Proposal for an optimised definition of adverse pathology (unfavourable histology) that predicts metastatic risk in prostatic adenocarcinoma independent of grade group and pathological stage.

AIMS: Histological grading of prostate cancer is a powerful prognostic tool, but current criteria for grade assignment are not fully optimised. Our goal was to develop and test a simplified histological grading model, based heavily on large cribriform/intraductal carcinoma, with optimised sensitivity for predicting metastatic potential. METHODS AND RESULTS: Two separate non-overlapping cohorts were identified: a 419-patient post-radical prostatectomy cohort with long term clinical follow-up and a 209-patient post-radical prostatectomy cohort in which all patients had pathologically confirmed metastatic disease. All prostatectomies were re-reviewed for high-risk histological patterns of carcinoma termed 'unfavourable histology'. Unfavourable histology is defined by any classic Gleason pattern 5 component, any large cribriform morphology (> 0.25 mm) or intraductal carcinoma, complex intraluminal papillary architecture, grade 3 stromogenic carcinoma and complex anastomosing cord-like growth. For the outcome cohort, Kaplan-Meier analysis compared biochemical recurrence, metastasis and death between subjects with favourable and unfavourable histology, stratified by pathological stage and grade group. Multivariable Cox proportional hazards models evaluated adding unfavourable histology to the Memorial Sloan Kettering Cancer Center (MSKCC) post-prostatectomy nomogram and stratification by percentage of unfavourable histology. At 15 years unfavourable histology predicted biochemical recurrence, with sensitivity of 93% and specificity of 88%, metastatic disease at 100 and 48% and death at 100 and 46%. Grade group 2 prostate cancers with unfavourable histology were associated with metastasis independent of pathological stage, while those without had no risk. Histological models for prediction of metastasis based on only large cribriform/intraductal carcinoma or increasing diameter of cribriform size improved specificity, but with lower sensitivity. Multivariable Cox proportional hazards models demonstrated that unfavourable histology significantly improved discriminatory power of the MSKCC post-prostatectomy nomogram for biochemical failure (likelihood ratio test P < 0.001). In the retrospective review of a separate RP cohort in which all patients had confirmed metastatic disease, none had unequivocal favourable histology. CONCLUSIONS: Unfavourable histology at radical prostatectomy is associated with metastatic risk, predicted adverse outcomes better than current grading and staging systems and improved the MSKCC post-prostatectomy nomogram. Most importantly, unfavourable histology stratified grade group 2 prostate cancers into those with and without metastatic potential, independent of stage. While unfavourable histology is driven predominantly by large cribriform/intraductal carcinoma, the recognition and inclusion of other specific architectural patterns add to the sensitivity for predicting metastatic disease. Moreover, a simplified dichotomous model improves communication and could increase implementation.

Increased α2,3-sialyl N-glycosylated prostate-specific membrane antigen (PSMA) in post-DRE urine is associated with high grade group prostate cancer.

INTRODUCTION: Aberrant glycosylation of proteins is an important hallmark in multiple cancers. Prostate-specific membrane antigen (PSMA), a highly glycosylated protein with 10 N-linked glycosylation sites, is an Food and Drug Administration approved theranostic for prostate cancer. However, glycosylation changes in PSMA that are associated with prostate cancer disease progression have not been fully characterized. METHODS: We investigated whether urinary PSMA sialylation correlate with high-grade prostate cancer. Urine samples were collected from men after digital rectal examination (DRE) before prostate biopsy. Lectin-antibody enzyme-linked immunoassay was used to quantify α2,3-sialyl PSMA in post-DRE urine samples from subjects with benign prostate tumors, Grade Group 1 prostate cancer and those with Grade Group ≥2 disease. RESULTS: There are significant increases in α2,3-sialylated PSMA in patients with Grade Group ≥2 disease compared to benign (p = 0.0009) and those with Grade Group 1 disease (p = 0.0063). There were no significant differences in α2,3-sialyl PSMA levels between Grade Group 1 and benign prostate tumors (p = 0.7947). CONCLUSIONS: Our study shows that there are significant differences in the abundance of α2,3-sialylated PSMA in post-DRE urines from disease stratified prostate cancer patients, and the increase is correlated with progression and disease severity. The detection of increased PSMA sialyation in post-DRE urines from patients with higher Grade Group ≥2 disease states provides novel untapped potential for the development of prognostic biomarkers for prostate cancer. Specifically, quantitation of α2,3-sialylated PSMA shows potential for discriminating between benign to intermediate grade disease, which is a significant clinical challenge in staging and risk stratification of prostate cancer.

