Multi-Omics Analysis of Primary Prostate Cancer Datasets Reveals Novel Biomarkers.

Abstract

Prostate cancer (PCa) ranks second in cancer-related deaths in men. Current screenings used in the diagnosis are not sufficient enough in the early stages therefore, more diagnostic biomarker studies are needed. We performed a meta-analysis on the biomarker potential of miRNAs, mRNAs, and methylation for the early stages of PCa by searching available microarrays from the GEO dataset for PCa tissue and benign prostatic hyperplasia (BPH) or normal adjacent to PCa. Target genes of miRNAs were determined using the miRWalk and miRDB datasets. The results were visualized using network analysis. qPCR quantification of potential miRNA and genes was performed in human prostate epithelial cell line (RWPE-1) and human prostate carcinoma epithelial cell line (22RV1). Our meta-analysis of potential biomarkers for the diagnosis of PCa identified several candidates. It was shown that miR-7-5p is overexpressed. CAMKK2, TMEM97 expression were upregulated and CLIP1 expression was downregulated and these genes were shown to be targets of miR-7-5p. CAMKK2, TMEM97, and CLIP1 genes were found to be hypermethylated. Although the changes in the expression levels of miR-7-5p and CAMKK2, TMEM97, and CLIP1 in the two cell lines used in our study were not consistent with the significant expression differences observed in the meta-analysis, our meta-analysis results would be promising in human prostate tissue or different human tumor cell line studies. This highlights the importance of our meta-analysis results in prostate cancer biomarker research, given the difficulty of experimental validation of our large-scale data meta-analysis results using a specific cell line.