A comprehensive risk model of disulfidoptosis-related lncRNAs predicts prognosis and therapeutic implications in bladder cancer

Background: Disulfidoptosis is an emerging form of regulated cell death; however, the roles of its associated long non-coding RNAs (dr-lncRNAs) in bladder cancer (BLCA) remain poorly characterized. By leveraging the most comprehensive curated dataset of disulfidoptosis-related genes to date, we syst...

Full description

Saved in:
Bibliographic Details
Main Authors: Zhixiong Zhang, Jinghua Zhong, Muhammad Sarfaraz Iqbal, Zhiwen Zeng, Xiaolu Duan
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Biochemistry and Biophysics Reports
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2405580825001475
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850246419157352448
author Zhixiong Zhang
Jinghua Zhong
Muhammad Sarfaraz Iqbal
Zhiwen Zeng
Xiaolu Duan
author_facet Zhixiong Zhang
Jinghua Zhong
Muhammad Sarfaraz Iqbal
Zhiwen Zeng
Xiaolu Duan
author_sort Zhixiong Zhang
collection DOAJ
description Background: Disulfidoptosis is an emerging form of regulated cell death; however, the roles of its associated long non-coding RNAs (dr-lncRNAs) in bladder cancer (BLCA) remain poorly characterized. By leveraging the most comprehensive curated dataset of disulfidoptosis-related genes to date, we systematically developed and validated a novel dr-lncRNA signature that elucidates the prognostic significance and immune microenvironmental dynamics in BLCA. Methods: The Cancer Genome Atlas (TCGA) database was utilized to extract significant clinical and RNA sequencing data of BLCA patients. Cox and Lasso regression with several variables was used to create a risk model. ROC, Kaplan-Meier, and nomogram analyses were carefully reviewed for validity. The validated study evaluated intricate interactions between functional enrichment, immune cell infiltration, cancer mutation load, and treatment sensitivity. Unsupervised consensus clustering identified subgroup patterns that reflected immune system alterations, medication susceptibility, and prognosis. Results: Nine lncRNAs significantly correlated with prognosis were collectively identified, subsequently forming the basis for constructing a risk model consisting of seven lncRNAs. The model exhibited significant superiority in predicting patient outcomes, effectively distinguishing between high-risk from low-risk individuals. Functional enrichment analysis uncovered their potential involvement in immune-related biological pathways. Patients in the high-risk group exhibited higher tumor mutation burdens, more active immune functions and a higher sensitivity to chemotherapeutic drugs. Variations among BLCA subgroups were identified by consensus cluster analysis, including clinical characteristics, prognosis, lncRNA expression, immune cell infiltration, and immune checkpoint profiles. Conclusion: The dr-lncRNAs-based risk model presents a promising tool for predicting prognosis and guiding personalized immunotherapy and treatment strategies in BLCA patients.
format Article
id doaj-art-0b80e3679378442e97cbd2646d19a28c
institution OA Journals
issn 2405-5808
language English
publishDate 2025-06-01
publisher Elsevier
record_format Article
series Biochemistry and Biophysics Reports
spelling doaj-art-0b80e3679378442e97cbd2646d19a28c2025-08-20T01:59:13ZengElsevierBiochemistry and Biophysics Reports2405-58082025-06-014210206010.1016/j.bbrep.2025.102060A comprehensive risk model of disulfidoptosis-related lncRNAs predicts prognosis and therapeutic implications in bladder cancerZhixiong Zhang0Jinghua Zhong1Muhammad Sarfaraz Iqbal2Zhiwen Zeng3Xiaolu Duan4Department of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangdong Provincial Key Laboratory of Urology, Guangdong Engineering Research Center of Urinary Minimally Invasive Surgery Robot and Intelligent Equipment, Guangzhou Institute of Urology, ChinaDepartment of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangdong Provincial Key Laboratory of Urology, Guangdong Engineering Research Center of Urinary Minimally Invasive Surgery Robot and Intelligent Equipment, Guangzhou Institute of Urology, ChinaDepartment of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangdong Provincial Key Laboratory of Urology, Guangdong Engineering Research Center of Urinary Minimally Invasive Surgery Robot and Intelligent Equipment, Guangzhou Institute of Urology, ChinaDepartment for Bipolar Disorders, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen, 518020, China; Corresponding author. No. 1080 Cuizhu Road, Luohu District, Shenzhen, Guangdong 518020, China.Department of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangdong Provincial Key Laboratory of Urology, Guangdong Engineering Research Center of Urinary Minimally Invasive Surgery Robot and Intelligent Equipment, Guangzhou Institute of Urology, China; Corresponding author. Kangda