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

Muqi Li,Shunli Shen,Tielong Wang,Tian Lan,Xiwen Wu,Minni Liang,Zhitao Chen,Baogang Peng,Wenxuan Xie

doi:10.3389/fmolb.2020.566491

Abstract

BackgroundLong non-coding RNA (LncRNA) plays an important role in the occurrence and development of hepatocellular carcinoma (HCC). This study aims to establish an immune-related LncRNA model for risk assessment and prognosis prediction in HCC patients.MethodsHepatocellular carcinoma 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 the Gene Set Enrichment Analysis (GSEA) website and matched with LncRNA in the TCGA to get immune-related LncRNA. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for screening the candidate LncRNAs and calculating the risk coefficient to establish the prognosis model. Patients were divided into a high-risk group and a 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 were used for function evaluation.ResultsA total of 319 samples met the screening criteria and were randomly distributed across the training cohort and the validation cohort. After comparison with the IMMUNE_RESPONSE gene set and the IMMUNE_SYSTEM_PROCESS gene set, a total of 3094 immune-related LncRNAs were screened. Ultimately, four immune-related LncRNAs were used to construct a formula using LASSO regression. According to the formula, the low-risk group showed a higher survival rate than the high-risk group in the validation cohort and the whole cohort. The receiver operating characteristic curves data demonstrated that the risk score was more specific than other traditional clinical characteristics in predicting the 5-year survival rate for HCC.ConclusionThe four-immune-related-LncRNA model can be used for survival prediction in HCC and guide clinical therapy.

Highlights

Hepatocellular carcinoma (HCC) is one of the most lethal cancers in the world
The receiver operating characteristic curves data demonstrated that the risk score was more specific than other traditional clinical characteristics in predicting the 5-year survival rate for HCC
The four-immune-related-Long non-coding RNA (LncRNA) model can be used for survival prediction in HCC and guide clinical therapy

Summary

Introduction

Hepatocellular carcinoma (HCC) is one of the most lethal cancers in the world. medical technology has improved in recent years, the 5-year survival rate and mortality rate of HCC have not significantly improved (Siegel et al, 2019). PD1 antibody-based immunotherapy has made considerable strides in the treatment of HCC, there are still some deficiencies in the clinical application of these drugs. These drugs may cause complications such as diarrhea, rashes, lung disease, and even lethal complications (Zhong et al, 2016; Zhang X. et al, 2019). Hepatocellular carcinoma has multiple immunophenotypes, which underscores the importance of further research on immune cell interaction in HCC and the development of individualized immunotherapy drugs (Hilmi et al, 2019; Llovet et al, 2019). This study aims to establish an immune-related LncRNA model for risk assessment and prognosis prediction in HCC patients

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