Differentially expressed glycoproteins in pre- and post-digital rectal examination urine samples for detecting aggressive prostate cancer.

Urinary glycoproteins associated with aggressive prostate cancer (AG-PCa) were previously reported using post-digital rectal examination (DRE) urine specimens. To explore the potential of using pre-DRE urine specimens for detecting AG-PCa, we compared glycoproteins between pre- and post-DRE urine specimens, verified the previously identified post-DRE AG-PCa-associated urinary glycoproteins in pre-DRE urine specimens, and explored potential new glycoproteins for AG-PCa detection in pre-DRE urine specimens. Quantitative glycoproteomic data were acquired for 154 pre-DRE urine specimens from 41 patients with no cancer at biopsy, 48 patients with non-AG-PCa (Gleason score = 6), and 65 patients with AG-PCa (Gleason score 7 or above). Compared to glycopeptides from the post-DRE urine data, humoral immunity-related proteins were enriched in pre-DRE urine samples, whereas cell mediated immune response proteins were enriched in post-DRE urine samples. Analyses of AG-PCa-associated glycoproteins from pre-DRE urine revealed that the three urinary glycoproteins, prostate-specific antigen (PSA), prostatic acid phosphatase (ACPP), and CD97 antigen (CD97) that were previously identified in post-DRE urine samples, were also observed as AG-PCa associated glycoproteins in pre-DRE urine. In addition, we identified three new glycoproteins, fibrillin 1 (FBN1), vitronectin (VTN), and hemicentin 2 (HMCN2), to be potentially associated with AG-PCa in pre-DRE urine specimens. In summary, glycoprotein profiles differ between pre- and post-DRE urine specimens. The identified AG-PCa-associated glycoproteins may be further evaluated in large cohort of pre-DRE urine specimens for detecting clinically significant PCa.

Biomarkers of Aggressive Prostate Cancer at Diagnosis.

In the United States, prostate cancer (CaP) remains the second leading cause of cancer deaths in men. CaP is predominantly indolent at diagnosis, with a small fraction (25-30%) representing an aggressive subtype (Gleason score 7-10) that is prone to metastatic progression. This fact, coupled with the criticism surrounding the role of prostate specific antigen in prostate cancer screening, demonstrates the current need for a biomarker(s) that can identify clinically significant CaP and avoid unnecessary biopsy procedures and psychological implications of being diagnosed with low-risk prostate cancer. Although several diagnostic biomarkers are available to clinicians, very few comparative trials have been performed to assess the clinical effectiveness of these biomarkers. It is of note, however, that a majority of these clinical trials have been over-represented by men of Caucasian origin, despite the fact that African American men have a 1.7 times higher incidence and 2.1 times higher rate of mortality from prostate cancer. Biomarkers for CaP diagnosis based on the tissue of origin include urine-based gene expression assays (PCA3, Select MDx, ExoDx Prostate IntelliScore, Mi-Prostate Score, PCA3-PCGEM1 gene panel), blood-based protein biomarkers (4K, PHI), and tissue-based DNA biomarker (Confirm MDx). Another potential direction that has emerged to aid in the CaP diagnosis include multi-parametric magnetic resonance imaging (mpMRI) and bi-parametric magnetic resonance imaging (bpMRI), which in conjunction with clinically validated biomarkers may provide a better approach to predict clinically significant CaP at diagnosis. In this review, we discuss some of the adjunctive biomarker tests along with newer imaging modalities that are currently available to help clinicians decide which patients are at risk of having high-grade CaP on prostate biopsy with the emphasis on clinical utility of the tests across African American (AA) and Caucasian (CA) men.

African-specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer.

