Molecular Subtype Of Prostate Cancer Research Articles

Proteomic landscape profiling of primary prostate cancer reveals a 16-protein panel for prognosis prediction

Prostate cancer (PCa) is the most common malignant tumor in men. Currently, there are few prognosis indicators for predicting PCa outcomes and guiding treatments. Here, we perform comprehensive proteomic profiling of 918 tissue specimens from 306 Chinese patients with PCa using data-independent acquisition mass spectrometry (DIA-MS). We identify over 10,000 proteins and define three molecular subtypes of PCa with significant clinical and proteomic differences. We develop a 16-protein panel that effectively predicts biochemical recurrence (BCR) for patients with PCa, which is validated in six published datasets andone additional 99-biopsy-sample cohort by targeted proteomics. Interestingly, this 16-protein panel effectively predicts BCR across different International Society of Urological Pathology (ISUP) grades and pathological stages and outperforms the D'Amico risk classification system in BCR prediction. Furthermore, double knockout of NUDT5 and SEPTIN8, two components from the 16-protein panel, significantly suppresses the PCa cells to proliferate, invade, and migrate, suggesting the combination of NUDT5 and SEPTIN8 may provide new approaches for PCa treatment.

ProstaMine: a bioinformatics tool for identifying subtype-specific co-alterations associated with aggressiveness in prostate cancer.

Prostate cancer is a leading cause of cancer-related deaths among men, marked by heterogeneous clinical and molecular characteristics. The complexity of the molecular landscape necessitates tools for identifying multi-gene co-alteration patterns that are associated with aggressive disease. The identification of such gene sets will allow for deeper characterization of the processes underlying prostate cancer progression and potentially lead to novel strategies for treatment. We developed ProstaMine to systematically identify co-alterations associated with aggressiveness in prostate cancer molecular subtypes defined by high-fidelity alterations in primary prostate cancer. ProstaMine integrates genomic, transcriptomic, and clinical data from five primary and one metastatic prostate cancer cohorts to prioritize co-alterations enriched in metastatic disease and associated with disease progression. Integrated analysis of primary tumors defined a set of 17 prostate cancer alterations associated with aggressive characteristics. We applied ProstaMine to NKX3-1-loss and RB1-loss tumors and identified subtype-specific co-alterations associated with metastasis and biochemical relapse in these molecular subtypes. In NKX3-1-loss prostate cancer, ProstaMine identified novel subtype-specific co-alterations known to regulate prostate cancer signaling pathways including MAPK, NF-kB, p53, PI3K, and Sonic hedgehog. In RB1-loss prostate cancer, ProstaMine identified novel subtype-specific co-alterations involved in p53, STAT6, and MHC class I antigen presentation. Co-alterations impacting autophagy were noted in both molecular subtypes. ProstaMine is a method to systematically identify novel subtype-specific co-alterations associated with aggressive characteristics in prostate cancer. The results from ProstaMine provide insights into potential subtype-specific mechanisms of prostate cancer progression which can be formed into testable experimental hypotheses. ProstaMine is publicly available at: https://bioinformatics.cuanschutz.edu/prostamine.

Abstract 3440: Etiology of prostate cancer with the TMPRSS2:ERG fusion: A systematic review of risk factors

Abstract Background: The TMPRSS2:ERG gene fusion is the most common somatic alteration in primary prostate cancer and an early event in carcinogenesis. There are emerging data highlighting etiologic differences in prostate cancer by TMPRSS2:ERG status. This systematic review synthesized evidence from epidemiologic studies on prostate cancer risk factors for tumors with and without the TMPRSS2:ERG fusion. Methods: A systematic literature search was performed in Ovid MEDLINE, EMBASE, and Web of Science without language restriction for studies published by September 27, 2022. Studies that assessed associations between epidemiologic and genetic factors and prostate cancer risk by tumor TMPRSS2:ERG (ERG) fusion status in human populations were included. Results: Of 3,071 records identified, 20 publications comprising prospective cohort and case-control studies from five study populations (published 2009-2022) were included. Risk factors included germline genetic variants, circulating hormones, diet, lifestyle factors, and medications. The included studies suggested that taller height and higher total and free circulating testosterone levels tended to be associated with higher risk of ERG-positive, but not ERG-negative prostate cancer. CAG repeat length in the androgen receptor (AR) gene, related inversely to transcriptional activity, appeared to be associated with a lower risk of ERG-positive, but not ERG-negative prostate cancer. There was statistical evidence for etiologic differences for several germline single nucleotide polymorphisms (SNPs) by ERG status. Excess body weight, greater vigorous physical activity, greater lycopene intake, and calcium channel blocker use appeared to specifically be associated with a lower risk of ERG-positive tumors. Associations of other potential etiologic factors, including diabetes mellitus, baldness, aspirin use, circulating antioxidant levels, and sex hormones other than testosterone, with ERG-positive prostate cancer were null or inconclusive. Most associations had low precision, and the results were based on few distinct study populations, highlighting a need for replication. Conclusions: Prostate cancer with the TMPRSS2:ERG fusion may be an etiologically distinct subtype impacted by certain modifiable and hormonally-acting risk factors that align with the established mechanistic role of this gene fusion in androgen, insulin, and growth factor pathways. The findings suggest a potentially distinct genetic predisposition to prostate cancer with or without the TMPRSS2:ERG fusion. More broadly, these findings suggest that considering molecular subtypes of prostate cancer, beyond TMPRSS2:ERG, may strengthen etiologic understanding of prostate cancer and evidence for prevention. Citation Format: Colleen B. McGrath, Alaina H. Shreves, Megan R. Shanahan, Hannah E. Guard, Manelisi V. Nhliziyo, Kathryn L. Penney, Tamara L. Lotan, Michelangelo Fiorentino, Konrad H. Stopsack, Lorelei A. Mucci. Etiology of prostate cancer with the TMPRSS2:ERG fusion: A systematic review of risk factors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3440.

