Epigenetic loss of heterogeneity from low to high grade localized prostate tumours

AbstractIdentifying precise molecular subtypes attributable to specific stages of localized prostate cancer has proven difficult due to high levels of heterogeneity. Bulk assays represent a population-average, which mask the heterogeneity that exists at the single-cell level. In this work, we sequence the accessible chromatin regions of 14,424 single-cells from 18 flash-frozen prostate tumours. We observe shared chromatin features among low-grade prostate cancer cells are lost in high-grade tumours. Despite this loss, high-grade tumours exhibit an enrichment for FOXA1, HOXB13 and CDX2 transcription factor binding sites, indicating a shared trans-regulatory programme. We identify two unique genes encoding neuronal adhesion molecules that are highly accessible in high-grade prostate tumours. We show NRXN1 and NLGN1 expression in epithelial, endothelial, immune and neuronal cells in prostate cancer using cyclic immunofluorescence. Our results provide a deeper understanding of the active gene regulatory networks in primary prostate tumours, critical for molecular stratification of the disease.

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Single-cell analysis of localized low- and high-grade prostate cancers

10.1101/2021.04.16.440238 ◽

2021 ◽

Author(s):

Sebnem Ece Eksi ◽

Alex Chitsazan ◽

Zeynep Sayar ◽

Andrew Fields ◽

Ryan Kopp ◽

...

Keyword(s):

Prostate Cancer ◽

Single Cell ◽

Single Cell Analysis ◽

Single Cells ◽

Neuroendocrine Cells ◽

Low Grade ◽

High Grade ◽

Cell Analysis ◽

Prostate Tumors ◽

Accessible Chromatin

Approximately, 30% of early-stage localized prostate cancer cases reoccur within 5 to 10 years [1, 2]. However, identifying precise molecular subtypes attributable to specific stages of prostate cancer has proven difficult due to high heterogeneity within localized tumors [3-5]. Bulk assays represent a population average, which is a result of the heterogeneity that exists at the individual prostate cancer cell level [6]. Here, we sequenced the accessible chromatin regions of 14,424 single-cells collected from 18 fresh-frozen prostate tumors using sci-ATAC-seq [7, 8]. We observed that shared chromatin features among low-grade prostate cancer epithelial cells were lost in high-grade tumors. Despite this loss, all high-grade tumors exhibited an enrichment for FOXA1, HOXB13 and CDX2 transcription factor binding sites within their accessible chromatin regions, indicating a shared trans-regulatory program. Single-cell analysis of the differentially accessible regions in high- versus low-grade prostate tumors identified two unique genes encoding neuronal adhesion molecules, NRXN1 and NLGN1. We found that NRXN1 and NLGN1 are expressed in the epithelial luminal, basal and neuroendocrine cells, as well as the immune, endothelial and neuronal cell types in all prostate tumors. Overall, these results provide a deeper understanding of the active gene regulatory networks in low- and high-grade prostate tumors at a striking resolution and provide critical insights for molecular stratification of the disease.

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Clinical use of the SelectMDx urinary-biomarker test with or without mpMRI in prostate cancer diagnosis: a prospective, multicenter study in biopsy-naïve men

Prostate Cancer and Prostatic Diseases ◽

10.1038/s41391-021-00367-8 ◽

2021 ◽

Author(s):

Rianne J. Hendriks ◽

Marloes M. G. van der Leest ◽

Bas Israël ◽

Gerjon Hannink ◽

Anglita YantiSetiasti ◽

...

Keyword(s):