Polygenic hazard score (PHS) models are associated with age at diagnosis of prostate cancer. Our model developed in Europeans (PHS46) showed reduced performance in men with African genetic ancestry. We used a cross-validated search to identify single nucleotide polymorphisms (SNPs) that might improve performance in this population. Anonymized genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Ten iterations of a 10-fold cross-validation search were conducted to select SNPs that would be included in the final PHS46+African model. The coefficients of PHS46+African were estimated in a Cox proportional hazards framework using age at diagnosis as the dependent variable and PHS46, and selected SNPs as predictors. The performance of PHS46 and PHS46+African was compared using the same cross-validated approach. Three SNPs (rs76229939, rs74421890 and rs5013678) were selected for inclusion in PHS46+African. All three SNPs are located on chromosome 8q24. PHS46+African showed substantial improvements in all performance metrics measured, including a 75% increase in the relative hazard of those in the upper 20% compared to the bottom 20% (2.47-4.34) and a 20% reduction in the relative hazard of those in the bottom 20% compared to the middle 40% (0.65-0.53). In conclusion, we identified three SNPs that substantially improved the association of PHS46 with age at diagnosis of prostate cancer in men with African genetic ancestry to levels comparable to Europeans.

A Urine Exosome Gene Expression Panel Distinguishes between Indolent and Aggressive Prostate Cancers at Biopsy.

PURPOSE: Prostate cancer is predominantly indolent at diagnosis with a small fraction (15% to 25%) representing aggressive subtype (Gleason score 7-10), which is prone to metastatic progression. It is critical to explore noninvasive assays for the early detection of this aggressive subtype, when it still can be treated effectively. Additionally, there is an emerging need to develop markers that perform equally well across races, as racial differences in the prevalence and mortality of prostate cancer has become evident. MATERIALS AND METHODS: First catch, nondigital rectal examination urine specimens were collected from patients undergoing diagnostic biopsy. Total RNA was extracted from urinary exosomes and a quantitative expression assay protocol using droplet digital polymerase chain reaction was developed for detection of candidate genes in exosomal mRNAs from urine. Clinical performance for the gene expression assay was evaluated to predict high grade cancer (Gleason score 7-10) from low grade cancer (Gleason score 6) and cancer negative cases at biopsy. Assay performance was examined in combination with standard of care to determine improvement in model prediction. RESULTS: In a racially diverse patient cohort a 2-gene panel (PCA3, PCGEM1), in combination with standard of care variables, significantly improved the prediction of high grade cancer at diagnosis compared to standard of care variables alone (AUC 0.88 vs 0.80, respectively, p=0.016). Decision curve analysis showed that there is a benefit of adopting the gene panel for detection of high grade cancer compared to standard of care alone. CONCLUSIONS: This study highlights the potential for developing broadly applicable prostate cancer diagnostic biomarker panels for aggressive prostate cancer using our novel gene expression assay platform.

Multi-omic serum biomarkers for prognosis of disease progression in prostate cancer.

BACKGROUND: Predicting the clinical course of prostate cancer is challenging due to the wide biological spectrum of the disease. The objective of our study was to identify prostate cancer prognostic markers in patients 'sera using a multi-omics discovery platform. METHODS: Pre-surgical serum samples collected from a longitudinal, racially diverse, prostate cancer patient cohort (N = 382) were examined. Linear Regression and Bayesian computational approaches integrated with multi-omics, were used to select markers to predict biochemical recurrence (BCR). BCR-free survival was modeled using unadjusted Kaplan-Meier estimation curves and multivariable Cox proportional hazards analysis, adjusted for key pathologic variables. Receiver operating characteristic (ROC) curve statistics were used to examine the predictive value of markers in discriminating BCR events from non-events. The findings were further validated by creating a training set (N = 267) and testing set (N = 115) from the cohort. RESULTS: Among 382 patients, 72 (19%) experienced a BCR event in a median follow-up time of 6.9 years. Two proteins-Tenascin C (TNC) and Apolipoprotein A1V (Apo-AIV), one metabolite-1-Methyladenosine (1-MA) and one phospholipid molecular species phosphatidic acid (PA) 18:0-22:0 showed a cumulative predictive performance of AUC = 0.78 [OR (95% CI) = 6.56 (2.98-14.40), P < 0.05], in differentiating patients with and without BCR event. In the validation set all four metabolites consistently reproduced an equivalent performance with high negative predictive value (NPV; > 80%) for BCR. The combination of pTstage and Gleason score with the analytes, further increased the sensitivity [AUC = 0.89, 95% (CI) = 4.45-32.05, P < 0.05], with an increased NPV (0.96) and OR (12.4) for BCR. The panel of markers combined with the pathological parameters demonstrated a more accurate prediction of BCR than the pathological parameters alone in prostate cancer. CONCLUSIONS: In this study, a panel of serum analytes were identified that complemented pathologic patient features in predicting prostate cancer progression. This panel offers a new opportunity to complement current prognostic markers and to monitor the potential impact of primary treatment versus surveillance on patient oncological outcome.

