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Graph convolutional neural networks have shown significant potential in natural and histopathology images. However, their use has only been studied in a single magnification or multi-magnification with either homogeneous graphs or only different node types. In order to leverage the multi-magnification information and improve message passing with graph convolutional networks, we handle different embedding spaces at each magnification by introducing the Multi-Scale Relational Graph Convolutional Network (MS-RGCN) as a multiple instance learning method. We model histopathology image patches and their relation with neighboring patches and patches at other scales (i.e., magnifications) as a graph. We define separate message-passing neural networks based on node and edge types to pass the information between different magnification embedding spaces. We experiment on prostate cancer histopathology images to predict the grade groups based on the extracted features from patches. We also compare our MS-RGCN with multiple state-of-the-art methods with evaluations on several source and held-out datasets. Our method outperforms the state-of-the-art on all of the datasets and image types consisting of tissue microarrays, whole-mount slide regions, and whole-slide images. Through an ablation study, we test and show the value of the pertinent design features of the MS-RGCN., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose: Prostate cancer (PCa) represents a highly heterogeneous disease that requires tools to assess oncologic risk and guide patient management and treatment planning. Current models are based on various clinical and pathologic parameters including Gleason grading, which suffers from a high interobserver variability. In this study, we determine whether objective machine learning (ML)-driven histopathology image analysis would aid us in better risk stratification of PCa., Materials and Methods: We propose a deep learning, histopathology image-based risk stratification model that combines clinicopathologic data along with hematoxylin and eosin- and Ki-67-stained histopathology images. We train and test our model, using a five-fold cross-validation strategy, on a data set from 502 treatment-naïve PCa patients who underwent radical prostatectomy (RP) between 2000 and 2012., Results: We used the concordance index as a measure to evaluate the performance of various risk stratification models. Our risk stratification model on the basis of convolutional neural networks demonstrated superior performance compared with Gleason grading and the Cancer of the Prostate Risk Assessment Post-Surgical risk stratification models. Using our model, 3.9% of the low-risk patients were correctly reclassified to be high-risk and 21.3% of the high-risk patients were correctly reclassified as low-risk., Conclusion: These findings highlight the importance of ML as an objective tool for histopathology image assessment and patient risk stratification. With further validation on large cohorts, the digital pathology risk classification we propose may be helpful in guiding administration of adjuvant therapy including radiotherapy after RP.

Background: Although the fusion of the transmembrane serine protease 2 gene (TMPRSS2) with the erythroblast transformation-specific-related gene (ERG), or TMPRSS2-ERG, occurs frequently in prostate cancer, its impact on clinical outcomes remains controversial. Roughly half of TMPRSS2-ERG fusions occur through intrachromosomal deletion of interstitial genes and the remainder via insertional chromosomal rearrangements. Because prostate cancers with deletion-derived TMPRSS2-ERG fusions are more aggressive than those with insertional fusions, we investigated the impact of interstitial gene loss on prostate cancer progression., Methods: We conducted an unbiased analysis of transcriptome data from large collections of prostate cancer samples and employed diverse in vitro and in vivo models combined with genetic approaches to characterize the interstitial gene loss that imposes the most important impact on clinical outcome., Results: This analysis identified FAM3B as the top-ranked interstitial gene whose loss is associated with a poor prognosis. The association between FAM3B loss and poor clinical outcome extended to fusion-negative prostate cancers where FAM3B downregulation occurred through epigenetic imprinting. Importantly, FAM3B loss drives disease progression in prostate cancer. FAM3B acts as an intermediator of a self-governing androgen receptor feedback loop. Specifically, androgen receptor upregulates FAM3B expression by binding to an intronic enhancer to induce an enhancer RNA and facilitate enhancer-promoter looping. FAM3B, in turn, attenuates androgen receptor signaling., Conclusion: Loss of FAM3B in prostate cancer, whether through the TMPRSS2-ERG translocation or epigenetic imprinting, causes an exit from this autoregulatory loop to unleash androgen receptor activity and prostate cancer progression. These findings establish FAM3B loss as a new driver of prostate cancer progression and support the utility of FAM3B loss as a biomarker to better define aggressive prostate cancer., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Treatment-induced neuroendocrine prostate cancer (t-NEPC) is a lethal subtype of castration-resistant prostate cancer resistant to androgen receptor (AR) inhibitors. Our study unveils that AR suppresses the neuronal development protein dihydropyrimidinase-related protein 5 (DPYSL5), providing a mechanism for neuroendocrine transformation under androgen deprivation therapy. Our unique CRPC-NEPC cohort, comprising 135 patient tumor samples, including 55 t-NEPC patient samples, exhibits a high expression of DPYSL5 in t-NEPC patient tumors. DPYSL5 correlates with neuroendocrine-related markers and inversely with AR and PSA. DPYSL5 overexpression in prostate cancer cells induces a neuron-like phenotype, enhances invasion, proliferation, and upregulates stemness and neuroendocrine-related markers. Mechanistically, DPYSL5 promotes prostate cancer cell plasticity via EZH2-mediated PRC2 activation. Depletion of DPYSL5 decreases proliferation, induces G1 phase cell cycle arrest, reverses neuroendocrine phenotype, and upregulates luminal genes. In conclusion, DPYSL5 plays a critical role in regulating prostate cancer cell plasticity, and we propose the AR/DPYSL5/EZH2/PRC2 axis as a driver of t-NEPC progression., (© 2024. The Author(s).)

Background: The phase 3 CALGB 90203 (Alliance) trial evaluated neoadjuvant chemohormonal therapy for high-risk localized prostate cancer before radical prostatectomy. We dissected the molecular features of post-treated tumors with long-term clinical outcomes to explore mechanisms of response and resistance to chemohormonal therapy., Methods: We evaluated 471 radical prostatectomy tumors, including 294 samples from 166 patients treated with 6 cycles of docetaxel plus androgen deprivation therapy before radical prostatectomy and 177 samples from 97 patients in the control arm (radical prostatectomy alone). Targeted DNA sequencing and RNA expression of tumor foci and adjacent noncancer regions were analyzed in conjunction with pathologic changes and clinical outcomes., Results: Tumor fraction estimated from DNA sequencing was significantly lower in post-treated tumor tissues after chemohormonal therapy compared with controls. Higher tumor fraction after chemohormonal therapy was associated with aggressive pathologic features and poor outcomes, including prostate-specific antigen-progression-free survival. SPOP alterations were infrequently detected after chemohormonal therapy, while TP53 alterations were enriched and associated with shorter overall survival. Residual tumor fraction after chemohormonal therapy was linked to higher expression of androgen receptor-regulated genes, cell cycle genes, and neuroendocrine genes, suggesting persistent populations of active prostate cancer cells. Supervised clustering of post-treated high-tumor-fraction tissues identified a group of patients with elevated cell cycle-related gene expression and poor clinical outcomes., Conclusions: Distinct recurrent prostate cancer genomic and transcriptomic features are observed after exposure to docetaxel and androgen deprivation therapy. Tumor fraction assessed by DNA sequencing quantifies pathologic response and could be a useful trial endpoint or prognostic biomarker. TP53 alterations and high cell cycle transcriptomic activity are linked to aggressive residual disease, despite potent chemohormonal therapy., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

RNF185 is a RING finger domain-containing ubiquitin ligase implicated in ER-associated degradation. Prostate tumor patient data analysis revealed a negative correlation between RNF185 expression and prostate cancer progression and metastasis. Likewise, several prostate cancer cell lines exhibited greater migration and invasion capabilities in culture upon RNF185 depletion. Subcutaneous inoculation of mouse prostate cancer MPC3 cells stably expressing short hairpin RNA against RNF185 into mice resulted in larger tumors and more frequent lung metastases. RNA-sequencing and Ingenuity Pathway Analysis identified wound-healing and cellular movement among the most significant pathways upregulated in RNF185-depleted lines, compared with control prostate cancer cells. Gene Set Enrichment Analyses performed in samples from patients harboring low RNF185 expression and in RNF185-depleted lines confirmed the deregulation of genes implicated in epithelial-to-mesenchymal transition. Among those, COL3A1 was identified as the primary mediator of RNF185's ability to impact migration phenotypes. Correspondingly, enhanced migration and metastasis of RNF185 knockdown (KD) prostate cancer cells were attenuated upon co-inhibition of COL3A1. Our results identify RNF185 as a gatekeeper of prostate cancer metastasis, partly via its control of COL3A1 availability., Implications: RNF185 is identified as an important regulator of prostate cancer migration and metastasis, in part due to its regulation of COL3A1. Both RNF185 and COL3A1 may serve as novel markers for prostate tumors., (©2023 American Association for Cancer Research.)

