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Objective: To develop and test the ability of a convolutional neural network (CNN) to accurately identify the presence of renal cell carcinoma (RCC) on histopathology specimens, as well as differentiate RCC histologic subtype and grade.Materials and Methods: Digital hematoxylin and eosin stained biopsy images were downloaded from The Cancer Genome Atlas. A CNN model was trained on 100 um2 samples of either normal (3000 samples) or RCC (12,168 samples) tissue samples from 42 patients. RCC specimens included clear cell, chromophobe, and papillary histiotypes, as well as tissue of Fuhrman grades 1 through 4. Model testing was performed on an additional held-out cohort of benign and RCC specimens. Model performance was assessed on the basis of diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value.Results: The CNN model achieved an overall accuracy of 99.1% in the testing cohort for distinguishing normal parenchyma from RCC (sensitivity 100%, specificity 97.1%). Accuracy for distinguishing between clear cell, papillary, and chromophobehistiotypes was 97.5%. Accuracy for predicting Fuhrman grade was 98.4%.Conclusion: CNNs are able to rapidly and accurately identify the presence of RCC, distinguish RCC histologic subtypes, and identify tumor grade by analyzing histopathology specimens. [ABSTRACT FROM AUTHOR]

Background TMPRSS2:ERG (T2:ERG) and prostate cancer antigen 3 (PCA3) are the most advanced urine-based prostate cancer (PCa) early detection biomarkers. Objective Validate logistic regression models, termed Mi-Prostate Score (MiPS), that incorporate serum prostate-specific antigen (PSA; or the multivariate Prostate Cancer Prevention Trial risk calculator version 1.0 [PCPTrc]) and urine T2:ERG and PCA3 scores for predicting PCa and high-grade PCa on biopsy. Design, setting, and participants T2:ERG and PCA3 scores were generated using clinical-grade transcription-mediated amplification assays. Pretrained MiPS models were applied to a validation cohort of whole urine samples prospectively collected after digital rectal examination from 1244 men presenting for biopsy. Outcome measurements and statistical analysis Area under the curve (AUC) was used to compare the performance of serum PSA (or the PCPTrc) alone and MiPS models. Decision curve analysis (DCA) was used to assess clinical benefit. Results and limitations Among informative validation cohort samples ( n = 1225 [98%], 80% from patients presenting for initial biopsy), models incorporating T2:ERG had significantly greater AUC than PSA (or PCPTrc) for predicting PCa (PSA: 0.693 vs 0.585; PCPTrc: 0.718 vs 0.639; both p < 0.001) or high-grade (Gleason score >6) PCa on biopsy (PSA: 0.729 vs 0.651, p < 0.001; PCPTrc: 0.754 vs 0.707, p = 0.006). MiPS models incorporating T2:ERG score had significantly greater AUC (all p < 0.001) than models incorporating only PCA3 plus PSA (or PCPTrc or high-grade cancer PCPTrc [PCPThg]). DCA demonstrated net benefit of the MiPS_PCPTrc (or MiPS_PCPThg) model compared with the PCPTrc (or PCPThg) across relevant threshold probabilities. Conclusions Incorporating urine T2:ERG and PCA3 scores improves the performance of serum PSA (or PCPTrc) for predicting PCa and high-grade PCa on biopsy. Patient summary Incorporation of two prostate cancer (PCa)-specific biomarkers ( TMPRSS2:ERG and PCA3 ) measured in the urine improved on serum prostate-specific antigen (or a multivariate risk calculator) for predicting the presence of PCa and high-grade PCa on biopsy. A combined test, Mi-Prostate Score, uses models validated in this study and is clinically available to provide individualized risk estimates. [ABSTRACT FROM AUTHOR]

