Construction and validation of a necroptosis-related lncRNAs prognosis signature of hepatocellular carcinoma - Peng, YunZhen; Wu, GuoJing; Qiu, Xin; Luo, Yue; Zou, YiShu; Wei, XueYan; Li, Aimin (Frontiers in Genetics, 2022)
Background: Immunotherapy has achieved remarkable success in treating advanced liver cancer. Current evidence shows that most of the available immune checkpoint inhibitors (ICB) treatments are suboptimal, and specific markers are needed for patients regarded as good candidates for immunotherapy. Necroptosis, a type of programmed cell death, plays an important role in hepatocellular carcinoma (HCC) progression and outcome. However, studies on the necroptosis-related lncRNA in hepatocellular carcinoma are scarce. In this view, the present study investigates the link among necroptosis-related lncRNA, prognosis, immune microenvironment and immunotherapy response. Methods: Gene transcriptome and clinical data were retrieved from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis of necroptosis-related genes was performed to identify necroptosis-related lncRNAs. Wilcoxon method was used to detect differentially expressed genes, prognostic relevant lncRNAs were obtained by univariate Cox regression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were utilised to functional enrichment analysis. Lasso-Cox stepwise regression analysis was employed to calculate risk score, which was involved in analyzing immune cells infiltration, immune checkpoints expression and predicting efficacy of immunotherapeutic. Quantitative RT-PCR (qRT-PCR) was performed to detect the expression pattern of lncRNA in cell lines. Results: The 10 lncRNAs generated in this study were used to create a prognostic risk model for HCC and group patients into groups based on risk. High-risk patients with HCC have a significantly lower OS rate than low-risk patients. Multivariate Cox regression analysis showed risk score is independent risk factors for HCC with high accuracy. Patients in high-risk group exhibited a weaker immune surveillance and higher expression level of immune checkpoint molecules. In terms of drug resistance, patients in low-risk group were more sensitive to sorafenib. The OS-related nomogram was constructed to verify the accuracy of our model. Finally, quantitative RT-PCR experiments was used to verified the expression patterns of candidate genes. Conclusion: The lncRNA signature established herein, encompassing 10 necroptosis-related lncRNAs, is valuable for survival prediction and holds promise as prognostic markers for HCC.