A New Prognostic Signature Constructed with Necroptosis-Related lncRNA in Bladder Cancer

The fate and function of non-coding RNAs during necroptosis

Necroptosis is a novel form of cell death which is activated when apoptotic cell death signals are disrupted. Accumulating body of observations suggests that noncoding RNAs, which are the lately discovered mystery of the human genome, are significantly associated with necroptotic signaling circuitry. The fate and function of miRNAs have been well documented in human disease, especially cancer. Recently, lncRNAs have gained much attention due to their diverse regulatory functions. Although available studies are currently based on bioinformatic analysis, predicted interactions desires further attention, as these hold significant promise and should not be overlooked. In the light of these, here we comprehensively review and discuss noncoding RNA molecules that play significant roles during execution of necroptotic cell death.

LncRNAs in necroptosis: Deciphering their role in cancer pathogenesis and therapy

Necroptosis, a controlled type of cell death that is different from apoptosis, has become a key figure in the aetiology of cancer and offers a possible target for treatment. A growing number of biological activities, including necroptosis, have been linked to long noncoding RNAs (lncRNAs), a varied family of RNA molecules with limited capacity to code for proteins. The complex interactions between LncRNAs and important molecular effectors of necroptosis, including mixed lineage kinase domain-like pseudokinase (MLKL) and receptor-interacting protein kinase 3 (RIPK3), will be investigated. We will explore the many methods that LncRNAs use to affect necroptosis, including protein-protein interactions, transcriptional control, and post-transcriptional modification. Additionally, the deregulation of certain LncRNAs in different forms of cancer will be discussed, highlighting their dual function in influencing necroptotic processes as tumour suppressors and oncogenes. The goal of this study is to thoroughly examine the complex role that LncRNAs play in controlling necroptotic pathways and how that regulation affects the onset and spread of cancer. In the necroptosis for cancer treatment, this review will also provide insight into the possible therapeutic uses of targeting LncRNAs. Techniques utilising LncRNA-based medicines show promise in controlling necroptotic pathways to prevent cancer from spreading and improve the effectiveness of treatment.

Prognosis Prediction of Disulfidptosis-Related Genes in Bladder Cancer and a Comprehensive Analysis of Immunotherapy

As a newly discovered mechanism of cell death, disulfidptosis is expected to help diagnose and treat bladder cancer patients. First, data obtained from public databases were analyzed using bioinformatics techniques. SVA packages were used to combine data from different databases to remove batch effects. Then, the differential analysis and COX regression analysis of ten disulfidptosis-related genes identified four prognostically relevant differentially expressed genes which were subjected to Lasso regression for further screening to obtain model-related genes and output model formulas. The predictive power of the prognostic model was verified and the immunohistochemistry of model-related genes was verified in the HPA database. Pathway enrichment analysis was performed to identify the mechanism of bladder cancer development and progression. The tumor microenvironment and immune cell infiltration of bladder cancer patients with different risk scores were analyzed to personalize treatment. Then, information from the IMvigor210 database was used to predict the responsiveness of different risk patients to immunotherapy. The oncoPredict package was used to predict the sensitivity of patients at different risk to chemotherapy drugs, and its results have some reference value for guiding clinical use. After confirming that our model could reliably predict the prognosis of bladder cancer patients, the risk scores were combined with clinical information to create a nomogram to accurately calculate the patient survival rate. A prognostic model containing three disulfidptosis-related genes (NDUFA11, RPN1, SLC3A2) was constructed. The functional enrichment analysis and immune-related analysis indicated patients in the high-risk group were candidates for immunotherapy. The results of drug susceptibility analysis can guide more accurate treatment for bladder cancer patients and the nomogram can accurately predict patient survival. NDUFA11, RPN1, and SLC3A2 are potential novel biomarkers for the diagnosis and treatment of bladder cancer. The comprehensive analysis of tumor immune profiles indicated that patients in the high-risk group are expected to benefit from immunotherapy.