Spatially resolved clonal copy number alterations in benign and malignant tissue.

Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

Histomic and transcriptomic features of MRI-visible and invisible clinically significant prostate cancers are associated with prognosis.

Magnetic resonance imaging (MRI) is increasingly used to triage patients for prostate biopsy. However, 9% to 24% of clinically significant (cs) prostate cancers (PCas) are not visible in MRI. We aimed to identify histomic and transcriptomic determinants of MRI visibility and their association to metastasis, and PCa-specific death (PCSD). We studied 45 radical prostatectomy-treated patients with csPCa (grade group [GG]2-3), including 30 with MRI-visible and 15 with MRI-invisible lesions, and 18 men without PCa. First, histological composition was quantified. Next, transcriptomic profiling was performed using NanoString technology. MRI visibility-associated differentially expressed genes (DEGs) and Reactome pathways were identified. MRI visibility was classified using publicly available genes in MSK-IMPACT and Decipher, Oncotype DX, and Prolaris. Finally, DEGs and clinical parameters were used to classify metastasis and PCSD in an external cohort, which included 76 patients with metastatic GG2-4 PCa, and 84 baseline-matched controls without progression. Luminal area was lower in MRI-visible than invisible lesions and low luminal area was associated with short metastasis-free and PCa-specific survival. We identified 67 DEGs, eight of which were associated with survival. Cell division, inflammation and transcriptional regulation pathways were upregulated in MRI-visible csPCas. Genes in Decipher, Oncotype DX and MSK-IMPACT performed well in classifying MRI visibility (AUC = 0.86-0.94). DEGs improved classification of metastasis (AUC = 0.69) and PCSD (AUC = 0.68) over clinical parameters. Our data reveals that MRI-visible csPCas harbor more aggressive histomic and transcriptomic features than MRI-invisible csPCas. Thus, targeted biopsy of visible lesions may be sufficient for risk stratification in patients with a positive MRI.

A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer.

BACKGROUND: Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. METHODS: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. RESULTS: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. CONCLUSIONS: This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICI efficacy. TRIAL REGISTRATION: CheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.

OSCAR: Optimal subset cardinality regression using the L0-pseudonorm with applications to prognostic modelling of prostate cancer.

In many real-world applications, such as those based on electronic health records, prognostic prediction of patient survival is based on heterogeneous sets of clinical laboratory measurements. To address the trade-off between the predictive accuracy of a prognostic model and the costs related to its clinical implementation, we propose an optimized L0-pseudonorm approach to learn sparse solutions in multivariable regression. The model sparsity is maintained by restricting the number of nonzero coefficients in the model with a cardinality constraint, which makes the optimization problem NP-hard. In addition, we generalize the cardinality constraint for grouped feature selection, which makes it possible to identify key sets of predictors that may be measured together in a kit in clinical practice. We demonstrate the operation of our cardinality constraint-based feature subset selection method, named OSCAR, in the context of prognostic prediction of prostate cancer patients, where it enables one to determine the key explanatory predictors at different levels of model sparsity. We further explore how the model sparsity affects the model accuracy and implementation cost. Lastly, we demonstrate generalization of the presented methodology to high-dimensional transcriptomics data.

Expected impact of MRI-targeted biopsy interreader variability among uropathologists on ProScreen prostate cancer screening trial: a pre-trial validation study.

PURPOSE: Prostate cancer (PCa) histology, particularly the Gleason score, is an independent prognostic predictor in PCa. Little is known about the inter-reader variability in grading of targeted prostate biopsy based on magnetic resonance imaging (MRI). The aim of this study was to assess inter-reader variability in Gleason grading of MRI-targeted biopsy among uropathologists and its potential impact on a population-based randomized PCa screening trial (ProScreen). METHODS: From June 2014 to May 2018, 100 men with clinically suspected PCa were retrospectively selected. All men underwent prostate MRI and 86 underwent targeted prostate of the prostate. Six pathologists individually reviewed the pathology slides of the prostate biopsies. The five-tier ISUP (The International Society of Urological Pathology) grade grouping (GG) system was used. Fleiss' weighted kappa (κ) and Model-based kappa for associations were computed to estimate the combined agreement between individual pathologists. RESULTS: GG reporting of targeted prostate was highly consistent among the trial pathologists. Inter-reader agreement for cancer (GG1-5) vs. benign was excellent (Model-based kappa 0.90, Fleiss' kappa κ = 0.90) and for clinically significant prostate cancer (csPCa) (GG2-5 vs. GG0 vs. GG1), it was good (Model-based kappa 0.70, Fleiss' kappa κ 0.67). CONCLUSIONS: Inter-reader agreement in grading of MRI-targeted biopsy was good to excellent, while it was fair to moderate for MRI in the same cohort, as previously shown. Importantly, there was wide consensus by pathologists in assigning the contemporary GG on MRI-targeted biopsy suggesting high reproducibility of pathology reporting in the ProScreen trial.

