Comparative RNA-sequencing analysis of the prostate in a mouse model of benign prostatic hyperplasia with bladder outlet obstruction

Abstract

In ageing men, benign prostatic hyperplasia (BPH) is a chronic disease that leads to progressive lower urinary tract symptoms (LUTS) caused by obstruction of the bladder outlet (BOO). Patients with LUTS (such as increased frequency and urgency of urination) and complications of BOO (such as hydronephrosis and bladder stones) are at risk of serious health problems. BPH causes a rapidly rising burden of LUTS far exceeding that of other urological conditions. Treatment outcomes are unsatisfactory for BPH largely due to the lacking of fully understanding of the pathogenesis. Hormonal imbalances related to androgen and oestrogen can cause BPH, but the exact mechanism is still unknown, even the animal model is not fully understood. Additionally, there are no large-scale data to explain this mechanism. A BPH mouse model was established using mixed slow-release pellets of testosterone (T) and estradiol (E2), and we measured gene expression in mouse prostate tissue using RNA-seq, verified the results using qRT‒PCR, and used bioinformatics methods to analyse the differentially expressed genes (DEGs).

Keywords: BOO; BPH; Estradiol; RNA-seq; Testosterone.

Fig. 1

Effects of T and E2 treatment on the gross and urogenital pathology of mice. A Mice were implanted subcutaneously with T + E2 slow-release pellets: B (1) Ventral view of the prostate and urethra of the CON group; (2) dorsal view of the prostate and bladder of the CON group (the yellow arrowhead indicates the connecting site of the urethra and bladder in the subplot); (3) ventral view of the prostate and urethra of the T + E2 group; (4) dorsal view of the prostate and bladder of the T + E2 group (the yellow arrowhead indicates the connecting site of the urethra and bladder in the subplot); (5) hydronephrosis of the T + E2 group (arrow marks the renal pelvis); (6) endoscopic observation of a stone in the bladder (red arrowhead), and green arrow indicates bladder lumen; C initial body weight; D final body weight; E prostate weight; F relative prostatic index: “Prostate weight”/ “Final body weight” × 100%; G prostatic urethral length; H bladder volume (Formula: volume = Length x width x height x (π/6)); I discovery of bladder stones; J discovery of hydronephrosis. AP = anterior prostate, VP/LP = ventral prostate/lateral prostate, U = urethra, DP = dorsal prostate, B = bladder. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; ns, not significant

Fig. 2

Pathological examination of prostate in mice. A Comparisons of HE staining images of prostate tissues between CON and T + E2 group (arrow head: prostate epithelial cells; scale bar = 100 μm); B compared with CON group, the thickness of prostate epithelial cells in T + E2 group increased significantly; C comparison of the urethral lumen in prostate between the CON and T + E2 groups (arrow head: urethral lumen; scale bar = 100 μm); D compared with CON group, the cross-sectional area of the urethral cavity in T + E2 group was significantly reduced; E comparison of renal parenchymal thickness between the CON and T + E2 groups (arrow head: renal parenchyma; scale bar = 200 μm); F comparison of bladder detrusor between the CON and T + E2 groups (arrow head: bladder detrusor; scale bar = 200 μm); G compared with CON group, the detrusor muscle of bladder in T + E2 group was significantly thinner. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; ns, not significant

Fig. 3

Results of gene expression profile identification and validation of DEGs. A Heatmap diagram of DEGs between the CON and T + E2 groups. B Volcano plots showing DEGs (the horizontal dotted line marks log2-fold changes of 1 or -1). C PCA plot showing the clustering of the samples using all DEGs. D Six differentially expressed genes were validated by qRT‒PCR

Fig. 4

Functional annotation and pathway enrichment analysis. A Bar graph of the top 20 enriched significant GO terms (Values represent-log10 p values); B GO enrichment analysis of upregulated and downregulated DEGs (Values represent-log10 p values); C bar graph shows the top 20 pathways (Values represent-log10 p values); D pathway enrichment analysis of upregulated and downregulated DEGs (Values represent-log10 P values); E bar plot of pathway score calculated by GSVA for the CON group and T + E2 group

Fig. 5

PPI network of the DEGs was generated, and hub genes were analysed. A The PPI network and the 16 most significant MCODE components. B Flower plot shows the hub genes obtained by 6 algorithms. C A comparison of the expression levels of the hub genes in different normal tissues. D Scatterplot shows a positive correlation between IGF1 and EPHA7 expression levels in prostate tissue from the GTEx database (P = 0.008); E Scatterplot shows a positive correlation between IGF1 and EPHA7 expression levels in the prostate of BPH patients from the GEO database (P = 0.181); F GeneMANIA network: black circles represent inputs into GeneMANIA, and grey circles correspond to GeneMANIA proposed hubs

Fig. 6

Generation of ceRNA interaction network. A lncRNA‒miRNA-mRNA ceRNA regulatory network; B circRNA-miRNA‒mRNA ceRNA regulatory network

Fig. 7

Proportion of 25 immune cells in each sample from the CON and T + E2 groups