Prostate Cancer Risk Stratification Research Articles

Circulating chromatin conformation signatures to enhance PSA positive predictive value and overall accuracy for prostate cancer detection.

e17016 Background: Prostate cancer (PCa) has a high lifetime prevalence (one out of six men), but currently there is no widely accepted screening programme. Widely used prostate specific antigen (PSA) test at cut-off of 3.0 ng/mL does not have sufficient accuracy for detection of any prostate cancer, resulting in numerous unnecessary prostate biopsies in men with benign disease and false reassurance in some men with PCa. We have recently identified circulating chromosome conformation signatures (CCSs, Episwitch PCa test) allowing PCa detection and risk stratification in line with standards of clinical PCa staging. The purpose of this study was to determine whether combining the Episwitch PCa test with the PSA test will increase its diagnostic accuracy. Methods: n = 109 whole blood samples of men enrolled in the PROSTAGRAM screening pilot study and n = 38 samples of patients with established PCa diagnosis and cancer-negative controls from Imperial College NHS Trust were used. Samples were tested for PSA, and the presence of CCSs in the loci encoding for of DAPK1, HSD3B2, SRD5A3, MMP1, and miRNA98 associated with high-risk PCa identified in our previous work. Results: PSA > 3 ng/mL alone showed a low positive predicted value (PPV) of 0.14 and a high negative predicted value (NPV) of 0.93. EpiSwitch alone showed a PPV of 0.91 and a NPV of 0.32. Combining PSA and Episwitch tests has significantly increased the PPV to 0.81 although reducing the NPV to 0.78. Furthermore, integrating PSA, as a continuous variable (rather than a dichotomised 3 ng/mL cut-off), with EpiSwitch in a new multivariant stratification model, Prostate Screening EpiSwitch (PSE) test, has yielded a remarkable combined PPV of 0.93 and NPV of 0.95 when tested on the independent prospective cohort. Conclusions: Our results demonstrate that combining the standard PSA readout with circulating chromosome conformations (PSE test) allows for significantly enhanced PSA PPV and overall accuracy for PCa detection. The PSE test is accurate, rapid, minimally invasive, and inexpensive, suggesting significant screening diagnostic potential to minimise unnecessary referrals for expensive and invasive MRI and/or biopsy testing, with further extended prospective blinded validation of the new combined signature in a screening cohort with low cancer prevalence as the next step for PSE adoption in PCa screening.

The value of DISCO and MUSE-DWI combined with prostate specific antigen density in the diagnosis and risk stratification of prostate cancer

Objective: To explore the value of differential subsampling with cartesian ordering (DISCO) and multiplexed sensitivity-encoding diffusion weighted-imaging (MUSE-DWI) combined with prostate specific antigen density (PSAD) in the diagnosis and risk stratification of prostate cancer (PCa). Methods: The data of 183 patients [aged from 48 to 86 (68±8) years] with prostate diseases in the General Hospital of Ningxia Medical University from July 2020 to August 2021 were retrospectively collected. Those patients were divided into non-PCa group (n=115) and PCa group (n=68) based on the disease condition. According to the risk degree, PCa group was subdivided into low risk PCa group (n=14) and medium-to-high risk PCa group (n=54). The differences of volume transfer constant (Ktrans), rate constant (Kep), extracellular volume fraction (Ve), apparent diffusion coefficient (ADC) and PSAD between groups were analyzed. Receiver operating characteristic (ROC) curves analysis were conducted for evaluating the diagnostic efficacy of quantitative parameters and PSAD in distinguishing non-PCa and PCa, low-risk PCa and medium-high risk PCa. Multivariate logistic regression model was used for screening out the predictors, which was statistically significant differences between non-PCa group and PCa group, for PCa prediction. Results: Ktrans, Kep, Ve and PSAD of PCa group all were higher than those of non-PCa group, and ADC value was lower than that of non-PCa group, and the differences all were statistically significant (all P<0.001). Ktrans, Kep and PSAD of medium-to-high risk PCa group all were higher than those of low risk PCa group, and ADC value was lower than that of low risk PCa group, and the differences were all statistically significant (all P<0.001). When distinguishing non-PCa from PCa, the area under ROC curve (AUC) of the combined model (Ktrans+Kep+Ve+ADC+PSAD) was higher than that of any single index [0.958 (95%CI: 0.918-0.982) vs 0.881 (95%CI: 0.825-0.924), 0.836 (95%CI: 0.775-0.887), 0.672 (95%CI: 0.599-0.740), 0.940(95%CI: 0.895-0.969), 0.816(95%CI:0.752-0.869), all P<0.05]. When distinguishing low-risk PCa and medium-to-high risk PCa, the AUC of the combined model (Ktrans+Kep+ADC+PSAD) were higher than those of Ktrans, Kep and PSAD[0.933 (95%CI: 0.845-0.979) vs 0.846 (95%CI:0.738-0.922), 0.782 (95%CI:0.665-0.873), 0.84 8(95%CI: 0.740-0.923), all P<0.05]. The multivariate logistic regression analysis showed that Ktrans (OR=1.005, 95%CI:1.001-1.010) and ADC values (OR=0.992, 95%CI:0.989-0.995) were predictors of PCa (P<0.05). Conclusions: DISCO and MUSE-DWI combined with PSAD can distinguish benign and malignant prostate lesions. Ktrans and ADC values were predictors of PCa; Ktrans, Kep, ADC values and PSAD are helpful in predicting the biological behavior of PCa.

