Prognostic value and immune landscapes of disulfidptosis‑related lncRNAs in bladder cancer

Liu,Yijiang; Tao,Huijing; Jia,Shengjun; Wang,Haozheng; Guo,Long; Hu,Zhuozheng; Zhang,Wenxiong; Liu,Fei

doi:10.3892/mco.2024.2814

Prognostic value and immune landscapes of disulfidptosis‑related lncRNAs in bladder cancer

Authors:
- Yijiang Liu
- Huijing Tao
- Shengjun Jia
- Haozheng Wang
- Long Guo
- Zhuozheng Hu
- Wenxiong Zhang
- Fei Liu
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Affiliations: Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China, Department of Urology Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
Published online on: December 13, 2024 https://doi.org/10.3892/mco.2024.2814
Article Number: 19
Copyright: © Liu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Disulfidptosis, which was recently identified, has shown promise as a potential cancer treatment. Nonetheless, the precise role of long non‑coding RNAs (lncRNAs) in this phenomenon is currently unclear. To elucidate their significance in bladder cancer (BLCA), a signature of disulfidptosis‑related lncRNAs (DRlncRNAs) was developed and their potential prognostic significance was explored. BLCA sample data were sourced from The Cancer Genome Atlas. A predictive signature comprising DRlncRNAs was formulated and subsequently validated. The combination of this signature with clinical characteristics facilitated the development of a nomogram with practical clinical utility. Additionally, enrichment analysis was conducted, the tumor microenvironment (TME) was assessed, the tumor mutational burden (TMB) was analyzed, and drug sensitivity was explored. Reverse transcription‑quantitative PCR (RT‑qPCR) was utilized to quantify lncRNA expression. The results revealed an eight‑gene signature based on DRlncRNAs was established, and the predictive accuracy of the nomogram that incorporated the risk score [area under the curve (AUC)=0.733] outperformed the nomogram without it (AUC=0.703). High‑risk groups were associated with pathways such as WNT signaling, focal adhesion and cell cycle pathways. The TME study revealed that high‑risk patients had increased immune infiltration, whereas the TMB and tumor immune dysfunction and exclusion scores in low‑risk patients indicated a potentially robust immune response. Drug sensitivity analysis identified appropriate antitumor drugs for each group. RT‑qPCR experiments validated significant differences in DRlncRNAs expression between normal and BLCA cell lines. In conclusion, the prognostic risk signature, which includes the eight identified DRlncRNAs, demonstrates promise for predicting prognosis of patients with BLCA and guiding the selection of suitable immunotherapy and chemotherapy strategies.