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.

Prostate-specific membrane antigen (PSMA) glycoforms in prostate cancer patients seminal plasma.

INTRODUCTION: Prostate-specific membrane antigen (PSMA) is a US Food and Drug Administration-approved theranostic target for prostate cancer (PCa). Although PSMA is known to be glycosylated, the composition and functional roles of its N-linked glycoforms have not been fully characterized. METHODS: PSMA was isolated from pooled seminal plasma from low-risk grade Groups 1 and 2 PCa patients. Intact glycopeptides were analyzed by mass spectrometry to identify site-specific glycoforms. RESULTS: We observed a rich distribution of PSMA glycoforms in seminal plasma from low and low-intermediate-risk PCa patients. Some interesting generalities can be drawn based on the predicted topology of PSMA on the plasma membrane. The glycoforms at ASN-459, ASN-476, and ASN-638 residues that are located at the basal domain facing the plasma membrane in cells, are predominantly high mannose glycans. ASN-76 which is located in the interdomain region adjacent to the apical domain of the protein shows a mixture of high mannose glycans and complex glycans, whereas ASN-121, ASN-195 and ASN-336 that are located and are exposed at the apical domain of the protein predominantly possess complex sialylated and fucosylated N-linked glycans. These highly accessible glycosites display the greatest diversity in isoforms across the patient samples. CONCLUSIONS: Our study provides novel qualitative insights into PSMA glycoforms that are present in the seminal fluid of PCa patients. The presence of a rich diversity of glycoforms in seminal plasma provides untapped potential for glycoprotein biomarker discovery and as a clinical sample for noninvasive diagnostics of male urological disorders and diseases including PCa. Specifically, our glycomics approach will be critical in uncovering PSMA glycoforms with utility in staging and risk stratification of PCa.

ST6GAL1-mediated aberrant sialylation promotes prostate cancer progression.

Aberrant glycosylation is a universal feature of cancer cells, and cancer-associated glycans have been detected in virtually every cancer type. A common change in tumour cell glycosylation is an increase in α2,6 sialylation of N-glycans, a modification driven by the sialyltransferase ST6GAL1. ST6GAL1 is overexpressed in numerous cancer types, and sialylated glycans are fundamental for tumour growth, metastasis, immune evasion, and drug resistance, but the role of ST6GAL1 in prostate cancer is poorly understood. Here, we analyse matched cancer and normal tissue samples from 200 patients and verify that ST6GAL1 is upregulated in prostate cancer tissue. Using MALDI imaging mass spectrometry (MALDI-IMS), we identify larger branched α2,6 sialylated N-glycans that show specificity to prostate tumour tissue. We also monitored ST6GAL1 in plasma samples from >400 patients and reveal ST6GAL1 levels are significantly increased in the blood of men with prostate cancer. Using both in vitro and in vivo studies, we demonstrate that ST6GAL1 promotes prostate tumour growth and invasion. Our findings show ST6GAL1 introduces α2,6 sialylated N-glycans on prostate cancer cells and raise the possibility that prostate cancer cells can secrete active ST6GAL1 enzyme capable of remodelling glycans on the surface of other cells. Furthermore, we find α2,6 sialylated N-glycans expressed by prostate cancer cells can be targeted using the sialyltransferase inhibitor P-3FAX -Neu5Ac. Our study identifies an important role for ST6GAL1 and α2,6 sialylated N-glycans in prostate cancer progression and highlights the opportunity to inhibit abnormal sialylation for the development of new prostate cancer therapeutics. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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.

