AUTHOR=Zhu Jinfeng , Huang Qian , Liu Sicheng , Peng Xingyu , Xue Ju , Feng Tangbin , Huang Wulang , Chen Zhimeng , Lai Kuiyuan , Ji Yufei , Wang Miaomiao , Yuan Rongfa 

TITLE=Construction of a Novel LncRNA Signature Related to Genomic Instability to Predict the Prognosis and Immune Activity of Patients With Hepatocellular Carcinoma

JOURNAL=Frontiers in Immunology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.856186

DOI=10.3389/fimmu.2022.856186

ISSN=1664-3224

ABSTRACT=Background
Genomic instability (GI) plays a crucial role in the occurrence and development of hepatocellular carcinoma (HCC). Therefore, it is meaningful for us to use long non-coding RNAs related to genomic instability to construct a prognostic signature for patients with HCC. 
Methods
We used the clinical data from the training set to perform univariate and multivariate Cox regression analyses of the GILncRNAs and establish a genomic instability-associated lncRNA signature (GILncSig). ROC curves were used to evaluate model performance. In vitro, functional experiments were used to verify the predictive performance of LUCAT1. Predict the related pathways of GILncSig by GSEA. Tumor microenvironments, immune infiltration, the half-maximal inhibitory concentration (IC50) and immunotherapy efficacy were compared between low- and high-risk groups with ESTIMATE, CIBERSORT, pRRophetic and TIDE program.
Results
Five lncRNAs (AC245041.2, AP003119.1, MIR210HG, LINC00221, and LUCAT1) were used to construct GILncSig. It was confirmed that the GILncSig has good prognostic evaluation performance for patients with HCC by drawing a time-dependent ROC curve. The GILncSig stratified patients into high-risk and low-risk groups. Compared with the low-risk group, the high-risk group had a significantly poorer prognosis. Independent prognostic analysis showed that the GILncSig could independently predict the prognosis of patients with HCC. In addition , the GILncSig was correlated with the mutation rate of the HCC genome, indicating that it has the potential to measure the degree of genome instability. LUCAT1 with the highest risk coefficient was further validated as a risk factor for HCC in vitro among GILncSig. The ESTIMATE analysis showed a significant difference in stromal scores p=4.2×10-6) and ESTIMATE scores p=0.021) between the groups. Multiple immune checkpoints have higher expression levels in th e high-risk group. CIBERSORT analysis showed higher T cells CD4 memory resting levels in the low-risk group and higher T cells CD4 memory activated and T cells follicular helper levels in the high-risk group. Finally, the GILncSig score was associated with chemotherapeutic drug sensitivity and immunotherapy efficacy of patients with HCC.
Conclusion
Our results indicate that GILncSig can be used for prognostic evaluation of patients with HCC and provide new insights for clinical decision-making and potential therapeutic strategies.