Integrated grade-wise profiling analysis reveals potential plasma miR-373-3p as prognostic indicator in Prostate Cancer & its target KPNA2

Abstract

Background: Plasma microRNAs (miRNAs) have recently garnered attention for their potential as stable biomarkers in the context of Prostate Cancer (PCa), demonstrating established associations with tumor grade, biochemical recurrence (BCR), and metastasis. This study seeks to assess the utility of plasma miRNAs as prognostic indicators for distinguishing between high-grade and low-grade PCa, and to explore their involvement in PCa pathogenesis.

Methodology: We conducted miRNA profiling in both plasma and tissue specimens from patients with varying PCa grades. Subsequently, the identified miRNAs were validated in a substantial independent PCa cohort. Furthermore, we identified and confirmed the gene targets of these selected miRNAs through Western blot analysis.

Results: In our plasma profiling investigation, we identified 98, 132, and 154 differentially expressed miRNAs (DEMs) in high-grade PCa vs. benign prostatic hyperplasia (BPH), low-grade PCa vs. BPH, and high-grade PCa vs. low-grade PCa, respectively. Our tissue profiling study revealed 111, 132, and 257 statistically significant DEMs for the same comparisons. Notably, miR-373-3p emerged as the sole consistently dysregulated miRNA in both plasma and tissue samples of PCa. This miRNA displayed significant overexpression in plasma and tissue samples, with fold changes of 3.584 ± 0.5638 and 8.796 ± 1.245, respectively. Furthermore, we observed a significant reduction in KPNA2 protein expression in PCa.

Conclusion: Our findings lend support to the potential of plasma miR-373-3p as a valuable biomarker for predicting and diagnosing PCa. Additionally, this miRNA may contribute to the progression of PCa by inhibiting KPNA2 expression, shedding light on its role in the disease.

Keywords: Differentially expressed miRNA; Plasma; Prostate cancer; Tissue; miRNA.

Fig. 1

The study's layout is represented as a diagram in the flowchart. Information regarding the total number of miRNAs and individual's miRNA evaluated at each investigation stage is displayed.

Fig. 2

Venn diagram illustrating a significant DEM across the different groups of the patient's plasma and tissue in PCa.

Fig. 3

Plasma miR-373-3p normalized relative expression (left) and tissue miR-373-3p normalized relative expression (right) in PCa vs BPH samples (n = 42).

Fig. 4

The ROC curve analysis of miR-373-3p in plasma (left) and ROC curve analysis of miR-373-3p in tissue (right) in PCa vs BPH samples.

Fig. 5

Venn diagram showing the putative common candidate genes of the identified miRNAs through Insilco analysis.

Fig. 6

The miR-373-3p and KPNA2 target gene description: upper graph showing miR-373-3p sequence and KPNA2 3′ UTR sequence and lower graph showing sequence similarity between miR-373-3p and targeted KPNA2.

Fig. 7

The Immunoblotting of KPNA2 expression (A) The KPNA2 protein expression pattern by western blotting in BPH and PCa tissues, loading control is represented by B-actin (B) Densitometric quantification of KPNA2, B-actin was used to normalize KPNA2 expression.

Fig. 8

Genetic change (A) The oncoplot of KPNA2 and (B) survival analyses of KPNA2 gene associated with PCa using TCGA data using the Kaplan-Meier approach.