Differential Activation of NRF2 Signaling Pathway in Renal-Cell Carcinoma Caki Cell Lines.

Renal-cell carcinoma (RCC) is a heterogeneous disease consisting of several subtypes based on specific genomic profiles and histological and clinical characteristics. The subtype with the highest prevalence is clear-cell RCC (ccRCC), next is papillary RCC (pRCC), and then chromophobe RCC (chRCC). The ccRCC cell lines are further subdivided into prognostic expression-based subtypes ccA or ccB. This heterogeneity necessitates the development, availability, and utilization of cell line models with the correct disease phenotypic characteristics for RCC research. In this study, we focused on characterizing proteomic differences between the Caki-1 and Caki-2 cell lines that are commonly used in ccRCC research. Both cells are primarily defined as human ccRCC cell lines. Caki-1 cell lines are metastatic, harboring wild-type VHL, whereas Caki-2 are considered as the primary ccRCC cell lines expressing wild-type von Hippel-Lindau protein (pVHL). Here, we performed a comprehensive comparative proteomic analysis of Caki-1 and Caki-2 cells using tandem mass-tag reagents together with liquid chromatography mass spectrometry (LC/MS) for the identification and quantitation of proteins in the two cell lines. Differential regulation of a subset of the proteins identified was validated using orthogonal methods including western blot, q-PCR, and immunofluorescence assays. Integrative bioinformatic analysis identifies the activation/inhibition of specific molecular pathways, upstream regulators, and causal networks that are uniquely regulated and associated with the two cell lines and RCC subtypes, and potentially the disease stage. Altogether, we have identified multiple molecular pathways, including NRF2 signaling, which is the most significantly activated pathway in Caki-2 versus Caki-1 cells. Some of the differentially regulated molecules and signaling pathways could serve as potential diagnostic and prognostic biomarkers and therapeutic targets amongst ccRCC subtypes.

Prospective comparison of restriction spectrum imaging and non-invasive biomarkers to predict upgrading on active surveillance prostate biopsy.

BACKGROUND: Protocol-based active surveillance (AS) biopsies have led to poor compliance. To move to risk-based protocols, more accurate imaging biomarkers are needed to predict upgrading on AS prostate biopsy. We compared restriction spectrum imaging (RSI-MRI) generated signal maps as a biomarker to other available non-invasive biomarkers to predict upgrading or reclassification on an AS biopsy. METHODS: We prospectively enrolled men on prostate cancer AS undergoing repeat biopsy from January 2016 to June 2019 to obtain an MRI and biomarkers to predict upgrading. Subjects underwent a prostate multiparametric MRI and a short duration, diffusion-weighted enhanced MRI called RSI to generate a restricted signal map along with evaluation of 30 biomarkers (14 clinico-epidemiologic features, 9 molecular biomarkers, and 7 radiologic-associated features). Our primary outcome was upgrading or reclassification on subsequent AS prostate biopsy. Statistical analysis included operating characteristic improvement using AUROC and AUPRC. RESULTS: The individual biomarker with the highest area under the receiver operator characteristic curve (AUC) was RSI-MRI (AUC = 0.84; 95% CI: 0.71-0.96). The best non-imaging biomarker was prostate volume-corrected Prostate Health Index density (PHI, AUC = 0.68; 95% CI: 0.53-0.82). Non-imaging biomarkers had a negligible effect on predicting upgrading at the next biopsy but did improve predictions of overall time to progression in AS. CONCLUSIONS: RSI-MRI, PIRADS, and PHI could improve the predictive ability to detect upgrading in AS. The strongest predictor of clinically significant prostate cancer on AS biopsy was RSI-MRI signal output.

Site-Specific Intact N-Linked Glycopeptide Characterization of Prostate-Specific Membrane Antigen from Metastatic Prostate Cancer Cells.

