Systematic identification of microRNA drivers of resistance to novel therapeutics in advanced prostate cancer – exploitation as stratification biomarkers and drug targets
Creators: name: Eringyte, Ieva
Publisher: name: Imperial College London
Year: 2021

description: Prostate cancer (PCa) is the most prevalent malignancy of Western males. Relapse on first-line anti-androgen treatment occurs almost invariably, leading to advanced castration-resistant PCa (CRPC). Whilst the currently used next-generation and chemotherapeutic drugs demonstrate efficacy in CRPC, only half of men respond to taxanes, approximately a third to androgen receptor (AR)-targeting agents. This calls for an urgent identification of optimal, tailored treatments to PCa patients, which can be aided via investigation of mechanisms of drug resistance and identification of resistance-predicting biomarkers. MicroRNAs (miRNAs), a class of ~22nt small noncoding RNAs, are implicated in drug resistance due to their complex regulatory roles. Their robustness and easy detection in patient serum, circulating or within extracellular vesicles, make them attractive candidates for non-invasive biomarkers. In order to investigate this, PCa cell line models resistant to CRPC therapeutics – taxanes (Docetaxel and Cabazitaxel), hormone therapies (Enzalutamide and Abiraterone), and next-generation targeted therapies (pan-AKT and PI3Kβ inhibitors) – were generated. qPCR array analysis identified significant dysregulation of literature-identified resistance markers, confirming resistance development. I additionally evaluated their EMT and stemness marker expression, apoptosis and invasion abilities via qPCR and cell-based assays. Small RNA-sequencing of the resistant models identified treatment-specific deregulated miRNAs. MiRNA expression was also investigated in cell line-secreted extracellular vesicles (EVs). Small RNA-sequencing additionally uncovered panels of deregulated small nucleolar RNAs (snoRNAs) and PIWI-interacting RNAs (piRNAs) which are increasingly becoming implicated in cancer-associated pathways and drug resistance, with potential to act as treatment-predictive biomarkers. Taxane, hormone therapy, and targeted therapy resistance models demonstrated gene expression deregulation across three drug resistance-associated mechanisms: changes in AR and androgen biosynthesis, PI3K/AKT pathway, and survival/anti-apoptotic factors. Whilst taxane resistance models downregulated AR and androgen biosynthesis enzyme AKR1C3, hormone therapy group showed upregulation of these factors. AR variants and glucocorticoid receptor (GR) were found upregulated in both groups. The activation of the PI3K/AKT pathway was observed across all resistance models. All three groups also showed upregulation of anti-apoptotic/survival factors, especially BCL2 and BIRC5. Some taxane and targeted therapy resistance models additionally showed altered expression of epithelial to mesenchymal transition (EMT) markers as well as increased invasiveness of tumour spheroids in Matrigel. Small RNA sequencing revealed panels of miRNAs, snoRNAs, and piRNAs to be deregulated across the CRPC resistance models. Among them, miR-224-5p and miR-452-5p were downregulated across all taxane resistance models. Hormone resistance models shared 20 deregulated miRs, and PI3K and AKT inhibitor models shared 9. Distinct subsets of dysregulated small RNAs were identified that were discrete to specific drug classes and shared across mechanistically distinct resistance models. The identified miRNAs, snoRNAs and piRNAs can be used to further investigate their contribution to drug resistance and resistance-predictive abilities. Drug resistance-associated miRNAs were found expressed in isolated extracellular vesicles (EVs), potentially indicating their ability to promote resistance in a paracrine or endocrine manner. A resistance-predicting miRNA panel offers opportunities for early intervention, improved drug selection and a more tailored treatment plan for better patient outcome that is urgently needed in CRPC.