Evidence map›Paper›PMID 40153109›Full record

ArticleDiscover oncology2025

Construction and validation of a reliable disulfidptosis-related lncRNAs signature of the subtype, prognostic, and immune landscape in bladder cancer.

Xiaoping Leng, Han Chen, Gang Chen

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Article in Discover oncology, 2025. 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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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Xiaoping LengDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Yuzhong District, Chongqing, 400016, China.
Han ChenDepartment of Urological Oncology Surgery, Chongqing University Cancer Hospital (Chongqing Cancer Institute & Chongqing Cancer Hospital), Chongqing, China.
Gang ChenDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Yuzhong District, Chongqing, 400016, China. chengang_urology@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBladder cancer (BLCA) is one of the most frequently-diagnosed tumors globally. Disulfidptosis represents a critical framework for cell death mechanism in cancer therapy. Our study constructed a predictive model utilizing disulfidptosis-related lncRNAs (DRLs) to provide value in evaluating diagnosis, drug sensibility, and prognosis of BLCA patients.

methodsThe study data of BLCA patients retrieved from TCGA-BLCA database. Cox and LASSO regression analysis were used to identify DRLs. Kaplan-Meier survival analysis, ROC curve, and nomograms were constructed to assess and forecast survival events. GSEA were performed to illustrate relevant enrichments results. Tumor mutation burden (TMB), immune status, and drug sensitivity were assessed. Muscle invasive bladder cancer (MIBC) tumor and tumor-adjacent normal tissues samples were collected in our department to validate the DRLs expression levels by RT-PCR.

resultsOverall, nine DRLs (AL590428.1, LSAMP-AS1, LINC01184, LINC-PINT, AC023825.2, AC010331.1, AC009716.1, AC104785.1, AC008764.6) were identified. These DRLs were used to calculate risk scores and create a prognostic model. ROC revealed higher diagnostic efficiency of the model than other clinical characteristics. Nomogram was constructed using the risk scores, age, and tumor stage, which showed excellent predictive power and was verified by calibration graph. BLCA patients were further classified into high-risk group and low-risk group using median risk score as the cut-off value. The high-risk group showed lesser TMB levels and developed worse prognosis. GSEA of the high-risk group identified pathways associated with BLCA progression such as WNT signaling pathway. Immune cells including CD4

conclusionBased on this study, it would be advisable to identify the key DRLs with potential prognostic value in BLCA to enhance the evaluation of clinical outcomes in this context.

Indexed as

Bladder cancerDisulfidptosisImmunotherapylncRNASignature

Identifiers

PMID40153109
PMCPMC11953504

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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.