Identification of microRNAs as a class of biomarkers for the early diagnosis of prostate cancer : an in silico and molecular approach
Prostate cancer (PCa) is the second most common form of cancer in men around the world. In many parts of Africa, data on prostate cancer is sparse. This is attributed to poor access to testing and diagnostics. The International Agency for Research on Cancer (GLOBOCAN) estimated that 28,000 deaths occurred as a result of PCa in Africa in 2008, 4500 of which were in South Africa. This figure (28,000) is predicated a rise to 57,000 over the next two decades. Currently, the most commonly used diagnostic tests for PCa are the DRE and PSA tests. The former is highly invasive and both have low specificity and poor sensitivity. Therefore, the need for a less invasive early detection method with the ability to overcome the lack of specificity and sensitivity is required. Biomarkers have recently been identified as a viable option for early detection of disease. Examples of biological indicators for disease are miRNAs. miRNAs are small non-coding RNA molecules which play a key role in controlling gene expression and certain biological processes. Studies have shown that aberrantly expressed miRNAs are a hallmark of several diseases like cancer. miRNA expression has been shown to be associated with tumour development, progression and response to therapy, suggesting their possible use as diagnostic, prognostic and predictive biomarkers. The study aimed to investigate the potential of miRNAs implicated in prostate cancer as putative biomarkers for the disease and evaluating these miRNAs in a panel of prostate as well as several other cancer cell lines using qRT-PCR. An in silico approach was used to identify 13 putative miRNAs implicated in prostate cancer of which 8 were further analysed in a parallel study and 5 in this study. Two publicly available target prediction software were used for target gene prediction of the 5 identified miRNAs. The target genes were subjected to functional analysis using web-based software, DAVID. Functions which were clustered with an enrichment score of 1.3 and greater were considered significant. Targets with gene ontologies linked to “transcription regulation”, “regulation of “apopotosis”, “extracellular region” and “metal ion binding” were considered for further analyses. Protein gene interaction analysis was performed to determine the pathways the target genes are involved in using STRING. Expression profile analysis of the genes in various tissues was also carried out using in silico methods through the TiGER and GeneHub-GEPIS databases. Analysis using DAVID resulted in 9 gene targets for the 5 miRNAs. It was found that miR3 seemed the most promising miRNA for biomarker validation based on the in silico analyses. Its target gene MNT was found to be abundantly expressed in prostate tissue from the TiGER results. The GeneHub-GEPIS results also indicated that the gene’s expression is up-regulated during prostate cancer. The expression levels of the miRNAs analysed using qRT-PCR indicated that miR3 is significantly over-expressed in prostate cancer cells when compared to the other cancer cell lines used in this study, corroborating the results observed from the in silico analyses. Another miRNA with interesting results was miR5. It was predicted to target two genes, YWHAZ and TNFSF13B. In TiGER, both were found to be expressed in prostate tissue. The genes were also found to be up regulated during prostate cancer in GeneHub-GEPIS. The expression level of miR5 in LNCaP was 15.32; it was significantly up-regulated in the cell line using qRT-PCR. However, miR5 was also present in HEPG2-7.06, MCF7-0.79, HT29-1.61 and H157-3.59. Thus, it was concluded it can be used as a biomarker in combination with other miRNAs. The miRNA miR2 was found to target the actin filament protein encoding gene AFAP1. The gene was predicted to be upregulated with a DEU of 33.25 in GeneHuB-GEPIS. The qRT-PCR analysis showed that the expression ratio in LNcaP was 8.79. However, miR2 expression was up-regulated in MCF7-0.85 and HT29-1.09 as well. The expression level of miR1 in BHP1 was found to be 4.85. It can be considered as an indicator for benign prostate hyperplasia. Future work would include investigating the expression of miR3 in a larger panel of cancer cells as well as in patient samples. In addition, analysis of the UTR sequences of the miRNAs targets experimentally to prove that the target genes identified using in silico methods, are indeed regulated by these miRNAs. Furthermore, performing gene “knock-out” studies on the genes that code for the miRNAs to study their roles in prostate cancer development.