Recommendations for patients with prostate cancer who wish to undergo a kidney transplant

Over the past half a century, kidney transplants have increased significantly and more patients that are elderly are receiving kidney transplants. As a result, the eligibility of patients with prostate cancer who wish to receive a kidney transplant has become a significant issue facing the transplant community. Many questions have arisen because prostate cancer is an extremely variable disease that many times do not harm the patients but at other times, can cause the death of the patient.If a patient has prostate cancer, should he be allowed to receive a kidney transplant? Should he receive the transplant after treatment for prostate cancer or without such treatment? How should the transplant community determine his eligibility? Most agree that those with high-risk prostate cancer should be treated first and have a waiting period prior to kidney transplant. Almost all low-risk prostate cancer patients are candidates for active surveillance. More and more urologists are doing active surveillance for favorable intermediate risk prostate cancer patients. We believe that all patients who are reasonable candidates for active surveillance based on the National Comprehensive Cancer Network (NCCN) guidelines for prostate cancer are reasonable candidates for kidney transplant without treatment for prostate cancer. We recommend using a combination of shared-decision making that involves prostate cancer risk-stratification as well as adjunctive tests such as imaging with multiparametric MRI (mpMRI) and genomic testing such as Decipher, Oncotype DX or Polaris, in order to inform whether or not patients with prostate cancer can receive a kidney transplant without treatment for prostate cancer.

PD-0164 The value of post Radiotherapy PSA dynamics for prostate cancer risk stratification models

PD-0164 The value of post Radiotherapy PSA dynamics for prostate cancer risk stratification models

Prognostic Values of Gene Copy Number Alterations in Prostate Cancer

Whilst risk prediction for individual prostate cancer (PCa) cases is of a high priority, the current risk stratification indices for PCa management have severe limitations. This study aimed to identify gene copy number alterations (CNAs) with prognostic values and to determine if any combination of gene CNAs could have risk stratification potentials. Clinical and genomic data of 500 PCa cases from the Cancer Genome Atlas stable were retrieved from the Genomic Data Commons and cBioPortal databases. The CNA statuses of a total of 52 genetic markers, including 21 novel markers and 31 previously identified potential prognostic markers, were tested for prognostic significance. The CNA statuses of a total of 51/52 genetic markers were significantly associated with advanced disease at an odds ratio threshold of ≥1.5 or ≤0.667. Moreover, a Kaplan-Meier test identified 27/52 marker CNAs which correlated with disease progression. A Cox Regression analysis showed that the amplification of MIR602 and deletions of MIR602, ZNF267, MROH1, PARP8, and HCN1 correlated with a progression-free survival independent of the disease stage and Gleason prognostic group grade. Furthermore, a binary logistic regression analysis identified twenty-two panels of markers with risk stratification potentials. The best model of 7/52 genetic CNAs, which included the SPOP alteration, SPP1 alteration, CCND1 amplification, PTEN deletion, CDKN1B deletion, PARP8 deletion, and NKX3.1 deletion, stratified the PCa cases into a localised and advanced disease with an accuracy of 70.0%, sensitivity of 85.4%, specificity of 44.9%, positive predictive value of 71.67%, and negative predictive value of 65.35%. This study validated prognostic gene level CNAs identified in previous studies, as well as identified new genetic markers with CNAs that could potentially impact risk stratification in PCa.

Risk Stratification of Low-risk Prostate Cancer: Individualizing Care in the Era of Active Surveillance.

