AUTHOR=Yan Yifeng , Ren Liang , Liu Yan , Liu Liang 

TITLE=Development and Validation of Genome Instability-Associated lncRNAs to Predict Prognosis and Immunotherapy of Patients With Hepatocellular Carcinoma

JOURNAL=Frontiers in Genetics

VOLUME=Volume 12 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.763281

DOI=10.3389/fgene.2021.763281

ISSN=1664-8021

ABSTRACT=Hepatocellular carcinoma (HCC) pathophysiology is prevalently related with the genomic instability. However, the study on associations of extensive genome instability lncRNA (GILnc) with prognosis and immunotherapy of HCC remains scarce. We placed the first 25% of somatic mutations into the genetically unstable group and placed the buttom 25% of somatic mutations into the genetically stable group, and then to identify different expression of GILnc between the two groups. Then, the LASSO was used to identify the most powerful prognostic GILnc, and a risk score for each patient was calculated according to the formula. Based on a computational frame, 245 different GILncs in HCC has been identified. Then, a 8 GILnc was successfully established to predict overall survival in HCC patients based on LASSO, then divided HCC patients into high-risk and low-risk groups, and a significant shorter overall survival in high-risk group was observed than those in low-risk group, and was validated in GSE76427 and Tongji cohorts. GSEA revealed that the high-risk group was more likely to be enriched in cancer-specific pathways. Besides, the GILnc signature has greater prognostic significance than TP53 mutation status alone and is capable of identifying intermediate subtype group existing with partial TP53 functionality in TP53 wild-type patients. Importantly, the high-risk group was associated with the therapeutic efficacy of PD-L1 blockade, suggesting that the development of potential drugs targeting these GILnc to aid the clinical benefits of immunotherapy. Finally, GILnc signature model is better than the prediction performance of two recently published lncRNA signatures. In summary, we applied bioinformatics approaches to suggest that a 8 GILncs could serve as prognostic biomarkers to provide a novel direction to explore the pathogenesis of HCC.