Revealing Prognostic and Immunotherapy-Sensitive Characteristics of a Novel Cuproptosis-Related LncRNA Model in Hepatocellular Carcinoma Patients by Genomic Analysis

SIMPLE SUMMARY: Hepatocellular carcinoma (HCC) remains a major health concern. Immunotherapy combined with targeted therapy brings hope to patients with HCC, but its primary beneficiaries have not been identified. Recent studies have found that copper induces cell death, which is named cuproptosis. As we know, cell death is closely related to tumor therapy, in which some non-coding RNAs involved. Therefore, we focused on whether some long non-coding RNAs (LncRNAs) are related to cuproptosis, and the cuproptosis-related LncRNAs (crLncRNAs) can classify tumor treatment-sensitive populations. In the study, we explore a model of crLncRNAs with excellent specificity and sensitivity that is capable of predicting the prognosis of HCC patients and classifying tumor immunotherapy-sensitive populations, thereby providing new insights for the development of appropriate clinical strategies. ABSTRACT: Immunotherapy has shown strong anti-tumor activity in a subset of patients. However, many patients do not benefit from the treatment, and there is no effective method to identify sensitive immunotherapy patients. Cuproptosis as a non-apoptotic programmed cell death caused by excess copper, whether it is related to tumor immunity has attracted our attention. In the study, we constructed the prognostic model of 9 cuproptosis-related LncRNAs (crLncRNAs) and assessed its predictive capability, preliminarily explored the potential mechanism causing treatment sensitivity difference between the high-/low-risk group. Our results revealed that the risk score was more effective than traditional clinical features in predicting the survival of HCC patients (AUC = 0.828). The low-risk group had more infiltration of immune cells (B cells, CD8(+) T cells, CD4(+) T cells), mainly with anti-tumor immune function (p < 0.05). It showed higher sensitivity to immune checkpoint inhibitors (ICIs) treatment (p < 0.001) which may exert the effect through the AL365361.1/hsa-miR-17-5p/NLRP3 axis. In addition, NLRP3 mutation-sensitive drugs (VNLG/124, sunitinib, linifanib) may have better clinical benefits in the high-risk group. All in all, the crLncRNAs model has excellent specificity and sensitivity, which can be used for classifying the therapy-sensitive population and predicting the prognosis of HCC patients.