The complexity of prostate cancer: genomic alterations and heterogeneity

Role of MicroRNA-21 in Prostate Cancer Progression and Metastasis: Molecular Mechanisms to Therapeutic Targets

The role of noncoding RNA has made remarkable progress in understanding progression, metastasis, and metastatic castration-resistant prostate cancer (mCRPC). A better understanding of the miRNAs has enhanced our knowledge of their targeting mainly at the therapy level in solid tumors, such as prostate cancer (PCa). microRNAs (miRNAs) belong to a class of endogenous RNA that deficit encoded proteins. Therefore, the role of miRNAs has been well-coined in the progression and development of PCa. miR-21 has a dual nature in its work both as a tumor suppressor and oncogenic role, but most of the recent studies showed that miR-21 is a tumor promoter and also is involved in castration-resistant prostate cancer (CRPC). Upregulation of miR-21 suppresses programmed cell death and inducing metastasis and castration resistant in PCa. miR-21 is involved in the different stages, such as proliferation, angiogenesis, migration, and invasion, and plays an important role in the progression, metastasis, and advanced stages of PCa. Recently, various studies directly linked the role of high levels of miR-21 with a poor therapeutic response in the patient of PCa. In the present review, we have explained the molecular mechanisms/pathways of miR-21 in PCa progression, metastasis, and castration resistant and summarized the role of miR-21 in diagnosis and therapeutic levels in PCa. In addition, we have spotlighted the recent therapeutic strategies for targeting different stages of PCa.

Metastatic Castration-Resistant Prostate Cancer: Advances in Treatment and Symptom Management

OPINION STATEMENT

The management of metastatic castrate-resistant prostate cancer (mCRPC) has evolved in the past decade due to substantial advances in understanding the genomic landscape and biology underpinning this form of prostate cancer. The implementation of various therapeutic agents has improved overall survival but despite the promising advances in therapeutic options, mCRPC remains incurable. The focus of treatment should be not only to improve survival but also to preserve the patient's quality of life (QoL) and ameliorate cancer-related symptoms such as pain. The choice and sequence of therapy for mCRPC patients are complex and influenced by various factors, such as side effects, disease burden, treatment history, comorbidities, patient preference and, more recently, the presence of actionable genomic alterations or biomarkers. Docetaxel is the first-line treatment for chemo-naïve patients with good performance status and those who have yet to progress on docetaxel in the castration-sensitive setting. Novel androgen agents (NHAs), such as abiraterone and enzalutamide, are effective treatment options that are utilized as second-line options. These medications can be considered upfront in frail patients or patients who are NHA naïve. Current guidelines recommend genetic testing in mCRPC for mutations in DNA repair deficiency genes to inform treatment decisions, as for example in breast cancer gene mutation testing. Other potential biomarkers being investigated include phosphatase and tensin homologues and homologous recombination repair genes. Despite a growing number of studies incorporating biomarkers in their trial designs, to date, only olaparib in the PROFOUND study and lutetium-177 in the VISION trial have improved survival. This is an unmet need, and future trials should focus on biomarker-guided treatment strategies. The advent of novel noncytotoxic agents has enhanced targeted drug delivery and improved treatment responses with favourable toxicity profiling. Trials should continue to incorporate and report health-related QoL scores and functional assessments into their trial designs.

Therapeutic targets of formononetin for treating prostate cancer at the single-cell level

Prostate cancer is one of the serious health problems of older male, about 13% of male was affected by prostate cancer. Prostate cancer is highly heterogeneity disease with complex molecular and genetic alterations. So, targeting the gene candidates in prostate cancer in single-cell level can be a promising approach for treating prostate cancer. In the present study, we analyzed the single cell sequencing data obtained from 2 previous reports to determine the differential gene expression of prostate cancer in single-cell level. By using the network pharmacology analysis, we identified the therapeutic targets of formononetin in immune cells and tissue cells of prostate cancer. We then applied molecular docking to determine the possible direct binding of formononetin to its target proteins. Our result identified a cluster of differential gene expression in prostate cancer which can serve as novel biomarkers such as immunoglobulin kappa C for prostate cancer prognosis. The result of network pharmacology delineated the roles of formononetin's targets such CD74 and THBS1 in immune cells' function of prostate cancer. Also, formononetin targeted insulin receptor and zinc-alpha-2-glycoprotein which play important roles in metabolisms of tissue cells of prostate cancer. The result of molecular docking suggested the direct binding of formononetin to its target proteins including INSR, TNF, and CXCR4. Finally, we validated our findings by using formononetin-treated human prostate cancer cell DU145. For the first time, our result suggested the use of formononetin for treating prostate cancer through targeting different cell types in a single-cell level.

ProstaMine: a bioinformatics tool for identifying subtype-specific co-alterations associated with aggressiveness in prostate cancer

Background

Prostate cancer is a leading cause of cancer-related deaths among men, marked by heterogeneous clinical and molecular characteristics. The complexity of the molecular landscape necessitates tools for identifying multi-gene co-alteration patterns that are associated with aggressive disease. The identification of such gene sets will allow for deeper characterization of the processes underlying prostate cancer progression and potentially lead to novel strategies for treatment.

Methods

We developed ProstaMine to systematically identify co-alterations associated with aggressiveness in prostate cancer molecular subtypes defined by high-fidelity alterations in primary prostate cancer. ProstaMine integrates genomic, transcriptomic, and clinical data from five primary and one metastatic prostate cancer cohorts to prioritize co-alterations enriched in metastatic disease and associated with disease progression.

Results

Integrated analysis of primary tumors defined a set of 17 prostate cancer alterations associated with aggressive characteristics. We applied ProstaMine to NKX3-1-loss and RB1-loss tumors and identified subtype-specific co-alterations associated with metastasis and biochemical relapse in these molecular subtypes. In NKX3-1-loss prostate cancer, ProstaMine identified novel subtype-specific co-alterations known to regulate prostate cancer signaling pathways including MAPK, NF-kB, p53, PI3K, and Sonic hedgehog. In RB1-loss prostate cancer, ProstaMine identified novel subtype-specific co-alterations involved in p53, STAT6, and MHC class I antigen presentation. Co-alterations impacting autophagy were noted in both molecular subtypes.

Conclusion

ProstaMine is a method to systematically identify novel subtype-specific co-alterations associated with aggressive characteristics in prostate cancer. The results from ProstaMine provide insights into potential subtype-specific mechanisms of prostate cancer progression which can be formed into testable experimental hypotheses. ProstaMine is publicly available at: https://bioinformatics.cuanschutz.edu/prostamine.

Genomic evolution shapes prostate cancer disease type

The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Alternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.

Circulating tumor DNA and tissue complementarily detect genomic alterations in metastatic hormone-sensitive prostate cancer

The clinical utility of circulating tumor DNA (ctDNA) in hormone-sensitive prostate cancer (HSPC) remains inadequately elucidated. This study presents the largest real-world cohort to conduct a concordance analysis between ctDNA and tissue-based genomic profiling in HSPC patients. The findings reveal diminished ctDNA abundance in cases with low tumor burden and demonstrate an increased concordance rate between ctDNA and tissue along with the progression of disease burden. Notably, a substantial number of exclusive genomic alterations (GAs) were identified either in ctDNA or tissue in high-volume metastatic disease. Integrating tissue and ctDNA analysis identified specific gene alterations (BRCA1, BRCA2, CDK12, TP53, PTEN, or RB1) associated with a shorter time to the progression to castration-resistant prostate cancer (CRPC), with an escalated CRPC risk correlated with cumulative GAs. This multicenter, real-world investigation underscores the complementary role of ctDNA and tissue in detecting clinically pertinent GAs, highlighting their potential integration into clinical practice for advanced prostate cancer management.