Prostate Cancer ◽

Risk Stratification ◽

Specific Antigen ◽

Low Grade ◽

Diagnostic Study ◽

High Grade ◽

Net Benefit ◽

Conditional Strategy ◽

Detection Rates ◽

Guided Biopsy

Abstract Background Risk stratification in men with suspicion of prostate cancer (PCa) requires reliable diagnostic tests, not only to identify high-grade PCa, also to minimize the overdetection of low-grade PCa, and reduction of “unnecessary” prostate MRIs and biopsies. This study aimed to evaluate the SelectMDx test to detect high-grade PCa in biopsy-naïve men. Subsequently, to assess combinations of SelectMDx test and multi-parametric (mp) MRI and its potential impact on patient selection for prostate biopsy. Methods This prospective multicenter diagnostic study included 599 biopsy-naïve patients with prostate-specific antigen level ≥3 ng/ml. All patients underwent a SelectMDx test and mpMRI before systematic transrectal ultrasound-guided biopsy (TRUSGB). Patients with a suspicious mpMRI also had an in-bore MR-guided biopsy (MRGB). Histopathologic outcome of TRUSGB and MRGB was used as reference standard. High-grade PCa was defined as ISUP Grade Group (GG) ≥ 2. The primary outcome was the detection rates of low- and high-grade PCa and number of biopsies avoided in four strategies, i.e., (1) SelectMDx test-only, (2) mpMRI-only, (3) SelectMDx test followed by mpMRI when SelectMDx test was positive (conditional strategy), and (4) SelectMDx test and mpMRI in all (joint strategy). A positive SelectMDx test outcome was a risk score of ≥−2.8. Decision curve analysis (DCA) was performed to assess clinical utility. Results Prevalence of high-grade PCa was 31% (183/599). Thirty-eight percent (227/599) of patients had negative SelectMDx test in whom biopsy could be avoided. Low-grade PCa was not detected in 35% (48/138) with missing 10% (18/183) high-grade PCa. Yet, mpMRI-only could avoid 49% of biopsies, not detecting 4.9% (9/183) of high-grade PCa. The conditional strategy reduces the number of mpMRIs by 38% (227/599), avoiding biopsy in 60% (357/599) and missing 13% (24/183) high-grade PCa. Low-grade PCa was not detected in 58% (80/138). DCA showed the highest net benefit for the mpMRI-only strategy, followed by the conditional strategy at-risk thresholds >10%. Conclusions SelectMDx test as a risk stratification tool for biopsy-naïve men avoids unnecessary biopsies in 38%, minimizes low-grade PCa detection, and misses only 10% high-grade PCa. Yet, using mpMRI in all patients had the highest net benefit, avoiding biopsy in 49% and missing 4.9% of high-risk PCa. However, if mpMRI availability is limited or expensive, using mpMRI-only in SelectMDx test positive patients is a good alternative strategy.

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Effect of Statins on the Risk of Different Stages of Prostate Cancer: A Meta-Analysis

Urologia Internationalis ◽

10.1159/000518164 ◽

2021 ◽

pp. 1-9

Author(s):

Yun Li ◽

Xuan Cheng ◽

Jia-lian Zhu ◽

Wen-wen Luo ◽

Huai-rong Xiang ◽

...

Keyword(s):

Prostate Cancer ◽

Lower Risk ◽

Advanced Prostate Cancer ◽

Meta Analysis ◽

Cochrane Library ◽

Low Grade ◽

High Grade ◽

The Cochrane Library ◽

The Relationship ◽

Comprehensive Literature Search

Introduction: The aim of this article was to investigate the relationship between statins and the risk of different stages or grades of prostate cancer. Methods: A comprehensive literature search was performed for articles published until December 18, 2020, on the PubMed, Embase, and the Cochrane Library databases. The pooled relative risk (RR) and 95% confidence interval (CI) were then analyzed using the STATA.16.0 software. Results: A total of 588,055 patients from 14 studies were included in the analysis. We found that the use of statins expressed a significant correlation with a lower risk of advanced prostate cancer (RR = 0.81, 95% CI: 0.73–0.91; RR = 0.86, 95% CI: 0.75–0.99, respectively). However, no evidence suggested that the use of statins was beneficial for the prevention of localized prostate cancer incidence. Similarly, the pooled results also revealed no association between the use of statins and the risk of high-grade and low-grade prostate cancer. Conclusion: It has been found that the use of statins is associated with a lower risk of advanced prostate cancer but was not related to the risk of localized, low-grade, or high-grade prostate cancer.

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The expression of YAP1 is increased in high-grade prostatic adenocarcinoma but is reduced in neuroendocrine prostate cancer

10.1101/832360 ◽

2019 ◽

Author(s):

Siyuan Cheng ◽

Nestor Prieto-Dominguez ◽

Shu Yang ◽

Zachary M. Connelly ◽

Samantha StPierre ◽

...

