Gene networks and microRNAs implicated in aggressive prostate cancer - PubMed (original) (raw)

Gene networks and microRNAs implicated in aggressive prostate cancer

Liang Wang et al. Cancer Res. 2009.

Abstract

Prostate cancer, a complex disease, can be relatively harmless or extremely aggressive. To identify candidate genes involved in causal pathways of aggressive prostate cancer, we implemented a systems biology approach by combining differential expression analysis and coexpression network analysis to evaluate transcriptional profiles using lymphoblastoid cell lines from 62 prostate cancer patients with aggressive phenotype (Gleason grade >or= 8) and 63 prostate cancer patients with nonaggressive phenotype (Gleason grade <or= 5). From 13,935 mRNA genes and 273 microRNAs (miRNA) tested, we identified significant differences in 1,100 mRNAs and 7 miRNAs with a false discovery rate (FDR) of <0.01. We also identified a coexpression module demonstrating significant association with the aggressive phenotype of prostate cancer (P = 3.67 x 10(-11)). The module of interest was characterized by overrepresentation of cell cycle-related genes (FDR = 3.50 x 10(-50)). From this module, we further defined 20 hub genes that were highly connected to other genes. Interestingly, 5 of the 7 differentially expressed miRNAs have been implicated in cell cycle regulation and 2 (miR-145 and miR-331-3p) are predicted to target 3 of the 20 hub genes. Ectopic expression of these two miRNAs reduced expression of target hub genes and subsequently resulted in cell growth inhibition and apoptosis. These results suggest that cell cycle is likely to be a molecular pathway causing aggressive phenotype of prostate cancer. Further characterization of cell cycle-related genes (particularly, the hub genes) and miRNAs that regulate these hub genes could facilitate identification of candidate genes responsible for the aggressive phenotype and lead to a better understanding of prostate cancer etiology and progression.

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Conflict of interest statement

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Figures

Figure 1

Figure 1. Gene co-expression network analysis

A. Branches (gene modules) of highly correlated genes by average linkage hierarchical clustering of 3100 genes. The colored bars directly corresponded to the module (color) designation for the clusters of genes. Grey denoted genes that were not part of any module. The remaining colors were used for the four modules. B. Multi-dimensional scaling plot of the entire gene expression network. Each dot represented a gene, where the color corresponded to the gene module. The distance between each dot indicated their topological overlap.

Figure 2

Figure 2. Identification of clinical trait-related hub genes

A. Scatterplot between gene significance (absolute r) (_y_-axis) and scaled intramodular connectivity (K/Kmax). Each point corresponded to a gene in the turquoise module. The intramodular connectivity was significantly correlated with gene significance (r = 0.61, p = 7.1 × 10−19). B. Visualization of gene-gene interaction within turquoise module. The connections were drawn using VisANT tool (ref 22). The genes with at least one connection when weighted cutoff value >=0.16 were shown. Each node represented a gene. Red nodes were hub genes. Bigger nodes indicated more connections.

Figure 3

Figure 3. Biological effect of ectopic expression of miR-145 and miR-331 in prostate cancer cell lines

A. qRT-PCR was used to measure expression level of target genes using total RNA from nucleofected cells. Expression values were normalized to GAPDH. Expression levels of target genes were significantly reduced by ectopic expression of the two miRNAs. Cell viability was examined in VCaP cells (B) and LNCaP cells (C). Live and dead cells were stained in green and red, respectively. Percentage of apoptotic cell population measured by FACS was shown below each corresponding cell image.

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