Deep learning-based automated pipeline for blood vessel detection and distribution analysis in multiplexed prostate cancer images

Introduction: Prostate cancer is a highly heterogeneous disease, presenting varying levels of aggressiveness and response to treatment. Angiogenesis is one of the hallmarks of cancer, providing oxygen and nutrient supply to tumors. Micro vessel density has previously been correlated with higher Gleason score and poor prognosis. Manual segmentation of blood vessels (BVs) In microscopy images is challenging, time consuming and may be prone to inter-rater variabilities. In this study, an automated pipeline is presented for BV detection and distribution analysis in multiplexed prostate cancer images. Methods: A deep learning model was trained to segment BVs by combining CD31, CD34 and collagen IV images. In addition, the trained model was used to analyze the size and distribution patterns of BVs in relation to disease progression in a cohort of prostate cancer patients (N = 215). Results: The model was capable of accurately detecting and segmenting BVs, as compared to ground truth annotations provided by two reviewers. The precision (P), recall (R) and dice similarity coefficient (DSC) were equal to 0.93 (SD 0.04), 0.97 (SD 0.02) and 0.71 (SD 0.07) with respect to reviewer 1, and 0.95 (SD 0.05), 0.94 (SD 0.07) and 0.70 (SD 0.08) with respect to reviewer 2, respectively. BV count was significantly associated with 5-year recurrence (adjusted p = 0.0042), while both count and area of blood vessel were significantly associated with Gleason grade (adjusted p = 0.032 and 0.003 respectively). Discussion: The proposed methodology is anticipated to streamline and standardize BV analysis, offering additional insights into the biology of prostate cancer, with broad applicability to other cancers.

Emerging frontiers in nanomedicine targeted therapy for prostate cancer

Prostate cancer is a prevalent cancer in men, often treated with chemotherapy. However, it tumor cells are clinically grows slowly and is heterogeneous, leading to treatment resistance and recurrence. Nanomedicines, through targeted delivery using nanocarriers, can enhance drug accumulation at the tumor site, sustain drug release, and counteract drug resistance. In addition, combination therapy using nanomedicines can target multiple cancer pathways, improving effectiveness and addressing tumor heterogeneity. The application of nanomedicine in prostate cancer treatment would be an important strategy in controlling tumor dynamic process as well as improve survival. Thus, this review highlights therapeutic nanoparticles as a solution for prostate cancer chemotherapy, exploring targeting strategies and approaches to combat drug resistance.

Identification of tumor-agnostic biomarkers for predicting prostate cancer progression and biochemical recurrence

The diverse clinical outcomes of prostate cancer have led to the development of gene signature assays predicting disease progression. Improved prostate cancer progression biomarkers are needed as current RNA biomarker tests have varying success for intermediate prostate cancer. Interest grows in universal gene signatures for invasive carcinoma progression. Early breast and prostate cancers share characteristics, including hormone dependence and BRCA1/2 mutations. Given the similarities in the pathobiology of breast and prostate cancer, we utilized the NanoString BC360 panel, comprising the validated PAM50 classifier and pathway-specific signatures associated with general tumor progression as well as breast cancer-specific classifiers. This retrospective cohort of primary prostate cancers (n=53) was stratified according to biochemical recurrence (BCR) status and the CAPRA-S to identify genes related to high-risk disease. Two public cohort (TCGA-PRAD and GSE54460) were used to validate the results. Expression profiling of our cohort uncovered associations between PIP and INHBA with BCR and high CAPRA-S score, as well as associations between VCAN, SFRP2, and THBS4 and BCR. Despite low levels of the ESR1 gene compared to AR, we found strong expression of the ER signaling signature, suggesting that BCR may be driven by ER-mediated pathways. Kaplan-Meier and univariate Cox proportional hazards regression analysis indicated the expression of ESR1, PGR, VCAN, and SFRP2 could predict the occurrence of relapse events. This is in keeping with the pathways represented by these genes which contribute to angiogenesis and the epithelial-mesenchymal transition. It is likely that VCAN works by activating the stroma and remodeling the tumor microenvironment. Additionally, SFRP2 overexpression has been associated with increased tumor size and reduced survival rates in breast cancer and among prostate cancer patients who experienced BCR. ESR1 influences disease progression by activating stroma, stimulating stem/progenitor prostate cancer, and inducing TGF-β. Estrogen signaling may therefore serve as a surrogate to AR signaling during progression and in hormone-refractory disease, particularly in prostate cancer patients with stromal-rich tumors. Collectively, the use of agnostic biomarkers developed for breast cancer stratification has facilitated a precise clinical classification of patients undergoing radical prostatectomy and highlighted the therapeutic potential of targeting estrogen signaling in prostate cancer.

Targeting MALAT1 Augments Sensitivity to PARP Inhibition by Impairing Homologous Recombination in Prostate Cancer

PARP inhibitors (PARPi) have emerged as a promising targeted therapeutic intervention for metastatic castrate-resistant prostate cancer (mCRPC). However, the clinical utility of PARPi is limited to a subset of patients who harbor aberrations in the genes associated with the homologous recombination (HR) pathway. Here, we report that targeting metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), an oncogenic long noncoding RNA (lncRNA), contrives a BRCAness-like phenotype, and augments sensitivity to PARPi. Mechanistically, we show that MALAT1 silencing reprograms the homologous recombination (HR) transcriptome and makes prostate cancer cells more vulnerable to PARPi. Particularly, coinhibition of MALAT1 and PARP1 exhibits a decline in clonogenic survival, delays resolution of γH2AX foci, and reduces tumor burden in mice xenograft model. Moreover, we show that miR-421, a tumor suppressor miRNA, negatively regulates the expression of HR genes, while in aggressive prostate cancer cases, miR-421 is sequestered by MALAT1, leading to increased expression of HR genes. Conclusively, our findings suggest that MALAT1 ablation confers sensitivity to PARPi, thus highlighting an alternative therapeutic strategy for patients with castration-resistant prostate cancer (CRPC), irrespective of the alterations in HR genes.

SIGNIFICANCE

PARPi are clinically approved for patients with metastatic CRPC carrying mutations in HR genes, but are ineffective for HR-proficient prostate cancer. Herein, we show that oncogenic lncRNA, MALAT1 is frequently overexpressed in advanced stage prostate cancer and plays a crucial role in maintaining genomic integrity. Importantly, we propose a novel therapeutic strategy that emphasizes MALAT1 inhibition, leading to HR dysfunction in both HR-deficient and -proficient prostate cancer, consequently augmenting their susceptibility to PARPi.

Meta-analysis of 18 F-PSMA-1007 PET/CT, 18 F-FDG PET/CT, and 68Ga-PSMA PET/CT in diagnostic efficacy of prostate Cancer

OBJECTIVE

To compare 18 F-PSMA-1007 PET/CT, 18 F-FDG PET/CT and 68Ga-PSMA PET/CT in the diagnostic value of prostate cancer.

METHOD

The Chinese and foreign databases, such as Pubmed, Cochrane Library, Embase, CNKI, VIP, Wanfang, etc., were systematically searched within the period from the establishment of the database to June 1, 2022. Clinical studies related to the diagnosis of prostate cancer by methods such as 18 F-PSMA-1007 PET/CT, 18 F-FDG PET/CTCT, 68Ga-PSMA PET/CT, were researched. Two (2) investigators independently screened literatures, extracted data, and assessed the risk of bias when these data were included in the studies with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Review Manager5.4, Stata 14.0, and Meta-disc 1.4 software were used for meta-analysis to compare the efficacy of different methods in the diagnose of prostate cancer.