Overexpression of androgen receptor (AR) is the primary cause of castration-resistant prostate cancer, although mechanisms upregulating AR transcription in this context are not well understood. Our RNA-seq studies revealed that SMAD3 knockdown decreased levels of AR and AR target genes, whereas SMAD4 or SMAD2 knockdown had little or no effect. ChIP-seq analysis showed that SMAD3 knockdown decreased global binding of AR to chromatin. Mechanistically, we show that SMAD3 binds to intron 3 of the AR gene to promote AR expression. Targeting these binding sites by CRISPRi reduced transcript levels of AR and AR targets. In addition, ∼50% of AR and SMAD3 ChIP-seq peaks overlapped, and SMAD3 may also cooperate with or co-activate AR for AR target expression. Functionally, AR re-expression in SMAD3-knockdown cells partially rescued AR target expression and cell growth defects. The SMAD3 peak in AR intron 3 overlapped with H3K27ac ChIP-seq and ATAC-seq peaks in datasets of prostate cancer. AR and SMAD3 mRNAs were upregulated in datasets of metastatic prostate cancer and CRPC compared with primary prostate cancer. A SMAD3 PROTAC inhibitor reduced levels of AR, AR-V7 and AR targets in prostate cancer cells. This study suggests that SMAD3 could be targeted to inhibit AR in prostate cancer., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The androgen inactivating UGT2B28 pathway emerges as a predictor of progression in prostate cancer (PCa). However, the clinical significance of UGT2B28 tumoral expression and its contribution to PCa progression remain unclear. Using the Canadian Prostate Cancer Biomarker Network biobank (CPCBN; n = 1512), we analyzed UGT2B28 tumor expression in relation to clinical outcomes in men with localized PCa. UGT2B28 was overexpressed in tumors compared to paired normal adjacent prostatic tissue and was associated with inferior outcomes. Functional analyses indicated that UGT2B28 promoted cell proliferation, and its expression was regulated by the androgen receptor (AR)/ARv7. Mechanistically, UGT2B28 was shown to be a protein partner of the endocytic adaptor protein huntingtin-interacting protein 1 (HIP1), increasing its stability and priming AR/epidermal growth factor receptor (EGFR) pathways, leading to ERK1/2 activation triggering cell proliferation and epithelial-to-mesenchymal transition (EMT). HIP1 knockdown in UGT2B28 positive cells, and dual pharmacological targeting of AR and EGFR pathways, abolished cell proliferative advantages conferred by UGT2B28. In conclusion, UGT2B28 is a prognosticator of progression in localized PCa, regulates both AR and EGFR oncogenic signaling pathways via HIP1, and therefore can be therapeutically targeted by using combination of existing AR/EGFR inhibitors., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Prostate cancer harboring BRCA1/2 mutations are often exceptionally sensitive to PARP inhibitors. However, genomic alterations in other DNA damage response genes have not been consistently predictive of clinical response to PARP inhibition. Here, we perform genome-wide CRISPR-Cas9 knockout screens in BRCA1/2-proficient prostate cancer cells and identify previously unknown genes whose loss has a profound impact on PARP inhibitor response. Specifically, MMS22L deletion, frequently observed (up to 14%) in prostate cancer, renders cells hypersensitive to PARP inhibitors by disrupting RAD51 loading required for homologous recombination repair, although this response is TP53-dependent. Unexpectedly, loss of CHEK2 confers resistance rather than sensitivity to PARP inhibition through increased expression of BRCA2, a target of CHEK2-TP53-E2F7-mediated transcriptional repression. Combined PARP and ATR inhibition overcomes PARP inhibitor resistance caused by CHEK2 loss. Our findings may inform the use of PARP inhibitors beyond BRCA1/2-deficient tumors and support reevaluation of current biomarkers for PARP inhibition in prostate cancer., (© 2023. The Author(s).)

Numerous cancers, including prostate cancer (PCa), are addicted to transcription programs driven by specific genomic regions known as super-enhancers (SEs). The robust transcription of genes at such SEs is enabled by the formation of phase-separated condensates by transcription factors and coactivators with intrinsically disordered regions. The androgen receptor (AR), the main oncogenic driver in PCa, contains large disordered regions and is co-recruited with the transcriptional coactivator mediator complex subunit 1 (MED1) to SEs in androgen-dependent PCa cells, thereby promoting oncogenic transcriptional programs. In this work, we reveal that full-length AR forms foci with liquid-like properties in different PCa models. We demonstrate that foci formation correlates with AR transcriptional activity, as this activity can be modulated by changing cellular foci content chemically or by silencing MED1. AR ability to phase separate was also validated in vitro by using recombinant full-length AR protein. We also demonstrate that AR antagonists, which suppress transcriptional activity by targeting key regions for homotypic or heterotypic interactions of this receptor, hinder foci formation in PCa cells and phase separation in vitro. Our results suggest that enhanced compartmentalization of AR and coactivators may play an important role in the activation of oncogenic transcription programs in androgen-dependent PCa., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Cribriform growth pattern is well-established as an adverse pathologic feature in prostate cancer. The literature suggests "large" cribriform glands associate with aggressive behavior; however, published studies use varying definitions for "large". We aimed to identify an outcome-based quantitative cut-off for "large" vs "small" cribriform glands. We conducted an initial training phase using the tissue microarray based Canary retrospective radical prostatectomy cohort. Of 1287 patients analyzed, cribriform growth was observed in 307 (24%). Using Kaplan-Meier estimates of recurrence-free survival curves (RFS) that were stratified by cribriform gland size, we identified 0.25 mm as the optimal cutoff to identify more aggressive disease. In univariable and multivariable Cox proportional hazard analyses, size >0.25 mm was a significant predictor of worse RFS compared to patients with cribriform glands ≤0.25 mm, independent of pre-operative PSA, grade, stage and margin status (p < 0.001). In addition, two different subset analyses of low-intermediate risk cases (cases with Gleason score ≤ 3 + 4 = 7; and cases with Gleason score = 3 + 4 = 7/4 + 3 = 7) likewise demonstrated patients with largest cribriform diameter >0.25 mm had a significantly lower RFS relative to patients with cribriform glands ≤0.25 mm (each subset p = 0.004). Furthermore, there was no significant difference in outcomes between patients with cribriform glands ≤ 0.25 mm and patients without cribriform glands. The >0.25 mm cut-off was validated as statistically significant in a separate 419 patient, completely embedded whole-section radical prostatectomy cohort by biochemical recurrence, metastasis-free survival, and disease specific death, even when cases with admixed Gleason pattern 5 carcinoma were excluded. In summary, our findings support reporting cribriform gland size and identify 0.25 mm as an optimal outcome-based quantitative measure for defining "large" cribriform glands. Moreover, cribriform glands >0.25 mm are associated with potential for metastatic disease independent of Gleason pattern 5 adenocarcinoma., (© 2022. The Author(s).)

To develop and validate a new tissue-based biomarker that improves prediction of outcomes in localized prostate cancer by quantifying the host response to tumor. We use digital image analysis and machine learning to develop a biomarker of the prostate stroma called quantitative reactive stroma (qRS). qRS is a measure of percentage tumor area with a distinct, reactive stromal architecture. Kaplan Meier analysis was used to determine survival in a large retrospective cohort of radical prostatectomy samples. qRS was validated in two additional, distinct cohorts that include international cases and tissue from both radical prostatectomy and biopsy specimens. In the developmental cohort (Baylor College of Medicine, n = 482), patients whose tumor had qRS > 34% had increased risk of prostate cancer-specific death (HR 2.94; p = 0.039). This result was replicated in two validation cohorts, where patients with qRS > 34% had increased risk of prostate cancer-specific death (MEDVAMC; n = 332; HR 2.64; p = 0.02) and also biochemical recurrence (Canary; n = 988; HR 1.51; p = 0.001). By multivariate analysis, these associations were shown to hold independent predictive value when compared to currently used clinicopathologic factors including Gleason score and PSA. qRS is a new, validated biomarker that predicts prostate cancer death and biochemical recurrence across three distinct cohorts. It measures host-response rather than tumor-based characteristics, and provides information not represented by standard prognostic measurements., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Cell division cycle-associated 8 (CDCA8) is a component of chromosomal passenger complex (CPC) that participates in mitotic regulation. Although cancer-related CDCA8 hyperactivation has been widely observed, its molecular mechanism remains elusive. Here, we report that CDCA8 overexpression maintains tumorigenicity and is associated with poor clinical outcome in patients with prostate cancer (PCa). Notably, enhancer of zeste homolog 2 (EZH2) is identified to be responsible for CDCA8 activation in PCa. Genome-wide assays revealed that EZH2-induced H3K27 trimethylation represses let-7b expression and thus protects the let-7b-targeting CDCA8 transcripts. More importantly, EZH2 facilitates the self-activation of E2F1 by recruiting E2F1 to its own promoter region in a methylation-independent manner. The high level of E2F1 further promotes transcription of CDCA8 along with the other CPC subunits. Taken together, our study suggests that EZH2-mediated cell cycle regulation in PCa relies on both its methyltransferase and non-methyltransferase activities., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

