miR-22 Regulates Invasion, Gene Expression and Predicts Overall Survival in Patients with Clear Cell Renal Cell Carcinoma

Abstract

Background: Clear cell renal cell carcinoma (ccRCC) is molecularly diverse and distinct molecular subtypes show different clinical outcomes. MicroRNAs (miRNAs) are essential components of gene regulatory networks and play a crucial role in progression of many cancer types including ccRCC.

Objective: Identify prognostic miRNAs and determine the role of miR-22 in ccRCC.

Methods: Hierarchical clustering was done in R using gene expression profiles of over 450 ccRCC cases in The Cancer Genome Atlas (TCGA). Kaplan-Meier analysis was performed to identify prognostic miRNAs in the TCGA dataset. RNA-Seq was performed to identify miR-22 target genes in primary ccRCC cells and Matrigel invasion assay was performed to assess the effects of miR-22 overexpression on cell invasion.

Results: Hierarchical clustering analysis using 2,621 prognostic genes previously identified by our group demonstrated that ccRCC patients with longer overall survival expressed lower levels of genes promoting proliferation or immune responses, while better maintaining gene expression associated with cortical differentiation and cell adhesion. Targets of 26 miRNAs were significantly enriched in the 2,621 prognostic genes and these miRNAs were prognostic by themselves. MiR-22 was associated with poor overall survival in the TCGA dataset. Overexpression of miR-22 promoted invasion of primary ccRCC cells in vitro and modulated transcriptional programs implicated in cancer progression including DNA repair, cell proliferation and invasion.

Conclusions: Our results suggest that ccRCCs with differential clinical outcomes have distinct transcriptomes for which miRNAs could serve as master regulators. MiR-22, as a master regulator, promotes ccRCC progression at least in part by enhancing cell invasion.

Keywords: MicroRNA; TCGA; clear cell renal cell carcinoma; miR-22; survival.

Fig.1

Differential expression of 2,621 genes in ccRCC patients from TCGA predicts survival. Unsupervised average linkage cluster based on the expression levels of 2,621 genes separated the 480 ccRCC patients into 2 main groups (A). Heatmap of this classification showed distinct gene expression patterns in these patients (B). Gene cluster 1 (yellow bar) was enriched with metabolism genes. Gene cluster 2 (blue bar) was enriched with genes promoting virus defense response and B and T cell activation. Genes involved in B, T and NK cell functions as well as antigen processing and presentation were enriched in gene cluster 4 (red bar). Gene cluster 3 (orange bar) was enriched with genes involved in cell cycle. Gene cluster 5 (green bar) was enriched with extracellular matrix (ECM) proteins. Gene cluster 6 (purple bar) was enriched with genes that are highly expressed in the normal kidney cortex. Patients in the 2 main groups had different outcomes determined by Kaplan-Meier analysis (C).

Fig.2

Identification of master regulator miRNAs associated with ccRCC survival. (A) Venn diagram of the prognostic miRNAs identified by Kaplan-Meier analysis based on miRNA expression in the TCGA dataset and the master regulator of the prognostic genes in the Stanford dataset. The overlapping miRNAs are listed under the plot. (B) Kaplan-Meier plots of overall survival for miR-22, P-value (log-rank test) indicated. High expression is defined as equal or greater than the mean and low expression smaller than the mean. (C) Of the 2,621 genes separating the 480 ccRCC patients into 2 main groups, 96 were identified as miR-22 target genes by TargetScan. (D) Supervised average linkage cluster based on the expression levels of the 96 miR-22 target genes separated the 480 ccRCC patients into 2 main groups, largely overlapping with stratification using the 2,621 genes.

Fig.3

Transcriptome (RNA-Seq) analysis of miR-22 overexpression in primary ccRCC cells identifies prognostic gene signatures in TCGA dataset. (A) Veen diagram illustrate genes≥1.5-fold upregulated (left) or downregulated (right) following transfection of miR-22 mimic into ccRCC cells. (B) Significantly enriched biological functions (by Ingenuity Pathway Analysis) associated with transfection of miR-22 mimic into cells at each of the two time points. (C) Hierarchical clustering of TCGA samples across the 308 genes affected by miR-22 mimic transfection into ccRCC cells (common among both time points). Note, two main sample clusters are observed (red and blue bars). (D) Kaplan-Meier survival analysis comparing the two TCGA sample clusters from above; P-value (log-rank test) indicated.

Fig.4

miR-22 promotes cell invasion in primary ccRCC cells. (A) MiR-22 downregulated cell adhesion promoting genes in primary ccRCC that are associated with good overall survival in TCGA patients. High expression is defined as equal or greater than the mean and low expression smaller than the mean. (B) Validation of miR-22 level in primary ccRCC cells after transfection with miR-22 mimics by qPCR. (C) Quantification of cell invasion following transfection of cells with miR-22 mimics, compared to no transfection and non-targeting control (NTC). P-value is significant by ANOVA.