Background Prostate cancer (PCa) molecular subtypes have been defined by essentially mutually exclusive events, including ETS gene fusions (most commonly involving ERG ) and SPINK1 overexpression. Clinical assessment may aid in disease stratification, complementing available prognostic tests. Objective To determine the analytical validity and clinicopatholgic associations of microarray-based molecular subtyping. Design, setting, and participants We analyzed Affymetrix GeneChip expression profiles for 1577 patients from eight radical prostatectomy cohorts, including 1351 cases assessed using the Decipher prognostic assay (GenomeDx Biosciences, San Diego, CA, USA) performed in a laboratory with Clinical Laboratory Improvements Amendment certification. A microarray-based (m-) random forest ERG classification model was trained and validated. Outlier expression analysis was used to predict other mutually exclusive non- ERG ETS gene rearrangements (ETS + ) or SPINK1 overexpression (SPINK1 + ). Outcome measurements Associations with clinical features and outcomes by multivariate logistic regression analysis and receiver operating curves. Results and limitations The m-ERG classifier showed 95% accuracy in an independent validation subset (155 samples). Across cohorts, 45% of PCas were classified as m-ERG + , 9% as m-ETS + , 8% as m-SPINK1 + , and 38% as triple negative (m-ERG − /m-ETS − /m-SPINK1 − ). Gene expression profiling supports three underlying molecularly defined groups: m-ERG + , m-ETS + , and m-SPINK1 + /triple negative. On multivariate analysis, m-ERG + tumors were associated with lower preoperative serum prostate-specific antigen and Gleason scores, but greater extraprostatic extension ( p < 0.001). m-ETS + tumors were associated with seminal vesicle invasion ( p = 0.01), while m-SPINK1 + /triple negative tumors had higher Gleason scores and were more frequent in Black/African American patients ( p < 0.001). Clinical outcomes were not significantly different among subtypes. Conclusions A clinically available prognostic test (Decipher) can also assess PCa molecular subtypes, obviating the need for additional testing. Clinicopathologic differences were found among subtypes based on global expression patterns. Patient summary Molecular subtyping of prostate cancer can be achieved using extra data generated from a clinical-grade, genome-wide expression-profiling prognostic assay (Decipher). Transcriptomic and clinical analysis support three distinct molecular subtypes: (1) m-ERG + , (2) m-ETS + , and (3) m-SPINK1 + /triple negative (m-ERG − /m-ETS − /m-SPINK1 − ). Incorporation of subtyping into a clinically available assay may facilitate additional applications beyond routine prognosis. [ABSTRACT FROM AUTHOR]

Objectives Prostate cancer has a variable clinical course, and molecular characterization has revealed striking mutational heterogeneity that may underlie the unpredictable clinical behavior of the disease. Advances in technology have resulted in a rapid expansion of our understanding of the genomic events responsible for the development and progression of prostate cancer. In this review, we discuss the genomic alterations underlying prostate cancer, and potential to utilize this knowledge for diagnostic and prognostic benefit. Methods and Materials We reviewed the relevant literature, with a focus on recent studies on somatic alterations in prostate cancer. Results Pathways known to affect tumorigenesis across a wide spectrum of tissues are dysregulated, such as the PI3K pathway, cell cycle control, and chromatin regulation. Lesions more specific to prostate cancer include alterations in androgen signaling, gene fusions of ETS transcription factors, and mutations in SPOP. Accumulating data suggests that prostate cancer can be subdivided based on a molecular profile of these genetic alterations. Conclusions These findings raise the possibility that prostate cancer could transition from a poorly understood, heterogeneous disease with a variable clinical course to a collection of homogenous subtypes, identifiable by molecular criteria, associated with distinct risk profiles, and perhaps amenable to specific management strategies or targeted therapies. [ABSTRACT FROM AUTHOR]

