Prostate Cancer Risk Stratification by Digital Histopathology and Deep Learning.

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.

Deciphering the Transcription Factor Landscape in Neuroendocrine Prostate Cancer Progression: A Novel Approach to Understand NE Transdifferentiation.

Background and Objective: Prostate cancer (PCa) is a leading cause of cancer mortality in men, with neuroendocrine prostate cancer (NEPC) representing a particularly resistant subtype. The role of transcription factors (TFs) in the progression from prostatic adenocarcinoma (PRAD) to NEPC is poorly understood. This study aims to identify and analyze lineage-specific TF profiles in PRAD and NEPC and illustrate their dynamic shifts during NE transdifferentiation. Methods: A novel algorithmic approach was developed to evaluate the weighted expression of TFs within patient samples, enabling a nuanced understanding of TF landscapes in PCa progression and TF dynamic shifts during NE transdifferentiation. Results: unveiled TF profiles for PRAD and NEPC, identifying 126 shared TFs, 46 adenocarcinoma-TFs, and 56 NEPC-TFs. Enrichment analysis across multiple clinical cohorts confirmed the lineage specificity and clinical relevance of these lineage-TFs signatures. Functional analysis revealed that lineage-TFs are implicated in pathways critical to cell development, differentiation, and lineage determination. Novel lineage-TF candidates were identified, offering potential targets for therapeutic intervention. Furthermore, our longitudinal study on NE transdifferentiation highlighted dynamic TF expression shifts and delineated a three-phase hypothesis for the process comprised of de-differentiation, dormancy, and re-differentiation. and proposing novel insights into the mechanisms of PCa progression. Conclusion: The lineage-specific TF profiles in PRAD and NEPC reveal a dynamic shift in the TF landscape during PCa progression, highlighting three distinct phases of NE transdifferentiation.

Multi-scale relational graph convolutional network for multiple instance learning in histopathology images.

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.

Long-Term Outcomes in Patients Using Protocol-Directed Active Surveillance for Prostate Cancer.

Importance: Outcomes from protocol-directed active surveillance for favorable-risk prostate cancers are needed to support decision-making. Objective: To characterize the long-term oncological outcomes of patients receiving active surveillance in a multicenter, protocol-directed cohort. Design, Setting, and Participants: The Canary Prostate Active Surveillance Study (PASS) is a prospective cohort study initiated in 2008. A cohort of 2155 men with favorable-risk prostate cancer and no prior treatment were enrolled at 10 North American centers through August 2022. Exposure: Active surveillance for prostate cancer. Main Outcomes and Measures: Cumulative incidence of biopsy grade reclassification, treatment, metastasis, prostate cancer mortality, overall mortality, and recurrence after treatment in patients treated after the first or subsequent surveillance biopsies. Results: Among 2155 patients with localized prostate cancer, the median follow-up was 7.2 years, median age was 63 years, 83% were White, 7% were Black, 90% were diagnosed with grade group 1 cancer, and median prostate-specific antigen (PSA) was 5.2 ng/mL. Ten years after diagnosis, the incidence of biopsy grade reclassification and treatment were 43% (95% CI, 40%-45%) and 49% (95% CI, 47%-52%), respectively. There were 425 and 396 patients treated after confirmatory or subsequent surveillance biopsies (median of 1.5 and 4.6 years after diagnosis, respectively) and the 5-year rates of recurrence were 11% (95% CI, 7%-15%) and 8% (95% CI, 5%-11%), respectively. Progression to metastatic cancer occurred in 21 participants and there were 3 prostate cancer-related deaths. The estimated rates of metastasis or prostate cancer-specific mortality at 10 years after diagnosis were 1.4% (95% CI, 0.7%-2%) and 0.1% (95% CI, 0%-0.4%), respectively; overall mortality in the same time period was 5.1% (95% CI, 3.8%-6.4%). Conclusions and Relevance: In this study, 10 years after diagnosis, 49% of men remained free of progression or treatment, less than 2% developed metastatic disease, and less than 1% died of their disease. Later progression and treatment during surveillance were not associated with worse outcomes. These results demonstrate active surveillance as an effective management strategy for patients diagnosed with favorable-risk prostate cancer.