While active surveillance is the preferred management for most men with low-risk prostate cancer, a subset may harbor more aggressive disease. In this review we examine the evidence underlying an accurate and nuanced assessment of oncologic risk in these men. We performed a nonsystematic literature review current to January 2023 on PubMed for articles relating to clinical, pathological, molecular, and imaging-based modalities available for risk assessment in men with low-risk prostate cancer. Relevant articles were reviewed by the authors and evidence was summarized. Many tools are available to personalize clinical decision-making for men with low-risk prostate cancer. Total volume of cancer, PSA density, and presence of ductal components have been consistently and strongly associated with current or future evidence of higher-grade disease. PSA kinetics, Prostate Imaging Reporting & Data System 4/5 lesions on MRI, perineural invasion, germline mutations, and genomic classifiers all appear to be associated with an increased risk, although are not as extensively validated. Race, percent free PSA, and other serum biomarkers such as Prostate Health Index and 4Kscore do not appear to be associated with long-term elevated risk. Long-term prognosis for men diagnosed with low-risk prostate cancer is excellent. There are many factors which should be routinely integrated into the initial management decision as well as determining intensity and frequency of active surveillance. Development of comprehensive multivariable instruments to guide clinical decisions is encouraged.

Abstract 5839: Novel stroma-derived prostate cancer subtypes are associated with risk of clinical progression

Abstract The tumor microenvironment influences prostate cancer aggressiveness, and by focusing on how different changes to the microenvironment can affect the cancer, we aimed to identify novel stromal subtypes in localized prostate cancer (LPC), characterize these subtypes, and utilize subtypes to increase accuracy in prostate cancer risk stratification. Subtype identification was conducted using non-negative matrix factorization with consensus clustering on a stroma-specific expression signature in RNA sequencing data. A discovery cohort (127 LPC patients) and two independent validation cohorts (406 LPC &amp; 126 LPC patients) were used for subtype identification. All three cohorts were subsequently used for subtype characterization and prognostic evaluation. Identified subtypes were characterized by evaluation of clinical characteristics, by gene set enrichment analysis, and by cell-type deconvolution analysis. Survival differences between subtypes were assessed using Kaplan-Meier and univariate Cox regression analyses with biochemical recurrence (BCR) as endpoint. Lastly, a high-risk stromal subtype was investigated for its ability to improve risk stratification for intermediate risk prostate cancer using hazard ratio changes from univariate Cox regression analysis. We identified three stromal subtypes (S1-S3) in prostate cancer. Of these, subtype S3 showed characteristics of a highly reactive stromal environment with significantly (adj. p &amp;lt; 0.05) decreased cell polarity and stroma related functions, significantly (adj. p &amp;lt; 0.05) reduced fibroblast infiltration, and a significantly (adj. p &amp;lt; 0.05) increased immune cells infiltration compared to the other subtypes. Survival analysis also revealed significant (p &amp;lt; 0.05) association of S3 with BCR in all three cohorts (HR = 3.2, 2.1, and 3.4 in cohorts 1, 2 and 3 respectively). Lastly, S3 significantly (p &amp;lt; 0.05) improved the risk prediction for patients with intermediate recurrence risk according to the clinical nomogram CAPRA-S (cohort 1, delta HR = 1.4; cohort 2, delta HR = 2.3; cohort 3, delta HR = 4.2). In conclusion, by focusing on the stromal alteration in prostate cancer, this study sheds new light on the influence of tumor microenvironment on LPC aggressiveness. A stromal subtype characterized by dysregulated stromal functions and changes in stroma and immune cells infiltration predicted adverse outcome in patients with a high prognostic ambiguity. This utilization of stromal information to improve risk assessment for clinically intermediate risk PC indicates a potential use in future evaluation of PC aggressiveness. Citation Format: Martin Rasmussen, Jacob Fredsøe, Paul V. Salachan, Marcus P. Blanke, Benedicte P. Ulhøi, Michael Borre, Karina D. Sørensen. Novel stroma-derived prostate cancer subtypes are associated with risk of clinical progression. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5839.

Identification of a prognostic biomarker predicting biochemical recurrence and construction of a novel nomogram for prostate cancer.

Biochemical recurrence (BCR) is common in prostate cancer (PCa), but its prediction is based predominantly on clinicopathological characteristics with low accuracy. We intend to identify a potential prognostic biomarker related to the BCR and construct a nomogram for improving the risk stratification of PCa patients. The transcriptome and clinical data of PCa patients were obtained from TCGA and GEO databases. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were used to screen out differentially expressed genes (DEGs) related to the BCR of PCa. Cox regression analysis was further applied to screen out DEGs related to BCR-free survival (BFS). Time-dependent receiver operating curve (ROC) analysis and Kaplan-Meier (K-M) survival analysis were conducted to assess the prognostic value. Then, a prognostic nomogram was established and evaluated. The clinicopathological correlation analysis, GSEA analysis, and immune analysis were used to explore the biological and clinical significance of the biomarker. Finally, the qRT-PCR, western blotting, and immunohistochemistry (IHC) were conducted to validate the expression of the biomarker. BIRC5 was identified to be the potential prognostic biomarker. The clinical correlation analysis and K-M survival analysis found that the BIRC5 mRNA expression was positively associated with disease progression and negatively associated with the BFS rate. Time-dependent ROC curves verified its accurate prediction performance. The GSEA and immune analysis suggested that the BIRC5 was related to immunity. A nomogram with an accurate prediction for BFS of PCa patients was constructed. qRT-PCR, western blotting, and IHC results validated the expression level of BIRC5 in PCa cells and tissues. Our study identified BIRC5 as a potential prognostic biomarker related to BCR of PCa and constructed an efficacy nomogram for predicting BFS to assist clinical decision-making.