The composition of N-linked glycans that are conjugated to the prostate-specific membrane antigen (PSMA) and their functional significance in prostate cancer progression have not been fully characterized. PSMA was isolated from two metastatic prostate cancer cell lines, LNCaP and MDAPCa2b, which have different tissue tropism and localization. Isolated PSMA was trypsin-digested, and intact glycopeptides were subjected to LC-HCD-EThcD-MS/MS analysis on a Tribrid Orbitrap Fusion Lumos mass spectrometer. Differential qualitative and quantitative analysis of site-specific N-glycopeptides was performed using Byonic and Byologic software. Comparative quantitative analysis demonstrates that multiple glycopeptides at asparagine residues 51, 76, 121, 195, 336, 459, 476, and 638 were in significantly different abundance in the two cell lines (p < 0.05). Biochemical analysis using endoglycosidase treatment and lectin capture confirm the MS and site occupancy data. The data demonstrate the effectiveness of the strategy for comprehensive analysis of PSMA glycopeptides. This approach will form the basis of ongoing experiments to identify site-specific glycan changes in PSMA isolated from disease-stratified clinical samples to uncover targets that may be associated with disease progression and metastatic phenotypes.

Analysis of separate training and validation radical prostatectomy cohorts identifies 0.25 mm diameter as an optimal definition for "large" cribriform prostatic adenocarcinoma.

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.

Development and validation of a quantitative reactive stroma biomarker (qRS) for prostate cancer prognosis.

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.

Assessment of the Banff Working Group classification of definitive BK polyomavirus nephropathy.

Polyomavirus associated nephropathy (PyVAN) continues to be a burden in renal transplantation leading to allograft insufficiency or graft failure. A presumptive diagnosis of PyVAN is made based on the presence of BK polyomavirus in patients' plasma; however, kidney biopsy remains the gold standard to establish a definitive diagnosis. The Banff Working Group on PyVAN proposed a novel classification of definitive PyVAN based on polyomavirus replication/load level and the extent of interstitial fibrosis. The aim of our study was to test the newly defined classes of PyVAN using independent cohorts of 124 kidney transplant patients with PyVAN with respect to the initial presentation and outcome, and to compare our analysis to that previously reported. Detailed analysis of our cohort revealed that the proposed classification of PyVAN did not stratify or identify patients at increased risk of allograft failure. Specifically, while class 3 was associated with the worst prognosis, there was no significant difference between the outcomes in classes 1 and 2. We also found that the timing post-transplantation and inflammation in areas of interstitial fibrosis and tubular atrophy might be additional factors contributing to an unfavorable allograft outcome in patients with PyVAN.

Restriction Spectrum Imaging-Magnetic Resonance Imaging to Improve Prostate Cancer Imaging in Men on Active Surveillance.

PURPOSE: Restriction spectrum imaging-magnetic resonance imaging is a short duration enhanced diffusion-weighted technique that seeks to standardize sequences and predict upgrading. We test this technology for active surveillance biopsies. Our objective is to investigate the utility of restriction spectrum imaging-magnetic resonance imaging to improve upgrading detection in a prostate cancer active surveillance cohort. MATERIALS AND METHODS: We prospectively enrolled men on active surveillance undergoing repeat biopsy from January 2016 to June 2019. Subjects underwent prostate multiparametric magnetic resonance imaging and restriction spectrum imaging-magnetic resonance imaging reviewed by a urological radiologist for PI-RADS® scored lesions, followed by magnetic resonance imaging-guided prostate biopsy by a urologist. Restriction spectrum imaging-magnetic resonance imaging analysis with proprietary research software (CorTechs Labs, San Diego, California) generated a restricted signal map. We compared the restricted signal map and apparent diffusion coefficient values using T-test, ANOVA, and logistic regression analyses for prediction of upgrading. RESULTS: Of 123 enrolled men we identified 74 restriction spectrum imaging-magnetic resonance imaging regions of interest (targeted lesions) in 110 subjects, with 105 subjects completing biopsy. The restricted signal map was significant per PI-RADS score for true-positive lesion detection (mean difference 28, SD 0.7, p=0.001), and better than apparent diffusion coefficient (mean difference -15, SD 55, p=0.6). Restriction spectrum imaging generated restricted signal map values >50 improved sensitivity, specificity, positive predictive value and negative predictive value (81.0%, 81.8%, 54.2% and 94.2%) over PI-RADS ≥3 (71.4%, 38.9%, 23.7% and 83.7%, respectively) for Gleason upgrading. Overall restriction spectrum imaging is able to improve the AUC of 0.70 (95% CI 0.49-0.92, p=0.03) to 0.90 (95% CI 0.82-0.98, p <0.001). CONCLUSIONS: Restriction spectrum imaging-magnetic resonance imaging enhances the standard PI-RADS system by providing a noninvasive radiological biomarker to predict upgrading in active surveillance.

