Identification of Epithelial Mesenchymal Transition-Related lncRNAs Associated with Prognosis and Tumor Immune Microenvironment of Hepatocellular Carcinoma.

Abstract

PURPOSE:

The long noncoding RNAs (lncRNAs) play the important role in tumor occurrence and progression, and the epithelial to mesenchymal transition (EMT) is the critical process for tumor migration. However, the role of EMT-related lncRNA in hepatocellular carcinoma (HCC) has not been elucidated.

METHODS:

In this study, we selected the EMT-related lncRNAs in HCC by using data from The Cancer Genome Atlas database (TCGA). Two prognostic models of the overall survival (OS) and relapse-free survival (RFS) were constructed and validated through Cox regression model, Kaplan-Meier analysis, and the receiver-operating characteristic (ROC) curves. The unsupervised clustering analysis was utilized to investigate the association between EMT-lncRNAs with tumor immune microenvironment. ESTIMATE algorithm and gene set enrichment analysis (GSEA) were used to estimate tumor microenvironment and associated KEGG pathways.

RESULTS:

Two EMT-related lncRNA prognostic models of OS and RFS were constructed. Kaplan-Meier curves showed the dismal prognosis of OS and RFS in the group with high-risk score. The ROC curves and AUC values in two prognostic models indicated the discriminative value in the training set and validation set. Patients with HCC were clustered into two subgroups according the unsupervised clustering analysis. Lnc-CCNY-1 was selected as the key lncRNA. GSVA analysis showed that lnc-CCNY-1 was negatively associated with peroxisome proliferator-activated receptor (PPAR) signaling pathway and positively correlated with CELL cycle pathway.

CONCLUSION:

Two EMT-related lncRNA prognostic models of OS and RFS were constructed to discriminate patients and predict prognosis of HCC. EMT-related lncRNAs may play a role on prognosis of HCC by influencing the immune microenvironment. Lnc-CCNY-1 was selected as the key EMT-related lncRNA for further exploration.

• Authors: Yongjie Zhou, Liangwen Wang, Wen Zhang, Jingqin Ma, Zihan Zhang, Minjie Yang, Jiaze Yu, Jianjun Luo, Zhiping Yan
• Journal: Disease markers (Dis Markers) Vol. 2022 Pg. 6335155 ( 2022) ISSN: 1875-8630 [Electronic] United States
• PMID: 35111268 (Publication Type: Journal Article)
• Copyright: Copyright © 2022 Yongjie Zhou et al.

Chemical References

• Biomarkers, Tumor
• CCNY protein, human
• Cyclins
• RNA, Long Noncoding

Topics

• Biomarkers, Tumor (genetics, metabolism)
• Carcinoma, Hepatocellular (pathology)
• Cyclins (genetics)
• Epithelial-Mesenchymal Transition (genetics)
• Gene Expression Profiling
• Gene Expression Regulation, Neoplastic
• Humans
• Liver Neoplasms (pathology)
• Neoplasm Recurrence, Local (genetics)
• Prognosis
• RNA, Long Noncoding (genetics, metabolism)
• Tumor Microenvironment (genetics)