RESULTS

Twenty-seven (27) studies, including 2891 subjects were included in our study. Meta-analysis results showed that the pooled sensitivities of 18 F-PSMA-1007 PET/CT, 18 F-FDG PET/CT, and 68Ga-PSMA PET/CT were 0.912 (95%CI: 0.883-0.936), 0.748 (95%CI: 0.698-0.795), and 0.916 (95%CI: 0.896-0.934), respectively; the pooled specification were 0.878 (0.844-0.907), 0.639 (95%CI: 0.589-0.687), and 0.734 (95%CI: 0.685-0.779), respectively; the positive likelihood ratios were 6.335 (95%CI: 4.288-9.357), 2.282 (95%CI: 1.497-3.477), and 3.593 (95%CI: 2.986-4.323), respectively; the negative likelihood ratios were 0.878 (95%CI: 0.844-0.907), 0.374 (95%CI: 0.280-0.499), and 0.110 (95%CI: 0.083-0.144), respectively; the diagnostic odds ratios were 65.125 (95%CI: 34.059-124.53), 7.094 (95%CI: 4.091-12.301), and 29.722 (95%CI: 20.141-43.863), respectively; the positive posterior probability was 64%, 38%, and 62%, respectively; the area under the SPOC curve was 0.95 (95%CI: 0.93-0.97), 0.81 (95%CI: 0.78-0.84), and 0.96 (95%CI: 0.92-0.98), respectively. The funnel plots indicated that there was no significant publication bias in the included literatures.

CONCLUSION

The current evidences showed that 18 F-PSMA-1007 PET/CT and 68Ga-PSMA PET/CT had higher diagnostic efficacy of prostate cancer compared with 18 F-FDG PET/CT, among which 68Ga-PSMA PET/CT was slightly higher in the sensitivity of the diagnosis of prostate cancer, while 18 F-PSMA-1007 PET/CT may have higher efficacy in specificity and confirmed positive rate. Due to the limitations of the quality of the included samples and literatures, the above conclusions should be further validated by expanding the sample size and improving the quality.

Molecular Targeted Therapies in Metastatic Prostate Cancer: Recent Advances and Future Challenges

Prostate cancer is the most frequent malignant tumor in men, and, despite the great improvements in survival in patients with localized cancer, the prognosis for metastatic disease remains poor. Novel molecular targeted therapies, which block specific molecules or signaling pathways in tumor cells or in their microenvironment, have shown encouraging results in metastatic castration-resistant prostate cancer. Among these therapeutic approaches, prostate-specific membrane antigen-targeted radionuclide therapies and DNA repair inhibitors represent the most promising ones, with some therapeutic protocols already approved by the FDA, whereas therapies targeting tumor neovascularization and immune checkpoint inhibitors have not yet demonstrated clear clinical benefits. In this review, the most relevant studies and clinical trials on this topic are illustrated and discussed, together with future research directions and challenges.

H3 histone methylation landscape in male urogenital cancers: from molecular mechanisms to epigenetic biomarkers and therapeutic targets

During the last decades, male urogenital cancers (including prostate, renal, bladder and testicular cancers) have become one of the most frequently encountered malignancies affecting all ages. While their great variety has promoted the development of various diagnosis, treatment and monitoring strategies, some aspects such as the common involvement of epigenetic mechanisms are still not elucidated. Epigenetic processes have come into the spotlight in the past years as important players in the initiation and progression of tumors, leading to a plethora of studies highlighting their potential as biomarkers for diagnosis, staging, prognosis, and even as therapeutic targets. Thus, fostering research on the various epigenetic mechanisms and their roles in cancer remains a priority for the scientific community. This review focuses on one of the main epigenetic mechanisms, namely, the methylation of the histone H3 at various sites and its involvement in male urogenital cancers. This histone modification presents a great interest due to its modulatory effect on gene expression, leading either to activation (e.g., H3K4me3, H3K36me3) or repression (e.g., H3K27me3, H3K9me3). In the last few years, growing evidence has demonstrated the aberrant expression of enzymes that methylate/demethylate histone H3 in cancer and inflammatory diseases, that might contribute to the initiation and progression of such disorders. We highlight how these particular epigenetic modifications are emerging as potential diagnostic and prognostic biomarkers or targets for the treatment of urogenital cancers.

Activin B and Activin C Have Opposing Effects on Prostate Cancer Progression and Cell Growth

Current prognostic and diagnostic tests for prostate cancer are not able to accurately distinguish between aggressive and latent cancer. Members of the transforming growth factor-β (TGFB) family are known to be important in regulating prostate cell growth and some have been shown to be dysregulated in prostate cancer. Therefore, the aims of this study were to examine expression of TGFB family members in primary prostate tumour tissue and the phenotypic effect of activins on prostate cell growth. Tissue cores of prostate adenocarcinoma and normal prostate were immuno-stained and protein expression was compared between samples with different Gleason grades. The effect of exogenous treatment with, or overexpression of, activins on prostate cell line growth and migration was examined. Activin B expression was increased in cores containing higher Gleason patterns and overexpression of activin B inhibited growth of PNT1A cells but increased growth and migration of the metastatic PC3 cells compared to empty vector controls. In contrast, activin C expression decreased in higher Gleason grades and overexpression increased growth of PNT1A cells and decreased growth of PC3 cells. In conclusion, increased activin B and decreased activin C expression is associated with increasing prostate tumor grade and therefore have potential as prognostic markers of aggressive prostate cancer.

Complexities of Prostate Cancer

Prostate cancer has a long disease history and a wide variety and uncertainty in individual patients' clinical progress. In recent years, we have seen a revolutionary advance in both prostate cancer patient care and in the research field. The power of deep sequencing has provided cistromic and transcriptomic knowledge of prostate cancer that has not discovered before. Our understanding of prostate cancer biology, from bedside and molecular imaging techniques, has also been greatly advanced. It is important that our current theragnostic schemes, including our diagnostic modalities, therapeutic responses, and the drugs available to target non-AR signaling should be improved. This review article discusses the current progress in the understanding of prostate cancer biology and the recent advances in diagnostic and therapeutic strategies.

Establishment of a five-enzalutamide-resistance-related-gene-based classifier for recurrence-free survival predicting of prostate cancer

To identify prostate cancer (PCa) patients with a high risk of recurrence is critical before delivering adjuvant treatment. We developed a classifier based on the Enzalutamide treatment resistance‐related genes to assist the currently available staging system in predicting the recurrence‐free survival (RFS) prognosis of PCa patients. We overlapped the DEGs from two datasets to obtain a more convincing Enzalutamide‐resistance‐related‐gene (ERRG) cluster. The five‐ERRG‐based classifier obtained good predictive values in both the training and validation cohorts. The classifier precisely predicted RFS of patients in four cohorts, independent of patient age, pathological tumour stage, Gleason score and PSA levels. The classifier and the clinicopathological factors were combined to construct a nomogram, which had an increased predictive accuracy than that of each variable alone. Besides, we also compared the differences between high‐ and low‐risk subgroups and found their differences were enriched in cancer progression‐related pathways. The five‐ERRG‐based classifier is a practical and reliable predictor, which adds value to the existing staging system for predicting the RFS prognosis of PCa after radical prostatectomy, enabling physicians to make more informed treatment decisions concerning adjuvant therapy.