We report a new mechanism of androgen receptor (AR) mRNA regulation and cytoprotection in response to AR pathway inhibition (ARPI) stress in prostate cancer (PCA). AR mRNA translation is coordinately regulated by RNA binding proteins, YTHDF3 and G3BP1. Under ambient conditions m6A-modified AR mRNA is bound by YTHDF3 and translationally stimulated, while m6A-unmodified AR mRNA is bound by G3BP1 and translationally repressed. When AR-regulated PCA cell lines are subjected to ARPI stress, m6A-modified AR mRNA is recruited from actively translating polysomes (PSs) to RNA-protein stress granules (SGs), leading to reduced AR mRNA translation. After ARPI stress, m6A-modified AR mRNA liquid-liquid phase separated with YTHDF3, while m6A-unmodified AR mRNA phase separated with G3BP1. Accordingly, these AR mRNA messages form two distinct YTHDF3-enriched or G3BP1-enriched clusters in SGs. ARPI-induced SG formation is cell-protective, which when blocked by YTHDF3 or G3BP1 silencing increases PCA cell death in response to ARPI stress. Interestingly, AR mRNA silencing also delays ARPI stress-induced SG formation, highlighting its supportive role in triggering this stress response. Our results define a new mechanism for stress adaptive cell survival after ARPI stress involving SG-regulated translation of AR mRNA, mediated by m6A RNA modification and their respective regulatory proteins., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Epithelial-mesenchymal transition (EMT) contributes to tumor invasion, metastasis and drug resistance. AKT activation is key in a number of cellular processes. While many positive regulators for either EMT or AKT activation have been reported, few negative regulators are established. Through kinase cDNA screen, we identified brain-type creatine kinase (CKB or BCK) as a potent suppressor for both. As a ubiquitously expressed kinase in normal tissues, CKB is significantly downregulated in several solid cancer types. Lower CKB expression is significantly associated with worse prognosis. Phenotypically, CKB overexpression suppresses, while its silencing promotes, EMT and cell migration, xenograft tumor growth and metastasis of prostate cancer cells. AKT activation is one of the most prominent signaling events upon CKB silencing in prostate cancer cells, which is in line with prostate cancer TCGA data. EMT enhanced by CKB silencing is abolished by AKT inhibition. Mechanistically, CKB interacts with AKT and sequestrates it from activation by mTOR. We further elucidated that an 84aa fragment at C-terminus of CKB protein interacts with AKT's PH domain. Ectopic expression of the 84aa CKB fragment inhibits AKT activation, EMT and cell proliferation. Interestingly, molecular dynamics simulation on crystal structures of AKT and CKB independently demonstrates that AKT's PH domain and CKB's 84aa fragment establish their major interaction interface. In summary, we have discovered CKB as a negative regulator of EMT and AKT activation, revealing a new mode of their regulation . We have also demonstrated that CKB downregulation is a poor prognosticator, which is sufficient to promote prostate cancer progression., (Published by Elsevier Inc.)

Cancers adapt to increasingly potent targeted therapies by reprogramming their phenotype. Here we investigated such a phenomenon in prostate cancer, in which tumours can escape epithelial lineage confinement and transition to a high-plasticity state as an adaptive response to potent androgen receptor (AR) antagonism. We found that AR activity can be maintained as tumours adopt alternative lineage identities, with changes in chromatin architecture guiding AR transcriptional rerouting. The epigenetic regulator enhancer of zeste homologue 2 (EZH2) co-occupies the reprogrammed AR cistrome to transcriptionally modulate stem cell and neuronal gene networks-granting privileges associated with both fates. This function of EZH2 was associated with T350 phosphorylation and establishment of a non-canonical polycomb subcomplex. Our study provides mechanistic insights into the plasticity of the lineage-infidelity state governed by AR reprogramming that enabled us to redirect cell fate by modulating EZH2 and AR, highlighting the clinical potential of reversing resistance phenotypes., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

One-carbon (1C) metabolism has a key role in metabolic programming with both mitochondrial (m1C) and cytoplasmic (c1C) components. Here we show that activating transcription factor 4 (ATF4) exclusively activates gene expression involved in m1C, but not the c1C cycle in prostate cancer cells. This includes activation of methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) expression, the central player in the m1C cycle. Consistent with the key role of m1C cycle in prostate cancer, MTHFD2 knockdown inhibited prostate cancer cell growth, prostatosphere formation, and growth of patient-derived xenograft organoids. In addition, therapeutic silencing of MTHFD2 by systemically administered nanoliposomal siRNA profoundly inhibited tumor growth in preclinical prostate cancer mouse models. Consistently, MTHFD2 expression is significantly increased in human prostate cancer, and a gene expression signature based on the m1C cycle has significant prognostic value. Furthermore, MTHFD2 expression is coordinately regulated by ATF4 and the oncoprotein c-MYC, which has been implicated in prostate cancer. These data suggest that the m1C cycle is essential for prostate cancer progression and may serve as a novel biomarker and therapeutic target. SIGNIFICANCE: These findings demonstrate that the mitochondrial, but not cytoplasmic, one-carbon cycle has a key role in prostate cancer cell growth and survival and may serve as a biomarker and/or therapeutic target., (©2021 American Association for Cancer Research.)

Treatment-induced adaptive pathways converge to support androgen receptor (AR) reactivation and emergence of castration-resistant prostate cancer (PCa) after AR pathway inhibition (ARPI). We set out to explore poorly defined acute adaptive responses that orchestrate shifts in energy metabolism after ARPI and identified rapid changes in succinate dehydrogenase (SDH), a TCA cycle enzyme with well-known tumor suppressor activity. We show that AR directly regulates transcription of its catalytic subunits (SDHA, SDHB) via androgen response elements (AREs). ARPI acutely suppresses SDH activity, leading to accumulation of the oncometabolite, succinate. Succinate triggers calcium ions release from intracellular stores, which in turn phospho-activates the AR-cochaperone, Hsp27 via p-CaMKK2/p-AMPK/p-p38 axis to enhance AR protein stabilization and activity. Activation of this pathway was seen in tissue microarray analysis on prostatectomy tissues and patient-derived xenografts. This adaptive response is blocked by co-targeting AR with Hsp27 under both in vitro and in vivo studies, sensitizing PCa cells to ARPI treatments., (© 2021 The Authors. Published under the terms of the CC BY 4.0 license.)

Resistance to next-generation anti-androgen enzalutamide (ENZ) constitutes a major challenge for the treatment of castration-resistant prostate cancer (CRPC). By performing genome-wide ChIP-seq profiling in ENZ-resistant CRPC cells we identify a set of androgen receptor (AR) binding sites with increased AR binding intensity (ARBS-gained). While ARBS-gained loci lack the canonical androgen response elements (ARE) and pioneer factor FOXA1 binding motifs, they are highly enriched with CpG islands and the binding sites of unmethylated CpG dinucleotide-binding protein CXXC5 and the partner TET2. RNA-seq analysis reveals that both CXXC5 and its regulated genes including ID1 are upregulated in ENZ-resistant cell lines and these results are further confirmed in patient-derived xenografts (PDXs) and patient specimens. Consistent with the finding that ARBS-gained loci are highly enriched with H3K27ac modification, ENZ-resistant PCa cells, organoids, xenografts and PDXs are hyper-sensitive to NEO2734, a dual inhibitor of BET and CBP/p300 proteins. These results not only reveal a noncanonical AR function in acquisition of ENZ resistance, but also posit a treatment strategy to target this vulnerability in ENZ-resistant CRPC.

Histopathology of Hematoxylin and Eosin (H&E)-stained tissue obtained from biopsy is commonly used in prostate cancer (PCa) diagnosis. Automatic PCa classification of digitized H&E slides has been developed before, but no attempts have been made to classify PCa using additional tissue stains registered to H&E. In this paper, we demonstrate that using H&E, Ki67 and p63-stained (3-stain) tissue improves PCa classification relative to H&E alone. We also show that we can infer PCa-relevant Ki67 and p63 information from the H&E slides alone, and use it to achieve H&E-based PCa classification that is comparable to the 3-stain classification. Reported improvements apply to classifying benign vs. malignant tissue, and low grade (Gleason group 2) vs. high grade (Gleason groups 3,4,5) cancer. Specifically, we conducted four classification tasks using 333 tissue samples extracted from 231 radical prostatectomy patients: regression tree-based classification using either (i) 3-stain features, with a benign vs malignant area under the curve (AUC = 92.9%), or (ii) real H&E features and H&E features learned from Ki67 and p63 stains (AUC = 92.4%), as well as deep learning classification using either (iii) real 3-stain tissue patches (AUC = 94.3%) and (iv) real H&E patches and generated Ki67 and p63 patches (AUC = 93.0%) using a deep convolutional generative adversarial network. Classification performance was assessed with Monte Carlo cross validation and quantified in terms of the Area Under the Curve, Brier score, sensitivity, and specificity. Our results are interpretable and indicate that the standard H&E classification could be improved by mimicking other stain types., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Therapy-induced neuroendocrine prostate cancer (t-NEPC) is a highly aggressive subtype of prostate cancer with poor patient survival. Emerging evidence indicates that t-NEPC can develop when prostate adenocarcinoma cells acquire cancer stem-like cell signaling in the presence of androgen receptor inhibition, followed by redifferentiation toward neuroendocrine lineage and subsequent t-NEPC progression. Whether the stem-like signaling is controlled by the core pluripotency stem cell genes (e.g., LIN28 and SOX2) remains unknown. Here, we report that the transcription of the LIN28B isoform and SOX2 were co-upregulated in t-NEPC patient tumors, patient-derived xenografts, transgenic mice, and cell models. Immunohistochemistry validated that LIN28B and SOX2 protein expression were elevated in t-NEPC patient biopsies. Using prostate adenocarcinoma and t-NEPC cell models, we demonstrated that LIN28B induced a stem-like gene network, neuroendocrine biomarkers, and neuroendocrine cell morphology. LIN28B depletion by CRISPR inhibited t-NEPC tumorigenesis and xenograft growth. These LIN28B functions were mediated mainly through the suppression of let-7 miRNA expression, resulting in de-repression of the transcription factor HMGA2 and HMGA2-mediated SOX2 expression. This study revealed a mechanism by which t-NEPC can develop through the LIN28B/let-7/SOX2 axis that regulates a cancer cell stem-like gene network, highlighting LIN28B as a potential therapeutic target in t-NEPC.

