miRNAs Dysregulated in Human Papillomavirus-Associated Benign Prostatic Lesions and Prostate Cancer

Abstract

Prostate pathologies, including chronic prostatitis, benign prostatic hyperplasia (BPH), and prostate cancer (PCa), are strongly associated with chronic inflammation, which is a key risk factor and hallmark of these diseases [...].

Keywords: BPH; HPV; angiogenesis; apoptosis; functional enrichment analysis; inflammation; interactomic analysis; metastasis; miRNAs; proliferation; prostate cancer; prostatitis.

Figure 1

H&E staining for histopathological analysis of benign and PCa biopsy samples. (a) Representative images of the tissue architecture of control; benign prostatic hyperplasia (BPH); and BPH plus prostatitis (BPH/prostatitis) samples. Black arrows indicate areas with increased epithelial growth and enlarged nuclei restricted to the basal layer, while red arrows highlight regions with significant inflammatory infiltrates. (b) Representative images of prostate tissue architecture in the stratification of low- and high-Gleason-grade PCa. Key tissue structures are shown in both panels,, including the acinar lumen (1), luminal cells (2), stroma (3), and cellular organization (4), are labeled for clarity. Scale bars represent 200 and 50 μm.

Figure 2

Koilocyte identification and in situ detection of HPV in BPH samples. Panel (a) shows the presence of koilocytes (black arrows) identified by H&E staining, and panel (b) demonstrates HR-HPV E6/E7 DNA detection via in situ PCR, with signals localized mainly in the nucleus (empty arrows) and in koilocytes (black arrows with “K”). Samples 97 and 3680 served as HPV-negative controls, while samples 364, 3669, 4556, 4572, 5975 and 8271 were HPV-positive. Amplifications: 40× and 63×. Panel (c) displays digital quantification of the signal. Statistical analysis: one-way ANOVA with Tukey’s test; results are expressed as mean ± SD, p < 0.033 (*).

Figure 3

Interactome analysis of miRNAs linked to PCa. The miRNAs highlighted in squares with different colors were selected for expression analysis in our study, based on documented studies supporting their relevance in this pathology.

Figure 4

Functional enrichment of miRNAs implicated with PCa. The top ten functional clusters are shown based on interactomic analysis and adjusted p-values (adj.Pval). Numbers on the bars indicate the number of miRNAs in each group.

Figure 5

miRNAs expression levels in HPV-negative (−) or HPV-positive (+) benign prostatic samples. Expression of indicated miRNAs in BPH (a) or in BPH/prostatitis (b) is shown. The expression data were normalized using RNU48 as an internal control. Statistical analysis was performed using multiple t-tests per row. The error bars represent the standard deviation. Three levels of significance were used for p-values: * p < 0.033, ** p < 0.002, and *** p < 0.001.

Figure 6

miRNAs expression levels in HPV-positive PCa samples compared to their expression in control prostate tissue. Statistical analysis was performed using multiple T-tests per row. The error bars represent the standard deviation. Three levels of significance were employed for p-values: ** p < 0.002, and *** p < 0.001.

Figure 7

Evaluation of miRNA expression levels in HPV-positive and HPV-negative PCa samples. The expression levels of miRNAs were determined in HPV-positive PCa samples of high grade (HG) and low grade (LG), as well as in HPV-negative PCa samples (NEG). Statistical analyses were performed using two-way ANOVA with Tukey’s multiple comparison test. p-values indicated statistically significant differences between the groups, where *** p < 0.001 wasused for comparisons between LG, HG, and NEG. Meanwhile, the symbol # was used to indicate p < 0.033 for direct comparisons between LG and HG groups.

Figure 8

Proposed mechanism of HPV-induced miRNAs dysregulation in benign lesions and PCa, promoting a pro-oncogenic environment and influencing key genes and cellular processes in cancer progression. Upward arrows indicate overexpression and downward arrows indicate downregulation based on our studies; target genes and cellular processes were predicted in silico.