Single-cell RNA combined with bulk RNA analysis to explore oxidative stress and energy metabolism factors and found a new prostate cancer oncogene MXRA8.

Prostate cancer is the most common malignancy among men worldwide, and its diagnosis and treatment are challenging due to its heterogeneity. Integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data, we identified two molecular subtypes of prostate cancer based on dysregulated genes involved in oxidative stress and energy metabolism. We constructed a risk score model (OMR) using common differentially expressed genes, which effectively evaluated prostate cancer prognosis. Our analysis demonstrated a significant correlation between the risk score model and various factors, including tumor immune microenvironment, genomic variations, chemotherapy resistance, and immune response. Notably, patients with low-risk scores exhibited increased sensitivity to chemotherapy and immunotherapy compared to those with high-risk scores, indicating the model's potential to predict patient response to treatment. Additionally, our investigation of MXRA8 in prostate cancer showed significant upregulation of this gene in the disease as confirmed by PCR and immunohistochemistry. Functional assays including CCK-8, transwell, plate cloning, and ROS generation assay demonstrated that depletion of MXRA8 reduced the proliferative, invasive, migratory capabilities of PC-3 cells, as well as their ROS generation capacity. Our study highlights the potential of oxidative stress and energy metabolism-related genes as prognostic markers and therapeutic targets in prostate cancer. The integration of scRNA-seq and bulk RNA-seq data enables a better understanding of prostate cancer heterogeneity and promotes personalized treatment development. Additionally, we identified a novel oncogene MXRA8 in prostate cancer.

The impact of SPOP gene alterations in men with metastatic prostate cancer: Results from the Prostate Cancer Precision Medicine Multi-Institutional Collaborative Effort (PROMISE) consortium.

225 Background: Inactivating mutations in the SPOP gene, encoding speckled-type poxvirus and zinc-finger protein, are common among men with localized and metastatic prostate cancer, occurring at a frequency of 6-15%. Previous studies have suggested the presence of an inactivating mutation in SPOP results in increased sensitivity to androgen deprivation therapy (ADT). In this multi-institutional clinical-genomic database, we evaluated the impact of SPOP alterations on survival outcomes in men with metastatic prostate cancer. Methods: Retrospective data from the PROMISE Consortium were utilized for this analysis. Eligible patients had metastatic prostate cancer and had undergone standard of care next-generation sequencing (NGS). Patients with inactivating mutations in SPOP were defined as SPOP mutated, where. as those lacking such alterations were defined as SPOP wild-type. The primary endpoint was overall survival defined as the time from diagnosis of metastatic prostate cancer to death from any cause, censored at the date of last follow-up. Secondary endpoints included time from metastatic disease to castration resistance and time from castration resistance to death. Results: Of the 2097 patients with available NGS testing, 5.5% (n=115) had SPOP alterations. The median age at diagnosis was 63 years, 427 were Black, and 83 were Hispanic. At last assessment, 66% had bone metastases, 7% lung metastases, and 5% liver metastases. The most frequent co-occurring alterations in the SPOP-mutated group were: TP53 (30.4%), APC (25.2%), and AR (21.7%). 1832 patients were included in the survival analysis [n=96 (5.2%) with and n=1736 (94.8%) without SPOP alterations]. Median overall survival was numerically longer, though not statistically significant, in the SPOP-mutated compared SPOP-wild-type group (75.9 versus 59.5 months, p=0.12). In patients with metastatic disease, median time to castration resistance was 14.6 months in the SPOP-mutated group versus 12.2 months in the SPOP-wild-type group (p=0.30). Median time from metastatic castration resistant to death was 45.0 months in the SPOP-mutated group and 40.2 months in the SPOP-wild type group. Conclusions: Our hypothesis generating data support that SPOP-mutated prostate cancer likely represents a unique molecular subtype of prostate cancer that may confer prolonged survival. Future studies of novel androgen-receptor targeting treatments should be tested in this molecular population.

