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Background: The international Intermediate Clinical Endpoints in Cancer of the Prostate working group has established metastasis-free survival as a surrogate for overall survival in localised prostate cancer based on the findings of 19 predominantly radiotherapy-based trials. We sought to comprehensively assess aggregate trial-level performance of commonly reported intermediate clinical endpoints across all randomised trials in localised prostate cancer., Methods: For this meta-analysis, we searched PubMed for all trials in localised or biochemically recurrent prostate cancer published between Jan 1, 1970, and Jan 15, 2020. Eligible trials had to be randomised, therapeutic, reporting overall survival and at least one intermediate clinical endpoint, and with a sample size of at least 70 participants. Trials of metastatic disease were excluded. Intermediate clinical endpoints included biochemical failure, local failure, distant metastases, biochemical failure-free survival, progression-free survival, and metastasis-free survival. Candidacy for surrogacy was assessed using the second condition of the meta-analytical approach (ie, correlation of the treatment effect of the intermediate clinical endpoint and overall survival), using R 2 weighted by the inverse variance of the log intermediate clinical endpoint hazard ratio. The intermediate clinical endpoint was deemed to be a surrogate for overall survival if R 2 was 0·7 or greater., Findings: 75 trials (53 631 patients) were included in our analysis. Median follow-up was 9·1 years (IQR 5·7-10·6). Biochemical failure (R 2 0·38 [95% CI 0·11-0·64]), biochemical failure-free survival (R 2 0·12 [0·0030-0·33]), biochemical failure and clinical failure (R 2 0·28 [0·0045-0·65]), and local failure (R 2 0·085 [0·00-0·37]) correlated poorly with overall survival. Progression-free survival (R 2 0·46 [95% CI 0·22-0·67]) showed moderate correlation with overall survival, and metastasis-free survival (R 2 0·78 [0·59-0·89]) correlated strongly., Interpretation: Intermediate clinical endpoints based on biochemical and local failure did not meet the second condition of the meta-analytical approach and are not surrogate endpoints for overall survival in localised prostate cancer. Our findings validate metastasis-free survival as the only identified surrogate endpoint for overall survival to date., Funding: Prostate Cancer Foundation and National Institutes of Health., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

BackgroundProstate cancer exhibits biological and clinical heterogeneity even within established clinico-pathologic risk groups. The Decipher genomic classifier (GC) is a validated method to further risk-stratify disease in patients with prostate cancer, but its performance solely within National Comprehensive Cancer Network (NCCN) high-risk disease has not been undertaken to date.MethodsA multi-institutional retrospective study of 405 men with high-risk prostate cancer who underwent primary treatment with radical prostatectomy (RP) or radiation therapy (RT) with androgen-deprivation therapy (ADT) at 11 centers from 1995 to 2005 was performed. Cox proportional hazards models were used to determine the hazard ratios (HR) for the development of metastatic disease based on clinico-pathologic variables, risk groups, and GC score. The area under the receiver operating characteristic curve (AUC) was determined for regression models without and with the GC score.ResultsOver a median follow-up of 82 months, 104 patients (26%) developed metastatic disease. On univariable analysis, increasing GC score was significantly associated with metastatic disease ([HR]: 1.34 per 0.1 unit increase, 95% confidence interval [CI]: 1.19-1.50, p  0.05). On multivariable analysis, GC score (HR: 1.33 per 0.1 unit increase, 95% CI: 1.19-1.48, p