Expert Perspectives on Controversies in Castration-Sensitive Prostate Cancer Management: Narrative Review and Report of the First US Prostate Cancer Conference Part 1.

Purpose: Castration-sensitive prostate cancer (CSPC) is a complex and heterogeneous condition encompassing a range of clinical presentations. As new approaches have expanded management options, clinicians are left with myriad questions and controversies regarding the optimal individualized management of CSPC. Materials and Methods: The US Prostate Cancer Conference (USPCC) multidisciplinary panel was assembled to address the challenges of prostate cancer management. The first annual USPCC meeting included experts in urology, medical oncology, radiation oncology, and nuclear medicine. USPCC co-chairs and session moderators identified key areas of controversy and uncertainty in prostate cancer management and organized the sessions with multidisciplinary presentations and discussion. Throughout the meeting, experts responded to questions prepared by chairs and moderators to identify areas of agreement and controversy. Results: The USPCC panel discussion and question responses for CSPC-related topics are presented. Key advances in CSPC management endorsed by USPCC experts included the development and clinical utilization of gene expression classifiers and artificial intelligence (AI) models for risk stratification and treatment selection in specific patient populations, the use of advanced imaging modalities in patients with clinically localized unfavorable intermediate or high-risk disease and those with biochemical recurrence, recommendations of doublet or triplet therapy for metastatic CSPC (mCSPC), and consideration of prostate and/or metastasis-directed radiation therapy in select patients with mCSPC. Conclusions: CSPC is a diverse disease with many therapeutic options and the potential for adverse outcomes associated with either undertreatment or overtreatment. Future studies are needed to validate and clinically integrate novel technologies, including genomics, AI, and advanced imaging, to optimize outcomes among patients with CSPC.

Expert Perspectives on Controversies in Metastatic Castration-Resistant Prostate Cancer Management: Narrative Review and Report of the First US Prostate Cancer Conference Part 2.

Background: Management strategies for metastatic castration-resistant prostate cancer (mCRPC) have rapidly shifted in recent years. As novel imaging and therapeutic approaches have made their way to the clinic, providers are encountering increasingly challenging clinical scenarios, with limited guidance from the current literature. Materials and Methods: The US Prostate Cancer Conference (USPCC) is a multidisciplinary meeting of prostate cancer experts intended to address the many challenges of prostate cancer management. At the first annual USPCC meeting, areas of controversy and consensus were identified during a 2-day meeting that included expert presentations, full-panel discussions, and postdiscussion responses to questions developed by the USPCC cochairs and session moderators. Results: This narrative review covers the USPCC expert discussion and perspectives relevant to mCRPC, including neuroendocrine/aggressive-variant prostate cancer (NEPC/AVPC). Areas of broad agreement identified among USPCC experts include the benefits of poly (ADP-ribose) polymerase (PARP) inhibitors for patients with BRCA1/2 mutations, the use of radioligand therapy in patients with prostate-specific membrane antigen (PSMA)-positive mCRPC, and the need for clinical trials that address real-world clinical questions, including the performance of novel therapies when compared with modern standard-of-care treatment. Ongoing areas of controversy and uncertainty included the appropriateness of PARP inhibitors in patients with non-BRCA1/2 mutations, the optimal definition of PSMA positivity, and systemic therapies for patients with NEPC/AVPC after progression on platinum-based therapies. Conclusions: The first annual USPCC meeting identified several areas of controversy in the management of mCRPC, highlighting the urgent need for clinical trials designed to facilitate treatment selection and sequencing in this heterogeneous disease state.

Long-Term Second Malignancies in Prostate Cancer Patients Treated With Low-Dose-Rate Brachytherapy and Radical Prostatectomy.