Protocol liver biopsy predicts graft survival after liver transplantation.

BACKGROUND: The use of protocol liver biopsy to monitor liver allograft status remains controversial. There is limited data from modern transplantation populations that includes protocol biopsies to evaluate its value in predicting clinical outcomes. METHODS: All protocol liver biopsies were identified from 875 patients who underwent liver transplantation at Helsinki University Hospital between 2000 and 2019. Each histologic component was analyzed for its ability to predict long-term outcomes, especially graft survival. We determined the frequency of significant biopsy findings based on the Banff working group definition. Liver function tests (LFTs) and clinical markers were evaluated for their ability to predict significant biopsy findings. RESULTS: In total, 867 protocol liver biopsies were analyzed. Significant findings were identified in 20.1% of the biopsies. In the first protocol biopsy, steatohepatitis (hazard ratio [HR] 3.504, p = .03) and moderate or severe congestion (HR 3.338, p = .04) predicted graft loss. The presence of cholangitis (HR 2.563, p = .04), necrosis (HR 7.635, p < .001), mild congestion (HR 4.291, p = .009), and significant biopsy finding (HR 2.540, p = .02) predicted inferior death-censored graft survival. While the degree of elevation of LFTs was positively associated with significant biopsy findings, the discrimination was poor (AUC .572-.622). Combined LFTs and clinical risk factors remained suboptimal for discriminating significant biopsy findings (AUC .696). CONCLUSIONS: Our findings support the use of protocol liver biopsies after liver transplantation since they frequently revealed changes associated with long-term outcomes, even when LFTs were normal.

Prostate Cancer Screening With PSA, Kallikrein Panel, and MRI: The ProScreen Randomized Trial.

Importance: Prostate-specific antigen (PSA) screening has potential to reduce prostate cancer mortality but frequently detects prostate cancer that is not clinically important. Objective: To describe rates of low-grade (grade group 1) and high-grade (grade groups 2-5) prostate cancer identified among men invited to participate in a prostate cancer screening protocol consisting of a PSA test, a 4-kallikrein panel, and a magnetic resonance imaging (MRI) scan. Design, Setting, and Participants: The ProScreen trial is a clinical trial conducted in Helsinki and Tampere, Finland, that randomized 61 193 men aged 50 through 63 years who were free of prostate cancer in a 1:3 ratio to either be invited or not be invited to undergo screening for prostate cancer between February 2018 and July 2020. Interventions: Participating men randomized to the intervention underwent PSA testing. Those with a PSA level of 3.0 ng/mL or higher underwent additional testing for high-grade prostate cancer with a 4-kallikrein panel risk score. Those with a kallikrein panel score of 7.5% or higher underwent an MRI of the prostate gland, followed by targeted biopsies for those with abnormal prostate gland MRI findings. Final data collection occurred through June 31, 2023. Main Outcomes and Measures: In descriptive exploratory analyses, the cumulative incidence of low-grade and high-grade prostate cancer after the first screening round were compared between the group invited to undergo prostate cancer screening and the control group. Results: Of 60 745 eligible men (mean [SD] age, 57.2 [4.0] years), 15 201 were randomized to be invited and 45 544 were randomized not to be invited to undergo prostate cancer screening. Of 15 201 eligible males invited to undergo screening, 7744 (51%) participated. Among them, 32 low-grade prostate cancers (cumulative incidence, 0.41%) and 128 high-grade prostate cancers (cumulative incidence, 1.65%) were detected, with 1 cancer grade group result missing. Among the 7457 invited men (49%) who refused participation, 7 low-grade prostate cancers (cumulative incidence, 0.1%) and 44 high-grade prostate cancers (cumulative incidence, 0.6%) were detected, with 7 cancer grade groups missing. For the entire invited screening group, 39 low-grade prostate cancers (cumulative incidence, 0.26%) and 172 high-grade prostate cancers (cumulative incidence, 1.13%) were detected. During a median follow-up of 3.2 years, in the group not invited to undergo screening, 65 low-grade prostate cancers (cumulative incidence, 0.14%) and 282 high-grade prostate cancers (cumulative incidence, 0.62%) were detected. The risk difference for the entire group randomized to the screening invitation vs the control group was 0.11% (95% CI, 0.03%-0.20%) for low-grade and 0.51% (95% CI, 0.33%-0.70%) for high-grade cancer. Conclusions and Relevance: In this preliminary descriptive report from an ongoing randomized clinical trial, 1 additional high-grade cancer per 196 men and 1 low-grade cancer per 909 men were detected among those randomized to be invited to undergo a single prostate cancer screening intervention compared with those not invited to undergo screening. These preliminary findings from a single round of screening should be interpreted cautiously, pending results of the study's primary mortality outcome. Trial Registration: ClinicalTrials.gov Identifier: NCT03423303.