A Rich Array of Prostate Cancer Molecular Biomarkers: Opportunities and Challenges.

Prostate cancer is the most prevalent non-skin cancer in men and is the leading cause of cancer-related death. Early detection of prostate cancer is largely determined by a widely used prostate specific antigen (PSA) blood test and biopsy is performed for definitive diagnosis. Prostate cancer is asymptomatic in the early stage of the disease, comprises of diverse clinico-pathologic and progression features, and is characterized by a large subset of the indolent cancer type. Therefore, it is critical to develop an individualized approach for early detection, disease stratification (indolent vs. aggressive), and prediction of treatment response for prostate cancer. There has been remarkable progress in prostate cancer biomarker discovery, largely through advancements in genomic technologies. A rich array of prostate cancer diagnostic and prognostic tests has emerged for serum (4K, phi), urine (Progensa, T2-ERG, ExoDx, SelectMDx), and tumor tissue (ConfirmMDx, Prolaris, Oncoytype DX, Decipher). The development of these assays has created new opportunities for improving prostate cancer diagnosis, prognosis, and treatment decisions. While opening exciting opportunities, these developments also pose unique challenges in terms of selecting and incorporating these assays into the continuum of prostate cancer patient care.

Prostate Cancer Genomics: Recent Advances and the Prevailing Underrepresentation from Racial and Ethnic Minorities.

Prostate cancer (CaP) is the most commonly diagnosed non-cutaneous cancer and the second leading cause of male cancer deaths in the United States. Among African American (AA) men, CaP is the most prevalent malignancy, with disproportionately higher incidence and mortality rates. Even after discounting the influence of socioeconomic factors, the effect of molecular and genetic factors on racial disparity of CaP is evident. Earlier studies on the molecular basis for CaP disparity have focused on the influence of heritable mutations and single-nucleotide polymorphisms (SNPs). Most CaP susceptibility alleles identified based on genome-wide association studies (GWAS) were common, low-penetrance variants. Germline CaP-associated mutations that are highly penetrant, such as those found in HOXB13 and BRCA2, are usually rare. More recently, genomic studies enabled by Next-Gen Sequencing (NGS) technologies have focused on the identification of somatic mutations that contribute to CaP tumorigenesis. These studies confirmed the high prevalence of ERG gene fusions and PTEN deletions among Caucasian Americans and identified novel somatic alterations in SPOP and FOXA1 genes in early stages of CaP. Individuals with African ancestry and other minorities are often underrepresented in these large-scale genomic studies, which are performed primarily using tumors from men of European ancestry. The insufficient number of specimens from AA men and other minority populations, together with the heterogeneity in the molecular etiology of CaP across populations, challenge the generalizability of findings from these projects. Efforts to close this gap by sequencing larger numbers of tumor specimens from more diverse populations, although still at an early stage, have discovered distinct genomic alterations. These research findings can have a direct impact on the diagnosis of CaP, the stratification of patients for treatment, and can help to address the disparity in incidence and mortality of CaP. This review examines the progress of understanding in CaP genetics and genomics and highlight the need to increase the representation from minority populations.

Activation of endogenous TRPV1 fails to induce overstimulation-based cytotoxicity in breast and prostate cancer cells but not in pain-sensing neurons.