PURPOSE: Second malignancy is a rare but potentially lethal event after prostate brachytherapy, but data remain scarce on its long-term risk. The objective of this study is to estimate the number of pelvic second malignancies following brachytherapy compared to radical prostatectomy (RP). MATERIALS AND METHODS: We retrospectively reviewed patients treated with low-dose 125I brachytherapy and RP in British Columbia from 1999 to 2010. Kaplan-Meier estimates for pelvic (bladder and rectum), invasive pelvic, any second malignancy, and death from any second malignancy were assessed. Cox multivariable analyses were performed adjusting for initial treatment type, age, post-RP adjuvant/salvage external beam radiation therapy status, and smoking history. RESULTS: Two thousand three hundred seventy-eight brachytherapy and 9089 RP patients were included. Median age was 66 years (interquartile range [IQR] 61-71) and 63 years (IQR 58-67), respectively. Median follow-up time to event or censured was 14 years (IQR 11.5-17.3). The Kaplan-Meier estimates for pelvic second malignancy at 15 and 20 years were 6.4% and 9.8%, respectively, after brachytherapy, and 3.2% and 4.2% after RP. Time to any second malignancy and time to death from any second malignancy were not significantly different (P > .05). On Cox multivariable analysis, brachytherapy, compared to surgery, was an independent factor for pelvic (hazard ratio [HR] 1.81 [95% CI 1.45-2.26], P < .001) and invasive pelvic second malignancy (HR 2.13 [95% CI 1.61-2.83], P < .001). Increased age and smoking were also associated with higher estimates of events (P < .001). CONCLUSIONS: After adjustment for age, post-RP adjuvant/salvage external beam radiation therapy status, and smoking status, numerically higher long-term HRs of pelvic and invasive pelvic second malignancy in patients treated with brachytherapy compared to RP were noted.

Clinically-observed FOXA1 mutations upregulate SEMA3C through transcriptional derepression in prostate cancer.

FOXA1 is a pioneer transcription factor that is frequently mutated in prostate, breast, bladder, and salivary gland malignancies. Indeed, metastatic castration-resistant prostate cancer (mCRPC) commonly harbour FOXA1 mutations with a prevalence of 35%. However, despite the frequent recurrence of FOXA1 mutations in prostate cancer, the mechanisms by which FOXA1 variants drive its oncogenic effects are still unclear. Semaphorin 3C (SEMA3C) is a secreted autocrine growth factor that drives growth and treatment resistance of prostate and other cancers and is known to be regulated by both AR and FOXA1. In the present study, we characterize FOXA1 alterations with respect to its regulation of SEMA3C. Our findings reveal that FOXA1 alterations lead to elevated levels of SEMA3C both in prostate cancer specimens and in vitro. We further show that FOXA1 negatively regulates SEMA3C via intronic cis elements, and that mutations in FOXA1 forkhead domain attenuate its inhibitory function in reporter assays, presumably by disrupting DNA binding of FOXA1. Our findings underscore the key role of FOXA1 in prostate cancer progression and treatment resistance by regulating SEMA3C expression and suggest that SEMA3C may be a driver of growth and tumor vulnerability of mCRPC harboring FOXA1 alterations.

A novel type-2 innate lymphoid cell-based immunotherapy for cancer.

Cell-based cancer immunotherapy has achieved significant advancements, providing a source of hope for cancer patients. Notwithstanding the considerable progress in cell-based immunotherapy, the persistently low response rates and the exorbitant costs associated with their implementation still present a formidable challenge in clinical settings. In the landscape of cell-based cancer immunotherapies, an uncharted territory involves Type 2 innate lymphoid cells (ILC2s) and interleukin-33 (IL-33) which promotes ILC2 functionality, recognized for their inherent ability to enhance immune responses. Recent discoveries regarding their role in actuating cytolytic T lymphocyte responses, including curbing tumor growth rates and hindering metastasis, have added a new dimension to our understanding of the IL-33/ILC2 axis. These recent insights may hold significant promise for ILC2 cell-based immunotherapy. Nevertheless, the prospect of adoptively transferring ILC2s to confer immune protection against tumors has yet to be investigated. The present study addresses this hypothesis, revealing that ILC2s isolated from the lungs of tumor-bearing mice, and tumor infiltrating ILC2s when adoptively transferred after tumor establishment at a ratio of one ILC2 per sixty tumor cells, leads to an influx of tumor infiltrating CD4+ and CD8+ T lymphocytes as well as tumor infiltrating eosinophils resulting in a remarkable reduction in tumor growth. Moreover, we find that post-adoptive transfer of ILC2s, the number of tumor infiltrating ILC2s is inversely proportional to tumor size. Finally, we find corollaries of the IL-33/ILC2 axis enhancing the infiltration of eosinophils in human prostate carcinomas patients' expressing high levels of IL-33 versus those expressing low levels of IL-33. Our results underscore the heightened efficacy of adoptively transferred ILC2s compared to alternative approaches, revealing an approximately one hundred fifty-fold superiority on a cell-per-cell basis over CAR T-cells in the specific targeting and elimination of tumors within the same experimental model. Overall, this study demonstrates the functional significance of ILC2s in cancer immunosurveillance and provides the proof of concept of the potential utility of ILC2 cell-based cancer immunotherapies.