Visual Assessment of 2-Dimensional Levels Within 3-Dimensional Pathology Data Sets of Prostate Needle Biopsies Reveals Substantial Spatial Heterogeneity.

Prostate cancer prognostication largely relies on visual assessment of a few thinly sectioned biopsy specimens under a microscope to assign a Gleason grade group (GG). Unfortunately, the assigned GG is not always associated with a patient's outcome in part because of the limited sampling of spatially heterogeneous tumors achieved by 2-dimensional histopathology. In this study, open-top light-sheet microscopy was used to obtain 3-dimensional pathology data sets that were assessed by 4 human readers. Intrabiopsy variability was assessed by asking readers to perform Gleason grading of 5 different levels per biopsy for a total of 20 core needle biopsies (ie, 100 total images). Intrabiopsy variability (Cohen κ) was calculated as the worst pairwise agreement in GG between individual levels within each biopsy and found to be 0.34, 0.34, 0.38, and 0.43 for the 4 pathologists. These preliminary results reveal that even within a 1-mm-diameter needle core, GG based on 2-dimensional images can vary dramatically depending on the location within a biopsy being analyzed. We believe that morphologic assessment of whole biopsies in 3 dimension has the potential to enable more reliable and consistent tumor grading.

Prognostic impact of kallikrein-related peptidase transcript levels in prostate cancer.

We aimed to study mRNA levels and prognostic impact of all 15 human kallikrein-related peptidases (KLKs) and their targets, proteinase-activated receptors (PARs), in surgically treated prostate cancer (PCa). Seventy-nine patients with localized grade group 2-4 PCas represented aggressive cases, based on metastatic progression during median follow-up of 11 years. Eighty-six patients with similar baseline characteristics, but no metastasis during follow-up, were assigned as controls. Transcript counts were detected with nCounter technology. KLK12 protein expression was investigated with immunohistochemistry. The effects of KLK12 and KLK15 were studied in LNCaP cells using RNA interference. KLK3, -2, -4, -11, -15, -10 and -12 mRNA, in decreasing order, were expressed over limit of detection (LOD). The expression of KLK2, -3, -4 and -15 was decreased and KLK12 increased in aggressive cancers, compared to controls (P < .05). Low KLK2, -3 and -15 expression was associated with short metastasis-free survival (P < .05) in Kaplan-Meier analysis. PAR1 and -2 were expressed over LOD, and PAR1 expression was higher, and PAR2 lower, in aggressive cases than controls. Together, KLKs and PARs improved classification of metastatic and lethal disease over grade, pathological stage and prostate-specific antigen combined, in random forest analyses. Strong KLK12 immunohistochemical staining was associated with short metastasis-free and PCa-specific survival in Kaplan-Meier analysis (P < .05). Knock-down of KLK15 reduced colony formation of LNCaP cells grown on Matrigel basement membrane preparation. These results support the involvement of several KLKs in PCa progression, highlighting, that they may serve as prognostic PCa biomarkers.

The roles of proteases in prostate cancer.

