ArticleTranslational cancer research2024
Determining new disulfidptosis-associated lncRNA signatures pertinent to breast cancer prognosis and immunological microenvironment.
Article in Translational cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Construction of a novel disulfidptosis-associated lncRNAs signature for risk features and immunotherapy in breast cancer.Translational cancer research · 2025Article
- Molecular signatures of disulfidptosis: interplay with programmed cell death pathways and therapeutic implications in oncology.Cellular & molecular biology letters · 2025Review
- Novel pyroptosis-immune-related lncRNA signature exhibits a distinct immune cell infiltration landscape in breast cancer.Frontiers in immunology · 2024Article
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Authors and funding
6 authors.
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Abstract
Background: Disulfidptosis is a novel form of cell death triggered by disulfide stress that may have important implications for breast cancer (BC) pathogenesis. Nevertheless, studies identifying disulfidptosis-associated long non-coding RNAs (lncRNAs) in BC have not been reported. This study aimed to investigate the prognostic potential of disulfidptosis-related lncRNAs in BC. Methods: RNA-sequencing data and clinical information of BC patients were obtained from The Cancer Genome Atlas (TCGA) database. The lncRNAs associated with disulfidptosis were identified through co-expression analysis. Subsequently, a risk signature consisting of 10 lncRNAs was constructed using univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses, and its predictive power was validated. Results: The risk signature was found to be an independent prognostic factor for BC patients. Notably, the two subgroups defined by the risk signature exhibited different mutant gene profiles, and risk scores were significantly correlated with tumor mutation burden (TMB). Additionally, single-sample gene set enrichment analysis (ssGSEA) and immune checkpoint analyses indicated that the predicted trait was significantly associated with the immune status of BC patients. Furthermore, 55 potential anticancer drugs were identified that were associated with the signature. Conclusions: In this study, we successfully developed a prognostic model based on disulfidptosis-related lncRNAs, which enhances the accuracy of predicting the prognosis of BC patients. This model also offers a potential target and theoretical foundation for BC treatment, laying a robust groundwork for future research on the functional roles of disulfidptosis-associated lncRNAs in BC.
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