Evidence map›Paper›PMID 38319718›Full record

ArticleAging2024

Construction of a necroptosis-related lncRNA signature for predicting prognosis and revealing the immune microenvironment in bladder cancer.

Jingsong Wang, Zhengyu Jiang, Kai Wang, Qingyuan Zheng, Jun Jian, Xiuheng Liu, Zhiyuan Chen, Rui Yang, Lei Wang

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Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Jingsong WangDepartment of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China.
Zhengyu JiangDepartment of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China.
Kai WangDepartment of Urology, People’s Hospital of Hanchuan City, Xiaogan, Hubei 432300, China.
Qingyuan ZhengDepartment of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China.
Jun JianDepartment of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China.
Xiuheng LiuDepartment of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China.
Zhiyuan ChenDepartment of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China.
Rui YangDepartment of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China.
Lei WangDepartment of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBladder cancer (BCa) is a common malignancy in the urinary system. Necroptosis, a recently discovered form of programmed cell death, is closely associated with the development and progression of various types of tumors. Targeting necroptosis through anti-cancer strategies has shown potential as a therapy for cancer. We aimed to develop a necroptosis-related lncRNAs (NRlncRNAs) risk model that can predict the survival and tumor immunity of BCa patients.

methodsWe analyzed sequencing data obtained from the TCGA database, and applied least absolute shrinkage and selection operator (LASSO) and Cox regression analysis to identify crucial NRlncRNAs for building a risk model. Using the risk score, we categorized patients into high- and low-risk groups, and assessed the accuracy with the area under the receiver operating characteristic (AUROC) and Kaplan-Meier curves. We performed the RT-qPCR to detect the expression differences of the genes based on the risk model.

resultsWe identified a total of 296 NRlncRNAs, and 6 of them were included in the prognostic model. The AUC values for 1-, 3-, and 5-year predictions were 0.675, 0.726 and 0.734, respectively. Our risk model demonstrated excellent predictive performance and served as an independent predictor with high predictive power. Additionally, we performed PCA, TMB, GSEA analyses, and evaluated immune cell infiltration, to reveal significant differences between the high- and low-risk groups in functional signaling pathways, immunological status, and mutation profiles. Finally, we assessed the chemotherapeutic response of several drugs. According to the RT-qPCR results, we found that four NRlncRNAs of the risk model were more highly expressed in BCa cell lines than human immortalized uroepithelial cell line and regulated the occurrence and progression of bladder cancer.

conclusionWe constructed a novel NRlncRNAs-associated risk model, which could predict the prognosis and immune response of BCa patients.

Indexed as

RNA, Long NoncodingUrinary Bladder NeoplasmsApoptosisHumansNecroptosisPrognosisTumor MicroenvironmentRNA, Long Noncodingbladder cancerchemotherapeutic responseimmune microenvironmentlncRNA signaturenecroptosissurvival

Identifiers

PMID38319718
PMCPMC10911338

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.