Validation of potential RNA biomarkers for prostate cancer diagnosis and monitoring in plasma and urinary extracellular vesicles.

Introduction: Prostate cancer (PCa), one of the most prevalent malignancies affecting men worldwide, presents significant challenges in terms of early detection, risk stratification, and active surveillance. In recent years, liquid biopsies have emerged as a promising non-invasive approach to complement or even replace traditional tissue biopsies. Extracellular vesicles (EVs), nanosized membranous structures released by various cells into body fluids, have gained substantial attention as a source of cancer biomarkers due to their ability to encapsulate and transport a wide range of biological molecules, including RNA. In this study, we aimed to validate 15 potential RNA biomarkers, identified in a previous EV RNA sequencing study, using droplet digital PCR. Methods: The candidate biomarkers were tested in plasma and urinary EVs collected before and after radical prostatectomy from 30 PCa patients and their diagnostic potential was evaluated in a test cohort consisting of 20 benign prostate hyperplasia (BPH) and 20 PCa patients' plasma and urinary EVs. Next, the results were validated in an independent cohort of plasma EVs from 31 PCa and 31 BPH patients. Results: We found that the levels of NKX3-1 (p = 0.0008) in plasma EVs, and tRF-Phe-GAA-3b (p < 0.0001) tRF-Lys-CTT-5c (p < 0.0327), piR-28004 (p = 0.0081) and miR-375-3p (p < 0.0001) in urinary EVs significantly decreased after radical prostatectomy suggesting that the main tissue source of these RNAs is prostate and/or PCa. Two mRNA biomarkers-GLO1 and NKX3-1 showed promising diagnostic potential in distinguishing between PCa and BPH with AUC of 0.68 and 0.82, respectively, in the test cohort and AUC of 0.73 and 0.65, respectively, in the validation cohort, when tested in plasma EVs. Combining these markers in a biomarker model yielded AUC of 0.85 and 0.71 in the test and validation cohorts, respectively. Although the PSA levels in the blood could not distinguish PCa from BPH in our cohort, adding PSA to the mRNA biomarker model increased AUC from 0.71 to 0.76. Conclusion: This study identified two novel EV-enclosed RNA biomarkers-NKX3-1 and GLO1-for the detection of PCa, and highlights the complementary nature of GLO1, NKX3-1 and PSA as combined biomarkers in liquid biopsies of PCa.

Viability Analysis and High-Content Live-Cell Imaging for Drug Testing in Prostate Cancer Xenograft-Derived Organoids.

Tumor organoids have been pushed forward as advanced model systems for in vitro oncology drug testing, with the eventual goal to direct personalized cancer treatments. However, drug testing efforts suffer from a large variation in experimental conditions for organoid culturing and organoid treatment. Moreover, most drug tests are restricted to whole-well viability as the sole read-out, thereby losing important information about key biological aspects that might be impacted due to the use of administered drugs. These bulk read-outs also discard potential inter-organoid heterogeneity in drug responses. To tackle these issues, we developed a systematic approach for processing organoids from prostate cancer (PCa) patient-derived xenografts (PDXs) for viability-based drug testing and identified essential conditions and quality checks for consistent results. In addition, we generated an imaging-based drug testing procedure using high-content fluorescence microscopy in living PCa organoids to detect various modalities of cell death. Individual organoids and cell nuclei in organoids were segmented and quantified using a dye combination of Hoechst 33342, propidium iodide and Caspase 3/7 Green, allowing the identification of cytostatic and cytotoxic treatment effects. Our procedures provide important insights into the mechanistic actions of tested drugs. Moreover, these methods can be adapted for tumor organoids originating from other cancer types to increase organoid-based drug test validity, and ultimately, accelerate clinical implementation.

Dynamic release of neuronal extracellular vesicles containing miR-21a-5p is induced by hypoxia.