Collapsing Focal Segmental Glomerulosclerosis and Acute Oxalate Nephropathy in a Patient With COVID-19: A Double Whammy.

As COVID-19 (coronavirus disease 2019) spreads across the world multiple therapeutic interventions have been tried to reduce morbidity and mortality. We describe a case of collapsing focal sclerosing glomerulosclerosis (FSGS) and acute oxalate nephropathy in a patient treated with high-dose intravenous vitamin C for severe COVID-19 infection. Collapsing FSGS has been described in patients with COVID-19 infection associated with APOL-1; however, this case had collapsing FSGS developing in low-risk heterozygous APOL-1 variant, and we postulate that the intensity of the COVID-19 cytokine storm overwhelmed the protective state of APOL-1 heterozygosity. This case illustrates the importance of assessing the risk and benefit of planned therapeutic interventions on a case-by-case basis especially when there are still so many unknowns in the management of COVID-19 infection. Strong consideration should be given for performing a renal biopsy in patients who develop multifactorial acute kidney injury.

A copy number gain on 18q present in primary prostate tumors is associated with metastatic outcome.

BACKGROUND: Most prostate cancers (CaPs) grow slowly and remain indolent, yet some become aggressive and metastasize. Clinical decision-making requires prognostic markers that can be utilized at the time of diagnosis to identify aggressive tumors. Previous studies have shown a correlation between genomic alterations on the long arm of chromosome 18 (18q) and metastatic CaP. OBJECTIVE: The goal of this study was to comprehensively profile copy number alterations found on 18q in prostate tumors with varying outcomes to identify putative biomarkers associated with more aggressive disease METHODS: A custom comparative genomic hybridization array was created composed of high-density tiling of 18q sequences. Primary prostate tumor tissues were gathered from men who underwent radical prostatectomy and were categorized based on the patient's long-term clinical outcome as either metastatic disease (MET) or no evidence of disease (NED). DNA was isolated from formalin-fixed, paraffin-embedded prostatectomy tumor tissues, and analyzed for copy number variations (CNVs). Protein levels of genes found within the region of CNVs were analyzed using immunohistochemistry. RESULTS: Thirty-Four primary prostate tumors were analyzed: 17 NEDs and 17 METs. Two significant regions of copy number gains were found on 18q associated with outcome. One gain located at 18q11.2 was found exclusively in NED outcome tumors while another gain, located at 18q21.31, was found exclusively in MET outcome tumors (P -value< 0.0076). Immunohistochemistry analysis of protein levels showed more protein associated with copy number gain in the MET samples vs. those without the gain as indicated by H-scores of 184.7 and 121.0 respectively. CONCLUSIONS: The latter of these CNVs represent a putative biomarker for aggressive disease and highlights a putative metastasis promoting gene. Further study of known connections to CaP suggests that the paracaspase MALT1 is the most likely target of the copy number gain and represents a potential therapeutic target. Future studies would be of interest to determine MALT1's role in aggressive CaP and the ability of this CNV region to differentiate CaP that will eventually metastasize.

Copy number alterations are associated with metastatic-lethal progression in prostate cancer.

