed that necroptosis genes such as FADD, FAS, MYC, STAT3, PLK1, LEF1, EGFR, RIPK3, CASP8, BRAF, ID1, GATA3, MYCN, CD40, and TNFRSF21 were significantly different between the two groups. CONCLUSIONS: The 7-NRlncRNAs signature can predict the overall survival of BC and may provide help for the individualized treatment of BC patients. Hindawi 2022-11-15 /pmc/articles/PMC9681547/ /pubmed/36425941 http://dx.doi.org/10.1155/2022/5643496 Text en Copyright © 2022 Zuhu Yu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yu, Zuhu
Lu, Bin
Gao, Hong
Liang, Rongfang
A New Prognostic Signature Constructed with Necroptosis-Related lncRNA in Bladder Cancer
title A New Prognostic Signature Constructed with Necroptosis-Related lncRNA in Bladder Cancer
title_full A New Prognostic Signature Constructed with Necroptosis-Related lncRNA in Bladder Cancer
title_fullStr A New Prognostic Signature Constructed with Necroptosis-Related lncRNA in Bladder Cancer
title_full_unstemmed A New Prognostic Signature Constructed with Necroptosis-Related lncRNA in Bladder Cancer
title_short A New Prognostic Signature Constructed with Necroptosis-Related lncRNA in Bladder Cancer
title_sort new prognostic signature constructed with necroptosis-related lncrna in bladder cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681547/
https://www.ncbi.nlm.nih.gov/pubmed/36425941
http://dx.doi.org/10.1155/2022/5643496
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