Since the proposition of the pro-invasive activity of proteolytic enzymes over 70 years ago, several roles for proteases in cancer progression have been established. About half of the 473 active human proteases are expressed in the prostate and many of the most well-characterized members of this enzyme family are regulated by androgens, hormones essential for development of prostate cancer. Most notably, several kallikrein-related peptidases, including KLK3 (prostate-specific antigen, PSA), the most well-known prostate cancer marker, and type II transmembrane serine proteases, such as TMPRSS2 and matriptase, have been extensively studied and found to promote prostate cancer progression. Recent findings also suggest a critical role for proteases in the development of advanced and aggressive castration-resistant prostate cancer (CRPC). Perhaps the most intriguing evidence for this role comes from studies showing that the protease-activated transmembrane proteins, Notch and CDCP1, are associated with the development of CRPC. Here, we review the roles of proteases in prostate cancer, with a special focus on their regulation by androgens.

Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins: A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer.

BACKGROUND: Accurate detection of clinically significant prostate cancer (csPCa), Gleason Grade Group ≥ 2, remains a challenge. Prostate MRI radiomics and blood kallikreins have been proposed as tools to improve the performance of biparametric MRI (bpMRI). PURPOSE: To develop and validate radiomics and kallikrein models for the detection of csPCa. STUDY TYPE: Retrospective. POPULATION: A total of 543 men with a clinical suspicion of csPCa, 411 (76%, 411/543) had kallikreins available and 360 (88%, 360/411) did not take 5-alpha-reductase inhibitors. Two data splits into training, validation (split 1: single center, n = 72; split 2: random 50% of pooled datasets from all four centers), and testing (split 1: 4 centers, n = 288; split 2: remaining 50%) were evaluated. FIELD STRENGTH/SEQUENCE: A 3 T/1.5 T, TSE T2-weighted imaging, 3x SE DWI. ASSESSMENT: In total, 20,363 radiomic features calculated from manually delineated whole gland (WG) and bpMRI suspicion lesion masks were evaluated in addition to clinical parameters, prostate-specific antigen, four kallikreins, MRI-based qualitative (PI-RADSv2.1/IMPROD bpMRI Likert) scores. STATISTICAL TESTS: For the detection of csPCa, area under receiver operating curve (AUC) was calculated using the DeLong's method. A multivariate analysis was conducted to determine the predictive power of combining variables. The values of P-value < 0.05 were considered significant. RESULTS: The highest prediction performance was achieved by IMPROD bpMRI Likert and PI-RADSv2.1 score with AUC = 0.85 and 0.85 in split 1, 0.85 and 0.83 in split 2, respectively. bpMRI WG and/or kallikreins demonstrated AUCs ranging from 0.62 to 0.73 in split 1 and from 0.68 to 0.76 in split 2. AUC of bpMRI lesion-derived radiomics model was not statistically different to IMPROD bpMRI Likert score (split 1: AUC = 0.83, P-value = 0.306; split 2: AUC = 0.83, P-value = 0.488). DATA CONCLUSION: The use of radiomics and kallikreins failed to outperform PI-RADSv2.1/IMPROD bpMRI Likert and their combination did not lead to further performance gains. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Population-based randomized trial of screening for clinically significant prostate cancer ProScreen: a pilot study.

OBJECTIVES: To evaluate the feasibility of a population-based screening trial using prostate-specific antigen (PSA), a kallikrein panel and multiparametric magnetic resonance imaging (MRI) aimed at minimizing overdiagnosis, while retaining mortality benefit. PATIENTS AND METHODS: Feasibility of the screening algorithm was evaluated in terms of participation, screening test results and cancer detection. A random sample of 400 men aged 65 years was identified from the population registry and invited for screening with three stepwise tests (PSA, kallikrein panel and MRI). Men with PSA levels ≥3 ng/mL were further tested with the kallikrein panel, and those with positive findings (risk >7.5%) were referred for prostate MRI. Men with positive MRI (Prostate Imaging Reporting and Data System [PI-RADS] score 3-5) had targeted biopsies only. Men with negative MRI, but PSA density ≥0.15 underwent systematic biopsies. RESULTS: Of the 399 men invited, 158 (40%) participated and 27 had PSA levels ≥3 ng/mL (7% of the invited and 17% of the participants). Of these, 22 had a positive kallikrein panel (6% of the invited and 81% of the PSA-positive men). Finally, 10 men (3% of the invited and 45% of 4Kscore [kallikrein panel]-positive) had a suspicious MRI finding (PI-RADS score ≥3) and five were diagnosed with a clinically significant prostate cancer (Gleason Grade Group [GG] ≥2) at fusion biopsy (3% of the participants), with two GG 1 cases (1%). Additional testing (kallikrein panel and MRI) after PSA reduced biopsies by 56%. CONCLUSION: The findings constitute proof of principle for our screening protocol, as we achieved a substantial detection rate for clinically significant cancer with few clinically insignificant cases. Participation, however, was suboptimal.

