Molecular profiling of long non-coding RNAs in prostate cancer cell lines

Abstract

Prostate cancer (PCa) incidence rates continue to rise with an estimation of 375 000 deaths and 1.4 million new cases in the year 2020. It has become the second most commonly occurring cancer and the fifth most frequent cause of cancer-related deaths in men. Prostate cancer is also the leading cancer to occur in men in the sub-Saharan region. In PCa, the aberrant expression of certain RNA molecules has been linked to PCa progression. Non-coding RNAs (ncRNAs) are RNA transcripts that are known for their involvement in numerous cellular processes. They are important in tumorigenesis and their presence may indicate cancer progression stages. Long non-coding ribonucleic acids (lncRNAs) are transcripts with 200 or more nucleotides. The focus on these lncRNAs can be attributed to their involvement in each of the cancer “hallmarks”. There have been multiple studies that have successfully identified lncRNAs in PCa. However, the landscape of the enriched molecular pathways targeted by these lncRNAs remains to be elucidated. Thus, this study aimed to profile aberrantly expressed lncRNAs and map the biological pathways associated with PCa progression. The differential expression patterns of 86 lncRNAs were compared between PC-3 and LNCaP PCa cell lines, which are highly metastatic and low metastatic (high grade and low grade), respectively. This was achieved by comparing the expression of lncRNAs between PC-3 and LNCaP cells using a 384-well plate of PCa lncRNA gene panel. LncRNA differential gene expression patterns were determined using the CFX Maestro software. The lncRNAs with a ±2 up or downregulation were considered to be differentially expressed. Annotation and enrichment analysis of lncRNA differential gene expression was performed using a human lncRNA sets database, LncSEA and DIANA-miRPath. Based on the PrimePCR array results and bioinformatics analysis, TERC lncRNA was selected for validation. The results of the array were validated with RT-qPCR using TERC primers. Thirty-six (36) of 86 lncRNAs were shown to be upregulated, while 12/86 of the lncRNA panel were downregulated. Bioinformatics analysis revealed that the upregulated lncRNAs are involved in various hallmarks of cancer. Interestingly, HOTAIR and TUG1 were demonstrated to be exosomal lncRNAs. In addition, the hypermethylation of HOTAIR and TERC was shown to sponge various miRNAs, promoting tumour progression. Furthermore, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and the Gene Ontology (GO) analysis revealed several cancer-related pathways, namely the signalling pathways regulating pluripotency of stem cells and the TGF-beta signalling pathway. Cytoscape ceRNA network analysis further illustrated the lncRNA/miRNA/mRNA axis in PCa progression. LncRNAs may be prognostic biomarkers as they have been reported to be stable in liquid and solid biopsies.