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1	Siegel RL, Giaquinto AN and Jemal A: Cancer statistics, 2024. CA Cancer J Clin. 74:12–49. 2024.PubMed/NCBI View Article : Google Scholar
2	Witjes JA, Bruins HM, Cathomas R, Compérat EM, Cowan NC, Gakis G, Hernández V, Linares Espinós E, Lorch A, Neuzillet Y, et al: European association of urology guidelines on muscle-invasive and metastatic bladder cancer: Summary of the 2020 guidelines. Eur Urol. 79:82–104. 2021.PubMed/NCBI View Article : Google Scholar
3	Tran L, Xiao JF, Agarwal N, Duex JE and Theodorescu D: Advances in bladder cancer biology and therapy. Nat Rev Cancer. 21:104–121. 2021.PubMed/NCBI View Article : Google Scholar
4	Liu X, Nie L, Zhang Y, Yan Y, Wang C, Colic M, Olszewski K, Horbath A, Chen X, Lei G, et al: Actin cytoskeleton vulnerability to disulfide stress mediates disulfidptosis. Nat Cell Biol. 25:404–414. 2023.PubMed/NCBI View Article : Google Scholar
5	Meng Y, Chen X and Deng G: Disulfidptosis: A new form of regulated cell death for cancer treatment. Mol Biomed. 4(18)2023.PubMed/NCBI View Article : Google Scholar
6	Esteller M: Non-coding RNAs in human disease. Nat Rev Genet. 12:861–874. 2011.PubMed/NCBI View Article : Google Scholar
7	Fang Y and Fullwood MJ: Roles, functions, and mechanisms of long non-coding RNAs in cancer. Genomics Proteomics Bioinformatics. 14:42–54. 2016.PubMed/NCBI View Article : Google Scholar
8	Tan YT, Lin JF, Li T, Li JJ, Xu RH and Ju HQ: LncRNA-mediated posttranslational modifications and reprogramming of energy metabolism in cancer. Cancer Commun (Lond). 41:109–120. 2021.PubMed/NCBI View Article : Google Scholar
9	Liu Z, Liu L, Weng S, Guo C, Dang Q, Xu H, Wang L, Lu T, Zhang Y, Sun Z and Han X: Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer. Nat Commun. 13(816)2022.PubMed/NCBI View Article : Google Scholar
10	Liang YL, Zhang Y, Tan XR, Qiao H, Liu SR, Tang LL, Mao YP, Chen L, Li WF, Zhou GQ, et al: A lncRNA signature associated with tumor immune heterogeneity predicts distant metastasis in locoregionally advanced nasopharyngeal carcinoma. Nat Commun. 13(2996)2022.PubMed/NCBI View Article : Google Scholar
11	Huang Z, Zhou JK, Peng Y, He W and Huang C: The role of long noncoding RNAs in hepatocellular carcinoma. Mol Cancer. 19(77)2020.PubMed/NCBI View Article : Google Scholar
12	Hutter C and Zenklusen JC: The cancer genome atlas: Creating lasting value beyond its data. Cell. 173:283–285. 2018.PubMed/NCBI View Article : Google Scholar
13	Love MI, Huber W and Anders S: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15(550)2014.PubMed/NCBI View Article : Google Scholar
14	Duforet-Frebourg N, Luu K, Laval G, Bazin E and Blum MGB: Detecting genomic signatures of natural selection with principal component analysis: Application to the 1000 genomes data. Mol Biol Evol. 33:1082–1093. 2016.PubMed/NCBI View Article : Google Scholar
15	Liu L, Xie J, Wu W, Chen H, Li S, He H, Yu Y, Hu M, Li J, Zheng R, et al: A simple nomogram for predicting failure of non-invasive respiratory strategies in adults with COVID-19: A retrospective multicentre study. Lancet Digit Health. 3:e166–e174. 2021.PubMed/NCBI View Article : Google Scholar
16	Reimand J, Isserlin R, Voisin V, Kucera M, Tannus-Lopes C, Rostamianfar A, Wadi L, Meyer M, Wong J, Xu C, et al: Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap. Nat Protoc. 14:482–517. 2019.PubMed/NCBI View Article : Google Scholar
17	Mayakonda A, Lin DC, Assenov Y, Plass C and Koeffler HP: Maftools: Efficient and comprehensive analysis of somatic variants in cancer. Genome Res. 28:1747–1756. 2018.PubMed/NCBI View Article : Google Scholar
18	Li T, Fu J, Zeng Z, Cohen D, Li J, Chen Q, Li B and Liu XS: TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 48 (W1):W509–W514. 2020.PubMed/NCBI View Article : Google Scholar
19	Jiang P, Gu S, Pan D, Fu J, Sahu A, Hu X, Li Z, Traugh N, Bu X, Li B, et al: Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med. 24:1550–1558. 2018.PubMed/NCBI View Article : Google Scholar
20	Maeser D, Gruener RF and Huang RS: oncoPredict: An R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data. Brief Bioinform. 22(bbab260)2021.PubMed/NCBI View Article : Google Scholar
21	Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 25:402–408. 2001.PubMed/NCBI View Article : Google Scholar
22	Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A and Bray F: Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 71:209–249. 2021.PubMed/NCBI View Article : Google Scholar
23	Dobruch J and Oszczudłowski M: Bladder cancer: Current challenges and future directions. Medicina (Kaunas). 57(749)2021.PubMed/NCBI View Article : Google Scholar
24	Zheng P, Zhou C, Ding Y and Duan S: Disulfidptosis: A new target for metabolic cancer therapy. J Exp Clin Cancer Res. 42(103)2023.PubMed/NCBI View Article : Google Scholar
25	Qi C, Ma J, Sun J, Wu X and Ding J: The role of molecular subtypes and immune infiltration characteristics based on disulfidptosis-associated genes in lung adenocarcinoma. Aging (Albany NY). 15:5075–5095. 2023.PubMed/NCBI View Article : Google Scholar