Adiponectin receptor agonist AdipoRon ameliorates renal inflammation in diet-induced obese mice and endotoxin-treated human glomeruli ex vivo.

AIMS/HYPOTHESIS: Chronic low-grade inflammation with local upregulation of proinflammatory molecules plays a role in the progression of obesity-related renal injury. Reduced serum concentration of anti-inflammatory adiponectin may promote chronic inflammation. Here, we investigated the potential anti-inflammatory and renoprotective effects and mechanisms of action of AdipoRon, an adiponectin receptor agonist. METHODS: Wild-type DBA/2J mice were fed with high-fat diet (HFD) supplemented or not with AdipoRon to model obesity-induced metabolic endotoxaemia and chronic low-grade inflammation and we assessed changes in the glomerular morphology and expression of proinflammatory markers. We also treated human glomeruli ex vivo and human podocytes in vitro with AdipoRon and bacterial lipopolysaccharide (LPS), an endotoxin upregulated in obesity and diabetes, and analysed the secretion of inflammatory cytokines, activation of inflammatory signal transduction pathways, apoptosis and migration. RESULTS: In HFD-fed mice, AdipoRon attenuated renal inflammation, as demonstrated by reduced expression of glomerular activated NF-κB p65 subunit (NF-κB-p65) (70%, p < 0.001), TNFα (48%, p < 0.01), IL-1ß (51%, p < 0.001) and TGFß (46%, p < 0.001), renal IL-6 and IL-4 (21% and 20%, p < 0.05), and lowered glomerular F4/80-positive macrophage infiltration (31%, p < 0.001). In addition, AdipoRon ameliorated HFD-induced glomerular hypertrophy (12%, p < 0.001), fibronectin accumulation (50%, p < 0.01) and podocyte loss (12%, p < 0.001), and reduced podocyte foot process effacement (15%, p < 0.001) and thickening of the glomerular basement membrane (18%, p < 0.001). In cultured podocytes, AdipoRon attenuated the LPS-induced activation of the central inflammatory signalling pathways NF-κB-p65, c-Jun N-terminal kinase (JNK) and p38 mitogen-activated protein kinase (p38-MAPK) (30%, 36% and 22%, respectively, p < 0.001), reduced the secretion of TNFα (32%, p < 0.01), and protected against podocyte apoptosis and migration. In human glomeruli ex vivo, AdipoRon reduced the LPS-induced secretion of inflammatory cytokines IL-1ß, IL-18, IL-6 and IL-10. CONCLUSIONS/INTERPRETATION: AdipoRon attenuated the renal expression of proinflammatory cytokines in HFD-fed mice and LPS-stimulated human glomeruli, which apparently contributed to the amelioration of glomerular inflammation and injury. Mechanistically, based on assays on cultured podocytes, AdipoRon reduced LPS-induced activation of the NF-κB-p65, JNK and p38-MAPK pathways, thereby impelling the decrease in apoptosis, migration and secretion of TNFα. We conclude that the activation of the adiponectin receptor by AdipoRon is a potent strategy to attenuate endotoxaemia-associated renal inflammation.

Transcript analysis of commercial prostate cancer risk stratification panels in hard-to-predict grade group 2-4 prostate cancers.