Prostate cancer in omics era

Recent advances in omics technology have prompted extraordinary attempts to define the molecular changes underlying the onset and progression of a variety of complex human diseases, including cancer. Since the advent of sequencing technology, cancer biology has become increasingly reliant on the generation and integration of data generated at these levels. The availability of multi-omic data has transformed medicine and biology by enabling integrated systems-level approaches. Multivariate signatures are expected to play a role in cancer detection, screening, patient classification, assessment of treatment response, and biomarker identification. This review reports current findings and highlights a number of studies that are both novel and groundbreaking in their application of multi Omics to prostate cancer.

Co-Inhibition of Androgen Receptor and PARP as a Novel Treatment Paradigm in Prostate Cancer-Where Are We Now?

Metastatic prostate cancer remains lethal with a 5-year survival rate of about 30%, indicating the need for better treatment options. Novel antiandrogens (NAA)-enzalutamide and abiraterone-have been the mainstay of treatment for advanced disease since 2011. In patients who progress on the first NAA, responses to the second NAA are infrequent (25-30%) and short-lasting (median PFS ~3 months). With the growing adoption of NAA therapy in pre-metastatic castration-resistant settings, finding better treatment options for first-line mCRPC has become an urgent clinical need. The regulatory approval of two PARP inhibitors in 2020-rucaparib and olaparib-has provided the first targeted therapy option for patients harboring defects in selected DNA damage response and repair (DDR) pathway genes. However, a growing body of preclinical and clinical data shows that co-inhibition of AR and PARP induces synthetic lethality and could be a promising therapy for patients without any DDR alterations. In this review article, we will investigate the limitations of NAA monotherapy, the mechanistic rationale for synthetic lethality induced by co-inhibition of AR and PARP, the clinical data that have led to the global development of a number of these AR and PARP combination therapies, and how this may impact patient care in the next 2-10 years.

Lack of consensus identifies important areas for future clinical research: Advanced Prostate Cancer Consensus Conference (APCCC) 2019 findings

BACKGROUND

Innovations in treatments, imaging and molecular characterisation have improved outcomes for people with advanced prostate cancer; however, many aspects of clinical management are devoid of high-level evidence. At the Advanced Prostate Cancer Consensus Conference (APCCC) 2019, many of these topics were addressed, and consensus was not always reached. The results from clinical trials will most reliably plus the gaps.

METHODS

An invited panel of 57 experts voted on 123 multiple-choice questions on clinical management at APCCC 2019. No consensus was reached on 88 (71.5%) questions defined as <75% of panellists voting for the same answer option. We reviewed clinicaltrials.gov to identify relevant ongoing phase III trials in these areas of non-consensus.

RESULTS

A number of ongoing phase III trials were identified that are relevant to these non-consensus issues. However, many non-consensus issues appear not to be addressed by current clinical trials. Of note, no phase III but only phase II trials were identified, investigating side effects of hormonal treatments and their management.

CONCLUSIONS

Lack of consensus almost invariably indicates gaps in existing evidence. The high percentage of questions lacking consensus at APCCC 2019 highlights the complexity of advanced prostate cancer care and the need for robust, clinically relevant trials that can fill current gaps with high-level evidence. Our review of these areas of non-consensus and ongoing trials provides a useful summary, indicating areas in which future consensus may soon be reached. This review may facilitate academic investigators to identify and prioritise topics for future research.

Epigenetic loss of heterogeneity from low to high grade localized prostate tumours

Identifying precise molecular subtypes attributable to specific stages of localized prostate cancer has proven difficult due to high levels of heterogeneity. Bulk assays represent a population-average, which mask the heterogeneity that exists at the single-cell level. In this work, we sequence the accessible chromatin regions of 14,424 single-cells from 18 flash-frozen prostate tumours. We observe shared chromatin features among low-grade prostate cancer cells are lost in high-grade tumours. Despite this loss, high-grade tumours exhibit an enrichment for FOXA1, HOXB13 and CDX2 transcription factor binding sites, indicating a shared trans-regulatory programme. We identify two unique genes encoding neuronal adhesion molecules that are highly accessible in high-grade prostate tumours. We show NRXN1 and NLGN1 expression in epithelial, endothelial, immune and neuronal cells in prostate cancer using cyclic immunofluorescence. Our results provide a deeper understanding of the active gene regulatory networks in primary prostate tumours, critical for molecular stratification of the disease.

Repurposing existing therapeutics, its importance in oncology drug development: Kinases as a potential target

Repurposing the large arsenal of existing non‐cancer drugs is an attractive proposition to expand the clinical pipelines for cancer therapeutics. The earlier successes in repurposing resulted primarily from serendipitous findings, but more recently, drug or target‐centric systematic identification of repurposing opportunities continues to rise. Kinases are one of the most sought‐after anti‐cancer drug targets over the last three decades. There are many non‐cancer approved drugs that can inhibit kinases as “off‐targets” as well as many existing kinase inhibitors that can target new additional kinases in cancer. Identifying cancer‐associated kinase inhibitors through mining commercial drug databases or new kinase targets for existing inhibitors through comprehensive kinome profiling can offer more effective trial‐ready options to rapidly advance drugs for clinical validation. In this review, we argue that drug repurposing is an important approach in modern drug development for cancer therapeutics. We have summarized the advantages of repurposing, the rationale behind this approach together with key barriers and opportunities in cancer drug development. We have also included examples of non‐cancer drugs that inhibit kinases or are associated with kinase signalling as a basis for their anti‐cancer action.

The CYP19A1 (TTTA)n Repeat Polymorphism May Affect the Prostate Cancer Risk: Evidence from a Meta-Analysis

Abnormal aromatase (CYP19A1) expression may participate in prostate cancer (PCa) carcinogenesis. However, the results of studies on the CYP19A1 gene polymorphisms and PCa are conflicting. This meta-analysis aimed to systematically evaluate the associations between the CYP19A1 Arg264Cys polymorphism and the (TTTA)n repeat polymorphism and PCa. Electronic databases (PubMed, EmBase, ScienceDirect, and Cochrane Library) were comprehensively searched to identify eligible studies. The strength of the association between the Arg264Cys polymorphism and PCa was assessed by pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) in allelic, dominant, recessive, homozygous, and heterozygous genetic models. To analyze the impact of the (TTTA)n repeat polymorphism, we sequentially took the N-repeat allele (where N equals 7,8,10,11,12, and 13) as the minor allele and the sum of all the other alleles as the major allele. The ORs and 95% CIs were calculated in the allelic model; this analysis was performed individually for each repeat number. Pooled estimates of nine studies addressing the Arg264Cys polymorphism indicated that this polymorphism was not associated with PCa risk in the overall population or in the Caucasian or Asian subgroups. The 8-repeat allele in the (TTTA)n repeat polymorphism increased PCa risk in the overall population (OR = 1.34, 95% CI = 1.14-1.58, p = .001) and in the subgroup with population-based (PB) controls (OR = 1.41, 95% CI = 1.13-1.74, p = .002) as well as in the subgroup using capillary electrophoresis to identify this polymorphism (OR = 1.34, 95% CI = 1.09-1.65, p = .006).The meta-analysis indicated that the CYP19A1 (TTTA)n repeat polymorphism, but not the Arg264Cys polymorphism, may affect PCa risk.