High expression of Trop2 is associated with aggressive localized prostate cancer and is a candidate urinary biomarker.

Distinguishing indolent from clinically significant localized prostate cancer is a major clinical challenge and influences clinical decision-making between treatment and active surveillance. The development of novel predictive biomarkers will help with risk stratification, and clinical decision-making, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2 is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study. We demonstrate that elevated Trop2 expression is correlated with worse clinical features including Gleason score, age, and pre-operative PSA levels. More importantly, we demonstrate that elevated Trop2 expression at radical prostatectomy predicts worse overall survival in men undergoing radical prostatectomy. Additionally, we detect shed Trop2 in urine from men with clinically significant prostate cancer. Our study identifies Trop2 as a novel tissue prognostic biomarker and a candidate non-invasive marker for prostate cancer.

DPYSL5 is highly expressed in treatment-induced neuroendocrine prostate cancer and promotes lineage plasticity via EZH2/PRC2.

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.

Molecular features of prostate cancer after neoadjuvant therapy in the phase 3 CALGB 90203 trial.

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.

RNF185 Control of COL3A1 Expression Limits Prostate Cancer Migration and Metastatic Potential.

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.

Semaphorin 3C promotes de novo steroidogenesis in prostate cancer cells.

Intratumoral androgen biosynthesis contributes to castration-resistant prostate cancer progression in patients treated with androgen deprivation therapy. The molecular mechanisms by which castration-resistant prostate cancer acquires the capacity for androgen biosynthesis to bypass androgen deprivation therapy are not entirely known. Here, we show that semaphorin 3C, a secreted signaling protein that is highly expressed in castration-resistant prostate cancer, can promote steroidogenesis by altering the expression profile of key steroidogenic enzymes. Semaphorin 3C not only upregulates enzymes required for androgen synthesis from dehydroepiandrosterone or de novo from cholesterol but also simultaneously downregulates enzymes involved in the androgen inactivation pathway. These changes in gene expression correlate with increased production of androgens induced by semaphorin 3C in prostate cancer model cells. Moreover, semaphorin 3C upregulates androgen synthesis in LNCaP cell-derived xenograft tumors, likely contributing to the enhanced in vivo tumor growth rate post castration. Furthermore, semaphorin 3C activates sterol regulatory element-binding protein, a transcription factor that upregulates enzymes involved in the synthesis of cholesterol, a sole precursor for de novo steroidogenesis. The ability of semaphorin 3C to promote intratumoral androgen synthesis may be a key mechanism contributing to the reactivation of the androgen receptor pathway in castration-resistant prostate cancer, conferring continued growth under androgen deprivation therapy. These findings identify semaphorin 3C as a potential therapeutic target for suppressing intratumoral steroidogenesis.

Improved Outcomes with Enzalutamide in Biochemically Recurrent Prostate Cancer.