PURPOSE:Protein kinases are known to play a prominent role in oncogenic progression across multiple cancer subtypes, yet their role in prostate cancer progression remains underexplored. The purpose of this study was to identify kinases that drive prostate cancer progression.Experimental Design: To discover kinases that drive prostate cancer progression, we investigated the association between gene expression of all known kinases and long-term clinical outcomes in tumor samples from 545 patients with high-risk disease. We evaluated the impact of genetic and pharmacologic inhibition of the most significant kinase associated with metastatic progression in vitro and in vivo. RESULTS:DNA-dependent protein kinase (DNAPK) was identified as the most significant kinase associated with metastatic progression in high-risk prostate cancer. Inhibition of DNAPK suppressed the growth of both AR-dependent and AR-independent prostate cancer cells. Gene set enrichment analysis nominated Wnt as the top pathway associated with DNAPK. We found that DNAPK interacts with the Wnt transcription factor LEF1 and is critical for LEF1-mediated transcription. CONCLUSIONS:Our data show that DNAPK drives prostate cancer progression through transcriptional regulation of Wnt signaling and is an attractive therapeutic target in aggressive prostate cancer.

Purpose To determine whether cotargeting poly (ADP-ribose) polymerase-1 plus androgen receptor is superior to androgen receptor inhibition in metastatic castration-resistant prostate cancer (mCRPC) and whether ETS fusions predict response. Patients and Methods Patients underwent metastatic site biopsy and were stratified by ETS status and randomly assigned to abiraterone plus prednisone without (arm A) or with veliparib (arm B). Primary objectives were: confirmed prostate-specific antigen (PSA) response rate (RR) and whether ETS fusions predicted response. Secondary objectives were: safety, measurable disease RR (mRR), progression-free survival (PFS), and molecular biomarker analysis. A total of 148 patients were randomly assigned to detect a 20% PSA RR improvement. Results A total of 148 patients with mCRPC were randomly assigned: arm A, n = 72; arm B, n = 76. There were no differences in PSA RR (63.9% v 72.4%; P = .27), mRR (45.0% v 52.2%; P = .51), or median PFS (10.1 v 11 months; P = .99). ETS fusions did not predict response. Exploratory analysis of tumor sequencing (80 patients) revealed: 41 patients (51%) were ETS positive, 20 (25%) had DNA-damage repair defect (DRD), 41 (51%) had AR amplification or copy gain, 34 (43%) had PTEN mutation, 33 (41%) had TP53 mutation, 39 (49%) had PIK3CA pathway activation, and 12 (15%) had WNT pathway alteration. Patients with DRD had significantly higher PSA RR (90% v 56.7%; P = .007) and mRR (87.5% v 38.6%; P = .001), PSA decline ≥ 90% (75% v 25%; P = .001), and longer median PFS (14.5 v 8.1 months; P = .025) versus those with wild-type tumors. Median PFS was longer in patients with normal PTEN (13.5 v 6.7 months; P = .02), TP53 (13.5 v 7.7 months; P = .01), and PIK3CA (13.8 v 8.3 months; P = .03) versus those with mutation or activation. In multivariable analysis adjusting for clinical covariates, DRD association with PFS remained significant. Conclusion Veliparib and ETS status did not affect response. Exploratory analysis identified a novel DRD association with mCRPC outcomes.

Long noncoding RNAs (lncRNAs) are an emerging class of oncogenic molecules implicated in a diverse range of human malignancies. We recently identified SChLAP1 as a novel lncRNA that demonstrates outlier expression in a subset of prostate cancers, promotes tumor cell invasion and metastasis, and associates with lethal disease. Based on these findings, we sought to develop an RNA in situ hybridization (ISH) assay for SChLAP1 to 1) investigate the spectrum of SChLAP1 expression from benign prostatic tissue to metastatic castration-resistant prostate cancer and 2) to determine whether SChLAP1 expression by ISH is associated with outcome after radical prostatectomy in patients with clinically localized disease. The results from our current study demonstrate that SChLAP1 expression increases with prostate cancer progression, and high SChLAP1 expression by ISH is associated with poor outcome after radical prostatectomy in patients with clinically localized prostate cancer by both univariate (hazard ratio = 2.343, P = .005) and multivariate (hazard ratio = 1.99, P = .032) Cox regression analyses. This study highlights a potential clinical utility for SChLAP1 ISH as a novel tissue-based biomarker assay for outcome prognostication after radical prostatectomy.

