A Mutation-Related Long Noncoding RNA Signature of Genome Instability Predicts Immune Infiltration and Hepatocellular Carcinoma Prognosis

Jianhua Wu,Shuai Lin,Shuqun Zhang,Xueting Ren,Chengxue Dang,Mengsha Chen,Ruina Zhou,Hao Zhang,Xin Xie,Nan Wang,Yifan Cai,Zhangjian Zhou

doi:10.3389/fgene.2021.779554

Abstract

Background: Long noncoding RNAs (lncRNAs) have been discovered to play a regulatory role in genomic instability (GI), which participates in the carcinogenesis of various cancers, including hepatocellular carcinoma (HCC). We endeavored to establish a GI-derived lncRNA signature (GILncSig) as a potential biomarker and explore its impact on immune infiltration and prognostic significance. Methods: Combining expression and somatic mutation profiles from The Cancer Genome Atlas database, we identified GI-related lncRNAs and conducted functional analyses on co-expressed genes. Based on Cox regression analysis, a GILncSig was established in the training cohort (n = 187), and an independent testing patient cohort (n = 183) was used to validate its predictive ability. Kaplan-Meier method and receiver operating characteristic curves were adopted to evaluate the performance. The correlation between GI and immune infiltration status was investigated based on the CIBERSORT algorithm and single sample gene set enrichment analysis. In addition, a comprehensive nomogram integrating the GILncSig and clinicopathological variables was constructed to efficiently assess HCC patient prognosis in clinical applications. Results: A total of 88 GI-related lncRNAs were screened out and the functional analyses indicated diversified effects on HCC progression. The GILncSig was established using four independent lncRNAs (AC116351.1, ZFPM2-AS1, AC145343.1, and MIR210HG) with significant prognostic value (p < 0.05). Following evaluation with the GILncSig, low-risk patients had significantly better clinical outcomes than high-risk patients in the training cohort (p < 0.001), which was subsequently validated in the independent testing cohort. High-risk group exhibited more immunocyte infiltration including B cells memory, macrophages M0 and neutrophils and higher expression of HLA gene set and immune checkpoint genes. Compared to existing HCC signatures, the GILncSig showed better prognosis predictive performance [area under the curve (AUC) = 0.709]. Furthermore, an integrated nomogram was constructed and validated to efficiently and reliably evaluate HCC patient prognosis (3-years survival AUC = 0.710 and 5-years survival AUC = 0.707). Conclusion: The GILncSig measuring GI and impacting immune infiltration serves as a potential biomarker and independent predictor of HCC patient prognosis. Our results highlight further investigation of GI and HCC molecular mechanisms.

Highlights

Hepatocellular carcinoma (HCC), or malignant hepatoma, has become the most common primary liver malignant tumor, accounting for 7% of all cancers globally (Budny et al, 2017)
In this study, we aimed to identify genomic instability (GI)-related Long noncoding RNAs (lncRNAs) by combining somatic mutation and expression profiles based on The Cancer Genome Atlas (TCGA) database and develop a GIderived lncRNA signature (GILncSig) to quantify GI in HCC and help to predict HCC patient prognosis
Based on cumulative somatic mutations, all HCC samples from TCGA were classified into the genomically unstable (GU)-like group of the top 25% of mutation numbers and the genomically stable (GS)-like group of the bottom 25% of mutation numbers

Summary

Introduction

Hepatocellular carcinoma (HCC), or malignant hepatoma, has become the most common primary liver malignant tumor, accounting for 7% of all cancers globally (Budny et al, 2017). It is widely acknowledged that the pathogenesis of HCC involves genetic and epigenetic changes, but the molecular mechanisms remain unclear (Ogunwobi et al, 2019). Scholars have focused on prognostic biomarkers and molecular risk models to better predict HCC patient prognosis and elucidate HCC carcinogenesis (Wang et al, 2019a; Zhang et al, 2020). There is an urgent need to utilize comprehensive methods to identify potential biomarkers and predict HCC prognosis in clinical management. Long noncoding RNAs (lncRNAs) have been discovered to play a regulatory role in genomic instability (GI), which participates in the carcinogenesis of various cancers, including hepatocellular carcinoma (HCC). We endeavored to establish a GI-derived lncRNA signature (GILncSig) as a potential biomarker and explore its impact on immune infiltration and prognostic significance

Objectives

Methods

Results

Conclusion