Visual inspection of histopathology images of stained biopsy tissue by expert pathologists is the standard method for grading of prostate cancer (PCa). However, this process is time-consuming and subject to high inter-observer variability. Machine learning-based methods have the potential to improve efficient throughput of large volumes of slides while decreasing variability, but they are not easy to develop because they require substantial amounts of labeled training data. In this paper, we propose a deep learning-based classification technique and data augmentation methods for accurate grading of PCa in histopathology images in the presence of limited data. Our method combines the predictions of three separate convolutional neural networks (CNNs) that work with different patch sizes. This enables our method to take advantage of the greater amount of contextual information in larger patches as well as greater quantity of smaller patches in the labeled training data. The predictions produced by the three CNNs are combined using a logistic regression model, which is trained separately after the CNN training. To effectively train our models, we propose new data augmentation methods and empirically study their effects on the classification accuracy. The proposed method achieves an accuracy of [Formula: see text] in classifying cancerous patches versus benign patches and an accuracy of [Formula: see text] in classifying low-grade (i.e., Gleason grade 3) from high-grade (i.e., Gleason grades 4 and 5) patches. The agreement level of our automatic grading method with expert pathologists is within the range of agreement between pathologists. Our experiments indicate that data augmentation is necessary for achieving expert-level performance with deep learning-based methods. A combination of image-space augmentation and feature-space augmentation leads to the best results. Our study shows that well-designed and properly trained deep learning models can achieve PCa Gleason grading accuracy that is comparable to an expert pathologist.

Purpose: DNA mismatch repair defects (MMRd) and tumor hypermutation are rare and under-characterized in metastatic prostate cancer (mPC). Furthermore, because hypermutated MMRd prostate cancers can respond to immune checkpoint inhibitors, there is an urgent need for practical detection tools., Experimental Design: We analyzed plasma cell-free DNA-targeted sequencing data from 433 patients with mPC with circulating tumor DNA (ctDNA) purity ≥2%. Samples with somatic hypermutation were subjected to 185 × whole-exome sequencing and capture of mismatch repair gene introns. Archival tissue was analyzed with targeted sequencing and IHC., Results: Sixteen patients (3.7%) had somatic hypermutation with MMRd etiology, evidenced by deleterious alterations in MSH2, MSH6 , or MLH1 , microsatellite instability, and characteristic trinucleotide signatures. ctDNA was concordant with mismatch repair protein IHC and DNA sequencing of tumor tissue. Tumor suppressors such as PTEN, RB1 , and TP53 were inactivated by mutation rather than copy-number loss. Hotspot mutations in oncogenes such as AKT1, PIK3CA , and CTNNB1 were common, and the androgen receptor ( AR )-ligand binding domain was mutated in 9 of 16 patients. We observed high intrapatient clonal diversity, evidenced by subclonal driver mutations and shifts in mutation allele frequency over time. Patients with hypermutation and MMRd etiology in ctDNA had a poor response to AR inhibition and inferior survival compared with a control cohort., Conclusions: Hypermutated MMRd mPC is associated with oncogene activation and subclonal diversity, which may contribute to a clinically aggressive disposition in selected patients. In patients with detectable ctDNA, cell-free DNA sequencing is a practical tool to prioritize this subtype for immunotherapy. See related commentary by Schweizer and Yu, p. 981 ., (©2019 American Association for Cancer Research.)

Kallikrein-related peptidase 14 (KLK14) is one of the several secreted KLK serine proteases involved in prostate cancer (PCa) pathogenesis. While relatively understudied, recent reports have identified KLK14 as overexpressed during PCa development. However, the modulation of KLK14 expression during PCa progression and the molecular and biological functions of this protease in the prostate tumor microenvironment remain unknown. To determine the modulation of KLK14 expression during PCa progression, we analyzed the expression levels of KLK14 in patient samples using publicly available databases and immunohistochemistry. In order to delineate the molecular mechanisms involving KLK14 in PCa progression, we integrated proteomic, transcriptomic, and in vitro assays with the goal to identify substrates, related-signaling pathways, and functional roles of this protease. We showed that KLK14 expression is elevated in advanced PCa, and particularly in metastasis. Additionally, KLK14 levels were found to be decreased in PCa tissues from patients responsive to neoadjuvant therapy compared to untreated patients. Furthermore, we also identified that KLK14 expression reoccurred in patients who developed castrate-resistant PCa. The combination of proteomic and transcriptomic analysis as well as functional assays revealed several new KLK14 substrates (agrin, desmoglein 2, vitronectin, laminins) and KLK14-regulated genes (Interleukin 32, midkine, SRY-Box 9), particularly an involvement of the mitogen-activated protein kinase 1 and interleukin 1 receptor pathways, and an involvement of KLK14 in the regulation of cellular migration, supporting its involvement in aggressive features of PCa progression. In conclusion, our work showed that KLK14 expression is associated with the development of aggressive PCa suggesting that targeting this protease could offer a novel route to limit the progression of prostate tumors. Additional work is necessary to determine the benefits and implications of targeting/cotargeting KLK14 in PCa as well as to determine the potential use of KLK14 expression as a predictor of PCa aggressiveness or response to treatment., (© 2019 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.)

Background: Prostate cancer development involves various mechanisms, which are poorly understood but pointing to epithelial mesenchymal transition (EMT) as the key mechanism in progression to metastatic disease. ABI1, a member of WAVE complex and actin cytoskeleton regulator and adaptor protein, acts as tumor suppressor in prostate cancer but the role of ABI1 in EMT is not clear., Methods: To investigate the molecular mechanism by which loss of ABI1 contributes to tumor progression, we disrupted the ABI1 gene in the benign prostate epithelial RWPE-1 cell line and determined its phenotype. Levels of ABI1 expression in prostate organoid tumor cell lines was evaluated by Western blotting and RNA sequencing. ABI1 expression and its association with prostate tumor grade was evaluated in a TMA cohort of 505 patients and metastatic cell lines., Results: Low ABI1 expression is associated with biochemical recurrence, metastasis and death (p = 0.038). Moreover, ABI1 expression was significantly decreased in Gleason pattern 5 vs. pattern 4 (p = 0.0025) and 3 (p = 0.0012), indicating an association between low ABI1 expression and highly invasive prostate tumors. Disruption of ABI1 gene in RWPE-1 cell line resulted in gain of an invasive phenotype, which was characterized by a loss of cell-cell adhesion markers and increased migratory ability of RWPE-1 spheroids. Through RNA sequencing and protein expression analysis, we discovered that ABI1 loss leads to activation of non-canonical WNT signaling and EMT pathways, which are rescued by re-expression of ABI1. Furthermore, an increase in STAT3 phosphorylation upon ABI1 inactivation and the evidence of a high-affinity interaction between the FYN SH2 domain and ABI1 pY421 support a model in which ABI1 acts as a gatekeeper of non-canonical WNT-EMT pathway activation downstream of the FZD2 receptor., Conclusions: ABI1 controls prostate tumor progression and epithelial plasticity through regulation of EMT-WNT pathway. Here we discovered that ABI1 inhibits EMT through suppressing FYN-STAT3 activation downstream from non-canonical WNT signaling thus providing a novel mechanism of prostate tumor suppression.

Cancer cells exploit many of the cellular adaptive responses to support their survival needs. One such critical pathway in eukaryotic cells is the unfolded protein response (UPR) that is important in normal physiology as well as disease states, including cancer. Since UPR can serve as a lever between survival and death, regulated control of its activity is critical for tumor formation and growth although the underlying mechanisms are poorly understood. Here we show that one of the main transcriptional effectors of UPR, activating transcription factor 4 (ATF4), is essential for prostate cancer (PCa) growth and survival. Using systemic unbiased gene expression and proteomic analyses, we identified a novel direct ATF4 target gene, family with sequence similarity 129 member A (FAM129A), which is critical in mediating ATF4 effects on prostate tumorigenesis. Interestingly, FAM129A regulated both PERK and eIF2α in a feedback loop that differentially channeled the UPR output. ATF4 and FAM129A protein expression is increased in patient PCa samples compared with benign prostate. Importantly, in vivo therapeutic silencing of ATF4-FAM129A axis profoundly inhibited tumor growth in a preclinical PCa model. These data support that one of the canonical UPR branches, through ATF4 and its target gene FAM129A, is required for PCa growth and thus may serve as a novel therapeutic target.

