RESUMEN
Since 2010, significant progress has been made in the treatment of metastatic castrate resistant prostate cancer (mCRPC). While these advancements have improved survival, mCRPC remains a lethal disease, with a precision medicine framework that is lagging behind compared to other cancers. Poly (ADP-ribose) polymerase (PARP) inhibitor (PARPi) studies in prostate cancer (PCa) have focused primarily on the homologous recombination repair (HRR) genes, specifically BRCA1 and BRCA2. While homologous recombination deficiency (HRD) can be prompted by germline or somatic BRCA1/2 genetic mutations, it can also exist in tumors with intact BRCA1/BRCA2 genes. While the sensitivity of PARPi in tumors with non-BRCA DNA damage signatures is not as well established, it has been suggested that genomic alterations in DNA damage repair (DDR) genes other than BRCA may confer synthetic lethality with PARPI in mCRPC. The aim of this review is to summarize the literature on PARPi and their activity treating BRCA and non BRCA tumors with DNA damage signatures.
RESUMEN
BACKGROUND: Enzalutamide is part of the treatment regimen for metastatic castration-resistant prostate cancer (MCRPC). However, both intrinsic and acquired resistance to the drug remain substantial clinical quandaries. circRNAs, a novel type of non-coding RNA, have been identified in a number of cancers including prostate cancer and have been associated with cancer development and progression. circRNAs have shown great potential as clinically useful blood-based 'liquid biopsies' and as therapeutic targets in prostate cancer. The aim of this study was to examine the role of circRNA transcripts in enzalutamide-resistant prostate cancer cells and assess their utility as biomarkers. METHODS: An isogenic cell line model of enzalutamide resistance was subjected to circRNA microarray profiling. Several differentially expressed circRNAs, along with their putative parental genes were validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). circRNAs of interest were stably overexpressed in the control cell line and drug sensitivity was assessed using an ELISA-based proliferation assay. The candidate circRNA, hsa_circ_0001275, was measured in patient plasma samples using RT-droplet digital PCR (RT-ddPCR). RESULTS: hsa_circ_0001275 and its parental gene, PLCL2, were significantly up-regulated in strongly resistant clones vs. control (p < 0.05). Overexpression of hsa_circ_0001275 in the control cell line resulted in increased resistance to enzalutamide (p < 0.05). While RT-ddPCR analysis of hsa_circ_0001275 expression in plasma samples of 44 clinical trial participants showed a trend that mirrored the stages of disease activity (as defined by PSA level), the association did not reach statistical significance. CONCLUSIONS: Our data suggest that increased levels of hsa_circ_0001275 contribute to enzalutamide resistance. hsa_circ_0001275 plasma expression showed a trend that mirrors the PSA level at specific disease time points, indicating that circRNAs mirror disease recurrence and burden and may be associated with enzalutamide resistance.
RESUMEN
Studies have demonstrated that men with Prostate Cancer (PCa) harboring BRCA2/BRCA1 genetic aberrations, are more likely to have worse disease and a poorer prognosis. A mutation in BRCA2 is known to confer the highest risk of PCa for men (8.6 fold in men ≤65 years) making BRCA genes a conceivable genomic biomarker for risk in PCa. These genes have attracted a lot of research attention however their role in the clinical assessment and treatment of PCa remains complex. Multiple studies have been published examining the relationship between prostate cancer and BRCA mutations. Here BRCA mutations are explored specifically as a biomarker for risk in PCa. It is in this context, we examined the prognostic, clinical and therapeutic role of BRCA2/BRCA1 mutations across the evolution of PCa. The impact of the inclusion of BRCA genes on genetic screening will also be outlined.
RESUMEN
Advanced diagnostics are enabling cancer treatments to become increasingly tailored to the individual through developments in immunotherapies and targeted therapies. However, long turnaround times and high costs of molecular testing hinder the widespread implementation of targeted cancer treatments. Meanwhile, gold-standard histopathological assessment carried out by a trained pathologist is widely regarded as routine and mandatory in most cancers. Recently, methods have been developed to mine hidden information from histopathological slides using deep learning applied to scanned and digitized slides; deep learning comprises a collection of computational methods which learn patterns in data in order to make predictions. Such methods have been reported to be successful in a variety of cancers for predicting the presence of biomarkers such as driver mutations, tumour mutational burden, and microsatellite instability. This information could prove valuable to pathologists and oncologists in clinical decision making for cancer treatment and triage for in-depth sequencing. In addition to identifying molecular features, deep learning has been applied to predict prognosis and treatment response in certain cancers. Despite reported successes, many challenges remain before the clinical implementation of such diagnostic strategies in the clinical setting is possible. This review aims to outline recent developments in the field of deep learning for predicting molecular genetics from histopathological slides, as well as to highlight limitations and pitfalls of working with histopathology slides in deep learning.
RESUMEN
Circular RNAs (circRNAs), a recently discovered non-coding RNA, have a number of functions including the regulation of miRNA expression. They have been detected in a number of malignancies including prostate cancer (PCa). The differential expression pattern of circRNAs associated with PCa and androgen receptor (AR) status was investigated in this study. circRNA profiling was performed using a high throughout microarray assay on a panel of prostate cell lines, which consisted of normal, benign, and malignant cells (n = 9). circRNAs were more commonly significantly up-regulated (p < 0.05) than downregulated in malignant cell lines (n = 3,409) vs. benign cell lines (n = 2,949). In a grouped analysis based on AR status, there were 2,127 down-regulated circRNAs in androgen independent cell lines compared to 2,236 in androgen dependent cell lines, thus identifying a potential circRNA signature reflective of androgen dependency. Through a bioinformatics approach, the parental genes associated with the top 10 differentially expressed circRNAs were identified such as hsa_circ_0064644, whose predicted parental gene target is RBMS3, and hsa_circ_0060539, whose predicted gene target is SDC4. Furthermore, we identified three circRNAs associated with the parental gene Caprin1 (hsa_circ_0021652, hsa_circ_0000288, and hsa_circ_0021647). Other studies have shown the importance of Caprin1 in PCa cell survival and drug resistance. Given the modified circRNA expression signatures identified here, these hypothesis generating results suggest that circRNAs may serve as potential putative diagnostic and predictive markers in PCa. However, further validation studies are required to assess the true potential of these markers in the clinical setting.
RESUMEN
Prostate Cancer (PCa) is a leading cause of morbidity and mortality among men worldwide. For most men with PCa, their disease will follow an indolent course. However, advanced PCa is associated with poor outcomes. There has been an advent of new therapeutic options with proven efficacy for advanced PCa in the last decade which has improved survival outcomes for men with this disease. Despite this, advanced PCa continues to be associated with a high rate of death. There is a lack of strong evidence guiding the timing and sequence of these novel treatment strategies. This paper focuses on a review of the strategies for diagnostic and the current evidence available for treatment selection in advanced PCa.