Hypoxia induces changes in the secretion of extracellular vesicles (EVs) in several non-neuronal cells and pathological conditions. EVs are packed with biomolecules, such as microRNA(miR)-21-5p, which respond to hypoxia. However, the true EV association of miR-21-5p, and its functional or biomarker relevance, are inadequately characterised. Neurons are extremely sensitive cells, and it is not known whether the secretion of neuronal EVs and miR-21-5p are altered upon hypoxia. Here, we characterised the temporal EV secretion profile and cell viability of neurons under hypoxia. Hypoxia induced a rapid increase of miR-21a-5p secretion in the EVs, which preceded the elevation of hypoxia-induced tissue or cellular miR-21a-5p. Prolonged hypoxia induced cell death and the release of morphologically distinct EVs. The EVs protected miR-21a-5p from enzymatic degradation but a remarkable fraction of miR-21a-5p remained fragile and non-EV associated. The increase in miR-21a-5p secretion may have biomarker potential, as high blood levels of miR-21-5p in stroke patients were associated with significant disability at hospital discharge. Our data provides an understanding of the dynamic regulation of EV secretion from neurons under hypoxia and provides a candidate for the prediction of recovery from ischemic stroke.

Patient-Derived Xenografts and Organoids Recapitulate Castration-Resistant Prostate Cancer with Sustained Androgen Receptor Signaling.

Castration-resistant prostate cancer (CRPC) remains an incurable and lethal malignancy. The development of new CRPC treatment strategies is strongly impeded by the scarcity of representative, scalable and transferable preclinical models of advanced, androgen receptor (AR)-driven CRPC. Here, we present contemporary patient-derived xenografts (PDXs) and matching PDX-derived organoids (PDXOs) from CRPC patients who had undergone multiple lines of treatment. These models were comprehensively profiled at the morphologic, genomic (n = 8) and transcriptomic levels (n = 81). All are high-grade adenocarcinomas that exhibit copy number alterations and transcriptomic features representative of CRPC patient cohorts. We identified losses of PTEN and RB1, MYC amplifications, as well as genomic alterations in TP53 and in members of clinically actionable pathways such as AR, PI3K and DNA repair pathways. Importantly, the clinically observed continued reliance of CRPC tumors on AR signaling is preserved across the entire set of models, with AR amplification identified in four PDXs. We demonstrate that PDXs and PDXOs faithfully reflect donor tumors and mimic matching patient drug responses. In particular, our models predicted patient responses to subsequent treatments and captured sensitivities to previously received therapies. Collectively, these PDX-PDXO pairs constitute a reliable new resource for in-depth studies of treatment-induced, AR-driven resistance mechanisms. Moreover, PDXOs can be leveraged for large-scale tumor-specific drug response profiling critical for accelerating therapeutic advances in CRPC.

Identifying genes targeted by disease-associated non-coding SNPs with a protein knowledge graph.

Genome-wide association studies (GWAS) have identified many single nucleotide polymorphisms (SNPs) that play important roles in the genetic heritability of traits and diseases. With most of these SNPs located on the non-coding part of the genome, it is currently assumed that these SNPs influence the expression of nearby genes on the genome. However, identifying which genes are targeted by these disease-associated SNPs remains challenging. In the past, protein knowledge graphs have often been used to identify genes that are associated with disease, also referred to as "disease genes". Here, we explore whether protein knowledge graphs can be used to identify genes that are targeted by disease-associated non-coding SNPs by testing and comparing the performance of six existing methods for a protein knowledge graph, four of which were developed for disease gene identification. We compare our performance against two baselines: (1) an existing state-of-the-art method that is based on guilt-by-association, and (2) the leading assumption that SNPs target the nearest gene on the genome. We test these methods with four reference sets, three of which were obtained by different means. Furthermore, we combine methods to investigate whether their combination improves performance. We find that protein knowledge graphs that include predicate information perform comparable to the current state of the art, achieving an area under the receiver operating characteristic curve (AUC) of 79.6% on average across all four reference sets. Protein knowledge graphs that lack predicate information perform comparable to our other baseline (genetic distance) which achieved an AUC of 75.7% across all four reference sets. Combining multiple methods improved performance to 84.9% AUC. We conclude that methods for a protein knowledge graph can be used to identify which genes are targeted by disease-associated non-coding SNPs.

Cell Line Characteristics Predict Subsequent Resistance to Androgen Receptor-Targeted Agents (ARTA) in Preclinical Models of Prostate Cancer.