Vanilloids including capsaicin and resiniferatoxin are potent transient receptor potential vanilloid type 1 (TRPV1) agonists. TRPV1 overstimulation selectively ablates capsaicin-sensitive sensory neurons in animal models in vivo. The cytotoxic mechanisms are based on strong Na(+) and Ca(2+) influx via TRPV1 channels, which leads to mitochondrial Ca(2+) accumulation and necrotic cell swelling. Increased TRPV1 expression levels are also observed in breast and prostate cancer and derived cell lines. Here, we examined whether potent agonist-induced overstimulation mediated by TRPV1 might represent a means for the eradication of prostate carcinoma (PC-3, Du 145, LNCaP) and breast cancer (MCF7, MDA-MB-231, BT-474) cells in vitro. While rat sensory neurons were highly vanilloid-sensitive, normal rat prostate epithelial cells were resistant in vivo. We found TRPV1 to be expressed in all cancer cell lines at mRNA and protein levels, yet protein expression levels were significantly lower compared to sensory neurons. Treatment of all human carcinoma cell lines with capsaicin didn't lead to overstimulation cytotoxicity in vitro. We assume that the low vanilloid-sensitivity of prostate and breast cancer cells is associated with low expression levels of TRPV1, since ectopic TRPV1 expression rendered them susceptible to the cytotoxic effect of vanilloids evidenced by plateau-type Ca(2+) signals, mitochondrial Ca(2+) accumulation and Na(+)- and Ca(2+)-dependent membrane disorganization. Moreover, long-term monitoring revealed that merely the ectopic expression of TRPV1 stopped cell proliferation and often induced apoptotic processes via strong activation of caspase-3 activity. Our results indicate that specific targeting of TRPV1 function remains a putative strategy for cancer treatment.

A long noncoding RNA connects c-Myc to tumor metabolism.

Long noncoding RNAs (lncRNAs) have been implicated in a variety of physiological and pathological processes, including cancer. In prostate cancer, prostate cancer gene expression marker 1 (PCGEM1) is an androgen-induced prostate-specific lncRNA whose overexpression is highly associated with prostate tumors. PCGEM1's tumorigenic potential has been recently shown to be in part due to its ability to activate androgen receptor (AR). Here, we report a novel function of PCGEM1 that provides growth advantages for cancer cells by regulating tumor metabolism via c-Myc activation. PCGEM1 promotes glucose uptake for aerobic glycolysis, coupling with the pentose phosphate shunt to facilitate biosynthesis of nucleotide and lipid, and generates NADPH for redox homeostasis. We show that PCGEM1 regulates metabolism at a transcriptional level that affects multiple metabolic pathways, including glucose and glutamine metabolism, the pentose phosphate pathway, nucleotide and fatty acid biosynthesis, and the tricarboxylic acid cycle. The PCGEM1-mediated gene regulation takes place in part through AR activation, but predominantly through c-Myc activation, regardless of hormone or AR status. Significantly, PCGEM1 binds directly to target promoters, physically interacts with c-Myc, promotes chromatin recruitment of c-Myc, and enhances its transactivation activity. We also identified a c-Myc binding domain on PCGEM1 that contributes to the PCGEM1-dependent c-Myc activation and target induction. Together, our data uncover PCGEM1 as a key transcriptional regulator of central metabolic pathways in prostate cancer cells. By being a coactivator for both c-Myc and AR, PCGEM1 reprograms the androgen network and the central metabolism in a tumor-specific way, making it a promising target for therapeutic intervention.

Prostate cancer marker panel with single cell sensitivity in urine.

BACKGROUND: Over one million men undergo prostate biopsies annually in the United States, a majority of whom due to elevated serum PSA. More than half of the biopsies turn out to be negative for prostate cancer (CaP). The limitations of both the PSA test and the biopsy procedure have led to the development for more precise CaP detection assays in urine (e.g., PCA3, TMPRSS2-ERG) or blood (e.g., PHI, 4K). Here, we describe the development and evaluation of the Urine CaP Marker Panel (UCMP) assay for sensitive and reproducible detection of CaP cells in post-digital rectal examination (post-DRE) urine. METHODS: The cellular content of the post-DRE urine was captured on a translucent filter membrane, which is placed on Cytoclear slides for direct evaluation by microscopy and immuno-cytochemistry (ICC). Cells captured on the membrane were assayed for PSA and Prostein expression to identify prostate epithelial cells, and for ERG and AMACR to identify prostate tumor cells. Immunostained cells were analyzed for quantitative and qualitative features and correlated with biopsy positive and negative status for malignancy. RESULTS: The assay was optimized for single cell capture sensitivity and downstream evaluations by spiking a known number of cells from established CaP cell lines, LNCaP and VCaP, into pre-cleared control urine. The cells captured from the post-DRE urine of subjects, obtained prior to biopsy procedure, were co-stained for ERG, AMACR (CaP specific), and Prostein or PSA (prostate epithelium specific) rendering a whole cell based analysis and characterization. A feasibility cohort of 63 post-DRE urine specimens was assessed. Comparison of the UCMP results with blinded biopsy results showed an assay sensitivity of 64% (16 of 25) and a specificity of 68.8% (22 of 32) for CaP detection by biopsy. CONCLUSIONS: This pilot study assessing a minimally invasive CaP detection assay with single cell sensitivity cell-capture and characterization from the post-DRE urine holds promise for further development of this novel assay platform. Prostate 75: 969-975, 2015. © 2015 The Authors. The Prostate, published by Wiley Periodicals, Inc.