Renal Function Parameters in Distinctive Molecular Subtypes of Prostate Cancer.

Prostate cancer is a prevalent malignancy in male patients, having diverse clinical outcomes. The follow-up of patients diagnosed with prostate cancer involves the evaluation of renal function, because its impairment reduces patient survival rates and adds complexity to their treatment and clinical care. This study aimed to investigate the relationship between renal function parameters and distinctive molecular subtypes of prostate adenocarcinomas, defined by the immunoexpression of the SPINK1, ERG, HOXB13, and TFF3 markers. The study group comprised 72 patients with prostate cancer and associated chronic kidney disease (CKD) who underwent radical prostatectomy. Histopathological, molecular, and renal parameters were analyzed. Patients were categorized based on ERG/SPINK1 and HOXB13/TFF3 status, and correlations with renal function and prognostic grade groups were assessed. The ERG+/SPINK1+ subgroup exhibited significantly higher postoperative CKD stages and serum creatinine levels compared to the ERG+/SPINK1- subgroup. This suggests an intricate relationship between SPINK1 overexpression and renal function dynamics. The HOXB13-/TFF3+ subgroup displayed higher preoperative serum creatinine levels and CKD stages than the HOXB13-/TFF3- subgroup, aligning with TFF3's potential role in renal function. Furthermore, the study revealed associations between CKD stages and prognostic grade groups in different molecular subtypes, pointing out an intricate interplay between renal function and tumor behavior. Although the molecular classification of prostate acinar ADK is not yet implemented, this research underscores the variability of renal function parameters in different molecular subtypes, offering potential insights into patient prognosis.

Multi-omics approach for identifying CNV-associated lncRNA signatures with prognostic value in prostate cancer

BackgroundProstate cancer, the second most prevalent malignancy among men, poses a significant threat to affected patients’ well-being due to its poor prognosis. Novel biomarkers are required to enhance clinical outcomes and tailor personalized treatments. Herein, we describe our research to explore the prognostic value of long non-coding RNAs (lncRNAs) deregulated by copy number variations (CNVs) in prostate cancer. MethodsThe study employed an integrative multi-omics data analysis of the prostate cancer transcriptomic, CNV and methylation datasets to identify prognosis-related subtypes. Subtype-specific expression profiles of protein-coding genes (PCGs) and lncRNAs were determined. We analysed CNV patterns of lncRNAs across the genome to identify subtype-specific lncRNAs with CNV changes. LncRNAs exhibiting significant amplification or deletion and a positive correlation were designated CNV-deregulated lncRNAs. A prognostic risk score model was subsequently developed using these CNV-driven lncRNAs. ResultsSix molecular subtypes of prostate cancer were identified, demonstrating significant differences in prognosis (P = 0.034). The CNV profiles of subtype-specific lncRNAs were examined, revealing their correlation with CNV amplification or deletion. Six lncRNAs (CCAT2, LINC01593, LINC00276, GACAT2, LINC00457, LINC01343) were selected based on significant CNV amplifications or deletions using a rigorous univariate Cox proportional risk regression model. A robust risk score model was developed, stratifying patients into high-risk and low-risk categories. Notably, our prognostic model based on these six lncRNAs exhibited exceptional predictive capabilities for recurrence-free survival (RFS) in prostate cancer patients (P = 0.024). ConclusionsOur study successfully identified a prognostic risk score model comprising six CNV-driven lncRNAs that could potentially be prognostic biomarkers for prostate cancer. These lncRNA signatures are closely associated with RFS, providing promising prospects for improved patient prognostication and personalized therapeutic strategies for novel prostate cancer treatment.

The Association between Cyclin Dependent Kinase 2 Associated Protein 1 (CDK2AP1) and Molecular Subtypes of Lethal Prostate Cancer.

Prostate cancer (PCa) is one of the most commonly diagnosed types of malignancy and is the second leading cause of cancer-related death in men in developed countries. Cyclin dependent kinase 2 associate protein 1(CDK2AP1) is an epigenetic and cell cycle regulator gene which has been downregulated in several malignancies, but its involvement in PCa has not yet been investigated in a clinical setting. We assessed the prognostic value of CDK2AP1 expression in a cohort of men diagnosed with PCa (n = 275) treated non-surgically by transurethral resection of the prostate (TURP) and studied the relationship between CDK2AP1 expression to various PCa molecular subtypes (ERG, PTEN, p53 and AR) and evaluated the association with clinical outcome. Further, we used bioinformatic tools to analyze the available TCGA PRAD transcriptomic data to explore the underlying mechanism. Our data confirmed increased expression of CDK2AP1 with higher Gleason Grade Group (GG) and metastatic PCa (p <0.0001). High CDK2AP1 expression was associated with worse overall survival (OS) (HR: 1.62, CI: 1.19-2.21, p = 0.002) and cause-specific survival (CSS) (HR: 2.012, CI 1.29-3.13, p = 0.002) using univariate analysis. When compared to each sub-molecular type. High CDK2AP1/PTEN-loss, abnormal AR or p53 expression showed even worse association to poorer OS and CCS and remained significant when adjusted for GG. Our data indicates that CDK2AP1 directly binds to p53 using the Co-Immunoprecipitation (Co-IP) technique, which was validated using molecular docking tools. This suggests that these two proteins have a significant association through several binding features and correlates with our observed clinical data. In conclusion, our results indicated that the CDK2AP1 overexpression is associate with worse OS and CSS when combined with certain PCa molecular subtypes; interaction between p53 stands out as the most prominent candidate which directly interacts with CDK2AP1.