BACKGROUND: Improved prognostication is needed to minimize overtreatment in grade group (GG) 2-4 prostate cancer. Our aim was to determine, at messenger RNA (mRNA) level, the performance of the genes in the commercial panels Decipher, Oncotype DX, Prolaris, and mutational panel MSK-IMPACT to predict metastasis-free and prostate cancer-specific death (PCSD) in patients with GG 2-4 prostate cancer at radical prostatectomy. METHODS: The retrospective cohort consisted of GG 2-4 patients treated with radical prostatectomy (median follow-up 10.4 years). Seventy-six cases with postoperative metastasis or PCSD and 84 controls with similar clinical baseline risk, but without progression, were analyzed. Index lesion mRNA transcripts were analyzed using NanoString technology. Random forest models were trained using panel gene sets to predict clinical endpoints and area under the curve (AUC), sensitivity, specificity, Youden index, and number needed to diagnose (NND) was measured. Survival probability was assessed with Kaplan-Meier estimator. RESULTS: All gene sets outperformed clinical parameters and predicted metastasis-free and prostate cancer-specific survival. However, there were significant differences between the panels. In metastasis prediction, the genes in Oncotype DX had inferior performance (area under the curve [AUC] = 0.65) compared to other panels (AUC = 0.73-0.74). Decipher, MSK-IMPACT and Prolaris showed similar NND (2.83-3.12) with Oncotype DX having highest NND (4.79). In PCSD prediction, the Prolaris gene set performed worse (AUC = 0.66) than MSK-IMPACT or Decipher (AUC = 0.72). Oncotype DX performed similarly to other panels (AUC = 0.69, p > .05). Oncotype DX demonstrated lowest NND (2.79) compared to other panels (4.22-5.66). CONCLUSION: Transcript analysis of genes included in commercial panels is feasible in survival prediction of GG 2-4 patients after radical prostatectomy and may aid in clinical decision making. There were significant differences between the panels, and overall stronger predictive gene sets are needed. Prospective investigation is warranted in biopsy materials.

PTEN and ERG expression in MRI-ultrasound guided fusion biopsy correlated with radical prostatectomy findings in men with prostate cancer.

BACKGROUND: Conventional systematic prostate biopsies (SBx) have multiple limitations, and magnetic resonance imaging (MRI)-ultrasound fusion targeting is increasingly applied (fusion biopsies [FBx]). In our previous studies, we have shown that loss of the tumor suppressor gene phosphatase and tensin homolog (PTEN) in radical prostatectomy (RP) specimens predicts poor disease-specific survival, and in active surveillance (AS), PTEN loss in SBx predicts an adverse AS outcome, although SBx PTEN status does not correlate well with the corresponding RP status. Here, we have hypothesized that PTEN and erythroblast transformation-specific related gene (ERG) status in FBx correlate better with RP than they would in SBx. METHODS: A total of 106 men, who had undergone FBx and subsequent RP in a single center between June 2015 and May 2017 were included. Fifty-three of the men had concomitant or previous SBx's. All biopsy and RP specimens were collected, and tissue microarrays (TMA) were constructed from RP specimens. Immunohistochemical stainings for PTEN and ERG expression were conducted on biopsies and RP TMAs and results were compared by using Fisher's exact test. RESULTS: The immunohistochemical predictive power of FBx, determined by the concordance of biopsy PTEN and ERG status with RP, is superior to SBx (77.6% vs 66.7% in PTEN, 92.4% vs 66.6% in ERG). FBx was superior to SBx in correlation with RP Gleason Grade Groups and MRI prostate imaging reporting and data system scores. CONCLUSION: FBx grading correlates with RP histology and MRI findings and predicts the biomarker status in the RP specimens more accurately than SBx. A longer follow-up is needed to evaluate if this translates to better prediction of disease outcomes, especially in AS and radiation therapy where prostatectomy specimens are not available for prognostication.

Qualitative and Quantitative Reporting of a Unique Biparametric MRI: Towards Biparametric MRI-Based Nomograms for Prediction of Prostate Biopsy Outcome in Men With a Clinical Suspicion of Prostate Cancer (IMPROD and MULTI-IMPROD Trials).