Analytical platform evaluation for quantification of ERG in prostate cancer using protein and mRNA detection methods.

BACKGROUND: The established methods for detecting prostate cancer (CaP) are based on tests using PSA (blood), PCA3 (urine), and AMACR (tissue) as biomarkers in patient samples. The demonstration of ERG oncoprotein overexpression due to gene fusion in CaP has thus provided ERG as an additional biomarker. Based on this, we hypothesized that ERG protein quantification methods can be of use in the diagnosis of prostate cancer. METHODS: An antibody-free assay for ERG3 protein detection was developed based on PRISM (high-pressure high-resolution separations with intelligent selection and multiplexing)-SRM (selected reaction monitoring) mass spectrometry. We utilized TMPRSS2-ERG positive VCaP and TMPRSS2-ERG negative LNCaP cells to simulate three different sample types (cells, tissue, and post-DRE urine sediment). Enzyme-linked immunosorbent assay (ELISA), western blot, NanoString, and qRT-PCR were also used in the analysis of these samples. RESULTS: Recombinant ERG3 protein spiked into LNCaP cell lysates could be detected at levels as low as 20 pg by PRISM-SRM analysis. The sensitivity of the PRISM-SRM assay was approximately 10,000 VCaP cells in a mixed cell population model of VCaP and LNCaP cells. Interestingly, ERG protein could be detected in as few as 600 VCaP cells spiked into female urine. The sensitivity of the in-house ELISA was similar to the PRISM-SRM assay, with detection of 30 pg of purified recombinant ERG3 protein and 10,000 VCaP cells. On the other hand, qRT-PCR exhibited a higher sensitivity, as TMPRSS2-ERG transcripts were detected in as few as 100 VCaP cells, in comparison to NanoString methodologies which detected ERG from 10,000 cells. CONCLUSIONS: Based on this data, we propose that the detection of both ERG transcriptional products with RNA-based assays, as well as protein products of ERG using PRISM-SRM assays, may be of clinical value in developing diagnostic and prognostic assays for prostate cancer given their sensitivity, specificity, and reproducibility.

Evaluation of ERG responsive proteome in prostate cancer.

BACKGROUND: Gene fusion between TMPRSS2 promoter and the ERG proto-oncogene is a major genomic alteration found in over half of prostate cancers (CaP), which leads to aberrant androgen dependent ERG expression. Despite extensive analysis for the biological functions of ERG in CaP, there is no systematic evaluation of the ERG responsive proteome (ERP). ERP has the potential to define new biomarkers and therapeutic targets for prostate tumors stratified by ERG expression. METHODS: Global proteome analysis was performed by using ERG (+) and ERG (-) CaP cells isolated by ERG immunohistochemistry defined laser capture microdissection and by using TMPRSS2-ERG positive VCaP cells treated with ERG and control siRNA. RESULTS: We identified 1,196 and 2,190 unique proteins stratified by ERG status from prostate tumors and VCaP cells, respectively. Comparative analysis of these two proteomes identified 330 concordantly regulated proteins characterizing enrichment of pathways modulating cytoskeletal and actin reorganization, cell migration, protein biosynthesis, and proteasome and ER-associated protein degradation. ERPs unique for ERG (+) tumors reveal enrichment for cell growth and survival pathways while proteasome and redox function pathways were enriched in ERPs unique for ERG (-) tumors. Meta-analysis of ERPs against CaP gene expression data revealed that Myosin VI and Monoamine oxidase A were positively and negatively correlated to ERG expression, respectively. CONCLUSIONS: This study delineates the global proteome for prostate tumors stratified by ERG expression status. The ERP data confirm the functions of ERG in inhibiting cell differentiation and activating cell growth, and identify potentially novel biomarkers and therapeutic targets.