Molecular classification of hormone-sensitive and castration-resistant prostate cancer, using nonnegative matrix factorization molecular subtyping of primary and metastatic specimens.

BackgroundDespite the rapidly evolving therapeutic landscape, immunotherapy has demonstrated limited activity in prostate cancer. A greater understanding of the molecular landscape, particularly the expression of immune‐related pathways, will inform future immunotherapeutic strategies. Consensus nonnegative matrix factorization (cNMF) is a novel model of molecular classification analyzing gene expression data, focusing on biological interpretation of metagenes and selecting meaningful clusters.ObjectiveWe aimed to identify molecular subtypes of prostate cancer using cNMF and correlate these with existing biomarkers to inform future immunotherapeutic strategies.MethodsA cohort of archival tumor specimens from hormone‐sensitive and castration‐resistant disease was studied. Whole transcriptomic profiles were generated using TruSeq RNA Access technology and subjected to cNMF. Comprehensive genomic profiling was performed with the FoundationOne assay. NMF subtypes were characterized by gene expression pathways, genomic alterations and correlated with clinical data, then applied to The Cancer Genome Atlas data set.ResultsWe studied 164 specimens, including 52 castration‐resistant and 13 paired primary/metastatic specimens. cNMF identified four distinct subtypes. NMF1 (19%) is enriched for immune‐related and stromal‐related pathways with transforming growth factor β (TGFβ) signature. NMF2 (36%) is associated with FOXO‐mediated transcription signature and AKT signaling, NMF3 (26%) is enriched for ribosomal RNA processing, while NMF4 (19%) is enriched for cell cycle and DNA‐repair pathways. The most common gene alterations included TMPRSS22 (42%), TP53 (23%), and DNA‐repair genes (19%), occurring across all subtypes. NMF4 is significantly enriched for MYC and Wnt‐signaling gene alterations. TMB, CD8 density, and PD‐L1 expression were low overall. NMF1 and NMF4 were NMF2 was associated with superior overall survival.ConclusionsUsing cNMF, we identified four molecularly distinct subtypes which may inform treatment selection. NMF1 demonstrates the most inflammatory signature with asuppressive TGFβ signature, suggesting potential benefit with immunotherapy combination strategies targeting TGFβ and PD‐(L)1. Prospective studies are required to evaluate the use of this novel model to molecularly stratify patients for optimal treatment selection.

GSTP1 positive prostatic adenocarcinomas are more common in Black than White men in the United States.

GSTP1 is a member of the Glutathione-S-transferase (GST) family silenced by CpG island DNA hypermethylation in 90-95% of prostate cancers. However, prostate cancers expressing GSTP1 have not been well characterized. We used immunohistochemistry against GSTP1 to examine 1673 primary prostatic adenocarcinomas on tissue microarrays (TMAs) with redundant sampling from the index tumor from prostatectomies. GSTP1 protein was positive in at least one TMA core in 7.7% of cases and in all TMA cores in 4.4% of cases. The percentage of adenocarcinomas from Black patients who had any GSTP1 positive TMA cores was 14.9%, which was 2.5 times higher than the percentage from White patients (5.9%; P < 0.001). Further, the percentages of tumors from Black patients who had all TMA spots positive for GSTP1 (9.5%) was 3-fold higher than the percentage from White patients (3.2%; P<0.001). In terms of association with other molecular alterations, GSTP1 positivity was enriched in ERG positive cancers among Black men. By in situ hybridization, GSTP1 mRNA expression was concordant with protein staining, supporting the lack of silencing of at least some GSTP1 alleles in GSTP1-positive tumor cells. This is the first report revealing that GSTP1-positive prostate cancers are substantially over-represented among prostate cancers from Black compared to White men. This observation should prompt additional studies to determine whether GSTP1 positive cases represent a distinct molecular subtype of prostate cancer and whether GSTP1 expression could provide a biological underpinning for the observed disparate outcomes for Black men.

Impact TMPRSS2-ERG Molecular Subtype on Prostate Cancer Recurrence.

