A cuproptosis-related lncRNA signature for predicting prognosis and immune response in hepatocellular carcinoma

Abstract Background: Hepatocellular carcinoma (HCC) has a high incidence and poor prognosis. Cuproptosis is a novel type of cell death, which differs from previously reported types of cell death such as apoptosis, autophagy, proptosis, ferroptosis, necroptosis, etc. Long non-coding RNAs (lncRNAs) play multiple roles in HCC. To improve the prognosis of HCC, it is necessary to construct a signature using cuproptosis-related lncRNAs. Methods: We downloaded information including RNA-seq transcriptome, clinical data and simple nucleotide variation data from The Cancer Genome Atlas (TCGA) database, and obtained cuproptosis-related genes from published studies. The cuproptosis-related lncRNAs were obtained by correlation analysis, and subsequently used to construct a prognostic cuproptosis-related lncRNA signature. Analyses of overall survival (OS) and progression-free survival (PFS) were used to evaluate prognostic validity. The receiver operating characteristic (ROC) curve with the area under the curve (AUC) values and the index of concordance (c-index) curve were drawn to evaluate the accuracy of the signature. The tumor microenvironment (TME) was analyzed by ESTIMATE algorithm. The immune cell data with various algorithms was downloaded from the Tumor Immune Estimation Resource (TIMER) 2.0 database. Immune-related pathways were analyzed by single-sample gene set enrichment analysis (ssGSEA) algorithm. Immunophenoscore (IPS) scores from The Cancer Immunome (TCIA) database were used to evaluate immunotherapy response. The "pRRophetic" R package was employed to screen drugs for high-risk patients. Results: We constructed a cuproptosis-related lncRNA signature containing 11 lncRNAs: AC125437.1, PCED1B-AS1, PICSAR, AP001372.2, AC027097.1, LINC00479, and SLC6A1-AS1 to predict the prognosis of HCC patients. This signature had excellent accuracy, and was independent of the stratification of clinicopathological features. Further study showed that high-risk tumors under this signature had higher TMB, fewer TME components and higher tumor purity. The immune-related analysis showed that the tumors with high risk were not enriched in immune cell infiltration or immune process pathways, and high-risk patients had a poor response to immunotherapy. Finally, 29 drugs such as sorafenib, dasatinib and paclitaxel were screened for high-risk HCC patients to improve their prognosis. Conclusion: Our prognostic cuproptosis-related lncRNA signature was accurate and effective for predicting the prognosis of HCC. The immunotherapy was unsuitable for high-risk HCC patients with this signature.