TMPRSS2-ERG gene fusions occur in 50% of prostate cancers and result in the overexpression of a chimeric fusion transcript that encodes a truncated ERG product. Previous attempts to detect truncated ERG products have been hindered by a lack of specific antibodies. Here, we characterize a rabbit anti-ERG monoclonal antibody (clone EPR 3864; Epitomics, Burlingame, CA) using immunoblot analysis on prostate cancer cell lines, synthetic TMPRSS2-ERG constructs, chromatin immunoprecipitation, and immunofluorescence. We correlated ERG protein expression with the presence of ERG gene rearrangements in prostate cancer tissues using a combined immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) analysis. We independently evaluated two patient cohorts and observed ERG expression confined to prostate cancer cells and high-grade prostatic intraepithelial neoplasia associated with ERG-positive cancer, as well as vessels and lymphocytes (where ERG has a known biologic role). Image analysis of 131 cases demonstrated nearly 100% sensitivity for detecting ERG rearrangement prostate cancer, with only 2 (1.5%) of 131 cases demonstrating strong ERG protein expression without any known ERG gene fusion. The combined pathology evaluation of 207 patient tumors for ERG protein expression had 95.7% sensitivity and 96.5% specificity for determining ERG rearrangement prostate cancer. In conclusion, this study qualifies a specific anti-ERG antibody and demonstrates exquisite association between ERG gene rearrangement and truncated ERG protein product expression. Given the ease of performing IHC versus FISH, ERG protein expression may be useful for molecularly subtyping prostate cancer based on ERG rearrangement status and suggests clinical utility in prostate needle biopsy evaluation. [ABSTRACT FROM AUTHOR]

Summary: ETS gene fusions have been characterized in a majority of prostate cancers; however, the key molecular alterations in ETS-negative cancers are unclear. Here we used an outlier meta-analysis (meta-COPA) to identify SPINK1 outlier expression exclusively in a subset of ETS rearrangement-negative cancers (∼10% of total cases). We validated the mutual exclusivity of SPINK1 expression and ETS fusion status, demonstrated that SPINK1 outlier expression can be detected noninvasively in urine, and observed that SPINK1 outlier expression is an independent predictor of biochemical recurrence after resection. We identified the aggressive 22RV1 cell line as a SPINK1 outlier expression model and demonstrate that SPINK1 knockdown in 22RV1 attenuates invasion, suggesting a functional role in ETS rearrangement-negative prostate cancers. [Copyright &y& Elsevier]

TMPRSS2--ERG gene fusions are the predominant molecular subtype of prostate cancer. Here, we explored the role of TMPRSS2--ERG gene fusion product using in vitro and in vivo model systems. Transgenic mice expressing the ERG gene fusion product under androgen-regulation develop mouse prostatic intraepithelial neoplasia (PIN), a precursor lesion of prostate cancer. Introduction of the ERG gene fusion product into primary or immortalized benign prostate epithelial cells induced an invasion-associated transcriptional program but did not increase cellular proliferation or anchorage-independent growth. These results suggest that TMPRSS2--ERG may not be sufficient for transformation in the absence of secondary molecular lesions. Transcriptional profiling of ERG knockdown in the TMPPRSS2--ERG--positive prostate cancer cell line VCaP revealed decreased expression of genes over-expressed in prostate cancer versus PIN and genes overexpressed in ETS-positive versus-negative prostate cancers in addition to inhibiting invasion. ERG knockdown in VCaP cells also induced a transcriptional program consistent with prostate differentiation. Importantly, VCaP cells and benign prostate cells overexpressing ERG directly engage components of the plasminogen activation pathway to mediate cellular invasion, potentially representing a downstream ETS target susceptible to therapeutic intervention. Our results support previous work suggesting that TMPRSS2--ERG fusions mediate invasion, consistent with the defining histologic distinction between PIN and prostate cancer. [ABSTRACT FROM AUTHOR]

Abstract: Although prostate-specific antigen (PSA) has evolved as a very useful tool for detection of prostate cancer, there remains an urgent need for more accurate biomarkers to diagnose prostate cancer and predict cancer-related outcomes. Recent advances in the study of proteomics and high throughput techniques have led to the discovery of many potential biomarkers for prostate cancer. This article briefly reviews the current status of PSA testing and discusses several candidate protein biomarkers for prostate cancer, as well as highlighting some recent proteomic discoveries with the potential to supplement or even replace PSA for the diagnosis and prognosis of prostate cancer. [Copyright &y& Elsevier]