Background: Prostate adenocarcinoma (AdPC) progression to treatment-induced neuroendocrine prostate cancer (t-NEPC) is associated with poor patient survival. While AdPC and t-NEPC share similar genomes, they possess distinct transcriptomes, suggesting that RNA splicing and epigenetic mechanisms may regulate t-NEPC development., Objective: To characterize the role of alternative RNA splicing of the histone demethylase BHC80 during t-NEPC progression., Design, Setting, and Participants: The expression of BHC80 splice variants (BHC80-1 and BHC80-2) were compared between AdPC and t-NEPC patient tumors. Regulatory mechanisms of RNA splicing of the BHC80 gene were studied, and the signal pathways mediated by BHC80 splice variants were investigated in t-NEPC cell and xenograft models., Results: Global transcriptome analyses identified that the BHC80-2 variant is highly expressed in t-NEPC. Compared with the known histone demethylation activities of the BHC80 gene, we discovered a novel nonepigenetic action of BHC80-2, whereby BHC80-2 is localized in the cytoplasm to trigger the MyD88-p38-TTP pathway, which results in increased RNA stability of multiple tumor-promoting cytokines. While BHC80-2 does not induce neuroendocrine differentiation of cancer cells, it stimulates cell proliferation and tumor progression independent of androgen receptor signaling. Blockade of BHC80-2-regulated MyD88 signaling suppresses growth of several t-NEPC cell spheroid and xenograft models., Conclusions: Gain of function of BHC80-2 through alternative RNA splicing activates immune responses of cancer cells to promote t-NEPC development., Patient Summary: The main obstacle to develop effective therapies for patients with t-NEPC is the lack of understanding on how t-NEPC is developed. Our study not only identifies a previously unknown BHC80-2-MyD88 signaling pathway that plays an important role during t-NEPC development, but also provides a proof of principle that targeting this signal pathway may offer an avenue to treat t-NEPC., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: The identification of patients with high-risk prostate cancer (PC) is a major challenge for clinicians, and the improvement of current prognostic parameters is an unmet clinical need. We and others have identified an association between the nuclear localization of NF-κB p65 and biochemical recurrence (BCR) in PC in small and/or single-centre cohorts of patients., Methods and Findings: In this study, we accessed 2 different multi-centre tissue microarrays (TMAs) representing cohorts of patients (Test-TMA and Validation-TMA series) of the Canadian Prostate Cancer Biomarker Network (CPCBN) to validate the association between p65 nuclear frequency and PC outcomes. Immunohistochemical staining of p65 was performed on the Test-TMA and Validation-TMA series, which include PC tissues from patients treated by first-line radical prostatectomy (n = 250 and n = 1,262, respectively). Two independent observers evaluated the p65 nuclear frequency in digital images of cancer tissue and benign adjacent gland tissue. Kaplan-Meier curves coupled with a log-rank test and univariate and multivariate Cox regression models were used for statistical analyses of continuous values and dichotomized data (cutoff of 3%). Multivariate analysis of the Validation-TMA cohort showed that p65 nuclear frequency in cancer cells was an independent predictor of BCR using continuous (hazard ratio [HR] 1.02 [95% CI 1.00-1.03], p = 0.004) and dichotomized data (HR 1.33 [95% CI 1.09-1.62], p = 0.005). Using a cutoff of 3%, we found that this biomarker was also associated with the development of bone metastases (HR 1.82 [95% CI 1.05-3.16], p = 0.033) and PC-specific mortality (HR 2.63 [95% CI 1.30-5.31], p = 0.004), independent of clinical parameters. BCR-free survival, bone-metastasis-free survival, and PC-specific survival were shorter for patients with higher p65 nuclear frequency (p < 0.005). As the small cores on TMAs are a limitation of the study, a backward validation of whole PC tissue section will be necessary for the implementation of p65 nuclear frequency as a PC biomarker in the clinical workflow., Conclusions: We report the first study using the pan-Canadian multi-centre cohorts of CPCBN and validate the association between increased frequency of nuclear p65 frequency and a risk of disease progression., Competing Interests: The authors have declared that no competing interests exist.

Background: Several systemic therapeutic options exist for metastatic castrate-sensitive prostate cancer (mCSPC). Circulating tumor DNA (ctDNA) can molecularly profile metastatic castration-resistant prostate cancer and can influence decision-making, but remains untested in mCSPC., Objective: To determine ctDNA abundance at de novo mCSPC diagnosis and whether ctDNA provides complementary clinically relevant information to a prostate biopsy., Design, Setting, and Participants: We collected plasma cell-free DNA (cfDNA) from 53 patients newly diagnosed with mCSPC and, where possible, during treatment. Targeted sequencing was performed on cfDNA and DNA from diagnostic prostate tissue., Results and Limitations: The median ctDNA fraction was 11% (range 0-84%) among untreated patients but was lower (1.0%, range 0-51%) among patients after short-term (median 22d) androgen deprivation therapy (ADT). TP53 mutations and DNA repair defects were identified in 47% and 21% of the cohort, respectively. The concordance for mutation detection in matched samples was 80%. Combined ctDNA and tissue analysis identified potential driver alterations in 94% of patients, whereas ctDNA or prostate biopsy alone was insufficient in 19 cases (36%). Limitations include the use of a narrow gene panel and undersampling of primary disease by prostate biopsy., Conclusions: ctDNA provides additional information to a prostate biopsy in men with de novo mCSPC, but ADT rapidly reduces ctDNA availability. Primary tissue and ctDNA share relevant somatic alterations, suggesting that either is suitable for molecular subtyping in de novo mCSPC. The optimal approach for biomarker development should utilize both a tissue and liquid biopsy at diagnosis, as neither captures clinically relevant somatic alterations in all patients., Patient Summary: In men with advanced prostate cancer, tumor DNA shed into the bloodstream can be measured via a blood test. The information from this test provides complementary information to a prostate needle biopsy and could be used to guide management strategies. Sequencing data were deposited in the European Genome-phenome Archive (EGA) under study identifier EGAS00001003351., (Copyright © 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

Importance: Proper evaluation of the performance of artificial intelligence techniques in the analysis of digitized medical images is paramount for the adoption of such techniques by the medical community and regulatory agencies., Objectives: To compare several cross-validation (CV) approaches to evaluate the performance of a classifier for automatic grading of prostate cancer in digitized histopathologic images and compare the performance of the classifier when trained using data from 1 expert and multiple experts., Design, Setting, and Participants: This quality improvement study used tissue microarray data (333 cores) from 231 patients who underwent radical prostatectomy at the Vancouver General Hospital between June 27, 1997, and June 7, 2011. Digitized images of tissue cores were annotated by 6 pathologists for 4 classes (benign and Gleason grades 3, 4, and 5) between December 12, 2016, and October 5, 2017. Patches of 192 µm2 were extracted from these images. There was no overlap between patches. A deep learning classifier based on convolutional neural networks was trained to predict a class label from among the 4 classes (benign and Gleason grades 3, 4, and 5) for each image patch. The classification performance was evaluated in leave-patches-out CV, leave-cores-out CV, and leave-patients-out 20-fold CV. The analysis was performed between November 15, 2018, and January 1, 2019., Main Outcomes and Measures: The classifier performance was evaluated by its accuracy, sensitivity, and specificity in detection of cancer (benign vs cancer) and in low-grade vs high-grade differentiation (Gleason grade 3 vs grades 4-5). The statistical significance analysis was performed using the McNemar test. The agreement level between pathologists and the classifier was quantified using a quadratic-weighted κ statistic., Results: On 333 tissue microarray cores from 231 participants with prostate cancer (mean [SD] age, 63.2 [6.3] years), 20-fold leave-patches-out CV resulted in mean (SD) accuracy of 97.8% (1.2%), sensitivity of 98.5% (1.0%), and specificity of 97.5% (1.2%) for classifying benign patches vs cancerous patches. By contrast, 20-fold leave-patients-out CV resulted in mean (SD) accuracy of 85.8% (4.3%), sensitivity of 86.3% (4.1%), and specificity of 85.5% (7.2%). Similarly, 20-fold leave-cores-out CV resulted in mean (SD) accuracy of 86.7% (3.7%), sensitivity of 87.2% (4.0%), and specificity of 87.7% (5.5%). Results of McNemar tests showed that the leave-patches-out CV accuracy, sensitivity, and specificity were significantly higher than those for both leave-patients-out CV and leave-cores-out CV. Similar results were observed for classifying low-grade cancer vs high-grade cancer. When trained on a single expert, the overall agreement in grading between pathologists and the classifier ranged from 0.38 to 0.58; when trained using the majority vote among all experts, it was 0.60., Conclusions and Relevance: Results of this study suggest that in prostate cancer classification from histopathologic images, patch-wise CV and single-expert training and evaluation may lead to a biased estimation of classifier's performance. To allow reproducibility and facilitate comparison between automatic classification methods, studies in the field should evaluate their performance using patient-based CV and multiexpert data. Some of these conclusions may be generalizable to other histopathologic applications and to other applications of machine learning in medicine.

Luminal water imaging (LWI) is a new MRI T 2 mapping technique that has been developed with the aim of diagnosis of prostate carcinoma (PCa). This technique measures the fractional amount of luminal water in prostate tissue, and has shown promising preliminary results in detection of PCa. To include LWI in clinical settings, further investigation on the accuracy of this technique is required. In this study, we compare the diagnostic accuracy of LWI with those of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI in detection and grading of PCa. Fifteen patients with biopsy-proven PCa consented to participate in this ethics-board-approved prospective study. Patients were examined with LWI, DWI, and DCE sequences at 3 T prior to radical prostatectomy. Maps of MRI parameters were generated and registered to whole-mount histology. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of individual and combined MR parameters. Correlation with Gleason score (GS) was evaluated using Spearman's rank correlation test. The results show that area under the ROC curve (AUC) obtained from LWI was equal to or higher than the AUC obtained from DWI, DCE, or their combination, in peripheral zone (0.98 versus 0.90, 0.89, and 0.91 respectively), transition zone (0.99 versus 0.98, n/a, and 0.98), and the entire prostate (0.85 versus 0.81, 0.75, and 0.84). The strongest correlation with GS was achieved from LWI (ρ = -0.81 ± 0.09, P < 0.001). Results of this pilot study show that LWI performs equally well as, or better than, DWI and DCE in detection of PCa. LWI provides significantly higher correlation with GS than DWI and DCE. This technique can potentially be included in clinical MRI protocols to improve characterization of tumors. However, considering the small size of the patient population in this study, a further study with a larger cohort of patients and broader range of GS is required to confirm the findings and draw a firm conclusion on the applicability of LWI in clinical settings., (© 2018 John Wiley & Sons, Ltd.)

Activation of endoplasmic reticulum (ER) stress/the unfolded protein response (UPR) has been linked to cancer, but the molecular mechanisms are poorly understood and there is a paucity of reagents to translate this for cancer therapy. Here, we report that an IRE1α RNase-specific inhibitor, MKC8866, strongly inhibits prostate cancer (PCa) tumor growth as monotherapy in multiple preclinical models in mice and shows synergistic antitumor effects with current PCa drugs. Interestingly, global transcriptomic analysis reveal that IRE1α-XBP1s pathway activity is required for c-MYC signaling, one of the most highly activated oncogenic pathways in PCa. XBP1s is necessary for optimal c-MYC mRNA and protein expression, establishing, for the first time, a direct link between UPR and oncogene activation. In addition, an XBP1-specific gene expression signature is strongly associated with PCa prognosis. Our data establish IRE1α-XBP1s signaling as a central pathway in PCa and indicate that its targeting may offer novel treatment strategies.