Keyword(s):

Prostate Cancer ◽

Cancer Progression ◽

Hippo Pathway ◽

Luciferase Reporter ◽

Low Grade ◽

Beta Catenin ◽

High Grade ◽

Protein Levels ◽

Neuroendocrine Prostate Cancer ◽

Functional Involvement

ABSTRACTBACKGROUNDAfter long-term androgen deprivation therapy, 25-30% prostate cancer (PCa) acquires an aggressive neuroendocrine (NE) phenotype. Dysregulation of YAP1, a key transcription coactivator of the Hippo pathway, has been related to cancer progression. However, its role in neuroendocrine prostate cancer (NEPC) has not been assessed.METHODSImmunohistochemistry was used to evaluate YAP1 protein levels during PCa initiation and progression. YAP1 knockdown and luciferase reporter assays were used to evaluate the ability of YAP1 to modulate Wnt/beta-Catenin signaling.RESULTSYAP1 expression was present in the basal epithelial cells in benign prostatic tissues, lost in low grade PCa, but elevated in high grade prostate adenocarcinomas. Interestingly, the expression of YAP1 was reduced/lost in both human and mouse NEPC. Finally, YAP1 knockdown in PCa cells activates Wnt/beta-Catenin signaling, which has been implicated in NE differentiation of PCa, supporting a functional involvement of the loss of YAP1 expression in NEPC development.CONCLUSIONSThe expression of YAP1 is elevated in high grade prostate adenocarcinomas while lost in NEPC. Reduced YAP1 activates Wnt/beta-Catenin signaling in PCa cells. These results suggest that when applied to PCa patients, YAP1 inhibitors shall be used with caution.

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Overdiagnosis and Overtreatment of Prostate Cancer

American Society of Clinical Oncology Educational Book ◽

10.14694/edbook_am.2012.32.98 ◽

2012 ◽

pp. e35-e39 ◽

Cited By ~ 4

Author(s):

Ian M. Thompson

Keyword(s):

Prostate Cancer ◽

Active Surveillance ◽

Specific Antigen ◽

The United States ◽

Assessment Tools ◽

Low Grade ◽

High Grade ◽

Surveillance Strategy ◽

Psa Testing ◽

Prostate Cancer Prevention

Overview: Prostate cancer is a ubiquitous disease, affecting as many as two-thirds of men in their 60s. Through widespread prostate-specific antigen (PSA) testing, increasing rates of prostate biopsy, and increased sampling of the prostate, a larger fraction of low-grade, low-volume tumors have been detected, consistent with tumors often found at autopsy. These tumors have historically been treated in a manner similar to that used for higher-grade tumors but, more recently, it has become evident that with a plan of active surveillance that reserves treatment for only those patients whose tumors show evidence of progression, very high disease-specific survival can be achieved. Unfortunately, the frequency of recommendation of an active surveillance strategy in the United States is low. An alternative strategy to improve prostate cancer detection is through selected biopsy of those men who are at greater risk of harboring high-grade, potentially lethal cancer. This strategy is currently possible through the use of risk assessment tools such as the Prostate Cancer Prevention Trial Risk Calculator ( www.prostate.cancer.risk.calculator.com ) as well as others. These tools can predict with considerable accuracy a man's risk of low-grade and high-grade cancer, allowing informed decision making for the patient with a goal of detection of high-risk disease. Ultimately, other biomarkers including PCA3, TMPRSS2:ERG, and [-2]proPSA will likely aid in discriminating these two types of cancer before biopsy.

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Elevated Tumor Lactate and Efflux in High-grade Prostate Cancer demonstrated by Hyperpolarized 13C Magnetic Resonance Spectroscopy of Prostate Tissue Slice Cultures

Cancers ◽

10.3390/cancers12030537 ◽

2020 ◽

Vol 12 (3) ◽

pp. 537 ◽

Cited By ~ 1

Author(s):

Renuka Sriram ◽

Mark Van Criekinge ◽

Justin DeLos Santos ◽

Fayyaz Ahamed ◽

Hecong Qin ◽

...