Road 1#, Haizhu District, Guangzhou, Guangdong, 510230, China.Background: Disulfidoptosis is an emerging form of regulated cell death; however, the roles of its associated long non-coding RNAs (dr-lncRNAs) in bladder cancer (BLCA) remain poorly characterized. By leveraging the most comprehensive curated dataset of disulfidoptosis-related genes to date, we systematically developed and validated a novel dr-lncRNA signature that elucidates the prognostic significance and immune microenvironmental dynamics in BLCA. Methods: The Cancer Genome Atlas (TCGA) database was utilized to extract significant clinical and RNA sequencing data of BLCA patients. Cox and Lasso regression with several variables was used to create a risk model. ROC, Kaplan-Meier, and nomogram analyses were carefully reviewed for validity. The validated study evaluated intricate interactions between functional enrichment, immune cell infiltration, cancer mutation load, and treatment sensitivity. Unsupervised consensus clustering identified subgroup patterns that reflected immune system alterations, medication susceptibility, and prognosis. Results: Nine lncRNAs significantly correlated with prognosis were collectively identified, subsequently forming the basis for constructing a risk model consisting of seven lncRNAs. The model exhibited significant superiority in predicting patient outcomes, effectively distinguishing between high-risk from low-risk individuals. Functional enrichment analysis uncovered their potential involvement in immune-related biological pathways. Patients in the high-risk group exhibited higher tumor mutation burdens, more active immune functions and a higher sensitivity to chemotherapeutic drugs. Variations among BLCA subgroups were identified by consensus cluster analysis, including clinical characteristics, prognosis, lncRNA expression, immune cell infiltration, and immune checkpoint profiles. Conclusion: The dr-lncRNAs-based risk model presents a promising tool for predicting prognosis and guiding personalized immunotherapy and treatment strategies in BLCA patients.http://www.sciencedirect.com/science/article/pii/S2405580825001475Bladder cancerDisulfidoptosisLong non-coding RNAPrognostic modelPersonalized treatment
spellingShingle Zhixiong Zhang
Jinghua Zhong
Muhammad Sarfaraz Iqbal
Zhiwen Zeng
Xiaolu Duan
A comprehensive risk model of disulfidoptosis-related lncRNAs predicts prognosis and therapeutic implications in bladder cancer
Biochemistry and Biophysics Reports
Bladder cancer
Disulfidoptosis
Long non-coding RNA
Prognostic model
Personalized treatment
title A comprehensive risk model of disulfidoptosis-related lncRNAs predicts prognosis and therapeutic implications in bladder cancer
title_full A comprehensive risk model of disulfidoptosis-related lncRNAs predicts prognosis and therapeutic implications in bladder cancer
title_fullStr A comprehensive risk model of disulfidoptosis-related lncRNAs predicts prognosis and therapeutic implications in bladder cancer
title_full_unstemmed A comprehensive risk model of disulfidoptosis-related lncRNAs predicts prognosis and therapeutic implications in bladder cancer
title_short A comprehensive risk model of disulfidoptosis-related lncRNAs predicts prognosis and therapeutic implications in bladder cancer
title_sort comprehensive risk model of disulfidoptosis related lncrnas predicts prognosis and therapeutic implications in bladder cancer
topic Bladder cancer
Disulfidoptosis
Long non-coding RNA
Prognostic model
Personalized treatment
url http://www.sciencedirect.com/science/article/pii/S2405580825001475
work_keys_str_mv AT zhixiongzhang acomprehensiveriskmodelofdisulfidoptosisrelatedlncrnaspredictsprognosisandtherapeuticimplicationsinbladdercancer
AT jinghuazhong acomprehensiveriskmodelofdisulfidoptosisrelatedlncrnaspredictsprognosisandtherapeuticimplicationsinbladdercancer
AT muhammadsarfaraziqbal acomprehensiveriskmodelofdisulfidoptosisrelatedlncrnaspredictsprognosisandtherapeuticimplicationsinbladdercancer
AT zhiwenzeng acomprehensiveriskmodelofdisulfidoptosisrelatedlncrnaspredictsprognosisandtherapeuticimplicationsinbladdercancer
AT xiaoluduan acomprehensiveriskmodelofdisulfidoptosisrelatedlncrnaspredictsprognosisandtherapeuticimplicationsinbladdercancer
AT zhixiongzhang comprehensiveriskmodelofdisulfidoptosisrelatedlncrnaspredictsprognosisandtherapeuticimplicationsinbladdercancer
AT jinghuazhong comprehensiveriskmodelofdisulfidoptosisrelatedlncrnaspredictsprognosisandtherapeuticimplicationsinbladdercancer
AT muhammadsarfaraziqbal comprehensiveriskmodelofdisulfidoptosisrelatedlncrnaspredictsprognosisandtherapeuticimplicationsinbladdercancer
AT zhiwenzeng comprehensiveriskmodelofdisulfidoptosisrelatedlncrnaspredictsprognosisandtherapeuticimplicationsinbladdercancer
AT xiaoluduan comprehensiveriskmodelofdisulfidoptosisrelatedlncrnaspredictsprognosisandtherapeuticimplicationsinbladdercancer