Neuroendocrine prostate cancer (NEPC), a lethal form of the disease, is characterized by loss of androgen receptor (AR) signaling during neuroendocrine transdifferentiation, which results in resistance to AR-targeted therapy. Clinically, genomically and epigenetically, NEPC resembles other types of poorly differentiated neuroendocrine tumors (NETs). Through pan-NET analyses, we identified ONECUT2 as a candidate master transcriptional regulator of poorly differentiated NETs. ONECUT2 ectopic expression in prostate adenocarcinoma synergizes with hypoxia to suppress androgen signaling and induce neuroendocrine plasticity. ONEUCT2 drives tumor aggressiveness in NEPC, partially through regulating hypoxia signaling and tumor hypoxia. Specifically, ONECUT2 activates SMAD3, which regulates hypoxia signaling through modulating HIF1α chromatin-binding, leading NEPC to exhibit higher degrees of hypoxia compared to prostate adenocarcinomas. Treatment with hypoxia-activated prodrug TH-302 potently reduces NEPC tumor growth. Collectively, these results highlight the synergy between ONECUT2 and hypoxia in driving NEPC, and emphasize the potential of hypoxia-directed therapy for NEPC patients.

Purpose: Targeted therapies that use the signaling pathways involved in prostate cancer are required to overcome chemoresistance and improve treatment outcomes for men. Molecular chaperones play a key role in the regulation of protein homeostasis and are potential targets for overcoming chemoresistance. Experimental Design: We established 4 chemoresistant prostate cancer cell lines and used image-based high-content siRNA functional screening, based on gene-expression signature, to explore mechanisms of chemoresistance and identify new potential targets with potential roles in taxane resistance. The functional role of a new target was assessed by in vitro and in vivo silencing, and mass spectrometry analysis was used to identify its downstream effectors., Results: We identified FKBP7, a prolyl-peptidyl isomerase overexpressed in docetaxel-resistant and in cabazitaxel-resistant prostate cancer cells. This is the first study to characterize the function of human FKBP7 and explore its role in cancer. We discovered that FKBP7 was upregulated in human prostate cancers and its expression correlated with the recurrence observed in patients receiving docetaxel. FKBP7 silencing showed that FKBP7 is required to maintain the growth of chemoresistant cell lines and chemoresistant tumors in mice. Mass spectrometry analysis revealed that FKBP7 interacts with eIF4G, a component of the eIF4F translation initiation complex, to mediate the survival of chemoresistant cells. Using small-molecule inhibitors of eIF4A, the RNA helicase component of eIF4F, we were able to kill docetaxel- and cabazitaxel-resistant cells., Conclusions: Targeting FKBP7 or the eIF4G-containing eIF4F translation initiation complex could be novel therapeutic strategies to eradicate taxane-resistant prostate cancer cells., (©2018 American Association for Cancer Research.)

Circulating insulin-like growth factor-1 (IGF-1) is consistently associated with prostate cancer risk. IGF-1 binds to IGF-1 receptor (IGF1R) and insulin receptor (IR), activating cancer hallmark pathways. Experimental evidence suggests that TMPRSS2:ERG may interact with IGF/insulin signaling to influence progression. We investigated IGF1R and IR expression and its association with lethal prostate cancer among 769 men. Protein expression of IGF1R, IR and ERG (i.e. a surrogate of ERG fusion genes) were assayed by immunohistochemistry. Cox models estimated hazard ratios (HR) and 95% confidence intervals (CI) adjusted for clinical characteristics. Among patients, 29% had strong tumor IGF1R expression and 10% had strong IR expression. During a mean follow-up of 13.2 years through 2012, 80 men (11%) developed lethal disease. Tumors with strong IGF1R or IR expression showed increased cell proliferation, decreased apoptosis and a higher prevalence of ERG. In multivariable models, strong IGF1R was associated with a borderline increased risk of lethal prostate cancer (HR 1.7; 95% CI 0.9-3.1). The association appeared greater in ERG-positive tumors (HR 2.8; 95% CI 0.9-8.4) than in ERG-negative tumors (HR 1.3; 95% CI 0.6-3.0, p-heterogeneity 0.08). There was no association between IR and lethal prostate cancer (HR 0.8; 95% CI 0.4-1.9). These results suggest that tumor IGF1R expression may play a role in prostate cancer progression to a lethal phenotype and that ERG-positive tumors may be more sensitive to IGF signaling. These data may improve our understanding of IGF signaling in prostate cancer and suggest therapeutic options for disease subtypes.

Prostate cancer (PCa) is a heterogeneous disease that is manifested in a diverse range of histologic patterns and its grading is therefore associated with an inter-observer variability among pathologists, which may lead to an under- or over-treatment of patients. In this work, we develop a computer aided diagnosis system for automatic grading of PCa in digitized histopathology images using supervised learning methods. Our pipeline comprises extraction of multi-scale features that include glandular, cellular, and image-based features. A number of novel features are proposed based on intra- and inter-nuclei properties; these features are shown to be among the most important ones for classification. We train our classifiers on 333 tissue microarray (TMA) cores that were sampled from 231 radical prostatectomy patients and annotated in detail by six pathologists for different Gleason grades. We also demonstrate the TMA-trained classifier's performance on additional 230 whole-mount slides of 56 patients, independent of the training dataset, by examining the automatic grading on manually marked lesions and randomly sampled 10% of the benign tissue. For the first time, we incorporate a probabilistic approach for supervised learning by multiple experts to account for the inter-observer grading variability. Through cross-validation experiments, the overall grading agreement of the classifier with the pathologists was found to be an unweighted kappa of 0.51, while the overall agreements between each pathologist and the others ranged from 0.45 to 0.62. These results suggest that our classifier's performance is within the inter-observer grading variability levels across the pathologists in our study, which are also consistent with those reported in the literature., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Small-cell prostate carcinoma (SCPC) is an aggressive malignancy that is managed similarly to small-cell lung cancer. SCPC can evolve from prostate adenocarcinoma in response to androgen deprivation therapy, but, in rare cases, is present at initial cancer diagnosis. The molecular aetiology of de novo SCPC is incompletely understood, owing to the scarcity of tumour tissue and the short life-expectancy of patients. Through a retrospective search of our regional oncology pharmacy database, we identified 18 patients diagnosed with de novo SCPC between 2004 and 2017. Ten patients had pure SCPC pathology, and the remainder had some admixed adenocarcinoma foci, but all were treated with first-line platinum-based chemotherapy. The median overall survival was 28 months. We performed targeted DNA sequencing, whole exome sequencing and mRNA profiling on formalin-fixed paraffin-embedded archival tumour tissue. We observed frequent biallelic deletion and/or mutation of the tumour suppressor genes TP53, RB1, and PTEN, similarly to what was found in treatment-related SCPC. Indeed, at the RNA level, pure de novo SCPC closely resembled treatment-related SCPC. However, five patients had biallelic loss of DNA repair genes, including BRCA1, BRCA2, ATM, and MSH2/6, potentially underlying the high genomic instability of this rare disease variant. Two patients with pure de novo SCPC harboured ETS gene rearrangements involving androgen-driven promoters, consistent with the evolution of de novo SCPC from an androgen-driven ancestor. Overall, our results reveal a highly aggressive molecular landscape that underlies this unusual pathological variant, and suggest opportunities for targeted therapy strategies in a disease with few treatment options. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd., (Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.)

Background: Refinement of parameters defining prostate cancer (PC) prognosis are urgently needed to identify patients with indolent versus aggressive disease. The Canadian Prostate Cancer Biomaker Network (CPCBN) consists of researchers from four Canadian provinces to create a validation cohort to address issues dealing with PC diagnosis and management., Methods: A total of 1512 radical prostatectomy (RP) specimens from five different biorepositories affiliated with teaching hospitals were selected to constitute the cohort. Tumoral and adjacent benign tissues were arrayed on tissue microarrays (TMAs). A patient clinical database was developed and includes data on diagnosis, treatment and clinical outcome., Results: Mean age at diagnosis of patients in the cohort was 61 years. Of these patients, 31% had a low grade (≤6) Gleason score (GS), 55% had GS 7 (40% of 3 + 4 and 15% of 4 + 3) and 14% had high GS (≥8) PC. The median follow-up of the cohort was 113 months. A total of 34% had a biochemical relapse, 4% developed bone metastasis and 3% of patients died from PC while 9% died of other causes. Pathological review of the TMAs confirmed the presence of tumor and benign tissue cores for > 94% of patients. Immunohistochemistry and FISH analyses, performed on a small set of specimens, showed high quality results and no biorepository-specific bias., Conclusions: The CPCBN RP cohort is representative of real world PC disease observed in the Canadian population. The frequency of biochemical relapse and bone metastasis as events allows for a precise assessment of the prognostic value of biomarkers. This resource is available, in a step-wise manner, for researchers who intend to validate prognostic biomarkers in PC. Combining multiple biomarkers with clinical and pathologic parameters that are predictive of outcome will aid in clinical decision-making for patients treated for PC.

