Protein-coding genes and non-coding RNAs cooperate mutually in cells. Integrative analysis of protein-coding and non-coding RNAs may facilitate characterizing tumor heterogeneity. We introduced integrated consensus clustering (ICC) method to integrate mRNA, miRNA and lncRNA expression profiles of 431 primary clear cell renal cell carcinomas (ccRCCs). We identified one RCC subgroup easily misdiagnosed as ccRCC in clinic and four robust ccRCC subtypes associated with distinct clinicopathologic and molecular features. In subtype R1, AMPK signaling pathway is significantly upregulated, which may improve the oncologic-metabolic shift and partially account for its best prognosis. Subtype R2 has more chromosomal abnormities, higher expression of cell cycle genes and less expression of genes in various metabolism pathways, which may explain its more aggressive characteristic and the worst prognosis. Moreover, much more miRNAs and lncRNAs are significantly upregulated in R2 and R4 respectively, suggesting more important roles of miRNAs in R2 and lncRNAs in R4. Triple-color co-expression network analysis identified 28 differentially expressed modules, indicating the importance of cooperative regulation of mRNAs, miRNAs and lncRNAs in ccRCC. This study establishes an integrated transcriptomic classification which may contribute to understanding the heterogeneity and implicating the treatment of ccRCC.
Keywords: ccRCC; integrative analysis; non-coding RNAs; subtyping; transcriptome.