BackgroundImproved clinical predictors for disease progression are needed for localised prostate cancer, since only a subset of patients develop recurrent or refractory disease after first-line treatment. Therefore, we undertook an unbiased analysis to identify RNA biomarkers associated with metastatic progression after prostatectomy.MethodsProstate cancer samples from patients treated with radical prostatectomy at three academic institutions were analysed for gene expression by a high-density Affymetrix GeneChip platform, encompassing more than 1 million genomic loci. In a discovery cohort, all protein-coding genes and known long non-coding RNAs were ranked by fold change in expression between tumours that subsequently metastasised versus those that did not. The top ranked gene was then validated for its prognostic value for metastatic progression in three additional independent cohorts. 95% of the gene expression assays were done in a Clinical Laboratory Improvements Amendments certified laboratory facility. All genes were assessed for their ability to predict metastatic progression by receiver-operating-curve area-under-the-curve analyses. Multivariate analyses were done for the primary endpoint of metastatic progression, with variables including Gleason score, preoperative prostate-specific antigen concentration, seminal vesicle invasion, surgical margin status, extracapsular extension, lymph node invasion, and expression of the highest ranked gene.Findings1008 patients were included in the study: 545 in the discovery cohort and 463 in the validation cohorts. The long non-coding RNA SChLAP1 was identified as the highest-ranked overexpressed gene in cancers with metastatic progression. Validation in three independent cohorts confirmed the prognostic value of SChLAP1 for metastatic progression. On multivariate modelling, SChLAP1 expression (high vs low) independently predicted metastasis within 10 years (odds ratio [OR] 2·45, 95% CI 1·70-3·53; p

Aims: Biphasic hyalinizing psammomatous (BHP) renal cell carcinoma (RCC) is a newly described emerging entity within the spectrum of papillary RCC in the WHO 2022 classification. Molecular analyses have discovered that BHP RCC consistently harbour somatic mutations in the neurofibromin 2 (NF2) gene. The NF2 gene product, merlin, is known to primarily function as a tumour suppressor. Merlin protein loss correlates closely with the presence of NF2 mutations in benign and malignant tumours arising in different sites. In the present study we explored the role of merlin immunohistochemistry (IHC) in tumours within the spectrum of BHP RCC to determine the diagnostic utility of this marker. Materials and Methods: We performed merlin IHC in 13 BHP RCC, 18 papillary RCC, 10 TFE3-translocation RCC, 15 TFEB-altered RCC (including 13 TFEB-rearranged and 2 TFEB-amplified), and 10 mucinous tubular and spindle cell carcinomas of unknown mutational status. Results: Unequivocal loss of merlin expression in >90% of the tumour cells was observed in 12/13 BHP-RCC (92%), with the remaining tumour demonstrating weak focal cytoplasmic expression in ~10% of the tumour. In contrast, merlin was diffusely or multifocally expressed in all papillary RCC, TFE3- translocation RCC, and TFEB-altered RCC, as well as in 70% of mucinous tubular and spindle carcinomas. Conclusions: In this study, merlin IHC was ~92% sensitive and ~94% specific for BHP RCC. These data suggest that merlin IHC is a reliable surrogate marker for the presence of underlying NF2 gene inactivation, being diagnostically useful to identify BHP RCC. Conclusions: In this study, merlin IHC was ~92% sensitive and ~94% specific for BHP RCC. These data suggest that merlin IHC is a reliable surrogate marker for the presence of underlying NF2 gene inactivation, being diagnostically useful to identify BHP RCC. [ABSTRACT FROM AUTHOR]