MP17-04 IMPACT OF TISSUE-BASED GENOMIC TESTING ON PAYMENTS FOR PROSTATE CANCER CARE

You have accessJournal of UrologyCME1 Apr 2023MP17-04 IMPACT OF TISSUE-BASED GENOMIC TESTING ON PAYMENTS FOR PROSTATE CANCER CARE Benjamin Croll, Dattatraya Patil, Sagar Patel, and Christopher Filson Benjamin CrollBenjamin Croll More articles by this author , Dattatraya PatilDattatraya Patil More articles by this author , Sagar PatelSagar Patel More articles by this author , and Christopher FilsonChristopher Filson More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003237.04AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Tissue-based genomic biomarkers have been approved for use in risk-stratification of prostate cancer for more than a decade. Prior cost analyses relied on simulation modeling of artificial cohorts, and there has been limited research on real-world expenditures. We assessed 12-month post-biopsy healthcare payments to compare payer expenditures for prostate cancer patients who did and did not receive post-biopsy tissue-based genomic testing. METHODS: We used IBM MarketScan Commercial Claims and Medicare Supplemental data to identify newly-diagnosed patients (2018–2019). Inflation-adjusted total healthcare payments were calculated in the 12-month period following diagnostic biopsy. Outliers with the top and bottom 2.5% percentile of total payments were excluded. Multivariable linear regression was conducted to estimate the effect of receiving genomic testing (Oncotype DX, Prolaris, and Decipher) on payments, after controlling for treatment modality, insurance status, and other demographic information. We stratified our analysis based on treatment received. RESULTS: We identified 10,859 patients in our cohort (9,242 privately-insured; 1,617 Medicare eligible). Among this group, 24% received radiation therapy (RT), 44% had radical prostatectomy (RP), and 33% had no identified treatment (AS/WW/NT). Genomic testing was more common in 2019 than 2018 (6.9% vs. 3.5%, p<.001) and was more common in the AS/WW/NT group (8.3%) than those treated with RT (3.4%) or RP (3.9%), p<.001. Median payments for each genomic test ranged from $2,156-3,873. Prediction modeling based on multivariable analysis demonstrated that genomic testing is associated with payment differences ranging from -$119 to +$494 in individual treatment groups (Figure 1). CONCLUSIONS: Use of tissue-based genomic testing is associated with significant expense. Despite this expense, their use was associated with similar total payments across treatment groups, with the greatest savings ($119) in Medicare patients receiving RT and the greatest expense in Medicare patients undergoing RP ($494). Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e213 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Benjamin Croll More articles by this author Dattatraya Patil More articles by this author Sagar Patel More articles by this author Christopher Filson More articles by this author Expand All Advertisement PDF downloadLoading ...

Review of Active Surveillance in Underrepresented and High-Risk Populations: Feasibility and Safety.

The purpose of this review is to investigate the current use and effectiveness of active surveillance (AS) for clinical low-risk prostate cancer (PCa) in men considered to be "high-risk" based on the factors of race, genetics, healthcare access, and socioeconomic status. Advances in molecular biomarkers and imaging have improved the detection, risk stratification, and treatment of PCa. Still, overdiagnosis and overtreatment of indolent disease remain a concern. AS is therefore the preferred option for clinical low-risk disease. Yet, because of the variability in PCa presentation based on the aforementioned environmental and genetic factors, the question remains: Is active surveillance a safe option for everyone? Provider hesitancy should not necessarily exclude high-risk men from participating in AS. Rather, clinicians should employ shared decision-making, sound clinical judgment, and stringent follow-up in order to effectively counsel AS candidates and optimize AS-related outcomes in "high-risk" individuals.

Serum Thymidine Kinase 1 - Potential Prostate Cancer Biomarker: A Clinical Study.