Chromosomal aberrations that accompany carcinogenesis have been documented for almost half a century, with gene fusions being the most prevalent type of aberration. Gene fusions leading to generation of aberrant fusion proteins or aberrant expression of normal proteins are a potent route to carcinogenesis and have recently emerged as attractive therapeutic targets. Intriguingly, although gene fusions have been widely observed in hematological malignancies, they have been far less frequently described in the more-common epithelial carcinomas. It has been recently proposed that technical issues, rather than any fundamental dichotomy between hematological and solid cancers, account for the underrepresentation of gene fusions in epithelial cancers. Recent reports from our group support this contention and provide evidence of widespread recurrent gene fusions in prostate cancer using a novel analysis of gene-expression profiles. Here, we provide an appraisal of the state of the knowledge of gene fusions in epithelial cancers. Future implications of gene fusions in common epithelial cancers are also discussed. [Copyright &y& Elsevier]

We recently reported the identification of recurrent gene fusions in the majority of prostate cancers involving the 5′ untranslated region of the androgen-regulated gene TMPRSS2 and the ETS family members ERG, ETV1, and ETV4. Here we report the noninvasive detection of these gene fusions in the urine of patients with clinically localized prostate cancer. By quantitative polymerase chain reaction, we assessed the expression of ERG and TMPRSS2:ERG transcripts in urine samples obtained after prostatic massage from 19 patients (11 prebiopsy and 8 pre-radical prostatectomy) with prostate cancer. We observed a strong concordance between ERG overexpression and TMPRSS2: ERG expression, with 8 of 19 (42%) patients having detectable TMPRSS2:ERG transcripts in their urine. Importantly, by fluorescence in situ hybridization, we confirmed the presence or the absence of TMPRSS2: ERG gene fusions in matched prostate cancer tissue samples from three of three patients with fusion transcripts in their urine and from two of two patients without fusion transcripts in their urine. These results demonstrate that TMPRSS2:ERG gene fusions can be detected in the urine of patients with prostate cancer and support larger studies on prospective cohorts for noninvasive detection of prostate cancer. [ABSTRACT FROM AUTHOR]

Expression profiling of clinically obtainable tumor specimens has been hindered by the need for microgram quantities of RNA. In vitro transcription (IVT)--based amplifications are most commonly used to amplify small quantities of RNA for microarray analysis. However, significant drawbacks exist with IVT-based amplification, and the need for alternative amplification methods remains. Herein, we validate whole transcriptome amplification (WTA), an exponential amplification technique that produces cDNA libraries and amplified target in 3 to 4 hours from nanogram quantities of total RNA using a combination of cDNA microarrays and quantitative polymerase chain reaction (PCR). We demonstrate that WTA material can serve as a "molecular archive" because a WTA cDNA library can be faithfully amplified through multiple rounds of PCR amplification, allowing it to serve as a bankable and distributable resource. To demonstrate applicability, WTA was combined with laser capture microdissection to profile frozen prostate tissues. Unlike most IVT-based and exponential amplification techniques, WTA does not depend on the presence of a poly-A tail. Thus, we demonstrate that WTA is compatible with artificially degraded RNA and RNA isolated from formalin-fixed paraffin-embedded tissues. Taken together, WTA represents a versatile approach to profile and archive cDNA from minute tumor samples and is compatible with partially degraded RNA. [ABSTRACT FROM AUTHOR]

With the proliferation of high-throughput technologies to profile the cancer genome, methods to distinguish causal from bystander genetic events are needed. Two recent reports by Zender et al. and Kim et al. in Cell use genetically defined mouse models to serve as biological filters to mine the human cancer genome. Integration of high-resolution copy number profiles of mouse tumor models and human tumors identified cIAP1 and Yap as oncogenes in human hepatocellular carcinoma, while NEDD9 was identified as a metastasis gene in human melanoma. Together, these reports demonstrate that a comparative oncogenomics approach can identify genes causally involved in oncogenesis and metastasis. [Copyright &y& Elsevier]

