A novel disulfidptosis-related lncRNA signature for predicting prognosis and potential targeted therapy in hepatocellular carcinoma

Abstract

Disulfidptosis is a recently discovered mode of cell death with a significant role in cancer. Long non-coding RNAs (lncRNAs) have been implicated in numerous biological processes including oncogenesis, invasion, and metastasis. In this work, we developed an lncRNA signature associated with disulfidptosis for prediction of survival of hepatocellular carcinoma (HCC) patients. Detailed HCC expression profiles and clinical information were obtained from The Cancer Genome Atlas, and 599 differentially expressed disulfidptosis-related lncRNAs were identified through Pearson correlation analysis. Finally, by the least absolute shrinkage and selection operator method, we constructed an HCC prognostic model containing 7 disulfidptosis-related lncRNAs. We split patients into high- and low-risk groups based on the risk values generated by this model and showed that patients in the high-risk group had shorter overall survival times. In the training dataset, receiver operating characteristic curves for 1-, 3-, and 5-year survival were drawn according to the standard (0.788, 0.801, 0.803) and internal validation set (0.684, 0.595, 0.704) to assess the efficacy of the signature. Risk value was confirmed as an independent predictor and used to construct a nomogram in combination with several clinical factors. We further assessed the signature with respect to tumor immune landscape, gene set enrichment analysis, principal component analysis, tumor mutation burden, tumor immune dysfunction and exclusion, and drug sensitivity. High-risk patients had higher immune function scores, except for type II IFN response, whereas low-risk patients had significantly lower tumor immune dysfunction and rejection scores, indicating that they were more sensitive to immune checkpoint inhibitors. Drug sensitivity analysis showed that low-risk patients could benefit more from certain anti-tumor drugs, including sulafenib. In summary, we have constructed a novel signature that shows good performance in predicting survival of patients with HCC and may provide new insights for targeted tumor therapy.