Keyword(s):

Prostate Cancer ◽

Magnetic Resonance ◽

Gleason Score ◽

Prostate Tissue ◽

Resonance Spectroscopy ◽

Low Grade ◽

High Grade ◽

Metabolic Alterations ◽

Ldh Activity ◽

Benign Prostate

Non-invasive assessment of the biological aggressiveness of prostate cancer (PCa) is needed for men with localized disease. Hyperpolarized (HP) 13C magnetic resonance (MR) spectroscopy is a powerful approach to image metabolism, specifically the conversion of HP [1-13C]pyruvate to [1-13C]lactate, catalyzed by lactate dehydrogenase (LDH). Significant increase in tumor lactate was measured in high-grade PCa relative to benign and low-grade cancer, suggesting that HP 13C MR could distinguish low-risk (Gleason score ≤3 + 4) from high-risk (Gleason score ≥4 + 3) PCa. To test this and the ability of HP 13C MR to detect these metabolic changes, we cultured prostate tissues in an MR-compatible bioreactor under continuous perfusion. 31P spectra demonstrated good viability and dynamic HP 13C-pyruvate MR demonstrated that high-grade PCa had significantly increased lactate efflux compared to low-grade PCa and benign prostate tissue. These metabolic differences are attributed to significantly increased LDHA expression and LDH activity, as well as significantly increased monocarboxylate transporter 4 (MCT4) expression in high- versus low- grade PCa. Moreover, lactate efflux, LDH activity, and MCT4 expression were not different between low-grade PCa and benign prostate tissues, indicating that these metabolic alterations are specific for high-grade disease. These distinctive metabolic alterations can be used to differentiate high-grade PCa from low-grade PCa and benign prostate tissues using clinically translatable HP [1-13C]pyruvate MR.

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A gene expression signature to predict high-grade prostate cancer response to oxaliplatin.

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.5_suppl.150 ◽

2012 ◽

Vol 30 (5_suppl) ◽

pp. 150-150

Author(s):

Philippe Pourquier ◽

Stephane Puyo ◽

Pierre Richaud ◽

Jacques Robert ◽

Nadine Houede

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Clinical Trials ◽

Cell Lines ◽

Gene Expression Signature ◽

Chemotherapeutic Agents ◽

Low Grade ◽

Gleason Grade ◽

High Grade ◽

Expression Signature

150 Background: Prostate cancer (PCa) is one of the leading causes of death from cancer in men. High Gleason grade prostate cancers are characterized by aggressive tumors with poorly differentiated cells and a high metastatic potential. They are often refractory to chemical castration but still treated with hormone therapy to which docetaxel or cabazitaxel are added when they become resistant to the anti-androgen. Despite many clinical trials with other chemotherapeutic agents, response rates remain low. Moreover, none of these trials took into account the tumor grade. Methods: We used an in silico approach to screen for drug candidates that could be used as an alternative to taxanes, based on a 86 genes signature which could distinguish between low-grade and high-grade tumors. We extracted from the NCI60 panel databases the expression profiles of the 86 genes across 60 human tumor cell lines and the corresponding in vitro cytotoxicity data of 152 drugs and looked for correlation between their expression level and cell sensitivity to each of these drugs. Results: Among the 86 genes, we identified 9 genes (PCCB, SHMT2, DPM1, RHOT2, RPL13, CD59, EIF4AI, CDKN2C, JUN) for which expression levels across the 60 cell lines was significantly correlated (p< 0.05) to oxaliplatin but not to cisplatin sensitivity. This signature was validated at the functional level since repression of each of these genes conferred a significant change in the sensitivity of PCa cell lines to oxaliplatin but not cisplatin. Conclusions: Our results provide a proof of concept that gene expression signature specific from high grade PCa could be used for the identification of alternative therapies to taxanes. They could also be used to select patients for further clinical trials and as predictive markers of response to these drugs, which represents a further step forward towards personalized therapy of PCa.

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Vasectomy and Risk of Aggressive Prostate Cancer: A 24-Year Follow-Up Study

Journal of Clinical Oncology ◽

10.1200/jco.2013.54.8446 ◽

2014 ◽

Vol 32 (27) ◽

pp. 3033-3038 ◽

Cited By ~ 31

Author(s):

Mohummad Minhaj Siddiqui ◽

Kathryn M. Wilson ◽

Mara M. Epstein ◽

Jennifer R. Rider ◽

Neil E. Martin ◽

...

