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A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma

OBJECTIVE: Many studies have drawn their attention to the immunotherapy of bladder urothelial carcinoma in terms of immunologic mechanisms of human body. These include immunogenicity of the tumor cells and involvement of long non-coding RNA (lncRNA). We constructed a necroptosis-related long noncodi...

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Autores principales: Hou, Jian, Lu, Zhenquan, Dong, Runan, Wu, Guoqing, Nie, Haibo, Yang, Guang, Tang, Cheng, Qu, Genyi, Xu, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270023/
https://www.ncbi.nlm.nih.gov/pubmed/35814472
http://dx.doi.org/10.3389/fonc.2022.928204
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author Hou, Jian
Lu, Zhenquan
Dong, Runan
Wu, Guoqing
Nie, Haibo
Yang, Guang
Tang, Cheng
Qu, Genyi
Xu, Yong
author_facet Hou, Jian
Lu, Zhenquan
Dong, Runan
Wu, Guoqing
Nie, Haibo
Yang, Guang
Tang, Cheng
Qu, Genyi
Xu, Yong
author_sort Hou, Jian
collection PubMed
description OBJECTIVE: Many studies have drawn their attention to the immunotherapy of bladder urothelial carcinoma in terms of immunologic mechanisms of human body. These include immunogenicity of the tumor cells and involvement of long non-coding RNA (lncRNA). We constructed a necroptosis-related long noncoding RNA (nrlncRNA) risk factor model to predict BLCA outcomes and calculate correlations with chemosensitivity and immune infiltration. METHODS: Transcriptomic data from BLCA specimens were accessed from The Cancer Genome Atlas, and nrlncRNAs were identified by performing co-expression analysis. Univariate analysis was performed to identify differentially expressed nrlncRNA pairs. We constructed least absolute contraction and selector operation regression models and drew receiver operating characteristic curves for 1-, 3-, and 5-year survival rates. Akaike information criterion (AIC) values for survival over 1 year were determined as cutoff values in high- and low-risk subgroups. We reassessed the differences between subgroups in terms of survival, clinicopathological characteristics, chemotherapy efficacy, tumor-infiltrating immune cells, and markers of immunosuppression. RESULTS: We identified a total of 260 necroptosis-related lncRNA pairs, of which we incorporated 13 into the prognostic model. Areas under the curve of 1-, 3-, and 5- year survival time were 0.763, 0.836, and 0.842, respectively. We confirmed the excellent predictive performance of the risk model. Based on AIC values, we confirmed that the high-risk group was susceptible to unfavorable outcomes. The risk scores correlated with survival were age, clinical stage, grade, and tumor node metastases. The risk model was an independent predictor and demonstrated higher predictive power. The risk model can also be utilized to determine immune cell infiltration status, expression levels of immune checkpoint genes, and the sensitivity to cisplatin, doxorubicin, and methotrexate. CONCLUSION: We constructed a novel necroptosis-related signature that predicts BLCA outcomes and performs satisfactorily in the immune landscape and chemotherapeutic responses.
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spelling pubmed-92700232022-07-09 A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma Hou, Jian Lu, Zhenquan Dong, Runan Wu, Guoqing Nie, Haibo Yang, Guang Tang, Cheng Qu, Genyi Xu, Yong Front Oncol Oncology OBJECTIVE: Many studies have drawn their attention to the immunotherapy of bladder urothelial carcinoma in terms of immunologic mechanisms of human body. These include immunogenicity of the tumor cells and involvement of long non-coding RNA (lncRNA). We constructed a necroptosis-related long noncoding RNA (nrlncRNA) risk factor model to predict BLCA outcomes and calculate correlations with chemosensitivity and immune infiltration. METHODS: Transcriptomic data from BLCA specimens were accessed from The Cancer Genome Atlas, and nrlncRNAs were identified by performing co-expression analysis. Univariate analysis was performed to identify differentially expressed nrlncRNA pairs. We constructed least absolute contraction and selector operation regression models and drew receiver operating characteristic curves for 1-, 3-, and 5-year survival rates. Akaike information criterion (AIC) values for survival over 1 year were determined as cutoff values in high- and low-risk subgroups. We reassessed the differences between subgroups in terms of survival, clinicopathological characteristics, chemotherapy efficacy, tumor-infiltrating immune cells, and markers of immunosuppression. RESULTS: We identified a total of 260 necroptosis-related lncRNA pairs, of which we incorporated 13 into the prognostic model. Areas under the curve of 1-, 3-, and 5- year survival time were 0.763, 0.836, and 0.842, respectively. We confirmed the excellent predictive performance of the risk model. Based on AIC values, we confirmed that the high-risk group was susceptible to unfavorable outcomes. The risk scores correlated with survival were age, clinical stage, grade, and tumor node metastases. The risk model was an independent predictor and demonstrated higher predictive power. The risk model can also be utilized to determine immune cell infiltration status, expression levels of immune checkpoint genes, and the sensitivity to cisplatin, doxorubicin, and methotrexate. CONCLUSION: We constructed a novel necroptosis-related signature that predicts BLCA outcomes and performs satisfactorily in the immune landscape and chemotherapeutic responses. Frontiers Media S.A. 2022-06-24 /pmc/articles/PMC9270023/ /pubmed/35814472 http://dx.doi.org/10.3389/fonc.2022.928204 Text en Copyright © 2022 Hou, Lu, Dong, Wu, Nie, Yang, Tang, Qu and Xu https://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 Oncology
Hou, Jian
Lu, Zhenquan
Dong, Runan
Wu, Guoqing
Nie, Haibo
Yang, Guang
Tang, Cheng
Qu, Genyi
Xu, Yong
A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma
title A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma
title_full A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma
title_fullStr A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma
title_full_unstemmed A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma
title_short A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma
title_sort necroptosis-related lncrna to develop a signature to predict the outcome, immune landscape, and chemotherapeutic responses in bladder urothelial carcinoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270023/
https://www.ncbi.nlm.nih.gov/pubmed/35814472
http://dx.doi.org/10.3389/fonc.2022.928204
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