Metastatic Spread in Prostate Cancer Patients Influencing Radiotherapy Response

Radiotherapy and surgery are curative treatment options for localized prostate cancer (PCa) with a 5-year survival rate of nearly 100%. Once PCa cells spread into distant organs, such as bone, the overall survival rate of patients drops dramatically. The metastatic cascade and organotropism of PCa cells are regulated by different cellular subtypes, organ microenvironment, and their interactions. This cross-talk leads to pre-metastatic niche formation that releases chemo-attractive factors enforcing the formation of distant metastasis. Biological characteristics of PCa metastasis impacting on metastatic sites, burden, and latency is of clinical relevance. Therefore, the implementation of modern hybrid imaging technologies into clinical routine increased the sensitivity to detect metastases at earlier stages. This enlarged the number of PCa patients diagnosed with a limited number of metastases, summarized as oligometastatic disease. These patients can be treated with androgen deprivation in combination with local-ablative radiotherapy or radiopharmaceuticals directed to metastatic sites. Unfortunately, the number of patients with disease recurrence is high due to the enormous heterogeneity within the oligometastatic patient population and the lack of available biomarkers with predictive potential for metastasis-directed radiotherapy. Another, so far unmet clinical need is the diagnosis of minimal residual disease before onset of clinical manifestation and/or early relapse after initial therapy. Here, monitoring of circulating and disseminating tumor cells in PCa patients during the course of radiotherapy may give us novel insight into how metastatic spread is influenced by radiotherapy and vice versa. In summary, this review critically compares current clinical concepts for metastatic PCa patients and discuss the implementation of recent preclinical findings improving our understanding of metastatic dissemination and radiotherapy resistance into standard of care.

A preliminary study of micro-RNAs as minimally invasive biomarkers for the diagnosis of prostate cancer patients

Background

A prostate cancer diagnosis is based on biopsy sampling that is an invasive, expensive procedure, and doesn’t accurately represent multifocal disease.

Methods

To establish a model using plasma miRs to distinguish Prostate cancer patients from non-cancer controls, we enrolled 600 patients histologically diagnosed as having or not prostate cancer at biopsy. Two hundred ninety patients were eligible for the analysis. Samples were randomly divided into discovery and validation cohorts.

Results

NGS-miR-expression profiling revealed a miRs signature able to distinguish prostate cancer from non-cancer plasma samples. Of 51 miRs selected in the discovery cohort, we successfully validated 5 miRs (4732-3p, 98-5p, let-7a-5p, 26b-5p, and 21-5p) deregulated in prostate cancer samples compared to controls (p ≤ 0.05). Multivariate and ROC analyses show miR-26b-5p as a strong predictor of PCa, with an AUC of 0.89 (CI = 0.83–0.95;p < 0.001). Combining miRs 26b-5p and 98-5p, we developed a model that has the best predictive power in discriminating prostate cancer from non-cancer (AUC = 0.94; CI: 0,835-0,954).

To distinguish between low and high-grade prostate cancer, we found that miR-4732-3p levels were significantly higher; instead, miR-26b-5p and miR-98-5p levels were lower in low-grade compared to the high-grade group (p ≤ 0.05).

Combining miR-26b-5p and miR-4732-3p we have the highest diagnostic accuracy for high-grade prostate cancer patients, (AUC = 0.80; CI 0,69-0,873).

Conclusions

Noninvasive diagnostic tests may reduce the number of unnecessary prostate biopsies.

The 2-miRs-diagnostic model (miR-26b-5p and miR-98-5p) and the 2-miRs-grade model (miR-26b-5p and miR-4732-3p) are promising minimally invasive tools in prostate cancer clinical management.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01875-0.

Prostate cancer

Prostate cancer is a complex disease that affects millions of men globally, predominantly in high human development index regions. Patients with localized disease at a low to intermediate risk of recurrence generally have a favourable outcome of 99% overall survival for 10 years if the disease is detected and treated at an early stage. Key genetic alterations include fusions of TMPRSS2 with ETS family genes, amplification of the MYC oncogene, deletion and/or mutation of PTEN and TP53 and, in advanced disease, amplification and/or mutation of the androgen receptor (AR). Prostate cancer is usually diagnosed by prostate biopsy prompted by a blood test to measure prostate-specific antigen levels and/or digital rectal examination. Treatment for localized disease includes active surveillance, radical prostatectomy or ablative radiotherapy as curative approaches. Men whose disease relapses after prostatectomy are treated with salvage radiotherapy and/or androgen deprivation therapy (ADT) for local relapse, or with ADT combined with chemotherapy or novel androgen signalling-targeted agents for systemic relapse. Advanced prostate cancer often progresses despite androgen ablation and is then considered castration-resistant and incurable. Current treatment options include AR-targeted agents, chemotherapy, radionuclides and the poly(ADP-ribose) inhibitor olaparib. Current research aims to improve prostate cancer detection, management and outcomes, including understanding the fundamental biology at all stages of the disease.

Prostate cancer

Prostate cancer is a complex disease that affects millions of men globally, predominantly in high human development index regions. Patients with localized disease at a low to intermediate risk of recurrence generally have a favourable outcome of 99% overall survival for 10 years if the disease is detected and treated at an early stage. Key genetic alterations include fusions of TMPRSS2 with ETS family genes, amplification of the MYC oncogene, deletion and/or mutation of PTEN and TP53 and, in advanced disease, amplification and/or mutation of the androgen receptor (AR). Prostate cancer is usually diagnosed by prostate biopsy prompted by a blood test to measure prostate-specific antigen levels and/or digital rectal examination. Treatment for localized disease includes active surveillance, radical prostatectomy or ablative radiotherapy as curative approaches. Men whose disease relapses after prostatectomy are treated with salvage radiotherapy and/or androgen deprivation therapy (ADT) for local relapse, or with ADT combined with chemotherapy or novel androgen signalling-targeted agents for systemic relapse. Advanced prostate cancer often progresses despite androgen ablation and is then considered castration-resistant and incurable. Current treatment options include AR-targeted agents, chemotherapy, radionuclides and the poly(ADP-ribose) inhibitor olaparib. Current research aims to improve prostate cancer detection, management and outcomes, including understanding the fundamental biology at all stages of the disease.

MicroRNA-4287 is a novel tumor suppressor microRNA controlling epithelial-to mesenchymal transition in prostate cancer

Prostate cancer (PCa) is a significant cause of male morbidity in the United States. Despite recent advances in diagnosis and therapeutic interventions, significant fraction of cases still progress to an advanced stage. Various genetic/epigenetic elements that facilitate this progression are not yet completely known and the mechanism that favors advanced disease is an area of investigation. A characteristic feature associated with progressive disease is deletion of chromosome 8p (chr8p) region, that harbors tumor-suppressor NKX3.1. Previous studies from our group has shown that there are cluster of microRNAs (miRNAs) located within this region whose loss favors advanced, metastatic disease. miR-4287 is a novel miRNA located within this region that has not been studied before. In the present study, we analyzed the role of miR-4287 in PCa using clinical tissues and cell lines. We observed that miR-4287 is significantly downregulated in patient-derived tumor tissues. Receiver operating curve (ROC) analysis showed that miR-4287 distinguishes prostate cancer from normal with a specificity of 88.24% and with an Area under the curve (AUC) of 0.66. Further, we found that miR-4287 levels correlate inversely with patients' serum prostate-specific antigen levels. Ectopic over-expression of miR-4287 in PCa cell lines showed that miR-4287 plays a tumor suppressor role. miR-4287 led to an increase in G2/M phase of cell cycle in PCa cell lines. Further, ectopic miR-4287 inhibited PCa epithelial-to-mesenchymal transition (EMT) by directly repressing SLUG and stem cell marker CD44. Since miR-4287 specifically targets metastasis pathway mediators, miR-4287 has potential diagnostic and therapeutic significance in preventing advanced, metastatic disease.

Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up

BACKGROUND

Heterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies.

METHODS

Using a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRT-PCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy.

RESULTS

The 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963-0.929) in the retrospective cohort (n = 614), AUC of 0.901 (0.929-0.873) in the prospective cohort (n = 396), and AUC of 0.936 (0.956-0.916) in the large combination cohort (n = 1010). It greatly improved diagnostic accuracy over PSA and risk factors (p < 0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980-0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947-0.909) in the combination cohort (n = 727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy.

CONCLUSIONS

The 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.

Clinical proteomics for prostate cancer: understanding prostate cancer pathology and protein biomarkers for improved disease management

Following the introduction of routine Prostate Specific Antigen (PSA) screening in the early 1990's, Prostate Cancer (PCa) is often detected at an early stage. There are also a growing number of treatment options available and so the associated mortality rate is generally low. However, PCa is an extremely complex and heterogenous disease and many patients suffer disease recurrence following initial therapy. Disease recurrence commonly results in metastasis and metastatic PCa has an average survival rate of just 3-5 years. A significant problem in the clinical management of PCa is being able to differentiate between patients who will respond to standard therapies and those who may benefit from more aggressive intervention at an earlier stage. It is also acknowledged that for many men the disease is not life threatenting. Hence, there is a growing desire to identify patients who can be spared the significant side effects associated with PCa treatment until such time (if ever) their disease progresses to the point where treatment is required. To these important clinical needs, current biomarkers and clinical methods for patient stratification and personlised treatment are insufficient. This review provides a comprehensive overview of the complexities of PCa pathology and disease management. In this context it is possible to review current biomarkers and proteomic technologies that will support development of biomarker-driven decision tools to meet current important clinical needs. With such an in-depth understanding of disease pathology, the development of novel clinical biomarkers can proceed in an efficient and effective manner, such that they have a better chance of improving patient outcomes.

Multi-ethnic transcriptome-wide association study of prostate cancer

The genetic risk for prostate cancer has been governed by a few rare variants with high penetrance and over 150 commonly occurring variants with lower impact on risk; however, most of these variants have been identified in studies containing exclusively European individuals. People of non-European ancestries make up less than 15% of prostate cancer GWAS subjects. Across the globe, incidence of prostate cancer varies with population due to environmental and genetic factors. The discrepancy between disease incidence and representation in genetics highlights the need for more studies of the genetic risk for prostate cancer across diverse populations. To better understand the genetic risk for prostate cancer across diverse populations, we performed PrediXcan and GWAS in a case-control study of 4,769 self-identified African American (2,463 cases and 2,306 controls), 2,199 Japanese American (1,106 cases and 1,093 controls), and 2,147 Latin American (1,081 cases and 1,066 controls) individuals from the Multiethnic Genome-wide Scan of Prostate Cancer. We used prediction models from 46 tissues in GTEx version 8 and five models from monocyte transcriptomes in the Multi-Ethnic Study of Atherosclerosis. Across the three populations, we predicted 19 gene-tissue pairs, including five unique genes, to be significantly (lfsr < 0.05) associated with prostate cancer. One of these genes, NKX3-1, replicated in a larger European study. At the SNP level, 110 SNPs met genome-wide significance in the African American study while 123 SNPs met significance in the Japanese American study. Fine mapping revealed three significant independent loci in the African American study and two significant independent loci in the Japanese American study. These identified loci confirm findings from previous GWAS of prostate cancer in diverse populations while PrediXcan-identified genes suggest potential new directions for prostate cancer research in populations across the globe.

Stochastic Sequential Modeling: Toward Improved Prostate Cancer Diagnosis Through Temporal-Ultrasound

Prostate cancer (PCa) is a common, serious form of cancer in men that is still prevalent despite ongoing developments in diagnostic oncology. Current detection methods lead to high rates of inaccurate diagnosis. We present a method to directly model and exploit temporal aspects of temporal enhanced ultrasound (TeUS) for tissue characterization, which improves malignancy prediction. We employ a probabilistic-temporal framework, namely, hidden Markov models (HMMs), for modeling TeUS data obtained from PCa patients. We distinguish malignant from benign tissue by comparing the respective log-likelihood estimates generated by the HMMs. We analyze 1100 TeUS signals acquired from 12 patients. Our results show improved malignancy identification compared to previous results, demonstrating over 85% accuracy and AUC of 0.95. Incorporating temporal information directly into the models leads to improved tissue differentiation in PCa. We expect our method to generalize and be applied to other types of cancer in which temporal-ultrasound can be recorded.

Dynamics of Cellular Plasticity in Prostate Cancer Progression

Despite the current advances in the treatment for prostate cancer, the patients often develop resistance to the conventional therapeutic interventions. Therapy-induced drug resistance and tumor progression have been associated with cellular plasticity acquired due to reprogramming at the molecular and phenotypic levels. The plasticity of the tumor cells is mainly governed by two factors: cell-intrinsic and cell-extrinsic. The cell-intrinsic factors involve alteration in the genetic or epigenetic regulators, while cell-extrinsic factors include microenvironmental cues and drug-induced selective pressure. Epithelial-mesenchymal transition (EMT) and stemness are two important hallmarks that dictate cellular plasticity in multiple cancer types including prostate. Emerging evidence has also pinpointed the role of tumor cell plasticity in driving anti-androgen induced neuroendocrine prostate cancer (NEPC), a lethal and therapy-resistant subtype. In this review, we discuss the role of cellular plasticity manifested due to genetic, epigenetic alterations and cues from the tumor microenvironment, and their role in driving therapy resistant prostate cancer.

Cause of Mortality after Radical Prostatectomy and the Impact of Comorbidity in Men with Prostate Cancer: A Multi-institutional Study in Korea

Purpose

This study aimed to examine the causes of death in Korean patients who underwent radical prostatectomy for prostate cancer and investigate the relationship between comorbidity and mortality.

Materials and Methods

We conducted a retrospective multicenter cohort study including 4,064 consecutive patients who had prostate cancer and underwent radical prostatectomy between January 1998 and June 2013. The primary endpoint of this study was all-cause mortality, and the secondary endpoints were cancer-specific mortality (CSM) and other-cause mortality (OCM). Charlson comorbidity index (CCI) was calculated to assess the comorbidities of each patient.

Results

Of 4,064 patients, 446 (11.0%) died during follow-up. The cause of death was prostate cancer in 132 patients (29.6%), other cancers in 121 patients (27.1%), and vascular disease in 57 patients (12.8%) in our cohort. The overall 10-year CSM rate was lower than the OCM rate (4.6% vs. 10.5%). The 10-year CSM rate was lower than the OCM rate in low- to intermediate-risk group patients (1.2% vs. 10.6%), whereas they were similar in high-risk group patients (11.8% vs. 10.1%). In the multivariable analysis, CCI was independently associated with all-cause mortality after radical prostatectomy, regardless of age and pathologic features.

Conclusion

Death from prostate cancer was rare in Korean men who underwent radical prostatectomy. Clinicians should be aware of the possibility of overtreatment of low-risk prostate cancer in men with significant comorbidity. Our findings may help to facilitate counseling and plan management in this patient group.