BACKGROUND: Multiparametric MRI of the prostate has been shown to improve the risk stratification of men with an elevated prostate-specific antigen (PSA). However, long acquisition time, high cost, and inter-center/reader variability of a routine prostate multiparametric MRI limit its wider adoption. PURPOSE: To develop and validate nomograms based on unique rapid biparametric MRI (bpMRI) qualitative and quantitative derived variables for prediction of clinically significant cancer (SPCa). STUDY TYPE: Retrospective analyses of single (IMPROD, NCT01864135) and multiinstitution trials (MULTI-IMPROD, NCT02241122). POPULATION: 161 and 338 prospectively enrolled men who completed the IMPROD and MULTI-IMPROD trials, respectively. FIELD STRENGTH/SEQUENCE: IMPROD bpMRI: 3T/1.5T, T2 -weighted imaging, three separate diffusion-weighted imaging (DWI) acquisitions: 1) b-values 0, 100, 200, 300, 500 s/mm2 ; 2) b values 0, 1500 s/mm2 ; 3) values 0, 2000 s/mm2 . ASSESSMENT: The primary endpoint of the combined trial analysis was the diagnostic accuracy of the combination of IMPROD bpMRI and clinical variables for detection of SPCa. STATISTICAL TESTS: Logistic regression models were developed using IMPROD trial data and validated using MULTI-IMPROD trial data. The model's performance was expressed as the area under the curve (AUC) values for the detection of SPCa, defined as ISUP Gleason Grade Group ≥2. RESULTS: A model incorporating clinical variables had an AUC (95% confidence interval) of 0.83 (0.77-0.89) and 0.80 (0.75-0.85) in the development and validation cohorts, respectively. The corresponding values for a model using IMPROD bpMRI findings were 0.93 (0.89-0.97), and 0.88 (0.84-0.92), respectively. Further addition of the quantitative DWI-based score did not improve AUC values (P < 0.05). DATA CONCLUSION: A prediction model using qualitative IMPROD bpMRI findings demonstrated high accuracy for predicting SPCa in men with an elevated PSA. Online risk calculator: http://petiv.utu.fi/multiimprod/ Level of Evidence: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1556-1567.

Metformin increases glucose uptake and acts renoprotectively by reducing SHIP2 activity.

Metformin, the first-line drug to treat type 2 diabetes (T2D), inhibits mitochondrial glycerolphosphate dehydrogenase in the liver to suppress gluconeogenesis. However, the direct target and the underlying mechanisms by which metformin increases glucose uptake in peripheral tissues remain uncharacterized. Lipid phosphatase Src homology 2 domain-containing inositol-5-phosphatase 2 (SHIP2) is upregulated in diabetic rodent models and suppresses insulin signaling by reducing Akt activation, leading to insulin resistance and diminished glucose uptake. Here, we demonstrate that metformin directly binds to and reduces the catalytic activity of the recombinant SHIP2 phosphatase domain in vitro. Metformin inhibits SHIP2 in cultured cells and in skeletal muscle and kidney of db/db mice. In SHIP2-overexpressing myotubes, metformin ameliorates reduced glucose uptake by slowing down glucose transporter 4 endocytosis. SHIP2 overexpression reduces Akt activity and enhances podocyte apoptosis, and both are restored to normal levels by metformin. SHIP2 activity is elevated in glomeruli of patients with T2D receiving nonmetformin medication, but not in patients receiving metformin, compared with people without diabetes. Furthermore, podocyte loss in kidneys of metformin-treated T2D patients is reduced compared with patients receiving nonmetformin medication. Our data unravel a novel molecular mechanism by which metformin enhances glucose uptake and acts renoprotectively by reducing SHIP2 activity.-Polianskyte-Prause, Z., Tolvanen, T. A., Lindfors, S., Dumont, V., Van, M., Wang, H., Dash, S. N., Berg, M., Naams, J.-B., Hautala, L. C., Nisen, H., Mirtti, T., Groop, P.-H., Wähälä, K., Tienari, J., Lehtonen, S. Metformin increases glucose uptake and acts renoprotectively by reducing SHIP2 activity.

Clonal heterogeneity influences drug responsiveness in renal cancer assessed by ex vivo drug testing of multiple patient-derived cancer cells.