Treatment of prostate cancer (PCa) has changed considerably in the last decade due to the introduction of novel androgen receptor (AR)-targeted agents (ARTAs) for patients progressing on androgen deprivation therapy (ADT). Preclinical research however still relies heavily on AR-negative cell line models. In order to investigate potential differences in castration-resistant PCa (CRPC) growth, we set out to create a comprehensive panel of ARTA-progressive models from 4 androgen-responsive AR wild-type PCa cell lines and analyzed its androgen response as opposed to its ADT-progressive counterparts. Parallel cultures of VCaP, DuCaP, PC346C, and LAPC4 were established in their respective culture media with steroid-stripped fetal calf serum (FCS) [dextran-coated charcoal-stripped FCS (DCC)] without androgen (ADT) or in DCC plus 1 µM of the ARTAs bicalutamide, OH-flutamide, or RD162 (an enzalutamide/apalutamide analog). Cell growth was monitored and compared to those of parental cell lines. Short-term androgen response was measured using cell proliferation 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. qRT-PCR was performed to assess the mRNA expression of markers for AR signaling, steroidogenesis, glucocorticoid receptor (GR) signaling, epithelial-mesenchymal transition (EMT), and WNT signaling. Out of 35 parallel cultures per cell line, a total of 24, 15, 34, and 16 CRPC sublines emerged for VCaP, DuCaP, PC346C, and LAPC4, respectively. The addition of bicalutamide or OH-flutamide significantly increased CRPC growth compared to ADT or RD162. VCaP, DuCaP, and PC346C CRPC clones retained an AR-responsive phenotype. The expression of AR and subsequent androgen response were completely lost in all LAPC4 CRPC lines. Markers for EMT and WNT signaling were found to be elevated in the resilient PC346C model and CRPC derivatives of VCaP, DuCaP, and LAPC4. Although the resistant phenotype is pluriform between models, it seems consistent within models, regardless of type of ARTA. These data suggest that the progression to and the phenotype of the CRPC state might already be determined early in carcinogenesis.

Abiraterone switches castration-resistant prostate cancer dependency from adrenal androgens towards androgen receptor variants and glucocorticoid receptor signalling.

INTRODUCTION: Castration-resistant prostate cancer (CRPC) remains dependent on androgen receptor (AR) signalling, which is largely driven by conversion of adrenal androgen precursors lasting after castration. Abiraterone, an inhibitor of the steroidogenic enzyme CYP17A1, has been demonstrated to reduce adrenal androgen synthesis and prolong CRPC patient survival. To study mechanisms of resistance to castration and abiraterone, we created coculture models using human prostate and adrenal tumours. MATERIALS AND METHODS: Castration-naïve and CRPC clones of VCaP were incubated with steroid substrates or cocultured with human adrenal cells (H295R) and treated with abiraterone or the antiandrogen enzalutamide. Male mice bearing VCaP xenografts with and without concurrent H295R xenografts were castrated and treated with placebo or abiraterone. Response was assessed by tumour growth and PSA release. Plasma and tumour steroid levels were assessed by LC/MS-MS. Quantitative polymerase chain reaction determined steroidogenic enzyme, nuclear receptor and AR target gene expression. RESULTS: In vitro, adrenal androgens induced castration-naïve and CRPC cell growth, while precursors steroids for de novo synthesis did not. In a coculture system, abiraterone blocked H295R-induced growth of VCaP cells. In vivo, H295R promoted castration-resistant VCaP growth. Abiraterone only inhibited VCaP growth or PSA production in the presence of H295R. Plasma steroid levels demonstrated CYP17A1 inhibition by abiraterone, whilst CRPC tumour tissue steroid levels showed no evidence of de novo intratumoural androgen production. Castration-resistant and abiraterone-resistant VCaP tumours had increased levels of AR, AR variants and glucocorticoid receptor (GR) resulting in equal AR target gene expression levels compared to noncastrate tumours. CONCLUSIONS: In our model, ligand-dependent AR-regulated regrowth of CRPC was predominantly supported via adrenal androgen precursor production while there was no evidence for intratumoural androgen synthesis. Abiraterone-resistant tumours relied on AR overexpression, expression of ligand-independent AR variants and GR signalling.