BACKGROUNDS: Aside from Gleason score few factors accurately identify the subset of prostate cancer (PCa) patients at high risk for metastatic progression. We hypothesized that copy number alterations (CNAs), assessed using CpG methylation probes on Illumina Infinium® Human Methylation450 (HM450K) BeadChip arrays, could identify primary prostate tumors with potential to develop metastatic progression. METHODS: Epigenome-wide DNA methylation profiling was performed in surgically resected primary tumor tissues from two cohorts of PCa patients with clinically localized disease who underwent radical prostatectomy (RP) as primary therapy and were followed prospectively for at least 5 years: (1) a Fred Hutchinson (FH) Cancer Research Center-based cohort (n = 323 patients); and (2) an Eastern Virginia (EV) Medical School-based cohort (n = 78 patients). CNAs were identified using the R package ChAMP. Metastasis was confirmed by positive bone scan, MRI, CT or biopsy, and death certificates confirmed cause of death. RESULTS: We detected 15 recurrent CNAs were associated with metastasis in the FH cohort and replicated in the EV cohort (p < 0.05) without adjusting for Gleason score in the model. Eleven of the recurrent CNAs were associated with metastatic progression in the FH cohort and validated in the EV cohort (p < 0.05) when adjusting for Gleason score. CONCLUSIONS: This study shows that CNAs can be reliably detected from HM450K-based DNA methylation data. There are 11 recurrent CNAs showing association with metastatic-lethal events following RP and improving prediction over Gleason score. Genes affected by these CNAs may functionally relate to tumor aggressiveness and metastatic progression.

DNA methylation profiles in African American prostate cancer patients in relation to disease progression.

This study examined whether differential DNA methylation is associated with clinical features of more aggressive disease at diagnosis and prostate cancer recurrence in African American men, who are more likely to die from prostate cancer than other populations. Tumor tissues from 76 African Americans diagnosed with prostate cancer who had radical prostatectomy as their primary treatment were profiled for epigenome-wide DNA methylation levels. Long-term follow-up identified 19 patients with prostate cancer recurrence. Twenty-three CpGs were differentially methylated (FDR q≤0.25, mean methylation difference≥0.10) in patients with vs. without recurrence, including CpGs in GCK, CDKL2, PRDM13, and ZFR2. Methylation differences were also observed between men with metastatic-lethal prostate cancer vs. no recurrence (five CpGs), regional vs. local pathological stage (two CpGs), and higher vs. lower tumor aggressiveness (one CpG). These results indicate that differentially methylated CpG sites identified in tumor tissues of African American men may contribute to prostate cancer aggressiveness.

A five-CpG DNA methylation score to predict metastatic-lethal outcomes in men treated with radical prostatectomy for localized prostate cancer.

BACKGROUND: Prognostic biomarkers for localized prostate cancer (PCa) could improve personalized medicine. Our group previously identified a panel of differentially methylated CpGs in primary tumor tissue that predict disease aggressiveness, and here we further validate these biomarkers. METHODS: Pyrosequencing was used to assess CpG methylation of eight biomarkers previously identified using the HumanMethylation450 array; CpGs with strongly correlated (r >0.70) results were considered technically validated. Logistic regression incorporating the validated CpGs and Gleason sum was used to define and lock a final model to stratify men with metastatic-lethal versus non-recurrent PCa in a training dataset. Coefficients from the final model were then used to construct a DNA methylation score, which was evaluated by logistic regression and Receiver Operating Characteristic (ROC) curve analyses in an independent testing dataset. RESULTS: Five CpGs were technically validated and all were retained (P < 0.05) in the final model. The 5-CpG and Gleason sum coefficients were used to calculate a methylation score, which was higher in men with metastatic-lethal progression (P = 6.8 × 10-6 ) in the testing dataset. For each unit increase in the score there was a four-fold increase in risk of metastatic-lethal events (odds ratio, OR = 4.0, 95%CI = 1.8-14.3). At 95% specificity, sensitivity was 74% for the score compared to 53% for Gleason sum alone. The score demonstrated better prediction performance (AUC = 0.91; pAUC = 0.037) compared to Gleason sum alone (AUC = 0.87; pAUC = 0.025). CONCLUSIONS: The DNA methylation score improved upon Gleason sum for predicting metastatic-lethal progression and holds promise for risk stratification of men with aggressive tumors. This prognostic score warrants further evaluation as a tool for improving patient outcomes.