Loss of the NKX3.1 tumorsuppressor promotes the TMPRSS2-ERG fusion gene expression in prostate cancer.

BACKGROUND: In normal prostate epithelium the TMPRSS2 gene encoding a type II serine protease is directly regulated by male hormones through the androgen receptor. In prostate cancer ERG protooncogene frequently gains hormonal control by seizing gene regulatory elements of TMPRSS2 through genomic fusion events. Although, the androgenic activation of TMPRSS2 gene has been established, little is known about other elements that may interact with TMPRSS2 promoter sequences to modulate ERG expression in TMPRSS2-ERG gene fusion context. METHODS: Comparative genomic analyses of the TMPRSS2 promoter upstream sequences and pathway analyses were performed by the Genomatix Software. NKX3.1 and ERG genes expressions were evaluated by immunoblot or by quantitative Real-Time PCR (qRT-PCR) assays in response to siRNA knockdown or heterologous expression. QRT-PCR assay was used for monitoring the gene expression levels of NKX3.1-regulated genes. Transcriptional regulatory function of NKX3.1 was assessed by luciferase assay. Recruitment of NKX3.1 to its cognate elements was monitored by Chromatin Immunoprecipitation assay. RESULTS: Comparative analysis of the TMPRSS2 promoter upstream sequences among different species revealed the conservation of binding sites for the androgen inducible NKX3.1 tumor suppressor. Defects of NKX3.1, such as, allelic loss, haploinsufficiency, attenuated expression or decreased protein stability represent established pathways in prostate tumorigenesis. We found that NKX3.1 directly binds to TMPRSS2 upstream sequences and negatively regulates the expression of the ERG protooncogene through the TMPRSS2-ERG gene fusion. CONCLUSIONS: These observations imply that the frequently noted loss-of-function of NKX3.1 cooperates with the activation of TMPRSS2-ERG fusions in prostate tumorigenesis.

A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer.

The Gleason score is an important predictor of prognosis in prostate cancer. However, its subjective nature can result in over- or under-grading. Our objective was to train an artificial intelligence (AI)-based algorithm to grade prostate cancer in specimens from patients who underwent radical prostatectomy (RP) and to assess the correlation of AI-estimated proportions of different Gleason patterns with biochemical recurrence-free survival (RFS), metastasis-free survival (MFS), and overall survival (OS). Training and validation of algorithms for cancer detection and grading were completed with three large datasets containing a total of 580 whole-mount prostate slides from 191 RP patients at two centers and 6218 annotated needle biopsy slides from the publicly available Prostate Cancer Grading Assessment dataset. A cancer detection model was trained using MobileNetV3 on 0.5 mm × 0.5 mm cancer areas (tiles) captured at 10× magnification. For cancer grading, a Gleason pattern detector was trained on tiles using a ResNet50 convolutional neural network and a selective CutMix training strategy involving a mixture of real and artificial examples. This strategy resulted in improved model generalizability in the test set compared with three different control experiments when evaluated on both needle biopsy slides and whole-mount prostate slides from different centers. In an additional test cohort of RP patients who were clinically followed over 30 years, quantitative Gleason pattern AI estimates achieved concordance indexes of 0.69, 0.72, and 0.64 for predicting RFS, MFS, and OS times, outperforming the control experiments and International Society of Urological Pathology system (ISUP) grading by pathologists. Finally, unsupervised clustering of test RP patient specimens into low-, medium-, and high-risk groups based on AI-estimated proportions of each Gleason pattern resulted in significantly improved RFS and MFS stratification compared with ISUP grading. In summary, deep learning-based quantitative Gleason scoring using a selective CutMix training strategy may improve prognostication after prostate cancer surgery.