The EGFRvIII transcriptome in glioblastoma: A meta-omics analysis.

BACKGROUND: EGFR is among the genes most frequently altered in glioblastoma, with exons 2-7 deletions (EGFRvIII) being among its most common genomic mutations. There are conflicting reports about its prognostic role and it remains unclear whether and how it differs in signaling compared with wildtype EGFR. METHODS: To better understand the oncogenic role of EGFRvIII, we leveraged 4 large datasets into 1 large glioblastoma transcriptome dataset (n = 741) alongside 81 whole-genome samples from 2 datasets. RESULTS: The EGFRvIII/EGFR expression ratios differ strongly between tumors and range from 1% to 95%. Interestingly, the slope of relative EGFRvIII expression is near-linear, which argues against a more positive selection pressure than EGFR wildtype. An absence of selection pressure is also suggested by the similar survival between EGFRvIII-positive and -negative glioblastoma patients. EGFRvIII levels are inversely correlated with pan-EGFR (all wildtype and mutant variants) expression, which indicates that EGFRvIII has a higher potency in downstream pathway activation. EGFRvIII-positive glioblastomas have a lower CDK4 or MDM2 amplification incidence than EGFRvIII-negative (P = .007), which may point toward crosstalk between these pathways. EGFRvIII-expressing tumors have an upregulation of "classical" subtype genes compared to those with EGFR-amplification only (P = 3.873e-6). Genomic breakpoints of the EGFRvIII deletions have a preference toward the 3'-end of the large intron-1. These preferred breakpoints preserve a cryptic exon resulting in a novel EGFRvIII variant and preserve an intronic enhancer. CONCLUSIONS: These data provide deeper insights into the complex EGFRvIII biology and provide new insights for targeting EGFRvIII mutated tumors.

Fusion transcripts and their genomic breakpoints in polyadenylated and ribosomal RNA-minus RNA sequencing data.

BACKGROUND: Fusion genes are typically identified by RNA sequencing (RNA-seq) without elucidating the causal genomic breakpoints. However, non-poly(A)-enriched RNA-seq contains large proportions of intronic reads that also span genomic breakpoints. RESULTS: We have developed an algorithm, Dr. Disco, that searches for fusion transcripts by taking an entire reference genome into account as search space. This includes exons but also introns, intergenic regions, and sequences that do not meet splice junction motifs. Using 1,275 RNA-seq samples, we investigated to what extent genomic breakpoints can be extracted from RNA-seq data and their implications regarding poly(A)-enriched and ribosomal RNA-minus RNA-seq data. Comparison with whole-genome sequencing data revealed that most genomic breakpoints are not, or minimally, transcribed while, in contrast, the genomic breakpoints of all 32 TMPRSS2-ERG-positive tumours were present at RNA level. We also revealed tumours in which the ERG breakpoint was located before ERG, which co-existed with additional deletions and messenger RNA that incorporated intergenic cryptic exons. In breast cancer we identified rearrangement hot spots near CCND1 and in glioma near CDK4 and MDM2 and could directly associate this with increased expression. Furthermore, in all datasets we find fusions to intergenic regions, often spanning multiple cryptic exons that potentially encode neo-antigens. Thus, fusion transcripts other than classical gene-to-gene fusions are prominently present and can be identified using RNA-seq. CONCLUSION: By using the full potential of non-poly(A)-enriched RNA-seq data, sophisticated analysis can reliably identify expressed genomic breakpoints and their transcriptional effects.

FASTAFS: file system virtualisation of random access compressed FASTA files.

BACKGROUND: The FASTA file format, used to store polymeric sequence data, has become a bioinformatics file standard used for decades. The relatively large files require additional files, beyond the scope of the original format, to identify sequences and to provide random access. Multiple compressors have been developed to archive FASTA files back and forth, but these lack direct access to targeted content or metadata of the archive. Moreover, these solutions are not directly backwards compatible to FASTA files, resulting in limited software integration. RESULTS: We designed a linux based toolkit that virtualises the content of DNA, RNA and protein FASTA archives into the filesystem by using filesystem in userspace. This guarantees in-sync virtualised metadata files and offers fast random-access decompression using bit encodings plus Zstandard (zstd). The toolkit, FASTAFS, can track all its system-wide running instances, allows file integrity verification and can provide, instantly, scriptable access to sequence files and is easy to use and deploy. The file compression ratios were comparable but not superior to other state of the art archival tools, despite the innovative random access feature implemented in FASTAFS. CONCLUSIONS: FASTAFS is a user-friendly and easy to deploy backwards compatible generic purpose solution to store and access compressed FASTA files, since it offers file system access to FASTA files as well as in-sync metadata files through file virtualisation. Using virtual filesystems as in-between layer offers format conversion without the need to rewrite code into different programming languages while preserving compatibility.