BACKGROUND: Patients with prostate cancer who have high-risk biochemical recurrence have an increased risk of progression. The efficacy and safety of enzalutamide plus androgen-deprivation therapy and enzalutamide monotherapy, as compared with androgen-deprivation therapy alone, are unknown. METHODS: In this phase 3 trial, we enrolled patients with prostate cancer who had high-risk biochemical recurrence with a prostate-specific antigen doubling time of 9 months or less. Patients were randomly assigned, in a 1:1:1 ratio, to receive enzalutamide (160 mg) daily plus leuprolide every 12 weeks (combination group), placebo plus leuprolide (leuprolide-alone group), or enzalutamide monotherapy (monotherapy group). The primary end point was metastasis-free survival, as assessed by blinded independent central review, in the combination group as compared with the leuprolide-alone group. A key secondary end point was metastasis-free survival in the monotherapy group as compared with the leuprolide-alone group. Other secondary end points were patient-reported outcomes and safety. RESULTS: A total of 1068 patients underwent randomization: 355 were assigned to the combination group, 358 to the leuprolide-alone group, and 355 to the monotherapy group. The patients were followed for a median of 60.7 months. At 5 years, metastasis-free survival was 87.3% (95% confidence interval [CI], 83.0 to 90.6) in the combination group, 71.4% (95% CI, 65.7 to 76.3) in the leuprolide-alone group, and 80.0% (95% CI, 75.0 to 84.1) in the monotherapy group. With respect to metastasis-free survival, enzalutamide plus leuprolide was superior to leuprolide alone (hazard ratio for metastasis or death, 0.42; 95% CI, 0.30 to 0.61; P<0.001); enzalutamide monotherapy was also superior to leuprolide alone (hazard ratio for metastasis or death, 0.63; 95% CI, 0.46 to 0.87; P = 0.005). No new safety signals were observed, with no substantial between-group differences in quality-of-life measures. CONCLUSIONS: In patients with prostate cancer with high-risk biochemical recurrence, enzalutamide plus leuprolide was superior to leuprolide alone with respect to metastasis-free survival; enzalutamide monotherapy was also superior to leuprolide alone. The safety profile of enzalutamide was consistent with that shown in previous clinical studies, with no apparent detrimental effect on quality of life. (Funded by Pfizer and Astellas Pharma; EMBARK ClinicalTrials.gov number, NCT02319837.).

RNF185 control of COL3A1 expression limits prostate cancer migration and metastatic potential.

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 shRNA 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, compared to 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 EMT. Among those, COL3A1 was identified as the primary mediator of RNF185's ability to impact migration phenotypes. Correspondingly, enhanced migration and metastasis of RNF185 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.

Influence of ADT on B7-H3 expression during CRPC progression from hormone-naïve prostate cancer.

Androgen deprivation therapy (ADT) is the standard care for advanced prostate cancer (PCa) patients. Unfortunately, although tumors respond well initially, they enter dormancy and eventually progress to fatal/incurable castration-resistant prostate cancer (CRPC). B7-H3 is a promising new target for PCa immunotherapy. CD276 (B7-H3) gene has a presumptive androgen receptor (AR) binding site, suggesting potential AR regulation. However, the relationship between B7-H3 and AR is controversial. Meanwhile, the expression pattern of B7-H3 following ADT and during CRPC progression is largely unknown, but critically important for identifying patients and determining the optimal timing of B7-H3 targeting immunotherapy. In this study, we performed a longitudinal study using our unique PCa patient-derived xenograft (PDX) models and assessed B7-H3 expression during post-ADT disease progression. We further validated our findings at the clinical level in PCa patient samples. We found that B7-H3 expression was negatively regulated by AR during the early phase of ADT treatment, but positively associated with PCa proliferation during the remainder of disease progression. Our findings suggest its use as a biomarker for diagnosis, prognosis, and ADT treatment response, and the potential of combining ADT and B7-H3 targeting immunotherapy for hormone-naïve PCa treatment to prevent fatal CRPC relapse.

Dependency of Tamoxifen Sensitive and Resistant ER+ Breast Cancer Cells on Semaphorin 3C (SEMA3C) for Growth.