Background There is a critical need for improved prognostic discrimination in patients with renal cell carcinoma (RCC) given the increasing awareness that some patients may be managed with active surveillance, while others with higher-risk disease might benefit from adjuvant therapy following surgery. Objective To determine whether a multigene proliferation signature predicts long-term oncologic outcomes in surgically resected RCC. Design, setting, and participants The cell cycle proliferation (CCP) score was determined after radical nephrectomy for localized clear cell, papillary, or chromophobe RCC in 565 patients. Outcome measurements and statistical analysis The primary end point was disease-specific mortality (DSM), and disease recurrence was a secondary end point. Association with outcomes was evaluated by Cox proportional hazards survival analysis. The CCP score was compared with the Karakiewicz nomogram, and a composite (R-CCP) score was developed. Results and limitations A total of 68 patients (12%) recurred and 32 (6%) died of disease within 5 yr of nephrectomy. The CCP score was an independent predictor of recurrence (hazard ratio [HR] 1.50, 95% confidence interval [CI] 1.07–2.09) and DSM (HR 2.49, 95% CI 1.53–4.04) after adjusting for clinical variables using the baseline nomogram. The composite R-CCP score gave a Harrell's concordance index of 0.87 and stratified patients into low- ( n = 338) and high-risk ( n = 202) categories with 99% and 84% cancer-specific survival probabilities, respectively ( p < 0.001). Conclusions The CCP score is a significant, independent predictor of long-term oncologic outcomes in patients who have undergone nephrectomy for RCC. Combining the molecular classifier with baseline clinical variables allows for accurate, patient-specific risk assessment for use in guiding clinical management. Patient summary In this study, we sought to understand how well gene expression information from individual kidney tumors can predict cancer recurrence and death following surgical removal. We found that the combination of the gene expression test and clinical characteristics provides an accurate prognostic assessment to help inform clinical decisions. [ABSTRACT FROM AUTHOR]

Multiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of critical biomarkers for cancer invasion and disease aggressiveness. Although gene and protein expression have been extensively profiled in human tumours, little is known about the global metabolomic alterations that characterize neoplastic progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we profiled more than 1,126 metabolites across 262 clinical samples related to prostate cancer (42 tissues and 110 each of urine and plasma). These unbiased metabolomic profiles were able to distinguish benign prostate, clinically localized prostate cancer and metastatic disease. Sarcosine, an N-methyl derivative of the amino acid glycine, was identified as a differential metabolite that was highly increased during prostate cancer progression to metastasis and can be detected non-invasively in urine. Sarcosine levels were also increased in invasive prostate cancer cell lines relative to benign prostate epithelial cells. Knockdown of glycine-N-methyl transferase, the enzyme that generates sarcosine from glycine, attenuated prostate cancer invasion. Addition of exogenous sarcosine or knockdown of the enzyme that leads to sarcosine degradation, sarcosine dehydrogenase, induced an invasive phenotype in benign prostate epithelial cells. Androgen receptor and the ERG gene fusion product coordinately regulate components of the sarcosine pathway. Here, by profiling the metabolomic alterations of prostate cancer progression, we reveal sarcosine as a potentially important metabolic intermediary of cancer cell invasion and aggressivity. [ABSTRACT FROM AUTHOR]

Genomic biomarkers have the potential to better predict the outcome and select the most appropriate treatment for patients with kidney cancer; however, further research is needed before any of the biomarkers currently developed are adopted into clinical practice. Dramatic gains in our understanding of the molecular biology of clear cell renal cell carcinoma (ccRCC) have created a foundation for clinical translation to improve patient care. To review and contextualize clinically impactful data surrounding genomic biomarkers in ccRCC. A systematic literature search was conducted focusing on genomic-based biomarkers with an emphasis on studies assessing clinical outcomes. The advancement of tumor sequencing techniques has led to a rapid increase in the knowledge of the molecular underpinnings of ccRCC and with that the discovery of multiple candidate genomic biomarkers. These include somatic gene mutations such as VHL , PBRM1, SETD2, and BAP1 ; copy number variations; transcriptomic multigene signatures; and specific immune cell populations. Many of these biomarkers have been assessed for their association with survival and a smaller number as potential predictors of a response to systemic therapy. In this scoping review, we discuss many of these biomarkers in detail. Further studies are needed to continue to refine and validate these molecular tools for risk stratification, with the ultimate goal of improving clinical decision-making and patient outcomes. While no tissue or blood-based biomarkers for ccRCC have been incorporated into routine clinical practice to date, the field continues to expand rapidly. There remains a critical need to develop and validate these tools in order to improve the care for patients with kidney cancer. Genomic biomarkers have the potential to better predict outcome and select the most appropriate treatment for patients with kidney cancer; however, further research is needed before any of these currently developed biomarkers are adopted into clinical practice. [ABSTRACT FROM AUTHOR]