Androgens alter the heterogeneity of small extracellular vesicles and the small RNA cargo in prostate cancer.

Proliferation and survival of prostate cancer cells are driven by the androgen receptor (AR) upon binding to androgen steroid hormones. Manipulating the AR signalling axis is the focus for prostate cancer therapy; thus, it is crucial to understand the role of androgens and AR on extracellular vesicle (EV) secretion and cargo. In this study, we report that plasma-derived circulating vesicles consisting of CD9 and double-positive for CD9 and Prostate Specific Membrane Antigen (PSMA) are increased in patients with advanced metastatic prostate cancer, whereas double positives for CD9 and CD63 small extracellular vesicles (S-EVs) are significantly higher in patients with localised prostate cancer. Androgen manipulation by dihydrotestosterone (DHT) and the clinical antagonist enzalutamide (ENZ) altered the heterogeneity and size of CD9 positive S-EVs in AR expressing prostate cancer cells, while assessment of the total number and protein cargo of total S-EVs was unaltered across different treatment groups. Furthermore, hormone stimulation caused strong and specific effects on the small RNA cargo of S-EVs. A total of 543 small RNAs were found to be regulated by androgens including miR-19-3p and miR-361-5p. Analysis of S-EVs heterogeneity and small RNA cargo may provide clinical utility for prostate cancer and be informative to understand further the mechanism of resistance to androgen targeted therapy in castration-resistant prostate cancer.

Blood-based PD-L1 analysis in tumor-derived extracellular vesicles: Applications for optimal use of anti-PD-1/PD-L1 axis inhibitors.

Monoclonal antibodies that inhibit the programmed cell death protein 1 axis (anti-PD-1/PD-L1) are part of a new pharmacological strategy aimed at reinforcing the immune response to cancer. Despite the success in several cancer types, a significant percentage of patients do not benefit from treatment with these drugs due to intrinsic or acquired resistance or the occurrence of immune-related adverse reactions. Assessment of PD-L1 expression in tumor tissues is currently used to predict drug response in the clinics; however, there is a growing interest in identifying blood-based biomarkers that, owing to the minimally-invasive nature, can allow a dynamic monitoring of drug response in daily clinical practice. In the current review article, we discuss whether the assessment of PD-L1 mRNA and protein levels in circulating extracellular vesicles may have the potential to predict the likelihood of tumor response to anti-PD-1/PD-L1 antibodies.

The Movember Prostate Cancer Landscape Analysis: an assessment of unmet research needs.

Prostate cancer is a heterogeneous cancer with widely varying levels of morbidity and mortality. Approaches to prostate cancer screening, diagnosis, surveillance, treatment and management differ around the world. To identify the highest priority research needs across the prostate cancer biomedical research domain, Movember conducted a landscape analysis with the aim of maximizing the effect of future research investment through global collaborative efforts and partnerships. A global Landscape Analysis Committee (LAC) was established to act as an independent group of experts across urology, medical oncology, radiation oncology, radiology, pathology, translational research, health economics and patient advocacy. Men with prostate cancer and thought leaders from a variety of disciplines provided a range of key insights through a range of interviews. Insights were prioritized against predetermined criteria to understand the areas of greatest unmet need. From these efforts, 17 research needs in prostate cancer were agreed on and prioritized, and 3 received the maximum prioritization score by the LAC: first, to establish more sensitive and specific tests to improve disease screening and diagnosis; second, to develop indicators to better stratify low-risk prostate cancer for determining which men should go on active surveillance; and third, to integrate companion diagnostics into randomized clinical trials to enable prediction of treatment response. On the basis of the findings from the landscape analysis, Movember will now have an increased focus on addressing the specific research needs that have been identified, with particular investment in research efforts that reduce disease progression and lead to improved therapies for advanced prostate cancer.