Increased frequency of CHD1 deletions in prostate cancers of African American men is associated with rapid disease progression without inducing homologous recombination deficiency.

We analyzed genomic data derived from the prostate cancer of African and European American men in order to identify differences that may contribute to racial disparity of outcome and that could also define novel therapeutic strategies. In addition to analyzing patient derived next generation sequencing data, we performed FISH based confirmatory studies of Chromodomain helicase DNA-binding protein 1 (CHD1) loss on prostate cancer tissue microarrays. We created CRISPR edited, CHD1 deficient prostate cancer cell lines for genomic, drug sensitivity and functional homologous recombination (HR) activity analysis. We found that subclonal deletion of CHD1 is nearly three times as frequent in prostate tumors of African American men than in men of European ancestry and it associates with rapid disease progression. We further showed that CHD1 deletion is not associated with homologous recombination deficiency associated mutational signatures in prostate cancer. In prostate cancer cell line models CHD1 deletion did not induce HR deficiency as detected by RAD51 foci formation assay or mutational signatures, which was consistent with the moderate increase of olaparib sensitivity. CHD1 deficient prostate cancer cells, however, showed higher sensitivity to talazoparib. CHD1 loss may contribute to worse outcome of prostate cancer in African American men. A deeper understanding of the interaction between CHD1 loss and PARP inhibitor sensitivity will be needed to determine the optimal use of targeted agents such as talazoparib in the context of castration resistant prostate cancer.

Frequent CHD1 deletions in prostate cancers of African American men is associated with rapid disease progression.

We analyzed genomic data from the prostate cancer of African- and European American men to identify differences contributing to racial disparity of outcome. We also performed FISH-based studies of Chromodomain helicase DNA-binding protein 1 (CHD1) loss on prostate cancer tissue microarrays. We created CHD1-deficient prostate cancer cell lines for genomic, drug sensitivity and functional homologous recombination (HR) activity analysis. Subclonal deletion of CHD1 was nearly three times as frequent in prostate tumors of African American than in European American men and it associates with rapid disease progression. CHD1 deletion was not associated with HR deficiency associated mutational signatures or HR deficiency as detected by RAD51 foci formation. This was consistent with the moderate increase of olaparib and talazoparib sensitivity with several CHD1 deficient cell lines showing talazoparib sensitivity in the clinically relevant concentration range. CHD1 loss may contribute to worse disease outcome in African American men.

Genetic and molecular differences in prostate carcinogenesis between African American and Caucasian American men.

Prostate cancer is the most common non-skin cancer and the second leading cause of cancer-related death for men in the United States. Prostate cancer incidence and associated mortality are highest in African American men in comparison to other races. The observed differences in incidence and disease aggressiveness at presentation support a potential role for different pathways of prostate carcinogenesis between African American and Caucasian men. This review focuses on some of the recent molecular biology discoveries, which have been investigated in prostate carcinogenesis and their likely contribution to the known discrepancies across race and ethnicity. Key discussion points include the androgen receptor gene structure and function, genome-wide association studies and epigenetics. The new observations of the ethnic differences of the ERG oncogene, the most common prostate cancer gene, are providing new insights into ERG based stratification of prostate cancers in the context of ethnically diverse patient populations. This rapidly advancing knowledge has the likely potential to benefit clinical practice. Current and future work will improve the ability to sub-type prostate cancers by molecular alterations and lead to targeted therapy against this common malignancy.

Clinical Biofluid Assays for Prostate Cancer.