Renal cell cancer (RCC) has become a prototype example of the extensive intratumor heterogeneity and clonal evolution of human cancers. However, there is little direct evidence on how the genetic heterogeneity impacts on drug response profiles of the cancer cells. Our goal was to determine how genomic clonal evolution impacts drug responses. Finding from our study could help to define the challenge that clonal evolution poses on cancer therapy. We established multiple patient-derived cells (PDCs) from different tumor regions of four RCC patients, verified their clonal relationship to each other and to the uncultured tumor tissue by genome sequencing. Furthermore, comprehensive drug-sensitivity testing with 460 oncological drugs was performed on all PDC clones. The PDCs retained many cancer-specific copy number alterations and mutations in driver genes such as VHL, PBRM1, PIK3C2A, KMD5C and TSC2 genes. The drug testing highlighted vulnerability in the PDCs toward approved RCC drugs, such as the mTOR-inhibitor temsirolimus, but also novel sensitivities were uncovered. The individual PDC clones from different tumor regions in a patient showed distinct drug-response profiles, suggesting that genomic heterogeneity contributes to the variability in drug responses. Studies of multiple PDCs from a patient with cancer are informative for elucidating cancer heterogeneity and for the determination on how the genomic evolution is manifested in cancer drug responsiveness. This approach could facilitate tailoring of drugs and drug combinations to individual patients.

Validation of IMPROD biparametric MRI in men with clinically suspected prostate cancer: A prospective multi-institutional trial.

BACKGROUND: Magnetic resonance imaging (MRI) combined with targeted biopsy (TB) is increasingly used in men with clinically suspected prostate cancer (PCa), but the long acquisition times, high costs, and inter-center/reader variability of routine multiparametric prostate MRI limit its wider adoption. METHODS AND FINDINGS: The aim was to validate a previously developed unique MRI acquisition and reporting protocol, IMPROD biparametric MRI (bpMRI) (NCT01864135), in men with a clinical suspicion of PCa in a multi-institutional trial (NCT02241122). IMPROD bpMRI has average acquisition time of 15 minutes (no endorectal coil, no intravenous contrast use) and consists of T2-weighted imaging and 3 separate diffusion-weighed imaging acquisitions. Between February 1, 2015, and March 31, 2017, 364 men with a clinical suspicion of PCa were enrolled at 4 institutions in Finland. Men with an equivocal to high suspicion (IMPROD bpMRI Likert score 3-5) of PCa had 2 TBs of up to 2 lesions followed by a systematic biopsy (SB). Men with a low to very low suspicion (IMPROD bpMRI Likert score 1-2) had only SB. All data and protocols are freely available. The primary outcome of the trial was diagnostic accuracy-including overall accuracy, sensitivity, specificity, negative predictive value (NPV), and positive predictive value-of IMPROD bpMRI for clinically significant PCa (SPCa), which was defined as a Gleason score ≥ 3 + 4 (Gleason grade group 2 or higher). In total, 338 (338/364, 93%) prospectively enrolled men completed the trial. The accuracy and NPV of IMPROD bpMRI for SPCa were 70% (113/161) and 95% (71/75) (95% CI 87%-98%), respectively. Restricting the biopsy to men with equivocal to highly suspicious IMPROD bpMRI findings would have resulted in a 22% (75/338) reduction in the number of men undergoing biopsy while missing 4 (3%, 4/146) men with SPCa. The main limitation is uncertainty about the true PCa prevalence in the study cohort, since some of the men may have PCa despite having negative biopsy findings. CONCLUSIONS: IMPROD bpMRI demonstrated a high NPV for SPCa in men with a clinical suspicion of PCa in this prospective multi-institutional clinical trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT02241122.

Fibroblast as a critical stromal cell type determining prognosis in prostate cancer.

BACKGROUND: Tumor stroma associates with prostate cancer (PCa) progression, but its specific cellular composition and association to patient survival outcome have not been characterized. METHODS: We analyzed stromal composition in human PCa using multiplex immunohistochemistry and quantitative, high-resolution image analysis in two retrospective, formalin-fixed paraffin embedded observational clinical cohorts (Cohort I, n = 117; Cohort II, n = 340) using PCa-specific mortality as outcome measurement. RESULTS: A high proportion of fibroblasts associated with aggressive disease and castration-resistant prostate cancer (CRPC). In a multivariate analysis, increase in fibroblast proportion predicted poor cancer-specific outcome independently in the two clinical cohorts studied. CONCLUSIONS: Fibroblasts were the most important cell type in determining prognosis in PCa and associated with CRPC. Thus, the stromal composition could be critically important in developing diagnostic and therapeutic approaches to aggressive prostate cancer.