Serum thymidine kinase 1 (STK1) is a proliferation biomarker that has been used as a diagnostic marker of several malignant diseases. However, there are limited data for prostate cancer (PCa). In this study, we retrospectively analysed serum samples from 169 patients with biopsy confirmed PCa, who had been indicated for radical prostatectomy (RP) between 2013-2016. The results were compared with those in serum samples from 39 healthy men. We used commercially available enzymatic immunoassay to determine the levels of STK1. The patients were divided into groups according to the Gleason score (GS) and risk factors for adjuvant radiotherapy (aRT), which were defined as GS 8-10, pT3, and a positive surgical margin. The median serum level of STK1 in PCa patients was 0.289 pmol/l. In the control group, the median value was 0.0116 pmol/l (p<0.001). By comparing the patients with GS≤6 vs. 7 vs. ≥8 (p=0.01), we found statistically significant differences. In the correlation of STK1 values with risk factors, we found statistically significant differences both in comparison of 0 vs. 1 vs. 2 vs. 3 risk factors (p=0.021), as well as ≤1 vs. 2≥ risk factors (p=0.009). The levels of STK1 are significantly higher in patients with PCa than those in healthy controls. Furthermore, STK1 values correlate with GS and predefined risk factors for aRT. Therefore, STK1 can be considered as a potential tumour marker of PCa diagnosis and risk stratification.

Chromosome-specific segment size alterations are determinants of prognosis in prostate cancer

Currently, risk stratification is the most difficult problem in prostate cancer (PCa) management. Gleason grading cannot adequately predict cancer progression. This study aimed to identify chromosome-specific segment size alterations that could aid risk stratification and predict metastasis using a retrospective cohort-study strategy. A binary logistic regression model was generated using 16 chromosome-specific segments with size alterations (deletions and amplifications) that showed associations with disease stage (primary versus metastatic). The regression model was trained with the MSKCC PIK3R1 PCa cohort (n = 1417), and validated with the TCGA Firehose Legacy (n = 500), MSKCC Prostate Oncogenome Project (n = 218), and the SU2C/PCF Dream Team (n = 150) PCa cohorts. Furthermore, the capacity of the model to predict metastasis between primary tumours with metastasis (n = 54) and primary tumours without metastasis (n = 54) was tested. The accuracy, sensitivity, and specificity of the model at disease stage stratification ranged from 69.02% to 88.55%, 72.8% to 86.00% and 66.30% to 89.50%, respectively. The model also showed good performance at metastasis prediction with accuracy, sensitivity, and specificity of 57.41%, 62.96% and 51.85%, respectively. The study conclusion was that chromosome-specific segment size alterations can aid risk stratification and metastasis prediction. The significance of the study findings is that in combinations with clinical, biochemical, and histopathological variables, chromosome-specific alterations could improve current risk stratification and prediction models for PCa.

The Use of MRI-Derived Radiomic Models in Prostate Cancer Risk Stratification: A Critical Review of Contemporary Literature

The development of precise medical imaging has facilitated the establishment of radiomics, a computer-based method of quantitatively analyzing subvisual imaging characteristics. The present review summarizes the current literature on the use of diagnostic magnetic resonance imaging (MRI)-derived radiomics in prostate cancer (PCa) risk stratification. A stepwise literature search of publications from 2017 to 2022 was performed. Of 218 articles on MRI-derived prostate radiomics, 33 (15.1%) generated models for PCa risk stratification. Prediction of Gleason score (GS), adverse pathology, postsurgical recurrence, and postradiation failure were the primary endpoints in 15 (45.5%), 11 (33.3%), 4 (12.1%), and 3 (9.1%) studies. In predicting GS and adverse pathology, radiomic models differentiated well, with receiver operator characteristic area under the curve (ROC-AUC) values of 0.50-0.92 and 0.60-0.92, respectively. For studies predicting post-treatment recurrence or failure, ROC-AUC for radiomic models ranged from 0.73 to 0.99 in postsurgical and radiation cohorts. Finally, of the 33 studies, 7 (21.2%) included external validation. Overall, most investigations showed good to excellent prediction of GS and adverse pathology with MRI-derived radiomic features. Direct prediction of treatment outcomes, however, is an ongoing investigation. As these studies mature and reach potential for clinical integration, concerted effort to validate these radiomic models must be undertaken.

The role of [18F]-DCFPyL PET/MRI radiomics for pathological grade group prediction in prostate cancer.