Currently, seven molecular subtypes of prostate cancer (PCa) are known, the most common of which being the subtype characterized by the presence of the TMPRSS2–ERG fusion transcript. While there is a considerable amount of work devoted to the influence of this transcript on the prognosis of the disease, data on its role in the progression and prognosis of PCa remain controversial. The present study is devoted to the analysis of the association between the TMPRSS2–ERG transcript and the biochemical recurrence of PCa. The study included two cohorts: the RNA–Seq sample of Russian patients with PCa (n = 72) and the TCGA–PRAD data (n = 203). The results of the analysis of the association between the TMPRSS2–ERG transcript and biochemical recurrence were contradictory. The differential expression analysis (biochemical recurrence cases versus biochemical recurrence-free) and the gene set enrichment analysis revealed a list of genes involved in major cellular pathways. The GNL3, QSOX2, SSPO, and SYS1 genes were selected as predictors of the potential prognostic model (AUC = 1.000 for a cohort of Russian patients with PCa and AUC = 0.779 for a TCGA–PRAD cohort).

MAP3K7 Loss Drives Enhanced Androgen Signaling and Independently Confers Risk of Recurrence in Prostate Cancer with Joint Loss of CHD1.

Prostate cancer genomic subtypes that stratify aggressive disease and inform treatment decisions at the primary stage are currently limited. Previously, we functionally validated an aggressive subtype present in 15% of prostate cancer characterized by dual deletion of MAP3K7 and CHD1. Recent studies in the field have focused on deletion of CHD1 and its role in androgen receptor (AR) chromatin distribution and resistance to AR-targeted therapy; however, CHD1 is rarely lost without codeletion of MAP3K7. Here, we show that in the clinically relevant context of co-loss of MAP3K7 and CHD1 there are significant, collective changes to aspects of AR signaling. Although CHD1 loss mainly impacts the expansion of the AR cistrome, loss of MAP3K7 drives increased AR target gene expression. Prostate cancer cell line models engineered to cosuppress MAP3K7 and CHD1 also demonstrated increased AR-v7 expression and resistance to the AR-targeting drug enzalutamide. Furthermore, we determined that low protein expression of both genes is significantly associated with biochemical recurrence (BCR) in a clinical cohort of radical prostatectomy specimens. Low MAP3K7 expression, however, was the strongest independent predictor for risk of BCR over all other tested clinicopathologic factors including CHD1 expression. Collectively, these findings illustrate the importance of MAP3K7 loss in a molecular subtype of prostate cancer that poses challenges to conventional therapeutic approaches. IMPLICATIONS: These findings strongly implicate MAP3K7 loss as a biomarker for aggressive prostate cancer with significant risk for recurrence that poses challenges for conventional androgen receptor-targeted therapies.

Long Non-Coding RNA Landscape in Prostate Cancer Molecular Subtypes: A Feature Selection Approach.

Prostate cancer is one of the most common malignancies in men. It is characterized by a high molecular genomic heterogeneity and, thus, molecular subtypes, that, to date, have not been used in clinical practice. In the present paper, we aimed to better stratify prostate cancer patients through the selection of robust long non-coding RNAs. To fulfill the purpose of the study, a bioinformatic approach focused on feature selection applied to a TCGA dataset was used. In such a way, LINC00668 and long non-coding(lnc)-SAYSD1-1, able to discriminate ERG/not-ERG subtypes, were demonstrated to be positive prognostic biomarkers in ERG-positive patients. Furthermore, we performed a comparison between mutated prostate cancer, identified as “classified”, and a group of patients with no peculiar genomic alteration, named “not-classified”. Moreover, LINC00920 lncRNA overexpression has been linked to a better outcome of the hormone regimen. Through the feature selection approach, it was found that the overexpression of lnc-ZMAT3-3 is related to low-grade patients, and three lncRNAs: lnc-SNX10-87, lnc-AP1S2-2, and ADPGK-AS1 showed, through a co-expression analysis, significant correlation values with potentially druggable pathways. In conclusion, the data mining of publicly available data and robust bioinformatic analyses are able to explore the unknown biology of malignancies.

NCOR1 may be a potential biomarker of a novel molecular subtype of prostate cancer.

Prostate cancer (PCa) is the most frequently diagnosed male cancer. An earlier study of a cohort of 333 primary prostate carcinomas showed that 74% of these tumors fell into one of seven subtypes of a molecular taxonomy defined by specific gene fusions (ERG, ETV1/4 and FLI1) or mutations (SPOP, FOXA1 and IDH1). Molecular subtypes may aid in distinguishing indolent cases from aggressive cases and improving management of the disease. However, molecular features of PCa outside the seven subtypes are still not well studied. Here we report molecular features of PCa cases without typical features of the established subtypes. We performed comprehensive genomic analysis of 91 patients, including 54 primary and 37 metastatic cases, by whole-exome sequencing. TP53, SPOP, FOXA1, AR (androgen receptor) and a TMPRSS2-ERG fusion emerged as the most commonly altered genes in primary cases, whereas AR, FOXA1, PTEN, CDK12, APC and TP53 were the most commonly altered genes in metastatic cases. Nuclear receptor corepressor (NCOR1) genomic alterations have been identified in 5% of cases, which are nontypical molecular features of PCa subtypes. A novel NCOR1 c.2182G>C (p.Val728Leu) was identified in tumor. RT-PCR was used to show that this mutation caused loss of NCOR1 exon 19 and might be oncogenic in PCa. NCOR1 is involved in maintenance of mitochondrial membrane potential in PCa cells, and loss of NCOR1 might contribute to PCa progression. Therefore, NCOR1 may be a potential molecular marker of a subtype of PCa.