Prostate cancer is the second leading cause of cancer-related deaths in men in North America and there is an urgent need for development of more effective therapeutic treatments against this disease. We have recently shown that diindolylmethane (DIM) and several of its halogenated derivatives (ring-DIMs) induce death and protective autophagy in human prostate cancer cells. However, the in vivo efficacy of ring-DIMs and the use of autophagy inhibitors as adjuvant therapy have not yet been studied in vivo. The objective of this study was to determine these effects on tumor growth in nude CD-1 mice bearing bioluminescent androgen-independent PC-3 human prostate cancer cells. We found that chloroquine (CQ) significantly sensitized PC-3 cells to death in the presence of sub-toxic concentrations of DIM or 4,4'-Br 2 DIM in vitro. Moreover, a combination of DIM (10 mg/kg) and CQ (60 mg/kg), 3× per week, significantly decreased PC-3 tumor growth in vivo after 3 and 4 weeks of treatment. Furthermore, 4,4'-Br 2 DIM at 10 mg/kg (3× per week) significantly inhibited tumour growth after 4 weeks of treatment. Tissues microarray analysis showed that DIM alone or combined with CQ induced apoptosis marker TUNEL; the combination also significantly inhibited the cell proliferation marker Ki67. In conclusion, we have confirmed that DIM and 4,4'-Br 2 DIM are effective agents against prostate cancer in vivo and shown that inhibition of autophagy with CQ enhances the anticancer efficacy of DIM. Our results suggest that including selective autophagy inhibitors as adjuvants may improve the efficacy of existing and novel drug therapies against prostate cancer.

Formation of the androgen receptor splicing variant 7 (AR-V7) is one of the major mechanisms by which resistance of prostate cancer to androgen deprivation therapy occurs. The histone demethylase JMJD1A (Jumonji domain containing 1A) functions as a key coactivator for AR by epigenetic regulation of H3K9 methylation marks. Here, we describe a role for JMJD1A in AR-V7 expression. While JMJD1A knockdown had no effect on full-length AR (AR-FL), it reduced AR-V7 levels in prostate cancer cells. Reexpression of AR-V7 in the JMJD1A-knockdown cells elevated expression of select AR targets and partially rescued prostate cancer cell growth in vitro and in vivo. The AR-V7 protein level correlated positively with JMJD1A in a subset of human prostate cancer specimens. Mechanistically, we found that JMJD1A promoted alternative splicing of AR-V7 through heterogeneous nuclear ribonucleoprotein F (HNRNPF), a splicing factor known to regulate exon inclusion. Knockdown of JMJD1A or HNRNPF inhibited splicing of AR-V7, but not AR-FL, in a minigene reporter assay. JMJD1A was found to interact with and promote the recruitment of HNRNPF to a cryptic exon 3b on AR pre-mRNA for the generation of AR-V7. Taken together, the role of JMJD1A in AR-FL coactivation and AR-V7 alternative splicing highlights JMJD1A as a potentially promising target for prostate cancer therapy., Competing Interests: The authors declare no conflict of interest.

Neuroendocrine prostate cancer (NEPC) is a lethal subtype of prostate cancer arising mostly from adenocarcinoma via neuroendocrine transdifferentiation following androgen deprivation therapy. Mechanisms contributing to both NEPC development and its aggressiveness remain elusive. In light of the fact that hyperchromatic nuclei are a distinguishing histopathologic feature of NEPC, we utilized transcriptomic analyses of our patient-derived xenograft (PDX) models, multiple clinical cohorts, and genetically engineered mouse models to identify 36 heterochromatin-related genes that are significantly enriched in NEPC. Longitudinal analysis using our unique, first-in-field PDX model of adenocarcinoma-to-NEPC transdifferentiation revealed that, among those 36 heterochromatin-related genes, heterochromatin protein 1α (HP1α) expression increased early and steadily during NEPC development and remained elevated in the developed NEPC tumor. Its elevated expression was further confirmed in multiple PDX and clinical NEPC samples. HP1α knockdown in the NCI-H660 NEPC cell line inhibited proliferation, ablated colony formation, and induced apoptotic cell death, ultimately leading to tumor growth arrest. Its ectopic expression significantly promoted NE transdifferentiation in adenocarcinoma cells subjected to androgen deprivation treatment. Mechanistically, HP1α reduced expression of androgen receptor and RE1 silencing transcription factor and enriched the repressive trimethylated histone H3 at Lys9 mark on their respective gene promoters. These observations indicate a novel mechanism underlying NEPC development mediated by abnormally expressed heterochromatin genes, with HP1α as an early functional mediator and a potential therapeutic target for NEPC prevention and management. Significance: Heterochromatin proteins play a fundamental role in NEPC, illuminating new therapeutic targets for this aggressive disease. Cancer Res; 78(10); 2691-704. ©2018 AACR ., (©2018 American Association for Cancer Research.)

Darolutamide (ODM-201) is a novel androgen receptor (AR) antagonist with a chemical structure distinctly different from currently approved AR antagonists that targets both wild-type and mutated ligand binding domain variants to inhibit AR nuclear translocation. Here, we evaluate the activity of darolutamide in enzalutamide-resistant castration resistant prostate cancer (CRPC) as well as in AR mutants detected in patients after treatment with enzalutamide, abiraterone, or bicalutamide. Darolutamide significantly inhibited cell growth and AR transcriptional activity in enzalutamide-resistant MR49F cells in vitro, and led to decreased tumor volume and serum prostate-specific antigen levels in vivo, prolonging survival in mice bearing enzalutamide-resistant MR49F xenografts. Moreover, darolutamide inhibited the transcriptional activity of AR mutants identified in the plasma of CRPC patients progressing on traditional therapies. In particular, darolutamide significantly inhibited the transcriptional activity of the F877L, H875Y/T878A, F877L/T878A, and the previously unreported T878G AR mutants, that transform enzalutamide into a partial agonist. In silico cheminformatics computer modeling provided atomic level insights confirming darolutamide antagonist effect in F877L and T878G AR mutants. In conclusion, our results provide a rationale for further clinical evaluation of darolutamide in enzalutamide-resistant CRPC, in particular in combination with circulating tumor DNA assays that detect AR mutants sensitive to darolutamide, in a precision oncology setting., Patient Summary: In this study we evaluated the novel drug darolutamide in preclinical models of prostate cancer. We found that darolutamide delays growth of enzalutamide-resistant prostate cancer, in particular in cells with mutated forms of the androgen receptor after previous treatment. Our data supports further evaluation of darolutamide in clinical trials., (Copyright © 2017. Published by Elsevier B.V.)

This study investigates whether Genomic Organization at Large Scales (which we propose to call GOALS) as quantified via nuclear phenotype characteristics and cell sociology features (describing cell organization within tissue) collected from prostate tissue microarrays (TMAs) can separate biochemical failure from biochemical nonevidence of disease (BNED) after radical prostatectomy (RP). Of the 78 prostate cancer tissue cores collected from patients treated with RP, 16 who developed biochemical relapse (failure group) and 16 who were BNED patients (nonfailure group) were included in the analyses (36 cores from 32 patients). A section from this TMA was stained stoichiometrically for DNA using the Feulgen-Thionin methodology, and scanned with a Pannoramic MIDI scanner. Approximately 110 nuclear phenotypic features, predominately quantifying large scale DNA organization (GOALS), were extracted from each segmented nuclei. In addition, the centers of these segmented nuclei defined a Voronoi tessellation and subsequent architectural analysis. Prostate TMA core classification as biochemical failure or BNED after RP using GOALS features was conducted (a) based on cell type and cell position within the epithelium (all cells, all epithelial cells, epithelial >2 cell layers away from basement membrane) from all cores, and (b) based on epithelial cells more than two cell layers from the basement membrane using a Classifier trained on Gleason 6, 8, 9 (16 cores) only and applied to a Test set consisting of the Gleason 7 cores (20 cores). Successful core classification as biochemical failure or BNED after RP by a linear classifier was 75% using all cells, 83% using all epithelial cells, and 86% using epithelial >2 layers. Overall success of predicted classification by the linear Classifier of (b) was 87.5% using the Training Set and 80% using the Test Set. Overall success of predicted progression using Gleason score alone was 75% for Gleason >7 as failures and 69% for Gleason >6 as failures. © 2017 International Society for Advancement of Cytometry., (© 2017 International Society for Advancement of Cytometry.)