To evaluate the diagnostic accuracy of [18F]-DCFPyL PET/MRI radiomics for the prediction of pathological grade group in prostate cancer (PCa) in therapy-naïve patients. Patients with confirmed or suspected PCa, who underwent [18F]-DCFPyL PET/MRI (n = 105), were included in this retrospective analysis of two prospective clinical trials. Radiomic features were extracted from the segmented volumes following the image biomarker standardization initiative (IBSI) guidelines. Histopathology obtained from systematic and targeted biopsies of the PET/MRI-detected lesions was the reference standard. Histopathology patterns were dichotomized as ISUP GG 1-2 vs. ISUP GG ≥ 3 categories. Different single-modality models were defined for feature extraction, including PET- and MRI-derived radiomic features. The clinical model included age, PSA, and lesions' PROMISE classification. Single models, as well as different combinations of them, were generated to calculate their performances. A cross-validation approach was used to evaluate the internal validity of the models. All radiomic models outperformed the clinical models. The best model for grade group prediction was the combination of PET + ADC + T2w radiomic features, showing sensitivity, specificity, accuracy, and AUC of 0.85, 0.83, 0.84, and 0.85, respectively. The MRI-derived (ADC + T2w) features showed sensitivity, specificity, accuracy, and AUC of 0.88, 0.78, 0.83, and 0.84, respectively. PET-derived features showed 0.83, 0.68, 0.76, and 0.79, respectively. The baseline clinical model showed 0.73, 0.44, 0.60, and 0.58, respectively. The addition of the clinical model to the best radiomic model did not improve the diagnostic performance. The performances of MRI and PET/MRI radiomic models as per the cross-validation scheme yielded an accuracy of 0.80 (AUC = 0.79), whereas clinical models presented an accuracy of 0.60 (AUC = 0.60). The combined [18F]-DCFPyL PET/MRI radiomic model was the best-performing model and outperformed the clinical model for pathological grade group prediction, indicating a complementary value of the hybrid PET/MRI model for non-invasive risk stratification of PCa. Further prospective studies are required to confirm the reproducibility and clinical utility of this approach.

Geographic variation of decipher genomic classifier in patients with early prostate cancer.

376 Background: External factors such as environmental or lifestyle-related exposure may influence genomic composition of cancer, and therefore its progression and outcome. Thus geographic data is of importance. Decipher is a gene expression classifier used in risk stratification of early non metastatic prostate cancer. Currently, there are no data reporting geographic variation of the test. We aimed to analyze Decipher genomic score results among Israeli patients, in comparison to American patients. Methods: The Decioher database (Decipher Biosciences Inc) contains data from patients who have given consent for broad data-sharing. We identified and analyzed Decipher test results ordered among Israeli patients with localized prostate cancer. Matched analysis to the US population was done. Results: 144 patients (median age 69.5, range 64-74) were included in the present analysis. The clinical NCCN risk grouping was low in 42.4% (n=61), favorable intermediate in 38.9% (n=56), unfavorable intermediate in 17.4% (n=25), and high risk in 1.4% (n=2). Physicians primarily obtained Decipher for low-intermediate NCCN risk. Median Decipher score was 0.57 (Q1 0.385, Q3 0.823). Decipher risk grouping was low in 38.1% (n=61), intermediate in 16.9% (n=27), and high in 45% (n=72). Median Decipher score increased with Grade Group. 46% of NCCN low risk patients had a higher risk as per Decipher. 82% of NCCN favorable intermediate and unfavorable intermediate risk were reclassified to lower or higher risk. 9% of NCCN high risk patients had a lower risk as per Decipher. The present study cohort had a higher proportion of higher Decipher scores than observed in similar grade US population (n=43065) in the Decipher database (Median 0.43, Q1 0.27, Q3 0.66; 52%/18%/30% with low/intermediate/high risk). Conclusions: The preliminary results of the present study suggest a higher proportion of high risk Decipher among Israeli patients with early prostate cancer. These results should be interpreted cautiously. The study and further data collection are ongoing.

Identification of miR-1-3p, miR-143–3p and miR-145–5p association with bone metastasis of Gleason 3+4 prostate cancer and involvement of LASP1 regulation

Gleason Score (GS) 3 + 4 prostate cancer (PCa) is heterogeneous in clinical course and molecular features. Risk stratification of indolent and aggressive PCa with GS 3 + 4 is critical, especially those with bone metastasis (BM) potential. Microarray-based microRNA(miRNA) profiling with eight PCa cases with or without BM was used to screen the candidate miRNAs associated with BM. Transwell and MTS assays were used to characterize the function of miRNAs and target gene LASP1. RT-qPCR and immunohistochemistry assays were utilized to illustrate the clinical significance of miRNAs and target gene in a cohort of 309 Chinese PCa cases. In the current study, we identified that miR-1-3p, miR-143–3p and miR-145–5p are associated with BM of GS 3 + 4 PCa. Through functional experiments, we show that miR-1-3p/143–3p/145–5p promotes proliferation and migration of PCa in vitro. LASP1 was predicted as the common target of these three miRNAs which was further confirmed by a luciferase assay. Overexpression of LASP1 was correlated with higher GS, higher pathological stage, and the presence of metastasis by immunohistochemistry. siRNA knockdown of LASP1 significantly suppressed proliferation and migration, whereas overexpression of LASP1 promoted it. Bioinformatics analysis revealed the involvement of Wnt signaling pathway in LASP1 mediated function. LASP1 may activate Wnt signaling by interacting with β-catenin. In all, we suggest that miR-1-3p/143–3p/145–5p are associated with BM of Gleason 3 + 4 PCa. LASP1 is the common target of these miRNAs and may active Wnt signaling by interacting with β-catenin.

