Identification of Epithelial–Mesenchymal Transition-Related lncRNA With Prognosis and Molecular Subtypes in Clear Cell Renal Cell Carcinoma - Zhong, Weimin; Zhang, Fengling; Huang, Chaoqun; Lin, Yao; Huang, Jiyi (Frontiers in Oncology, 2020)
Epithelial-mesenchymal transition (EMT) is a reversible cellular program, regulated by a family of transcription factors, induction factors and an array of signaling pathway genes, which is important for tumor progression. However, the prognostic role and biological functions of EMT-related lncRNAs in ccRCC are largely unknown. In the present study, the gene expression data and clinical information from The Cancer Genome Atlas (TCGA) database (N =512) and International Cancer Genome Consortium (ICGC) database (N =90) were used as training dataset and external validation dataset, respectively. We then constructed an EMT-related lncRNA risk signature on the basis of comprehensively analyzed the EMT-related lncRNA expression data and clinical information. The Kaplan-Meier curve analysis indicated that patients in low-risk group and high-risk group have a significant divergence for the overall survival (OS) and disease-free survival (DFS) of ccRCC, as well as the validation dataset. The cox regression analysis for the clinical factors and risk signature in the OS and DFS suggested the risk signature can serve as an independent prognostic predictor. Moreover, we developed an individualized prognosis prediction model through nomogram and receive operator curve (ROC) analysis based on the independent factors. The Gene Set Enrichment Analysis (GSEA) indicated that patients in the low risk group were involved in adherens junction, focal adhesion, MAPK signaling pathway, pathways in cancer and renal cell carcinoma pathway. In addition, we identified three robust subtypes (named C1, C2 and C3) of ccRCC with distinct clinical characteristics and prognosis in the TCGA dataset and ICGC dataset. Among them, C1 was corresponding to a better survival outcome, while C2 and C3 corresponding to worse survival outcome and have more advance-stage patients. Moreover, C2 have more likelihood to be responded to immunotherapy and sensitive to the chemo drugs, which may providing a reference for the clinicians to develop individualized treatment. Together, we constructed an reliable EMT-related lncRNA risk signature that can independently predict the OS and DFS of ccRCC, and identified three stable molecular subtypes based on the EMT-related lncRNA expression, which may promote the understanding of the underlying molecular mechanism of ccRCC.