Purpose: The combination of docetaxel chemotherapy and androgen deprivation therapy (ADT) has become a standard treatment for patients with metastatic prostate cancer. The recently accrued phase III CALGB 90203 trial was designed to investigate the clinical effectiveness of this treatment approach earlier in the disease. Specimens from this trial offer a unique opportunity to interrogate the acute molecular response to docetaxel and ADT and identify potential biomarkers. Experimental Design: We evaluated baseline clinical data, needle biopsies, and radical prostatectomy (RP) specimens from 52 (of 788) patients enrolled on CALGB 90203 at one high volume center. Pathology review, tumor and germline-targeted DNA sequencing ( n = 72 genes), and expression profiling using NanoString platform ( n = 163 genes) were performed to explore changes in critical prostate cancer pathways linked to aggression and resistance. Results: Three of 52 patients had only microfocal residual cancer at prostatectomy. The most common alterations included TMPRSS2-ERG fusion ( n = 32), TP53 mutation or deletion ( n = 11), PTEN deletion ( n = 6), FOXA1 ( n = 6), and SPOP ( n = 4) mutation, with no significant enrichment in posttreated specimens. We did not observe AR amplification or mutations. The degree of AR signaling suppression varied among treated tumors and there was upregulation of both AR and AR-V7 expression as well as a subset of neuroendocrine and plasticity genes. Conclusions: These data support the feasibility of targeted and temporal genomic and transcriptome profiling of neoadjuvant-treated prostate cancer with limited formalin-fixed paraffin embedded tissue requirement. Characterization of the heterogeneity of treatment response and molecular outliers that arise posttreatment provides new insight into potential early markers of resistance. Clin Cancer Res; 23(22); 6802-11. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Purpose: To determine the relationship between parameters measured from luminal water imaging (LWI), a new magnetic resonance imaging (MRI) T 2 mapping technique, and the corresponding tissue composition in prostate., Materials and Methods: In all, 17 patients with prostate cancer were examined with a 3D multiecho spin echo sequence at 3T prior to undergoing radical prostatectomy. Maps of seven MR parameters, called N, T 2-short , T 2-long , A short , A long , geometric mean T 2 time (gmT 2 ), and luminal water fraction (LWF), were generated using nonnegative least squares (NNLS) analysis of the T 2 decay curves. MR parametric maps were correlated to digitized whole-mount histology sections. Percentage area of tissue components, including luminal space, nuclei, and cytoplasm plus stroma, was measured on the histology sections by using color-based image segmentation. Spearman's rank correlation test was used to evaluate the correlation between MR parameters and the corresponding tissue components, with particular attention paid to the correlation between LWF and percentage area of luminal space., Results: N, T 2-short , A long , gmT 2 , and LWF showed significant correlation (P < 0.05) with percentage area of luminal space and stroma plus cytoplasm. T 2-short and gmT 2 also showed significant correlation (P < 0.05) with percentage area of nuclei. Overall, the strongest correlation was observed between LWF and luminal space (Spearman's coefficient of rank correlation = 0.75, P < 0.001)., Conclusion: Results of this study show that LWF measured with MRI is strongly correlated with the fractional amount of luminal space in prostatic tissue. This result suggests that LWI can potentially be applied for evaluation of prostatic diseases in which the extent of luminal space differs between normal and abnormal tissues., Level of Evidence: 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:861-869., (© 2017 International Society for Magnetic Resonance in Medicine.)

Recent evidence has implicated the transmembrane co-receptor neuropilin-1 (NRP1) in cancer progression. Primarily known as a regulator of neuronal guidance and angiogenesis, NRP1 is also expressed in multiple human malignancies, where it promotes tumor angiogenesis. However, non-angiogenic roles of NRP1 in tumor progression remain poorly characterized. In this study, we define NRP1 as an androgen-repressed gene whose expression is elevated during the adaptation of prostate tumors to androgen-targeted therapies (ATTs), and subsequent progression to metastatic castration-resistant prostate cancer (mCRPC). Using short hairpin RNA (shRNA)-mediated suppression of NRP1, we demonstrate that NRP1 regulates the mesenchymal phenotype of mCRPC cell models and the invasive and metastatic dissemination of tumor cells in vivo. In patients, immunohistochemical staining of tissue microarrays and mRNA expression analyses revealed a positive association between NRP1 expression and increasing Gleason grade, pathological T score, positive lymph node status and primary therapy failure. Furthermore, multivariate analysis of several large clinical prostate cancer (PCa) cohorts identified NRP1 expression at radical prostatectomy as an independent prognostic biomarker of biochemical recurrence after radiation therapy, metastasis and cancer-specific mortality. This study identifies NRP1 for the first time as a novel androgen-suppressed gene upregulated during the adaptive response of prostate tumors to ATTs and a prognostic biomarker of clinical metastasis and lethal PCa.

Prostate cancer (PCa) is the most common non-cutaneous cancer in men. The androgen receptor (AR), a ligand-activated transcription factor, constitutes the main drug target for advanced cases of the disease. However, a variety of other transcription factors and signaling networks have been shown to be altered in patients and to influence AR activity. Amongst these, the oncogenic transcription factor c-Myc has been studied extensively in multiple malignancies and elevated protein levels of c-Myc are commonly observed in PCa. Its impact on AR activity, however, remains elusive. In this study, we assessed the impact of c-Myc overexpression on AR activity and transcriptional output in a PCa cell line model and validated the antagonistic effect of c-MYC on AR-targets in patient samples. We found that c-Myc overexpression partially reprogrammed AR chromatin occupancy and was associated with altered histone marks distribution, most notably H3K4me1 and H3K27me3. We found c-Myc and the AR co-occupy a substantial number of binding sites and these exhibited enhancer-like characteristics. Interestingly, c-Myc overexpression antagonised clinically relevant AR target genes. Therefore, as an example, we validated the antagonistic relationship between c-Myc and two AR target genes, KLK3 (alias PSA, prostate specific antigen), and Glycine N-Methyltransferase (GNMT), in patient samples. Our findings provide unbiased evidence that MYC overexpression deregulates the AR transcriptional program, which is thought to be a driving force in PCa., (Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.)

Purpose: Androgen deprivation therapy (ADT) commonly leads to incomplete cell death and the fate of persistent cells involves, in part, a senescent phenotype. Senescence is terminal growth arrest in response to cell stress that is characterized by increased lysosomal-β-galactosidase (GLB1) the origin of senescence associated-β-gal activity (SA-β-gal). In the current study senescence is examined in vivo after ADT use in a neoadjuvant trial., Methods and Materials: Tissue microarrays were generated from prostate cancer specimens (n = 126) from a multicenter neoadjuvant ADT trial. Arrays were subjected to multiplexed immunofluorescent staining for GLB1, Ki67, cleaved caspase 3 (CC3) and E-cadherin. Automated quantitative imaging was performed using Vectra™ and expression correlated with clinicopathologic features., Results: Tissue was analyzed from 59 patients treated with neoadjuvant ADT and 67 receiving no therapy preoperatively. Median follow-up was 85.3 mo and median ADT treatment was 5 mo. In PC treated with neoadjuvant ADT, GLB1 expression increased in intermediate Gleason score (GS 6-7; p = 0.001), but not high grade (GS 8-10) cancer. Significantly higher levels of GLB1 were seen in tissues undergoing neoadjuvant ADT longer than 5 months compared to untreated tissues (p = 0.002). In contrast, apoptosis significantly increased earlier (1-4 mo) after ADT treatment (p<0.5)., Conclusions: Increased GLB1 after neoadjuvant ADT occurs primarily among more clinically favorable intermediate grade cancers and enrichment of the phenotype occurs in a temporally prolonged fashion. Senescence may explain the persistence of PCa cells after ADT. Given concerns for the detrimental longer term presence of senescent cells, targeting these cells for removal may improve outcomes.

Mechanisms controlling the emergence of lethal neuroendocrine prostate cancer (NEPC), especially those that are consequences of treatment-induced suppression of the androgen receptor (AR), remain elusive. Using a unique model of AR pathway inhibitor-resistant prostate cancer, we identified AR-dependent control of the neural transcription factor BRN2 (encoded by POU3F2) as a major driver of NEPC and aggressive tumor growth, both in vitro and in vivo Mechanistic studies showed that AR directly suppresses BRN2 transcription, which is required for NEPC, and BRN2-dependent regulation of the NEPC marker SOX2. Underscoring its inverse correlation with classic AR activity in clinical samples, BRN2 expression was highest in NEPC tumors and was significantly increased in castration-resistant prostate cancer compared with adenocarcinoma, especially in patients with low serum PSA. These data reveal a novel mechanism of AR-dependent control of NEPC and suggest that targeting BRN2 is a strategy to treat or prevent neuroendocrine differentiation in prostate tumors., Significance: Understanding the contribution of the AR to the emergence of highly lethal, drug-resistant NEPC is critical for better implementation of current standard-of-care therapies and novel drug design. Our first-in-field data underscore the consequences of potent AR inhibition in prostate tumors, revealing a novel mechanism of AR-dependent control of neuroendocrine differentiation, and uncover BRN2 as a potential therapeutic target to prevent emergence of NEPC. Cancer Discov; 7(1); 54-71. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 1., (©2016 American Association for Cancer Research.)

Background: The uncertainties inherent in clinical measures of prostate cancer (CaP) aggressiveness endorse the investigation of clinically validated tissue biomarkers. MUC1 expression has been previously reported to independently predict aggressive localized prostate cancer. We used a large cohort to validate whether MUC1 protein levels measured by immunohistochemistry (IHC) predict aggressive cancer, recurrence and survival outcomes after radical prostatectomy independent of clinical and pathological parameters., Material and Methods: MUC1 IHC was performed on a multi-institutional tissue microarray (TMA) resource including 1,326 men with a median follow-up of 5 years. Associations with clinical and pathological parameters were tested by the Chi-square test and the Wilcoxon rank sum test. Relationships with outcome were assessed with univariable and multivariable Cox proportional hazard models and the Log-rank test., Results: The presence of MUC1 expression was significantly associated with extracapsular extension and higher Gleason score, but not with seminal vesicle invasion, age, positive surgical margins or pre-operative serum PSA levels. In univariable analyses, positive MUC1 staining was significantly associated with a worse recurrence free survival (RFS) (HR: 1.24, CI 1.03-1.49, P = 0.02), although not with disease specific survival (DSS, P>0.5). On multivariable analyses, the presence of positive surgical margins, extracapsular extension, seminal vesicle invasion, as well as higher pre-operative PSA and increasing Gleason score were independently associated with RFS, while MUC1 expression was not. Positive MUC1 expression was not independently associated with disease specific survival (DSS), but was weakly associated with overall survival (OS)., Conclusion: In our large, rigorously designed validation cohort, MUC1 protein expression was associated with adverse pathological features, although it was not an independent predictor of outcome after radical prostatectomy., Competing Interests: The authors have declared that no competing interests exist.