Molecular tracing of prostate cancer lethality.

Prostate cancer is diagnosed mostly in men over the age of 50 years, and has favorable 5-year survival rates due to early cancer detection and availability of curative surgical management. However, progression to metastasis and emergence of therapeutic resistance are responsible for the majority of prostate cancer mortalities. Recent advancement in sequencing technologies and computational capabilities have improved the ability to organize and analyze large data, thus enabling the identification of novel biomarkers for survival, metastatic progression and patient prognosis. Large-scale sequencing studies have also uncovered genetic and epigenetic signatures associated with prostate cancer molecular subtypes, supporting the development of personalized targeted-therapies. However, the current state of mainstream prostate cancer management does not take full advantage of the personalized diagnostic and treatment modalities available. This review focuses on interrogating biomarkers of prostate cancer progression, including gene signatures that correspond to the acquisition of tumor lethality and those of predictive and prognostic value in progression to advanced disease, and suggest how we can use our knowledge of biomarkers and molecular subtypes to improve patient treatment and survival outcomes.

Cellular and Molecular Progression of Prostate Cancer: Models for Basic and Preclinical Research.

Simple SummaryThe molecular progression of prostate cancer is complex and elusive. Biological research relies heavily on in vitro and in vivo models that can be used to examine gene functions and responses to the external agents in laboratory and preclinical settings. Over the years, several models have been developed and found to be very helpful in understanding the biology of prostate cancer. Here we describe these models in the context of available information on the cellular and molecular progression of prostate cancer to suggest their potential utility in basic and preclinical prostate cancer research. The information discussed herein should serve as a hands-on resource for scholars engaged in prostate cancer research or to those who are making a transition to explore the complex biology of prostate cancer.We have witnessed noteworthy progress in our understanding of prostate cancer over the past decades. This basic knowledge has been translated into efficient diagnostic and treatment approaches leading to the improvement in patient survival. However, the molecular pathogenesis of prostate cancer appears to be complex, and histological findings often do not provide an accurate assessment of disease aggressiveness and future course. Moreover, we also witness tremendous racial disparity in prostate cancer incidence and clinical outcomes necessitating a deeper understanding of molecular and mechanistic bases of prostate cancer. Biological research heavily relies on model systems that can be easily manipulated and tested under a controlled experimental environment. Over the years, several cancer cell lines have been developed representing diverse molecular subtypes of prostate cancer. In addition, several animal models have been developed to demonstrate the etiological molecular basis of the prostate cancer. In recent years, patient-derived xenograft and 3-D culture models have also been created and utilized in preclinical research. This review is an attempt to succinctly discuss existing information on the cellular and molecular progression of prostate cancer. We also discuss available model systems and their tested and potential utility in basic and preclinical prostate cancer research.

Abstract 1308: CDK12 alterations define a distinct molecular subtype of prostate cancers with unique genomic and clinical characteristics

Abstract Background: CDK12 alterations are present in several tumor types but little is known regarding their oncogenic role and their clinical significance. Here we sought to describe the landscape of CDK12 alterations across solid cancers and the clinical features of CDK12-altered prostate cancer. Methods: A total of 26,743 patients across 25 solid tumor types with available targeted sequencing data from MSK-IMPACT as part of their clinical care were included. Clinicopathological features and outcomes were assessed in prostate cancer. CDK12 alterations and association with genomic characteristics are described. For prostate cancer patients, overall survival from the date of metastasis and time to castration-resistance from the start of androgen deprivation therapy were assessed using univariable and multivariable Cox regression analysis. Results: CDK12 alterations were identified in 404/26,743 (1.5%) patients overall, but were most frequent in prostate (100/1875, 5.3%) and ovarian cancer (43/1034, 4.2%) where they were associated with a high prevalence of truncating variants and biallelic inactivation. CDK12 alterations defined a distinct subtype of prostate cancer with more aggressive clinical features, a unique copy number alteration profile and involvement of distinct oncogenic pathway alterations, including cell cycle pathway genes. Independent of standard clinical factors and genomic instability, CDK12-altered prostate cancer patients were associated with shorter overall survival (median 64.4 vs 74.9 months, adjusted hazard ratio [aHR] 1.65, 95% CI 1.07-2.53, p = 0.03) and shorter time to the development of castration-resistant disease (median 10.8 months vs 13.1, aHR 1.43, 95%CI 1.07-1.8, p = 0.02). Conclusions: CDK12 loss of function is a rare event across solid cancers but defines a distinct molecular subtype of prostate cancer that is associated with more aggressive clinical features and unique genomic alterations. Citation Format: Bastien Nguyen, Jose Mauricio Mota, Subhiksha Nandakumar, Konrad H. Stopsack, Emily Weg, Dana Rathkopf, Michael J. Morris, Howard Scher, Philip W. Kantoff, Anuradha Gopalan, Dmitriy Zamarin, David B. Solit, Nikolaus Schultz, Wassim Abida. CDK12 alterations define a distinct molecular subtype of prostate cancers with unique genomic and clinical characteristics [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1308.