Keyword(s):

Prostate Cancer ◽

Cancer Treatment ◽

Specific Antigen ◽

Prostate Cancer Risk ◽

The United States ◽

Low Grade ◽

High Grade ◽

Follow Up Study ◽

Increased Risk

Purpose Conflicting reports remain regarding the association between vasectomy, a common form of male contraception in the United States, and prostate cancer risk. We examined prospectively this association with extended follow-up and an emphasis on advanced and lethal disease. Patients and Methods Among 49,405 US men in the Health Professionals Follow-Up Study, age 40 to 75 years at baseline in 1986, 6,023 patients with prostate cancer were diagnosed during the follow-up to 2010, including 811 lethal cases. In total, 12,321 men (25%) had vasectomies. We used Cox proportional hazards models to estimate the relative risk (RR) and 95% CIs of total, advanced, high-grade, and lethal disease, with adjustment for a variety of possible confounders. Results Vasectomy was associated with a small increased risk of prostate cancer overall (RR, 1.10; 95% CI, 1.04 to 1.17). Risk was elevated for high-grade (Gleason score 8 to 10; RR, 1.22; 95% CI, 1.03 to 1.45) and lethal disease (death or distant metastasis; RR, 1.19; 95% CI, 1.00 to 1.43). Among a subcohort of men receiving regular prostate-specific antigen screening, the association with lethal cancer was stronger (RR, 1.56; 95% CI, 1.03 to 2.36). Vasectomy was not associated with the risk of low-grade or localized disease. Additional analyses suggested that the associations were not driven by differences in sex hormone levels, sexually transmitted infections, or cancer treatment. Conclusion Our data support the hypothesis that vasectomy is associated with a modest increased incidence of lethal prostate cancer. The results do not appear to be due to detection bias, and confounding by infections or cancer treatment is unlikely.

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Predicting the Grade of Prostate Cancer Based on a Biparametric MRI Radiomics Signature

Contrast Media & Molecular Imaging ◽

10.1155/2021/7830909 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Li Zhang ◽

Xia Zhe ◽

Min Tang ◽

Jing Zhang ◽

Jialiang Ren ◽

...

Keyword(s):

Prostate Cancer ◽

Machine Learning ◽

Logistic Regression ◽

Learning Algorithm ◽

Area Under The Curve ◽

Machine Learning Algorithms ◽

Support Vector ◽

Low Grade ◽

High Grade ◽

Random Forest Tree

Purpose. This study aimed to investigate the value of biparametric magnetic resonance imaging (bp-MRI)-based radiomics signatures for the preoperative prediction of prostate cancer (PCa) grade compared with visual assessments by radiologists based on the Prostate Imaging Reporting and Data System Version 2.1 (PI-RADS V2.1) scores of multiparametric MRI (mp-MRI). Methods. This retrospective study included 142 consecutive patients with histologically confirmed PCa who were undergoing mp-MRI before surgery. MRI images were scored and evaluated by two independent radiologists using PI-RADS V2.1. The radiomics workflow was divided into five steps: (a) image selection and segmentation, (b) feature extraction, (c) feature selection, (d) model establishment, and (e) model evaluation. Three machine learning algorithms (random forest tree (RF), logistic regression, and support vector machine (SVM)) were constructed to differentiate high-grade from low-grade PCa. Receiver operating characteristic (ROC) analysis was used to compare the machine learning-based analysis of bp-MRI radiomics models with PI-RADS V2.1. Results. In all, 8 stable radiomics features out of 804 extracted features based on T2-weighted imaging (T2WI) and ADC sequences were selected. Radiomics signatures successfully categorized high-grade and low-grade PCa cases ( P < 0.05 ) in both the training and test datasets. The radiomics model-based RF method (area under the curve, AUC: 0.982; 0.918), logistic regression (AUC: 0.886; 0.886), and SVM (AUC: 0.943; 0.913) in both the training and test cohorts had better diagnostic performance than PI-RADS V2.1 (AUC: 0.767; 0.813) when predicting PCa grade. Conclusions. The results of this clinical study indicate that machine learning-based analysis of bp-MRI radiomic models may be helpful for distinguishing high-grade and low-grade PCa that outperformed the PI-RADS V2.1 scores based on mp-MRI. The machine learning algorithm RF model was slightly better.

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