Purpose: Numerous definitions of adverse pathology at radical prostatectomy (RP) have been proposed and implemented for both research and clinical care, and there is tremendous variation in the specific criteria used to define adverse pathology in these settings. Given the current landscape in which magnetic resonance imaging criteria and biomarker cutoffs are validated for disparate adverse pathology definitions, we sought to identify which of these is most closely tied to biochemical recurrence (BCR) after RP.Materials and Methods: A total of 2,837 patients who underwent RP at a single institution for localized prostate cancer (PCa) were included. We evaluated the following existing definitions of adverse pathology at RP: (1) Gleason score ≥7, (2) primary Gleason pattern ≥4, (3) Gleason score ≥7 or pathologic stage T3-4, (4) pathologic stage T3-4, (5) primary Gleason pattern ≥4 or pathologic stage T3-4. The primary outcome measure was BCR. Multiple statistical techniques were used to assess BCR prediction.Results: Of the 5 definitions assessed, 1 (primary Gleason pattern ≥4 or pathologic stage T3-4, 540 patients [19% of cohort]) consistently outperformed the other definitions across all statistical measures. Additionally, a total of only 13 (6.6%) and 34 (10.3%) men with very-low-risk and low-risk cancer per National Comprehensive Cancer Network guideline, respectively, met this definition of adverse pathology at the time of RP.Conclusions: Varying definitions of adverse pathology differ in their prognostic performance. The criteria defined by either primary Gleason pattern ≥4 or pT3-4 disease appears to most accurately predict BCR in this subset of patients with lower risk PCa at the time of diagnosis. Additionally, men with very-low-risk or low-risk PCa per National Comprehensive Cancer Network guidelines are relatively unlikely to have adverse pathology at the time of surgical resection. These data may help inform the use of imaging and molecular markers as well as the intensity of surveillance in men with newly diagnosed PCa. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: Prostate cancer has a variable clinical course, and molecular characterization has revealed striking mutational heterogeneity that may underlie the unpredictable clinical behavior of the disease. Advances in technology have resulted in a rapid expansion of our understanding of the genomic events responsible for the development and progression of prostate cancer. In this review, we discuss the genomic alterations underlying prostate cancer, and potential to utilize this knowledge for diagnostic and prognostic benefit. Methods and Materials: We reviewed the relevant literature, with a focus on recent studies on somatic alterations in prostate cancer. Results: Pathways known to affect tumorigenesis across a wide spectrum of tissues are dysregulated, such as the PI3K pathway, cell cycle control, and chromatin regulation. Lesions more specific to prostate cancer include alterations in androgen signaling, gene fusions of ETS transcription factors, and mutations in SPOP. Accumulating data suggests that prostate cancer can be subdivided based on a molecular profile of these genetic alterations. Conclusions: These findings raise the possibility that prostate cancer could transition from a poorly understood, heterogeneous disease with a variable clinical course to a collection of homogenous subtypes, identifiable by molecular criteria, associated with distinct risk profiles, and perhaps amenable to specific management strategies or targeted therapies. [Copyright &y& Elsevier]