HLA Class I Allele Expression and Clinical Outcome in De Novo Metastatic Prostate Cancer

The prognostic value of human leukocyte antigen (HLA) class I molecules in prostate cancer (PCa) remains unclear. Herein, we investigated the prognostic relevance of the most frequently expressed HLA-A alleles in Greece (A*02:01 and HLA-A*24:02) in de novo metastatic hormone-sensitive PCa (mPCa), which is a rare and aggressive disease characterized by a rapid progression to castration-resistance (CR) and poor overall survival (OS), contributing to almost 50% of PCa-related deaths. We identified 56 patients who had either progressed to CR (these patients were retrospectively analyzed for the time to the progression of CR and prospectively for OS) or had at least three months’ follow-up postdiagnosis without CR progression and, thus, were prospectively analyzed for both CR and OS. Patients expressing HLA-A*02:01 showed poor clinical outcomes vs. HLA-A*02:01⁻negative patients. HLA-A*24:02⁻positive patients progressed slower to CR and had increased OS. Homozygous HLA-A*02:01 patients progressed severely to CR, with very short OS. Multivariate analyses ascribed to both HLA alleles significant prognostic values for the time to progression (TTP) to CR and OS. The presence of HLA-A*02:01 and HLA-A*24:02 alleles in de novo mPCa patients are significantly and independently associated with unfavorable or favorable clinical outcomes, respectively, suggesting their possible prognostic relevance for treatment decision-making in the context of precision medicine.

Integrative Analysis of MicroRNA and Gene Interactions for Revealing Candidate Signatures in Prostate Cancer

MicroRNA (miRNA)-gene interactions are well-recognized as involved in the progression of almost all cancer types including prostate cancer, which is one of the most common cancers in men. This study explored the significantly dysregulated genes and miRNAs and elucidated the potential miRNA-gene regulatory network in prostate cancer. Integrative analysis of prostate cancer and normal prostate transcriptomic data in The Cancer Genome Atlas dataset was conducted using both differential expression analysis and weighted correlation network analysis (WGCNA). Thirteen genes (RRM2, ORC6, CDC45, CDKN2A, E2F2, MYBL2, CCNB2, PLK1, FOXM1, CDC25C, PKMYT1, GTSE1, and CDC20) were potentially correlated with prostate cancer based on functional enrichment analyses. MiRNAs targeting these genes were predicted and eight miRNAs were intersections between those miRNAs and the hub miRNAs obtained from miRNA WGCNA analysis. Three genes (E2F2, RRM2, and PKMYT1) and four miRNAs (hsa-mir-17-5p, hsa-mir-20a-5p, hsa-mir-92a-3p, and hsa-mir-93-5p) were key factors according to the interaction network. RRM2 and PKMYT1 were significantly related to survival. These findings partially elucidated the dysregulation of gene expressions in prostate cancer. Efficient manipulations of the miRNA-gene interactions in prostate cancer may be exploited as promising therapeutics.

TIP5 primes prostate luminal cells for the oncogenic transformation mediated by PTEN-loss

The cell of origin and the temporal order of oncogenic events in tumors play important roles for disease state. This is of particular interest for PCa due to its highly variable clinical outcome. However, these features are difficult to analyze in tumors. We established an in vitro murine PCa organoid model taking into account the cell of origin and the temporal order of events. We found that TIP5 primes luminal prostate cells for Pten-loss mediated oncogenic transformation whereas it is dispensable once the transformation is established. Cross-species transcriptomic analyses revealed a PTEN-loss gene signature that identified a set of aggressive tumors with PTEN-del, or low PTEN expression, and high-TIP5 expression. This paper provides a powerful tool to elucidate PCa mechanisms.

Prostate cancer (PCa) is the second leading cause of cancer death in men. Its clinical and molecular heterogeneities and the lack of in vitro models outline the complexity of PCa in the clinical and research settings. We established an in vitro mouse PCa model based on organoid technology that takes into account the cell of origin and the order of events. Primary PCa with deletion of the tumor suppressor gene PTEN (PTEN-del) can be modeled through Pten-down-regulation in mouse organoids. We used this system to elucidate the contribution of TIP5 in PCa initiation, a chromatin regulator that is implicated in aggressive PCa. High TIP5 expression correlates with primary PTEN-del PCa and this combination strongly associates with reduced prostate-specific antigen (PSA) recurrence-free survival. TIP5 is critical for the initiation of PCa of luminal origin mediated by Pten-loss whereas it is dispensable once Pten-loss mediated transformation is established. Cross-species analyses revealed a PTEN gene signature that identified a group of aggressive primary PCas characterized by PTEN-del, high-TIP5 expression, and a TIP5-regulated gene expression profile. The results highlight the modeling of PCa with organoids as a powerful tool to elucidate the role of genetic alterations found in recent studies in their time orders and cells of origin, thereby providing further optimization for tumor stratification to improve the clinical management of PCa.

Engineering Prostate Cancer from Induced Pluripotent Stem Cells-New Opportunities to Develop Preclinical Tools in Prostate and Prostate Cancer Studies

One of the key issues hampering the development of effective treatments for prostate cancer is the lack of suitable, tractable, and patient-specific in vitro models that accurately recapitulate this disease. In this review, we address the challenges of using primary cultures and patient-derived xenografts to study prostate cancer. We describe emerging approaches using primary prostate epithelial cells and prostate organoids and their genetic manipulation for disease modelling. Furthermore, the use of human prostate-derived induced pluripotent stem cells (iPSCs) is highlighted as a promising complimentary approach. Finally, we discuss the manipulation of iPSCs to generate 'avatars' for drug disease testing. Specifically, we describe how a conceptual advance through the creation of living biobanks of "genetically engineered cancers" that contain patient-specific driver mutations hold promise for personalised medicine.

Sulfiredoxin as a Potential Therapeutic Target for Advanced and Metastatic Prostate Cancer

The incidence of prostate cancer (PCa) is increasing, and it is currently the second most frequent cause of death by cancer in men. Despite advancements in cancer therapies, new therapeutic approaches are still needed for treatment-refractory advanced metastatic PCa. Cross-species analysis presents a robust strategy for the discovery of new potential therapeutic targets. This strategy involves the integration of genomic data from genetically engineered mouse models (GEMMs) and human PCa datasets. Considering the role of antioxidant pathways in tumor initiation and progression, we searched oxidative stress-related genes for a potential therapeutic target for PCa. First, we analyzed RNA-sequencing data from Pb-Cre4; Pten^f/f mice and discovered an increase in sulfiredoxin (Srxn1) mRNA expression in high-grade prostatic intraepithelial neoplasia (PIN), well-differentiated adenocarcinoma (medium-stage tumors), and poor-differentiated adenocarcinoma (advanced-stage prostate tumors). The increase of SRXN1 protein expression was confirmed by immunohistochemistry in mouse prostate tumor paraffin samples. Analyses of human databases and prostate tissue microarrays demonstrated that SRXN1 is overexpressed in a subset of high-grade prostate tumors and correlates with aggressive PCa with worse prognosis and decreased survival. Analyses in vitro showed that SRXN1 expression is also higher in most PCa cell lines compared to normal cell lines. Furthermore, siRNA-mediated downregulation of SRXN1 led to decreased viability of PCa cells LNCaP. In conclusion, we identified the antioxidant enzyme SRXN1 as a potential therapeutic target for PCa. Our results suggest that the use of specific SRXN1 inhibitors may be an effective strategy for the adjuvant treatment of castration-resistant PCa with SRXN1 overexpression.

Disparities in prostate cancer incidence and mortality rates: Solvable or not?