Abstract 2959: Glycogen synthase kinase 3-β expression in prostate cancer (PCa) correlates with aggressive pathological features and its blockade with 9-ING-41 inhibits viability of PCa cell lines

Abstract Castration-resistant prostate cancer (CRPC) represents a lethal stage of disease with limited treatment options beyond androgen receptor (AR) inhibitors and chemotherapy. GSK-3β is a serine/threonine kinase established as a therapeutic target in several solid tumors. GSK-3β inhibitors reduce prostate cancer cell growth and inhibit AR-V7 transcriptional activity in vitro (Rinnab L et al 2008; Schütz SV et al 2011; Nakata et al 2017). This study aimed to characterize the GSK-3β expression in molecular subtypes of PCa and the antitumor activity of 9-ING-41, a selective small molecule GSK-3β inhibitor currently in phase 1/2 clinical studies (NCT03678883). We hypothesized that GSK3-β expression may correlate with sensitivity to GSK3-β inhibition as well as suppression of anti-apoptotic pathways. We evaluated the expression of GSK-3β in a tissue microarray of 134 specimens of PCa tumors from radical prostatectomies (median age 69, serum PSA 10.5 ± 7.6 ng/ml; grade groups (GG): 18 - GG 1 (13.4%), 67 - GG 2 (48.5%), 29 - GG 3 (21.4%), 7 - GG 4 (5.2%), 13 - GG 5 (9.7%); 72 patients (54.9%) had pT2 tumors, and 52 (39,1%) were pT3. Seven patients (5.7%) had positive lymph node (pN1 disease). ERG expression and PTEN loss were observed in 52% (71/134) and 42%, respectively. The GSK-3β histologic score (% of positive tumor cells multiplied by intensity 0-3) correlated with higher Gleason grade (p&amp;lt;0.05), extraprostatic extension (pT3a, p&amp;lt;0.05), but not with serum PSA, tumor volume, margin status or size of index nodule. Cases with predominant nuclear localization of GSK-3β (5%; N=7) had higher Gleason score, pathologic stage, and all but one had PTEN loss. The antiproliferative effect of 9-ING-41 in four PCa human cell lines (PC3, DU145, LNCAP and 22rV1) was investigated using Cell-Titer-Glo (CTG) viability assay. 9-ING-41 demonstrated a dose-dependent decrease in proliferation of AR positive (IC50s 0.3 μM LNCAP; 0.8 μM 22rV1) and AR negative cell lines (IC50 0.6 μM PC3, 0.2 μM DU145). 9-ING-41 induced robust apoptosis (cleaved PARP) in LNCAP and PC3 cells, but not in DU145. All four cell lines expressed GSK-3β, the target of 9-ING-41 and its level were not altered by treatment. 9-ING-41 decreased the expression of phosphorylated NF-kβ (Ser536), anti-apoptotic proteins MCL-1 and BCL-2 by western immunoblotting. Interestingly, the most sensitive cell line, DU145, had lower levels of NF-kβ and suppressed both MCL-1 and BCL-2 after exposure to 9-ING-41. Our current work is evaluating the extent of apoptosis versus growth arrest, especially in the DU145 cell line, where PARP cleavage was not observed. We are also evaluating the effects of the 9-ING-41 on cellular targets of GSK-3β as potential markers of drug efficacy. 9-ING-41 has potent anti-proliferative activity against PCa cell lines. These data support the inclusion of patients with CRPC in clinical studies of 9-ING-41 and its further investigation for the treatment of CRPC. Citation Format: Fabio Tavora, Tamara Lotan, Marclesson Alves, Lanlan Zhou, Ali Amin, Navaraj Arunasalam, Andre De Souza, Anthony Mega, Dragan Golijanin, Frank Giles, Wafik El-Deiry, Benedito Carneiro. Glycogen synthase kinase 3-β expression in prostate cancer (PCa) correlates with aggressive pathological features and its blockade with 9-ING-41 inhibits viability of PCa cell lines [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2959.