26	Wang T, Guo K, Zhang D, Wang H, Yin J, Cui H and Wu W: Disulfidptosis classification of hepatocellular carcinoma reveals correlation with clinical prognosis and immune profile. Int Immunopharmacol. 120(110368)2023.PubMed/NCBI View Article : Google Scholar
27	Feng Z, Chen R, Huang N and Luo C: Long non-coding RNA ASMTL-AS1 inhibits tumor growth and glycolysis by regulating the miR-93-3p/miR-660/FOXO1 axis in papillary thyroid carcinoma. Life Sci. 244(117298)2020.PubMed/NCBI View Article : Google Scholar
28	Jiang Z, Zhang Y, Chen X, Wu P and Chen D: Long noncoding RNA RBMS3-AS3 acts as a microRNA-4534 sponge to inhibit the progression of prostate cancer by upregulating VASH1. Gene Ther. 27:143–156. 2020.PubMed/NCBI View Article : Google Scholar
29	Xu J, Huang QY and Ge CJ: Identification of prognostic long intergenic non-coding RNAs as competing endogenous RNAs with KRAS mutations in colorectal cancer. Oncol Lett. 22(717)2021.PubMed/NCBI View Article : Google Scholar
30	Kar S: Unraveling cell-cycle dynamics in cancer. Cell Syst. 2:8–10. 2016.PubMed/NCBI View Article : Google Scholar
31	Lin X, Zhuang S, Chen X, Du J, Zhong L, Ding J, Wang L, Yi J, Hu G, Tang G, et al: lncRNA ITGB8-AS1 functions as a ceRNA to promote colorectal cancer growth and migration through integrin-mediated focal adhesion signaling. Mol Ther. 30:688–702. 2022.PubMed/NCBI View Article : Google Scholar
32	Li Y, Kong Y, An M, Luo Y, Zheng H, Lin Y, Chen J, Yang J, Liu L, Luo B, et al: ZEB1-mediated biogenesis of circNIPBL sustains the metastasis of bladder cancer via Wnt/β-catenin pathway. J Exp Clin Cancer Res. 42(191)2023.PubMed/NCBI View Article : Google Scholar
33	Valero C, Lee M, Hoen D, Wang J, Nadeem Z, Patel N, Postow MA, Shoushtari AN, Plitas G, Balachandran VP, et al: The association between tumor mutational burden and prognosis is dependent on treatment context. Nat Genet. 53:11–15. 2021.PubMed/NCBI View Article : Google Scholar
34	McGrail DJ, Pilié PG, Rashid NU, Voorwerk L, Slagter M, Kok M, Jonasch E, Khasraw M, Heimberger AB, Lim B, et al: High tumor mutation burden fails to predict immune checkpoint blockade response across all cancer types. Ann Oncol. 32:661–672. 2021.PubMed/NCBI View Article : Google Scholar
35	Lyu Q, Lin A, Cao M, Xu A, Luo P and Zhang J: Alterations in TP53 are a potential biomarker of bladder cancer patients who benefit from immune checkpoint inhibition. Cancer Control. 27(1073274820976665)2020.PubMed/NCBI View Article : Google Scholar
36	Zhou Z, Zhou Y, Liu W and Dai J: A novel cuproptosis-related lncRNAs signature predicts prognostic and immune of bladder urothelial carcinoma. Front Genet. 14(1148430)2023.PubMed/NCBI View Article : Google Scholar
37	Conde M and Frew IJ: Therapeutic significance of ARID1A mutation in bladder cancer. Neoplasia. 31(100814)2022.PubMed/NCBI View Article : Google Scholar
38	Zhao Z, Aoi Y, Philips CN, Meghani KA, Gold SR, Yu Y, John LS, Qian J, Zeidner JM, Meeks JJ and Shilatifard A: Somatic mutations of MLL4/COMPASS induce cytoplasmic localization providing molecular insight into cancer prognosis and treatment. Proc Natl Acad Sci USA. 120(e2310063120)2023.PubMed/NCBI View Article : Google Scholar
39	Ulitsky I and Bartel DP: lincRNAs: Genomics, evolution, and mechanisms. Cell. 154:26–46. 2013.PubMed/NCBI View Article : Google Scholar
40	Liang T, Tao T, Wu K, Liu L, Xu W, Zhou D, Fang H, Ding Q, Huang G and Wu S: Cancer-associated fibroblast-induced remodeling of tumor microenvironment in recurrent bladder cancer. Adv Sci (Weinh). 10(e2303230)2023.PubMed/NCBI View Article : Google Scholar
41	Noyes D, Bag A, Oseni S, Semidey-Hurtado J, Cen L, Sarnaik AA, Sondak VK and Adeegbe D: Tumor-associated Tregs obstruct antitumor immunity by promoting T cell dysfunction and restricting clonal diversity in tumor-infiltrating CD8+ T cells. J Immunother Cancer. 10(e004605)2022.PubMed/NCBI View Article : Google Scholar
42	Yang MW, Tao LY, Jiang YS, Yang JY, Huo YM, Liu DJ, Li J, Fu XL, He R, Lin C, et al: Perineural invasion reprograms the immune microenvironment through cholinergic signaling in pancreatic ductal adenocarcinoma. Cancer Res. 80:1991–2003. 2020.PubMed/NCBI View Article : Google Scholar
43	Meeks JJ and Lerner SP: Molecular landscape of non-muscle invasive bladder cancer. Cancer Cell. 32:550–551. 2017.PubMed/NCBI View Article : Google Scholar
44	Carneiro BA and El-Deiry WS: Targeting apoptosis in cancer therapy. Nat Rev Clin Oncol. 17:395–417. 2020.PubMed/NCBI View Article : Google Scholar
45	Sun Z, Wang J, Fan Z, Yang Y, Meng X, Ma Z, Niu J, Guo R, Tran LJ, Zhang J, et al: Investigating the prognostic role of lncRNAs associated with disulfidptosis-related genes in clear cell renal cell carcinoma. J Gene Med. 26(e3608)2024.PubMed/NCBI View Article : Google Scholar
46	Lu H, Wu J, Liang L, Wang X and Cai H: Identifying a novel defined pyroptosis-associated long noncoding RNA signature contributes to predicting prognosis and tumor microenvironment of bladder cancer. Front Immunol. 13(803355)2022.PubMed/NCBI View Article : Google Scholar