Prostate cancer (PCa) is recognized as a disease possessing not only great variation in its geographic and racial distribution but also tremendous variation in its potential to cause morbidity and death and it, therefore, ought not to be considered a homogenous disease entity. Morbidity and death from PCa are disproportionately higher in men of African ancestry (MAA) who are generally observed to have more aggressive disease and worse outcomes following treatment compared to men of European ancestry (MEA). The higher rates of PCa among MAA relative to MEA appear to be multifactorial and related to inherent differences in biological aggressiveness; a continued lack of awareness of the disease and methods of prevention; a lower prevalence of screen-detected PCa; comparatively lower access to quality healthcare as well as systemic and institutionalized disparities in the administration of optimal care to MAA in developed countries such as the United States of America where high-quality care is available. Even when access to quality healthcare is assured in equal access settings, it appears that MAA still have worse outcomes after PCa treatment stage-for-stage and grade-for-grade compared to MEA, suggesting that, inherent racial, ethnic and biological differences are paramount in predicting poor outcomes. This review has explored the different contributing factors to the current disparities in PCa incidence and mortality rates with emphasis on the incongruence in how research has been conducted in understanding the disease towards developing therapies.

Extracellular vesicles in urological malignancies: an update

Extracellular vesicles (EVs) have an essential functional role in local tumour progression, metastatic spread and the emergence of drug resistance in bladder, kidney and prostate cancer. Thus, EVs could be diagnostic, prognostic and predictive biomarkers for these malignancies. Virtually all biomolecules (including DNA, mRNA, microRNA, long non-coding RNA, proteins and lipids) packaged into EVs have been tested as biomarkers in blood and urine samples. The results are very heterogeneous, but promising biomarker candidates have been identified. Differing methods of EV isolation, characterization and analysis of their content have been used owing to a lack of international consensus; hence, comparing study results is challenging. Furthermore, validation of potential biomarkers in independent cohorts or prospective trials has rarely been performed. Future efforts to establish EV-derived biomarkers need to adequately address these points. In addition, emerging technologies such as mass spectroscopy and chip-based approaches can identify surface markers specific for cancer-associated EVs and will enable specific separation from blood and urine EVs, which probably will improve their performance as biomarkers. Moreover, EVs could be harnessed as therapeutic drug delivery vehicles for precise and effective anticancer therapy.

The genomic landscape of metastatic castration-resistant prostate cancers reveals multiple distinct genotypes with potential clinical impact

Metastatic castration-resistant prostate cancer (mCRPC) has a highly complex genomic landscape. With the recent development of novel treatments, accurate stratification strategies are needed. Here we present the whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 mCRPC patients. Using unsupervised clustering based on genomic features, we define eight distinct genomic clusters. We observe potentially clinically relevant genotypes, including microsatellite instability (MSI), homologous recombination deficiency (HRD) enriched with genomic deletions and BRCA2 aberrations, a tandem duplication genotype associated with CDK12-/- and a chromothripsis-enriched subgroup. Our data suggests that stratification on WGS characteristics may improve identification of MSI, CDK12-/- and HRD patients. From WGS and ChIP-seq data, we show the potential relevance of recurrent alterations in non-coding regions identified with WGS and highlight the central role of AR signaling in tumor progression. These data underline the potential value of using WGS to accurately stratify mCRPC patients into clinically actionable subgroups.

The Δ133p53β isoform promotes an immunosuppressive environment leading to aggressive prostate cancer

Prostate cancer is the second most common cancer in men, for which there are no reliable biomarkers or targeted therapies. Here we demonstrate that elevated levels of Δ133TP53β isoform characterize prostate cancers with immune cell infiltration, particularly T cells and CD163+ macrophages. These cancers are associated with shorter progression-free survival, Gleason scores ≥ 7, and an immunosuppressive environment defined by a higher proportion of PD-1, PD-L1 and colony-stimulating factor 1 receptor (CSF1R) positive cells. Consistent with this, RNA-seq of tumours showed enrichment for pathways associated with immune signalling and cell migration. We further show a role for hypoxia and wild-type p53 in upregulating Δ133TP53 levels. Finally, AUC analysis showed that Δ133TP53β expression level alone predicted aggressive disease with 88% accuracy. Our data identify Δ133TP53β as a highly accurate prognostic factor for aggressive prostate cancer.

Immune checkpoint inhibitors in mCRPC - rationales, challenges and perspectives

The advancement of immune-therapeutics in cancer treatment has proven to be promising in various malignant diseases. However, in castration resistant prostate cancer (mCRPC) major Phase III trials have been unexpectedly disappointing. To contribute to a broader understanding of the role and use of immune-therapeutics in mCRPC, we conducted a systematic review. We searched the websites ClinicalTrials.gov, PubMed and ASCO Meeting Library for clinical trials employing immune checkpoint inhibitors in mCRPC. This article not only describes the rationale of individual trials, but it also summarizes the current status of the field and sheds light on strategies for future success.

Association of imputed prostate cancer transcriptome with disease risk reveals novel mechanisms

Here we train cis-regulatory models of prostate tissue gene expression and impute expression transcriptome-wide for 233,955 European ancestry men (14,616 prostate cancer (PrCa) cases, 219,339 controls) from two large cohorts. Among 12,014 genes evaluated in the UK Biobank, we identify 38 associated with PrCa, many replicating in the Kaiser Permanente RPGEH. We report the association of elevated TMPRSS2 expression with increased PrCa risk (independent of a previously-reported risk variant) and with increased tumoral expression of the TMPRSS2:ERG fusion-oncogene in The Cancer Genome Atlas, suggesting a novel germline-somatic interaction mechanism. Three novel genes, HOXA4, KLK1, and TIMM23, additionally replicate in the RPGEH cohort. Furthermore, 4 genes, MSMB, NCOA4, PCAT1, and PPP1R14A, are associated with PrCa in a trans-ethnic meta-analysis (N = 9117). Many genes exhibit evidence for allele-specific transcriptional activation by PrCa master-regulators (including androgen receptor) in Position Weight Matrix, Chip-Seq, and Hi-C experimental data, suggesting common regulatory mechanisms for the associated genes.

Role of a novel race-related tumor suppressor microRNA located in frequently deleted chromosomal locus 8p21 in prostate cancer progression

The prostate cancer (PCa) genome is characterized by deletions of chromosome 8p21-22 region that increase significantly with tumor grade and are associated with poor prognosis. We proposed and validated a novel, paradigm-shifting hypothesis that this region is associated with a set of microRNA genes-miR-3622, miR-3622b, miR-383-that are lost in PCa and play important mechanistic roles in PCa progression and metastasis. Extending our hypothesis, in this study, we evaluated the role of a microRNA gene located in chromosome 8p-miR-4288-by employing clinical samples and cell lines. Our data suggests that (i) miR-4288 is widely downregulated in primary prostate tumors and cell lines; (ii) miR-4288 expression is lost in metastatic castration-resistant PCa; (ii) miR-4288 downregulation is race-related PCa alteration that is prevalent in Caucasian patients and not in African Americans; (iii) in Caucasians, miR-4288 was found to be associated with increasing tumor grade and high serum prostate-specific antigen, suggesting that miR-4288 downregulation/loss may be associated with tumor progression specifically in Caucasians; (iv) miR-4288 possess significant potential as a molecular biomarker to predict aggressiveness/metastasis; and (v) miR-4288 is anti-proliferative, is anti-invasive and inhibits epithelial-to-mesenchymal transition; and (vi) miR-4288 directly represses expression of metastasis/invasion-associated genes MMP16 and ROCK1. Thus, the present study demonstrates a tumor suppressor role for a novel miRNA located with a frequently lost region in PCa, strengthening our hypothesis that this locus is causally related to PCa disease progression via loss of microRNA genes. Our study suggests that miR-4288 may be a novel biomarker and therapeutic target, particularly in Caucasians.