Radical Prostatectomy without Prior Biopsy in Patients with High Suspicion of Prostate Cancer Based on Multiparametric Magnetic Resonance Imaging and Prostate-Specific Membrane Antigen Positron Emission Tomography: A Prospective Cohort Study

Modern risk stratification of prostate cancer (PCa) allows for prediction of advanced disease with a high level of certainty. We aimed to evaluate a prospective series of patients undergoing radical prostatectomy without prior biopsy based solely on clinical criteria and imaging results. The patients were divided into three groups. Group 1 included 27 patients with: (i) suspicious digital rectal examination, (ii) PSA ≥ 10 ng/mL, (iii) PI-RADS 4/5 on mpMRI, and (iv) high suspicion of PCa on PSMA-PET. Group 2 included six patients who fulfilled criteria i, ii, and iii but did not undergo PSMA-PET imaging. Group 3 included 17 patients with at least one clinical (i or ii) and one imaging (iii or iv) criterion. All of the patients were diagnosed with PCa. Comparison of Group 1 and 2 versus Group 3 showed a significantly higher ratio of locally advanced PCa for Groups 1 and 2 compared to Group 3 (60.6% versus 11.8%, p = 0.005, respectively). Similarly, these patients displayed a significantly higher ratio of aggressive PCa (ISUP grade > 2: 66.7% versus 23.5%, p = 0.027, respectively) and tumor infiltration (median tumor infiltration: 32.5% vs. 15%, p = 0.001, respectively) in the final specimen compared to Group 3. In conclusion, we have shown that radical prostatectomy without prior biopsy is safe in terms of the diagnosis of clinically significant PCa when proper preoperative risk stratification involving mpMRI and PSMA-PET imaging is applied.

Adverse Pathology after Radical Prostatectomy of Patients Eligible for Active Surveillance-A Summary 7 Years after Introducing mpMRI-Guided Biopsy in a Real-World Setting.

Over the last decade, active surveillance (AS) of low-risk prostate cancer has been increasing. The mpMRI fusion-guided biopsy of the prostate (FBx) is considered to be the gold standard in preoperative risk stratification. However, the role of FBx remains unclear in terms of risk stratification of low-risk prostate cancer outside high-volume centers. The aim of this study was to evaluate adverse pathology after radical prostatectomy (RP) in a real-world setting, focusing on patients diagnosed with Gleason score (GS) 6 prostate cancer (PCa) and eligible for AS by FBx. Between March 2015 and March 2022, 1297 patients underwent FBx at the Department of Urology, Ludwig-Maximilians-University of Munich, Germany. MpMRI for FBx was performed by 111 different radiology centers. FBx was performed by 14 urologists from our department with different levels of experience. In total, 997/1297 (77%) patients were diagnosed with prostate cancer; 492/997 (49%) of these patients decided to undergo RP in our clinic and were retrospectively included. Univariate and multivariable logistic regression analyses were performed to evaluate clinical and histopathological parameters associated with adverse pathology comparing FBx and RP specimens. To compare FBx and systematic randomized biopsies performed in our clinic before introducing FBx (SBx, n = 2309), we performed a propensity score matching on a 1:1 ratio, adjusting for age, number of positive biopsy cores, and initial PSA (iPSA). A total of 492 patients undergoing FBx or SBx was matched. In total, 55% of patients diagnosed with GS 6 by FBx were upgraded to clinically significant PCa (defined as GS ≥ 7a) after RP, compared to 52% of patients diagnosed by SBx (p = 0.76). A time delay between FBx and RP was identified as the only correlate associated with upgrading. A total of 5.9% of all FBx patients and 6.1% of all SBx patients would have been eligible for AS (p > 0.99) but decided to undergo RP. The positive predictive value of AS eligibility (diagnosis of low-risk PCa after biopsy and after RP) was 17% for FBx and 6.7% for SBx (p = 0.39). In this study, we show, in a real-world setting, that introducing FBx did not lead to significant change in ratio of adverse pathology for low-risk PCa patients after RP compared to SBx.

Comparison and combination of amide proton transfer magnetic resonance imaging and the apparent diffusion coefficient in differentiating the grades of prostate cancer.