AR splice variants in circulating tumor cells of patients with castration-resistant prostate cancer: relation with outcome to cabazitaxel.

The androgen receptor splice variant (AR-V) 7 in circulating tumor cells (CTCs) is a predictor for resistance to anti-AR-targeted treatment, but not to taxane-based chemotherapy in metastatic castration-resistant prostate cancer (mCRPC). In this study, we investigated whether the presence of two constitutively active variants (AR-V3, AR-V7) and two other conditionally activated variants (AR-V1, AR-V9) vs full-length androgen receptor (AR-FL) measured in CTCs from patients with mCRPC were associated with outcome to therapy with the taxane cabazitaxel. Blood was collected at baseline and after two cycles of cabazitaxel from 118 mCRPC patients starting cabazitaxel in a prospective phase II trial. CellSearch-enriched CTCs were enumerated and in parallel characterized for the presence of the AR-Vs by reverse transcription quantitative polymerase chain reaction. Correlations with CTC and prostate-specific antigen response to cabazitaxel as well as associations with overall survival (OS) were investigated. All AR-Vs were frequently present and co-expressed at frequencies of 31-48% at baseline and at 19-40% after two cycles of cabazitaxel. No specific directions of change in the measured variants were detected between the start of treatment and after two cycles of cabazitaxel. No associations between the presence of AR-V3 and AR-V7 and outcome to cabazitaxel were observed. While a reduction in CTCs to < 5 CTCs during treatment (CTC5-response) was less often observed in patients with AR-V9-positive CTCs at baseline (P = 0.004), the CTC5-adjusted detection of AR-V1 after two cycles of cabazitaxel was an independent prognostic factor for OS [HR 2.4 (95% CI 1.1-5.1, P = 0.03)]. These novel findings are expected to contribute to more personalized treatment approaches in mCRPC patients.

Extracellular Vesicle Quantification and Characterization: Common Methods and Emerging Approaches.

Extracellular vesicles (EVs) are a family of small membrane vesicles that carry information about cells by which they are secreted. Growing interest in the role of EVs in intercellular communication, but also in using their diagnostic, prognostic and therapeutic potential in (bio) medical applications, demands for accurate assessment of their biochemical and physical properties. In this review, we provide an overview of available technologies for EV analysis by describing their working principles, assessing their utility in EV research and summarising their potential and limitations. To emphasise the innovations in EV analysis, we also highlight the unique possibilities of emerging technologies with high potential for further development.

Epithelial-Mesenchymal Transition in Human Prostate Cancer Demonstrates Enhanced Immune Evasion Marked by IDO1 Expression.

Cancer invasion and metastasis are driven by epithelial-mesenchymal transition (EMT), yet the exact mechanisms that account for EMT in clinical prostate cancer are not fully understood. Expression of N-cadherin is considered a hallmark of EMT in clinical prostate cancer. In this study, we determined the molecular mechanisms associated with N-cadherin expression in patients with prostate cancer. We performed laser capture microdissection of matched N-cadherin-positive and -negative prostate cancer areas from patient samples (n = 8), followed by RNA sequencing. N-cadherin expression was significantly associated with an immune-regulatory signature including profound upregulation of indoleamine 2,3-dioxygenase (IDO1; log2-fold change = 5.1; P = 2.98E-04). Fluorescent immunostainings of patient samples confirmed expression of IDO1 protein and also its metabolite kynurenine in primarily N-cadherin-positive areas. N-cadherin-positive areas also exhibited a local decrease of intraepithelial cytotoxic (CD8+) T cells and an increase of immunosuppressive regulatory T cells (CD4+/FOXP3+). In conclusion, EMT in clinical prostate cancer is accompanied by upregulated expression of IDO1 and an increased number of regulatory T cells. These data indicate that EMT, which is an important step in tumor progression, can be protected from effective immune control in patients with prostate cancer.Significance: These findings demonstrate EMT is linked to an immunosuppressive environment in clinical prostate cancer, suggesting that patients with prostate cancer can potentially benefit from combinatorial drug therapy. Cancer Res; 78(16); 4671-9. ©2018 AACR.

