Four Immune-Related Long Non-coding RNAs for Prognosis Prediction in Patients With Hepatocellular Carcinoma

Abstract Background: Long non-coding RNA(LncRNA) plays an important role in the occurrence and development of Hepatocellular carcinioma (HCC). This study aims to establish an immune-related LncRNA model for risk assessment and prognosis prediction in HCC patients. Method HCC patient samples with complete clinical data and corresponding whole-transcriptome expression were obtained from the Cancer Genome Atlas (TCGA). Immune related genes were acquired from Gene Enrichment Analysis (GSEA) website and matched with LncRNA in TCGA to get immune-related LncRNA. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to screen the candidate LncRNAs and calculate the risk coefficient to establish the prognosis model. Patients were divided into the high-risk group and the low-risk group depending on the median risk score. The reliability of the prediction was evaluated in the validation cohort and the whole cohort. GSEA and Principal Component Analysis (PCA) were used for the function evaluation. Result A total of 319 samples met the screening criteria and were randomly divided into the training cohort and the validation cohort. After comparison with IMMUNE_RESPONSE gene set and IMMUNE_SYSTEM_PROCESS gene set, a total of 3094 immune-related LncRNA were screened and finally 4 immune-related LncRNAs were used to construct a formula by LASSO regression. The low-risk group according to the formula showed a higher survival rate than the high-risk group in the validation cohort and the whole cohort. The ROC data demonstrated that the risk score was more specific than other traditional clinical characteristics in the prediction 5-year survival in HCC. Conclusion The 4 immune-related LncRNAs model can be used in survival prediction in HCC and guide the clinical therapy.