Global molecular profiling of cancers has shown broad utility in delineating pathways and processes underlying disease, in predicting prognosis and response to therapy, and in suggesting novel treatments. To gain further insights from such data, we have integrated and analyzed a comprehensive collection of "molecular concepts" representing > 2500 cancer-related gene expression signatures from Oncomine and manual curation of the literature, drug treatment signatures from the Connectivity Map, target gene sets from genome-scale regulatory motif analyses, and reference gene sets from several gene and protein annotation databases. We computed pairwise association analysis on all 13,364 molecular concepts and identified > 290,000 significant associations, generating hypotheses that link cancer types and subtypes, pathways, mechanisms, and drugs. To navigate a network of associations, we developed an analysis platform, the Molecular Concepts Map. We demonstrate the utility of the approach by highlighting molecular concepts analyses of Myc pathway activation, breast cancer relapse, and retinoic acid treatment. Neoplasia (2007) 9, 443-454. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the association of the MyProstateScore (MPS) urine test on the decision to undergo biopsy in men referred for prostate biopsy in urology practice.Methods: MPS testing was offered as an alternative to immediate biopsy in men referred to the University of Michigan for prostate biopsy from October 2013 through October 2016. The primary endpoint was the decision to perform biopsy. The proportion of patients undergoing biopsy was compared to predicted risk scores from the Prostate Cancer Prevention Trial risk calculator (PCPTrc). Analyses were stratified by the use of multiparametric magnetic resonance imaging (mpMRI). The associations of PCPTrc, MPS, and mpMRI with the decision to undergo biopsy were explored in a multivariable logistic regression model.Results: Of 248 patients, 134 (54%) proceeded to prostate biopsy. MPS was significantly higher in biopsied patients (median 29 vs14, P < .001). The use of biopsy was strongly associated with MPS, with biopsy rates of 26%, 38%, 58%, 90%, and 85% in the first through fifth quintiles, respectively (P < .001). MPS association with biopsy persisted upon stratification by mpMRI. On multivariable analysis, MPS was strongly associated with the decision to undergo biopsy when modeled as both a continuous (odds ratio [OR] 1.05, 95%; confidence interval [CI] 1.04-1.08; <.001) and binary (OR 7.76, 95%; CI 4.14-14.5; P < .001) variable.Conclusion: Many patients (46%) undergoing clinical MPS testing as an alternative to immediate prostate biopsy were able to avoid biopsy. Increasing MPS was strongly associated with biopsy rates. These findings were robust to use of mpMRI. [ABSTRACT FROM AUTHOR]

Overexpression of centromeric proteins has been identified in a number of human malignancies, but the functional and mechanistic contributions of these proteins to disease progression have not been characterized. The centromeric histone H3 variant centromere protein A (CENPA) is an epigenetic mark that determines centromere identity. Here, using an array of approaches, including RNA-sequencing and ChIP-sequencing analyses, immunohistochemistry-based tissue microarrays, and various cell biology assays, we demonstrate that CENPA is highly overexpressed in prostate cancer in both tissue and cell lines and that the level of CENPA expression correlates with the disease stage in a large cohort of patients. Gain-of-function and loss-of-function experiments confirmed that CENPA promotes prostate cancer cell line growth. The results from the integrated sequencing experiments suggested a previously unidentified function of CENPA as a transcriptional regulator that modulates expression of critical proliferation, cell-cycle, and centromere/kinetochore genes. Taken together, our findings show that CENPA overexpression is crucial to prostate cancer growth. [ABSTRACT FROM AUTHOR]

While circulating tumor cell (CTC)–based detection of AR-V7 has been demonstrated to predict patient response to second-generation androgen receptor therapies, the rarity of AR-V7 expression in metastatic castrate-resistant prostate cancer (mCRPC) suggests that other drivers of resistance exist. We sought to use a multiplex gene expression platform to interrogate CTCs and identify potential markers of resistance to abiraterone and enzalutamide. 37 patients with mCRPC initiating treatment with enzalutamide (n = 16) or abiraterone (n = 21) were prospectively enrolled for CTC collection and gene expression analysis using a panel of 89 prostate cancer–related genes. Gene expression from CTCs was correlated with PSA response and radioclinical progression-free survival (PFS) using Kaplan-Meier and Cox regression analyses. Twenty patients (54%) had detectable CTCs. At a median follow-up of 11.3 months, increased expression of the following genes was significantly associated with shorter PSA PFS and radioclinical PFS: AR , AR-V7 , PSA , PSCA , TSPAN8 , NKX3.1 , and WNT5B. Additionally, high SPINK1 expression was associated with increased PFS. A predictive model including all eight genes gave an area under the curve (AUC) of 0.84 for PSA PFS and 0.86 for radioclinical PFS. In comparison, the AR-V7 only model resulted in AUC values of 0.65 and 0.64.These data demonstrate that clinically relevant information regarding gene expression can be obtained from whole blood using a CTC-based approach. Multigene classifiers in this setting may allow for the development of noninvasive predictive biomarkers to guide clinical management. [ABSTRACT FROM AUTHOR]