Prostate cancer is the most common type of tumor found in American men and is the second leading cause of cancer death in males. To identify biomarkers that distinguish prostate cancer from normal, we compared multiple gene expression profiling studies. Through meta-analysis of expression array data from multiple prostate cancer studies, we identified GOLM1 (Golgi membrane protein 1, Golm 1) as consistently up-regulated in clinically localized prostate cancer. This observation was confirmed by reverse transcription-polymerase chain reaction (RT-PCR) and validated at the protein level by immunoblot assay and immunohistochemistry. Prostate epithelial cells were identified as the cellular source of GOLM1 expression using laser capture microdissection. Immunohistochemical staining localized the GOLM1 signal to the subapical cytoplasmic region, typical of a Golgi distribution. Surprisingly, GOLM1 immunoreactivity was detected in the supernatants of prostate cell lines and in the urine of patients with prostate cancer. The mechanism by which intact GOLM1 might be released from cells has not yet been elucidated. GOLM1 transcript levels were measured in urine sediments using quantitative PCR on a cohort of patients presenting for biopsy or radical prostatectomy. We found that urinary GOLM1 mRNA levels were a significant predictor of prostate cancer. Further, GOLM1 outperformed serum prostate-specific antigen (PSA) in detecting prostate cancer. The area under the receiver-operating characteristic curve was 0.622 for GOLM1 (P = .0009) versus 0.495 for serum PSA (P = .902). Our data indicating the up-regulation of GOLM1 expression and its appearance in patients' urine suggest GOLM1 as a potential novel biomarker for clinically localized prostate cancer. [ABSTRACT FROM AUTHOR]

Molecular biomarkers aim to address the established limitations of clinicopathologic factors to accurately risk stratify patients with prostate cancer (PCa). Questions remain as to whether sufficient evidence supports adoption of these biomarkers for clinical use. To perform a systematic review of the available evidence supporting the clinical utility of the Decipher genomic classifier (GC). The review was performed as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines by searching PubMed and conference abstracts from January 2010 to June 2020. Evidence was then graded using the criteria of Simon et al (Simon RM, Paik S, Hayes DF. Use of archived specimens in evaluation of prognostic and predictive biomarkers. J Natl Cancer Inst 2009;101:1446–52) and American Urology Association (AUA) criteria. In total, 42 studies and 30 407 patients were included. GC performance data were available for localized, postprostatectomy, nonmetastatic castration-resistant, and metastatic hormone-sensitive PCa as part of retrospective studies (n = 12 141), prospective registries (n = 17 053), and prospective and post hoc randomized trial analyses (n = 1213). In 32 studies (n = 12 600), the GC was independently prognostic for all study endpoints (adverse pathology, biochemical failure, metastasis, and cancer-specific and overall survival) on multivariable analysis and improved the discrimination over standard of care in 24 studies (n = 8543). GC use changed the management in active surveillance (number needed to test [NNT] = 9) and postprostatectomy (NNT = 1.5–4) settings in five studies (n = 4331). Evidence strength was levels 1 and 2 by the Simon criteria for all disease states other than high-risk PCa, and grades A and B by AUA criteria depending on disease state. Consistent data are now present from diverse levels of evidence, which when viewed together, have demonstrated clinical utility of the GC in PCa. The utility of the GC is strongest for intermediate-risk PCa and postprostatectomy decision-making. In this paper, we review the evidence of the Decipher genomic classification tool for men with prostate cancer. We found consistent evidence that the test helps identify which cancers are more or less aggressive, which in turn aids in personalized treatment decision-making. The Decipher genomic classifier is a risk-stratification tool for men with prostate cancer that, when combined with standard clinicopathologic factors, demonstrates superior performance to clinicopathologic factors alone. This has been shown to change management in prospective trials and identify patients less likely to benefit from treatment intensification. [ABSTRACT FROM AUTHOR]

