Weighted gene co-expression network analysis identifies CCNA2 as a treatment target of prostate cancer through inhibiting cell cycle

Abstract

Prostate cancer is a malignant tumor disease that seriously harms the lives of middle-aged and elderly men. Weighted gene co-expression analysis can be used to construct gene co-expression networks to explore gene sets and genes that are significantly correlated with clinical features. In this study, the transcriptome data of prostate cancer on TCGA was analyzed by weighted gene co-expression network, and the gene with a significant correlation with disease Gleason stage and tumor T stage was identified: CCNA2. CCNA2 was significantly associated with biochemical recurrence, disease-free survival and overall survival rate of prostate cancer. The ability of cancer cell proliferation, invasion and metastasis was decreased after down-regulated expression of CCNA2 in prostate cancer cell lines. Flow cytometry revealed that tumor cells were arrested in the S phase after down-regulated the expression of CCNA2. Taken together, we used WGCNA and obtain a gene CCNA2 which is significantly associated with the prognosis of prostate cancer, which may be an indicator of the prognosis of prostate cancer and a new therapeutic target.

Keywords: CCNA2; Weighted gene co-expression network; cell cycle; prognosis; prostate cancer.

Figure 1

This figure describes the key steps in obtaining the pink gene module. Figure 1A shows the determination of soft threshold. Figure 1B shows the correlation between different gene module and the two clinical features. The depth of color represents the value of the correlation, red represents the positive correlation and green represents the negative correlation. Figure 1C shows the correlation analysis between genes in the pink gene module and Gleason score. Figure 1D shows the correlation between the pink gene module and pathological T stage.

Figure 2

This graph describes the important steps to obtain the 15 hub genes from the pink gene module. Figure 2A shows the relationship between pink genes in STRING database. Figure 2B shows the enrichment of pink gene set on Cellular component in GO analysis. Figure 2C shows the enrichment of pink gene set on biology process in GO analysis. Figure 2D shows the enrichment of pink gene set on molecular function in GO analysis. Figure 2E shows the enrichment results of pink gene set on KEGG analysis. Figure 2F shows 15 genes at the core of the pink gene set.

Figure 3

This figure describes the correlation between CCNA2 and clinical features and some cytological features. Figure 3A shows the differential expression of CCNA2 between cancer and paracancerous. Figure 3B shows the differential expression of CCNA2 between prostate cancer and normal prostate gland. Figure 3C showed a correlation between CCNA2 and biochemical recurrence rate of prostate cancer. Figure 3D shows the correlation between CCNA2 and overall survival of prostate cancer. Figure 3E shows the correlation between CCNA2 and disease free survival rate in prostate cancer. Figure 3F showed the effect of si-CCNA2 on the down-regulation of CCNA2 mRNA in C42 and PC3 cell lines. Figure 3G showed the effect of si-CCNA2 on the down-regulation of CCNA2 protein in C42 and PC3 cell lines. Figure 3H showed the result on the proliferation rate of C42 cells after down-regulating the expression of CCNA2. Figure 3I showed the result on the proliferation rate of PC3 cells after down-regulation of CCNA2 expression.

Figure 4

This figure describes the cytological characteristics of CCNA2 on C42 and PC3. Figure 4A showed the effect of down-regulation of CCNA2 expression on migration ability of C42 cells and PC3 cells. Figure 4B showed the effect of down-regulation of CCNA2 expression on invasive ability of C42 cells and PC3 cells. Figure 4C showed the effect of down-regulation of CCNA2 expression on the cell cycle of C42 and PC3.