Comparison of miRNA and gene expression profiles between metastatic and primary prostate cancer

Abstract

Abstract. The present study aimed to identify the regulatory mechanisms associated with the metastasis of prostate cancer (PC). The microRNA (miRNA/miR) microarray dataset GSE21036 and gene transcript dataset GSE21034 were downloaded from the Gene Expression Omnibus database. Following pre-processing, differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) between samples from patients with primary prostate cancer (PPC) and metastatic prostate cancer (MPC) with |log 2 fold change (FC)| >1 and a false discovery rate <0.05 were selected using the Linear Models for Microarray and RNA-seq Data 4 package of R. Next, a DEM-DEG regulatory network was constructed by downloading miRNA-DEG pairs from the miRNA.org database. Finally, functional annotation of each DEM-DEG module was performed using the Database for Annotation, Visualization and Integrated Discovery based on the Gene Ontology database. The upregulated miRNAs, including miR-144, miR-494 and miR-181a, exhibited a higher degree of connections compared with other nodes, including in the DEM-DEG regulatory network, and regulated a number of downregulated DEGs. According to the functional annotation of the DEM-DEG modules, miR-144 and its targeted DEGs enriched the highest number of biological process terms (36 terms), followed by miR-494 (24 terms), miR-30d (18 terms), miR-181a (15 terms), hsa-miR-196a (8 terms), miR-708 (7 terms) and miR-486-5p (2 terms). Therefore, these miRNAs may serve roles in the metastasis of PC cells via downregulation of their corresponding target DEGs.

Circulating microRNAs in plasma among men with low‐grade and high‐grade prostate cancer at prostate biopsy

“…MiR‐708 has been previously associated with biochemical recurrence and prostate cancer metastasis; however, the reported association with these outcomes was in both directions. For example, Guo et al reported upregulation of miR‐708 in prostate tumor samples from primary prostate cancer cases to metastasis prostate cancer cases, which supports our study findings of higher expression of miR‐708 in high‐grade compared to low‐grade prostate cancer cases and the positive correlation observed between miR‐708 levels and Gleason score. However, Watahiki et al found miR‐708 statistically significantly downregulated from primary prostate cancer cell lines to metastatic prostate cancer cell lines, where it reached undetectable levels.…”

“…Nevertheless, relationships between these circulating miRNAs in plasma and high‐grade prostate cancer were observed. In addition, higher expression of miR‐100 and lower expression of miR‐708 in men with more advanced disease compared to early‐stage disease are consistent with previous studies . Because circulating miRNAs are stable in blood, a noninvasive biomarker, and differentially expressed between low‐ and high‐grade prostate cancer cases, they still remain promising prostate cancer diagnostic biomarkers.…”

“…Among the circulating miRNAs in plasma that had a higher expression in high‐grade compared to low‐grade prostate cancer cases in the present study, miR‐708 and ‐376c have been linked to factors associated with aggressive prostate cancer in tissues or prostate cancer cell lines . MiR‐708 has been previously associated with biochemical recurrence and prostate cancer metastasis; however, the reported association with these outcomes was in both directions.…”

miR‑210 promotes human osteosarcoma cell migration and invasion by targeting FGFRL1

“…miRNA is a kind of small non-coding RNA and plays crucial role in regulating gene expression, being considered as cancer biomarkers ( 6 , 7 ). Studies have indicated that the expressions of almost 30% human genes were controlled by different miRNAs ( 8 , 9 ).…”

Exploring Small Extracellular Vesicles for Precision Medicine in Prostate Cancer

“…However, vesicular miRNA quantification can be affected by inadequate procedural choices, including the choice of optimal endogenous miRNA for expression normalization ( 39 ). Differential expression analysis of vesicular mRNAs or miRNAs between samples from primary PCa, metastatic cancers, and healthy subjects can lead to the identification of candidate biomarkers ( 40 ). In addition, other gene expression analysis methods, including co-expression network analysis, can suggest potential diagnostic and prognostic biomarkers ( 41 – 43 ).…”