Management of bone metastasis remains clinically challenging and requires the identification of new molecular target(s) that can be therapeutically exploited to improve patient outcome. Galectin- 3 (Gal-3) has been implicated as a secreted factor that alters the bone microenvironment. Proteolytic cleavage of Gal-3 may also contribute to malignant cellular behaviors, but has not been addressed in cancer metastasis. Here, we report that Gal-3 modulates the osteolytic bone tumor microenvironment in the presence of RANKL. Gal-3 was localized on the osteoclast cell surface, and its suppression by RNAi or a specific antagonist markedly inhibited osteoclast differentiation markers, including tartrateresistant acid phosphatase, and reduced the number of mature osteoclasts. Structurally, the 158-175 amino acid sequence in the carbohydrate recognition domain (CRD) of Gal-3 was responsible for augmented osteoclastogenesis. During osteoclast maturation, Gal-3 interacted and colocalized with myosin-2A along the surface of cell-cell fusion. Pathologically, bone metastatic cancers expressed and released an intact form of Gal-3, mainly detected in breast cancer bone metastases, as well as a cleaved form, more abundant in prostate cancer bone metastases. Secreted intact Gal-3 interacted with myosin-2A, leading to osteoclastogenesis, whereas a shift to cleaved Gal-3 attenuated the enhancement in osteoclast differentiation. Thus, our studies demonstrate that Gal-3 shapes the bone tumor microenvironment through distinct roles contingent on its cleavage status, and highlight Gal-3 targeting through the CRD as a potential therapeutic strategy for mitigating osteolytic bone remodeling in the metastatic niche. [ABSTRACT FROM AUTHOR]

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

Background: New biomarkers, such as autoantibody signatures, may improve the early detection of prostate cancer. Methods: With a phage-display library derived from prostate-cancer tissue, we developed and used phage protein microarrays to analyze serum samples from 119 patients with prostate cancer and 138 controls, with the samples equally divided into training and validation sets. A phage-peptide detector that was constructed from the training set was evaluated on an independent validation set of 128 serum samples (60 from patients with prostate cancer and 68 from controls). Results: A 22-phage-peptide detector had 88.2 percent specificity (95 percent confidence interval, 0.78 to 0.95) and 81.6 percent sensitivity (95 percent confidence interval, 0.70 to 0.90) in discriminating between the group with prostate cancer and the control group. This panel of peptides performed better than did prostate-specific antigen (PSA) in distinguishing between the group with prostate cancer and the control group (area under the curve for the autoantibody signature, 0.93; 95 percent confidence interval, 0.88 to 0.97; area under the curve for PSA, 0.80; 95 percent confidence interval, 0.71 to 0.88). Logistic-regression analysis revealed that the phage-peptide panel provided additional discriminative power over PSA (P<0.001). Among the 22 phage peptides used as a detector, 4 were derived from in-frame, named coding sequences. The remaining phage peptides were generated from untranslated sequences. Conclusions: Autoantibodies against peptides derived from prostate-cancer tissue could be used as the basis for a screening test for prostate cancer. N Engl J Med 2005;353:1209-23. [ABSTRACT FROM AUTHOR]