More effective risk stratification of prostate cancer (PCa) than that possible with current methods can reduce undertreatment and guard against overtreatment. The aim of this study is to validate the differences and combined effects of amide proton transfer (APT) imaging and apparent diffusion coefficient (ADC) in discriminating the PCa grade group (GG) ≤2 from GG ≥3 PCa. This is an ongoing prospective study conducted in the radiology department of Nanxishan Hospital of Guangxi Zhuang Autonomous Region. Patients pathologically diagnosed with PCa were enrolled consecutively according to the eligibility criteria. A total of 180 patients (age range, 42-92 years) were included in this study. Using histopathology as the reference standard, we placed 71 cases in GG ≤2 (mean age 67.03±8.696 years) and 109 cases in GG ≥3 (age 69.60±9.638 years). Magnetic resonance imaging (MRI) parameters, including APT and ADC values, were analyzed using an independent samples t-test and binary logistic regression analysis stratified with GG. Receiver operating characteristic curve was used to analyze the diagnostic performance for different parameters distinguishing GG ≤2 and GG ≥3. APT [odds ratio (OR) for the transitional zone (TZ) PCa: 3.20, 95% CI: 1.14-8.98, P=0.02; OR for the peripheral zone (PZ) PCa: 86.32, 95% CI: 13.24-562.88, P=0.003] and ADC values (OR for TZ PCa: 89.79; 95% CI: 2.85-2,827.99, P=0.01; OR for PZ PCa: 39.92; 95% CI: 3.22-494.18, P=0.004) were independent predictors that differentiated the GG of patients. The sensitivity and specificity of the APT values were 61.1% and 81.0%, respectively, while the sensitivity and specificity of the ADC values were 83.3% and 61.9%, respectively. The optimal cutoff value of APT was 3.35% and which of ADC was 1.25×10-3 mm2/s in TZ origin PCa. At the optimal cutoff values of 3.31% (APT) and 0.79×10-3 mm2/s (ADC) in PZ PCa, the sensitivity and specificity of the APT values were 74.0% and 83.6%, respectively, while the sensitivity and specificity of the ADC values were 94.0% and 53.4%, respectively. The area under the curve of the combination of APT and ADC was significantly higher than either of APT or ADC alone in Delong test (TZ: P=0.002 and P=0.020; PZ: P=0.033 and P<0.001). APT and ADC have complementary effects on the sensitivity and specificity for identifying different PCa GGs. A combination model of APT and ADC could improve the diagnostic efficacy of PCa differentiation.

Circulating Chromosome Conformation Signatures Significantly Enhance PSA Positive Predicting Value and Overall Accuracy for Prostate Cancer Detection.

Prostate cancer (PCa) has a high lifetime prevalence (one out of six men), but currently there is no widely accepted screening programme. Widely used prostate specific antigen (PSA) test at cut-off of 3.0 ng/mL does not have sufficient accuracy for detection of any prostate cancer, resulting in numerous unnecessary prostate biopsies in men with benign disease and false reassurance in some men with PCa. We have recently identified circulating chromosome conformation signatures (CCSs, Episwitch® PCa test) allowing PCa detection and risk stratification in line with standards of clinical PCa staging. The purpose of this study was to determine whether combining the Episwitch PCa test with the PSA test will increase its diagnostic accuracy. n = 109 whole blood samples of men enrolled in the PROSTAGRAM screening pilot study and n = 38 samples of patients with established PCa diagnosis and cancer-negative controls from Imperial College NHS Trust were used. Samples were tested for PSA, and the presence of CCSs in the loci encoding for of DAPK1, HSD3B2, SRD5A3, MMP1, and miRNA98 associated with high-risk PCa identified in our previous work. PSA > 3 ng/mL alone showed a low positive predicted value (PPV) of 0.14 and a high negative predicted value (NPV) of 0.93. EpiSwitch alone showed a PPV of 0.91 and a NPV of 0.32. Combining PSA and Episwitch tests has significantly increased the PPV to 0.81 although reducing the NPV to 0.78. Furthermore, integrating PSA, as a continuous variable (rather than a dichotomised 3 ng/mL cut-off), with EpiSwitch in a new multivariant stratification model, Prostate Screening EpiSwitch (PSE) test, has yielded a remarkable combined PPV of 0.92 and NPV of 0.94 when tested on the independent prospective cohort. Our results demonstrate that combining the standard PSA readout with circulating chromosome conformations (PSE test) allows for significantly enhanced PSA PPV and overall accuracy for PCa detection. The PSE test is accurate, rapid, minimally invasive, and inexpensive, suggesting significant screening diagnostic potential to minimise unnecessary referrals for expensive and invasive MRI and/or biopsy testing. Further extended prospective blinded validation of the new combined signature in a screening cohort with low cancer prevalence would be the recommended step for PSE adoption in PCa screening.