This mini review summarizes the currently available clinical biofluid assays for PCa. The second most prevalent cancer worldwide is PCa. PCa is a heterogeneous disease, with a large percentage of prostate tumors being indolent, and with a relatively slow metastatic potential. However, due to the high case numbers, the absolute number of PCa-related deaths is still high. In fact, it causes the second highest number of cancer deaths in American men. As a first step for the diagnosis of PCa, the PSA test has been widely used. However, it has low specificity, which results in a high number of false positives leading to overdiagnosis and overtreatment. Newer derivatives of the original PSA test, including the Food and Drug Administration (FDA)-approved 4K (four kallikreins) and the PHI (Prostate Health Index) blood tests, have higher specificities. Tissue-based PCa tests are problematic as biopsies are invasive and have limited accuracy due to prostate tumor heterogeneity. Liquid biopsies offer a minimally or non-invasive choice for the patients, while providing a more representative reflection of the spatial heterogeneity in the prostate. In addition to the abovementioned blood-based tests, urine is a promising source of PCa biomarkers, offering a supplementary avenue for early detection and improved tumor classification. Four urine-based PCa tests are either FDA- or CLIA-approved: PCA3 (PROGENSA), ExoDX Prostate Intelliscore, MiPS, and SelectMDx. We will discuss these urine-based, as well as the blood-based, clinical PCa tests in more detail. We also briefly discuss a few promising biofluid marker candidates (DNA methylation, micro-RNAs) which are not in clinical application. As no single assay is perfect, we envision that a combination of biomarkers, together with imaging, will become the preferred practice.

Association of TP53 Single Nucleotide Polymorphisms with Prostate Cancer in a Racially Diverse Cohort of Men.

Growing evidence indicates the involvement of a genetic component in prostate cancer (CaP) susceptibility and clinical severity. Studies have reported the role of germline mutations and single nucleotide polymorphisms (SNPs) of TP53 as possible risk factors for cancer development. In this single institutional retrospective study, we identified common SNPs in the TP53 gene in AA and CA men and performed association analyses for functional TP53 SNPs with the clinico-pathological features of CaP. The SNP genotyping analysis of the final cohort of 308 men (212 AA; 95 CA) identified 74 SNPs in the TP53 region, with a minor allele frequency (MAF) of at least 1%. Two SNPs were non-synonymous in the exonic region of TP53: rs1800371 (Pro47Ser) and rs1042522 (Arg72Pro). The Pro47Ser variant had an MAF of 0.01 in AA but was not detected in CA. Arg72Pro was the most common SNP, with an MAF of 0.50 (0.41 in AA; 0.68 in CA). Arg72Pro was associated with a shorter time to biochemical recurrence (BCR) (p = 0.046; HR = 1.52). The study demonstrated ancestral differences in the allele frequencies of the TP53 Arg72Pro and Pro47Ser SNPs, providing a valuable framework for evaluating CaP disparities among AA and CA men.

Development and characterization of an ETV1 rabbit monoclonal antibody for the immunohistochemical detection of ETV1 expression in cancer tissue specimens.

BACKGROUND: Aberrant ETV1 overexpression arising from gene rearrangements or mutations occur frequently in prostate cancer, round cell sarcomas, gastrointestinal stromal tumors, gliomas, and other malignancies. The absence of specific monoclonal antibodies (mAb) has limited its detection and our understanding of its oncogenic function. METHODS: An ETV1 specific rabbit mAb (29E4) was raised using an immunogenic peptide. Key residues essential for its binding were probed by ELISA and its binding kinetics were measured by surface plasmon resonance imaging (SPRi). Its selective binding to ETV1 was assessed by immunoblots and immunofluorescence assays (IFA), and by both single and double-immuno-histochemistry (IHC) assays on prostate cancer tissue specimens. RESULTS: Immunoblot results showed that the mAb is highly specific and lacked cross-reactivity with other ETS factors. A minimal epitope with two phenylalanine residues at its core was found to be required for effective mAb binding. SPRi measurements revealed an equilibrium dissociation constant in the picomolar range, confirming its high affinity. ETV1 (+) tumors were detected in prostate cancer tissue microarray cases evaluated. IHC staining of whole-mounted sections revealed glands with a mosaic staining pattern of cells that are partly ETV1 (+) and interspersed with ETV1 (-) cells. Duplex IHC, using ETV1 and ERG mAbs, detected collision tumors containing glands with distinct ETV1 (+) and ERG (+) cells. CONCLUSIONS: The selective detection of ETV1 by the 29E4 mAb in immunoblots, IFA, and IHC assays using human prostate tissue specimens reveals a potential utility for the diagnosis, the prognosis of prostate adenocarcinoma and other cancers, and the stratification of patients for treatment by ETV1 inhibitors.