Abstract 2135: Characterization of robust and prognostic molecular subtypes in prostate cancer

Abstract Introduction: Multiple biomarkers and molecular subtypes have been proposed in prostate cancer (PCa) with limited overlap, in part due to the heterogeneity of the disease and issues with data scaling. By applying Almac Diagnostic's unique software driven tool, claraT, cancer gene expression datasets can be characterized according to six of the well-established Hallmarks of Cancer using published signatures, proprietary assays and single gene targets. This retrospective study aimed to identify robust molecular subtypes of PCa that are prognostic and validated by applying claraT to multiple gene expression datasets. Experimental procedures: claraT was applied to three primary PCa gene expression datasets, TCGA (n = 331, Illumina HiSeq), Walker et al Discovery (n = 91, Almac Prostate DSA) and Walker et al Validation (n = 322, Almac Prostate DSA). Six sets of signature scores were generated, each representing a different hallmark and consensus clustering was performed using the signature scores. Clinical relevance was assessed using metastatic-free survival (MFS) and disease-free survival (DFS) as end-points. Using statistical tests, association of the identified subtypes with variables was investigated. Results: Of the six hallmarks investigated, robust and stable molecular subtypes were established using the Genome-Instability (GI) signature set. Four subtypes, two with good prognosis and two with poor prognosis, were characterized in the Walker Validation (MFS log-rank, p=6.798e-10), TCGA (DFS log-rank, p=0.0012) and Walker Discovery (chi-square - metastases, p=0.004). Subtypes were significantly associated with Gleason, biochemical recurrence, and Almac's Prostate Dx assay (chi-square, p&amp;lt;0.00001). Clustering analysis revealed the poor prognosis subtypes to have high GI signature expression e.g. chromosome instability and homologous recombination deficiency signatures. The median number of copy number alterations (CNAs) amongst the subtypes was higher in the poor prognosis subtypes (Wilcoxin, p=1.0363e-18) thus validating the genome-unstable phenotype association with the poor prognosis subtypes. Conclusion: Of the six hallmarks investigated, Genome-Instability was the most robust and prognostic. Molecular subtypes with distinct prognoses have been identified and validated. These poor prognosis subtypes are characterized by an active genome instability biology and high levels of CNAs. Therefore, these poor prognosis subtypes of PCa, with a dominant genome instability biology, may represent a larger target subgroup of PCa's which may benefit from DNA repair targeted therapies such as PARP inhibitors. Citation Format: Cathal McKinney, Nuala McCabe, Paul Harkin, Richard Kennedy, Jaine Blayney. Characterization of robust and prognostic molecular subtypes in prostate cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2135.

Abstract 5302: Molecular subtype stratification for prostate cancer from mpMRI and histopathology images using convolutional neural networks and transfer learning

Abstract Objective: Molecular subtypes have been found to be associated with prognosis and treatment response for prostate cancer (PCa) patients and have the potential to aid personalized treatment planning. We aim to stratify molecular subtypes by lesion characterization from multiparametric magnetic resonance images (mp-MRI) using convolutional neural networks (CNN) and knowledge transferred from lesion malignancy classification task. Methods: We identified 23 PCa patients with available mpMRI and molecular subtype information. Each patient may harbor multi-focal lesions of different molecular subtypes. Automated antibody based dual-color immunohistochemistry assays were developed for the simultaneous assessment of ERG-PTEN and ERG-SPINK1 status in PCa on the whole mount microscopic sections. In 7 patients 11 intraprostatic lesions (ILs) were identified as ERG+, 3 patients 3 ILs as SPINK1+, and 10 patients 11 ILs as triple negative (ERG-, SPINK1- and ETS-). We fed a CNN using intratumoral region of interest defined in a slice-by-slice manner from T2WI, ADC and DWIb50. The feature maps from the third convolutional layer were flattened into 7,744 dimensional vectors to represent each IL slice. To compensate for the small sample size, we utilized transfer learning, from the task of tumor malignancy stratification. The CNN model was pre-trained on mpMRI with 320 ILs from 201 patients for malignancy stratification using a different cohort we published previously, which was later fined tuned on this cohort on malignancy classification for domain adaptation purpose. Results: The clustering accuracy (Top 3 estimates) using cosine similarity metrics was shown in Table 1 for each molecular subtype category respectively. The preliminary results supported our hypothesis that task of lesion malignancy and molecular sub-types stratification were correlated in the imaging features derived from mpMRI. Table 1:Clustering accuracy for each molecular category. Each ILs input had 3 consecutive slices in a sequence, know as 2.5D, to incorporate lesion growth pattern.Accuracy (# of 2.5D image slices)Top 1 predictionsTop 2 predictionsTop 3 predictionsERG+ (21)0.670.900.95SPINK1+ (4)0.50.750.75Negative (17)0.650.760.76 Conclusions: This work showed the potential to classify the molecular subtypes of PCa from mp-MRI. The small sample size problem was tackled using transfer learning. Acknowledgement: The work was supported by a Research Scholar Grant: RSG-15-137-01-CCE from the American Cancer Society. Citation Format: Weiwei Zong, Eric N. Carver, Aharon Feldman, Nallasivam Palanisamy, Ning Wen. Molecular subtype stratification for prostate cancer from mpMRI and histopathology images using convolutional neural networks and transfer learning [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5302.