The Detection of Androgen Receptor Splice Variant 7 in Plasma-derived Exosomal RNA Strongly Predicts Resistance to Hormonal Therapy in Metastatic Prostate Cancer Patients.

BACKGROUND: The androgen receptor splice variant 7 (AR-V7) is associated with resistance to hormonal therapy in castration-resistant prostate cancer (CRPC). Due to limitations of the methods available for AR-V7 analysis, the identification of a reliable detection method may facilitate the use of this biomarker in clinical practice. OBJECTIVE: To confirm AR-V7 as a predictor of resistance to hormonal therapy and develop a new approach to assess AR-V7 by highly sensitive digital droplet polymerase chain reaction (ddPCR) in plasma-derived exosomal RNA. DESIGN, SETTING, AND PARTICIPANTS: Plasma samples were collected from 36 CRPC patients before they began second-line hormonal treatment. Exosomes were isolated and RNA extracted for analysis of AR-V7 by ddPCR. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The absolute target gene concentration as copies per milliliter (copies/ml) was determined by ddPCR. Statistical analyses were performed with SPSS software (IBM Corp., Armonk, NY, USA). RESULTS AND LIMITATIONS: A total of 26 patients received abiraterone and 10 enzalutamide; 39% of patients were found to be AR-V7 positive (AR-V7+). Median progression-free survival was significantly longer in AR-V7 negative (AR-V7-) versus AR-V7+ patients (20 vs 3 mo; p<0.001). Overall survival was significantly shorter in AR-V7+ participants at baseline compared with AR-V7- participants (8 mo vs not reached; p<0.001). CONCLUSIONS: This study demonstrates that plasma-derived exosomal RNA is a reliable source of AR-V7 that can be detected sensitively by ddPCR assay. We also showed that resistance to hormonal therapy may be predicted by AR-V7, making it a clinically relevant biomarker. PATIENT SUMMARY: We report a first study on a method for androgen receptor splice variant 7 (AR-V7) detection in RNA extracted from cancer cell vesicles released in blood. Results confirmed the role of AR-V7 as a predictive biomarker of resistance to hormonal therapy. Our assay showed that vesicles are a reliable source of AR-V7 RNA and that the method is fast, highly sensitive, and affordable.

The Potential of MicroRNAs as Prostate Cancer Biomarkers.

CONTEXT: Short noncoding RNAs known as microRNAs (miRNAs) control protein expression through the degradation of RNA or the inhibition of protein translation. The miRNAs influence a wide range of biologic processes and are often deregulated in cancer. This family of small RNAs constitutes potentially valuable markers for the diagnosis, prognosis, and therapeutic choices in prostate cancer (PCa) patients, as well as potential drugs (miRNA mimics) or drug targets (anti-miRNAs) in PCa management. OBJECTIVE: To review the currently available data on miRNAs as biomarkers in PCa and as possible tools for early detection and prognosis. EVIDENCE ACQUISITION: A systematic review was performed searching the PubMed database for articles in English using a combination of the following terms: microRNA, miRNA, cancer, prostate cancer, miRNA profiling, diagnosis, prognosis, therapy response, and predictive marker. EVIDENCE SYNTHESIS: We summarize the existing literature regarding the profiling of miRNA in PCa detection, prognosis, and response to therapy. The articles were reviewed with the main goal of finding a common recommendation that could be translated from bench to bedside in future clinical practice. CONCLUSIONS: The miRNAs are important regulators of biologic processes in PCa progression. A common expression profile characterizing each tumor subtype and stage has still not been identified for PCa, probably due to molecular heterogeneity as well as differences in study design and patient selection. Large-scale studies that should provide additional important information are still missing. Further studies, based on common clinical parameters and guidelines, are necessary to validate the translational potential of miRNAs in PCa clinical management. Such common signatures are promising in the field and emerge as potential biomarkers. PATIENT SUMMARY: The literature shows that microRNAs hold potential as novel biomarkers that could aid prostate cancer management, but additional studies with larger patient cohorts and common guidelines are necessary before clinical implementation.