Estrogen receptor positive (ER+) breast cancer (BCa) accounts for the highest proportion of breast cancer-related deaths. While endocrine therapy is highly effective for this subpopulation, endocrine resistance remains a major challenge and the identification of novel targets is urgently needed. Previously, we have shown that Semaphorin 3C (SEMA3C) is an autocrine growth factor that drives the growth and treatment resistance of various cancers, but its role in breast cancer progression and endocrine resistance is poorly understood. Here, we report that SEMA3C plays a role in maintaining the growth of ER+ BCa cells and is a novel, tractable therapeutic target for the treatment of ER+ BCa patients. Analyses of publicly available clinical datasets indicate that ER+ BCa patients express significantly higher levels of SEMA3C mRNA than other subtypes. Furthermore, SEMA3C mRNA expression was positively correlated with ESR1 mRNA expression. ER+ BCa cell lines (MCF7 and T47D) expressed higher levels of SEMA3C mRNA and protein than a normal mammary epithelial MCF10A cell line. ER siRNA knockdown was suppressed, while dose-dependent beta-estradiol treatment induced SEMA3C expression in both MCF7 and T47D cells, suggesting that SEMA3C is an ER-regulated gene. The stimulation of ER+ BCa cells with recombinant SEMA3C activated MAPK and AKT signaling in a dose-dependent manner. Conversely, SEMA3C silencing inhibited Estrogen Receptor (ER) expression, MAPK and AKT signaling pathways while simultaneously inducing apoptosis, as monitored by flow cytometry and Western blot analyses. SEMA3C silencing significantly inhibited the growth of ER+ BCa cells, implicating a growth dependency of ER+ BCa cells on SEMA3C. Moreover, the analysis of tamoxifen resistant (TamR) cell models (TamC3 and TamR3) showed that SEMA3C levels remain high despite treatment with tamoxifen. Tamoxifen-resistant cells remained dependent on SEMA3C for growth and survival. Treatment with B1SP Fc fusion protein, a SEMA3C pathway inhibitor, attenuated SEMA3C-induced signaling and growth across a panel of tamoxifen sensitive and resistant ER+ breast cancer cells. Furthermore, SEMA3C silencing and B1SP treatment were associated with decreased EGFR signaling in TamR cells. Here, our study implicates SEMA3C in a functional role in ER+ breast cancer signaling and growth that suggests ER+ BCa patients may benefit from SEMA3C-targeted therapy.

Artificial Intelligence-Based PTEN Loss Assessment as an Early Predictor of Prostate Cancer Metastasis After Surgery: A Multicenter Retrospective Study.

Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and can be measured via immunohistochemistry. The purpose of the study was to establish the clinical application of an in-house developed artificial intelligence (AI) image analysis workflow for automated detection of PTEN loss on digital images for identifying patients at risk of early recurrence and metastasis. Postsurgical tissue microarray sections from the Canary Foundation (n = 1264) stained with anti-PTEN antibody were evaluated independently by pathologist conventional visual scoring (cPTEN) and an automated AI-based image analysis pipeline (AI-PTEN). The relationship of PTEN evaluation methods with cancer recurrence and metastasis was analyzed using multivariable Cox proportional hazard and decision curve models. Both cPTEN scoring by the pathologist and quantification of PTEN loss by AI (high-risk AI-qPTEN) were significantly associated with shorter metastasis-free survival (MFS) in univariable analysis (cPTEN hazard ratio [HR], 1.54; CI, 1.07-2.21; P = .019; AI-qPTEN HR, 2.55; CI, 1.83-3.56; P < .001). In multivariable analyses, AI-qPTEN showed a statistically significant association with shorter MFS (HR, 2.17; CI, 1.49-3.17; P < .001) and recurrence-free survival (HR, 1.36; CI, 1.06-1.75; P = .016) when adjusting for relevant postsurgical clinical nomogram (Cancer of the Prostate Risk Assessment [CAPRA] postsurgical score [CAPRA-S]), whereas cPTEN does not show a statistically significant association (HR, 1.33; CI, 0.89-2; P = .2 and HR, 1.26; CI, 0.99-1.62; P = .063, respectively) when adjusting for CAPRA-S risk stratification. More importantly, AI-qPTEN was associated with shorter MFS in patients with favorable pathological stage and negative surgical margins (HR, 2.72; CI, 1.46-5.06; P = .002). Workflow also demonstrated enhanced clinical utility in decision curve analysis, more accurately identifying men who might benefit from adjuvant therapy postsurgery. This study demonstrates the clinical value of an affordable and fully automated AI-powered PTEN assessment for evaluating the risk of developing metastasis or disease recurrence after radical prostatectomy. Adding the AI-qPTEN assessment workflow to clinical variables may affect postoperative surveillance or management options, particularly in low-risk patients.