Non-Invasive Prediction of Prostate Cancer Gleason Scores via Radiomics Analysis

2019 ◽  
Author(s):  
Lixin Gong ◽  
Min Xu ◽  
Mengjie Fang ◽  
Jian Zou ◽  
Shudong Yang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Non Invasive

Expression of Urokinase and Its Receptor in Invasive and Non-Invasive Prostate Cancer Cell Lines

1992 ◽  
Vol 68 (06) ◽  
pp. 662-666 ◽  
Author(s):  
W Hollas ◽  
N Hoosein ◽  
L W K Chung ◽  
A Mazar ◽  
J Henkin ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Steady State ◽  
Cell Surface ◽  
Cell Lines ◽  
Cancer Cell ◽  
Prostate Cancer Cell ◽  
Cancer Cell Lines ◽  
Lncap Cells ◽  
Prostate Cancer Cell Lines ◽  
Non Invasive

SummaryWe previously reported that extracellular matrix invasion by the prostate cancer cell lines, PC-3 and DU-145 was contingent on endogenous urokinase being bound to a specific cell surface receptor. The present study was undertaken to characterize the expression of both urokinase and its receptor in the non-invasive LNCaP and the invasive PC-3 and DU-145 prostate cells. Northern blotting indicated that the invasive PC-3 cells, which secreted 10 times more urokinase (680 ng/ml per 106 cells per 48 h) than DU-145 cells (63 ng/ml per 106 cells per 48 h), had the most abundant transcript for the plasminogen activator. This, at least, partly reflected a 3 fold amplification of the urokinase gene in the PC-3 cells. In contrast, urokinase-specific transcript could not be detected in the non-invasive LNCaP cells previously characterized as being negative for urokinase protein. Southern blotting indicated that this was not a consequence of deletion of the urokinase gene. Crosslinking of radiolabelled aminoterminal fragment of urokinase to the cell surface indicated the presence of a 51 kDa receptor in extracts of the invasive PC-3 and DU-145 cells but not in extracts of the non-invasive LNCaP cells. The amount of binding protein correlated well with binding capacities calculated by Scatchard analysis. In contrast, the steady state level of urokinase receptor transcript was a poor predictor of receptor display. PC-3 cells, which were equipped with 25,000 receptors per cell had 2.5 fold more steady state transcript than DU-145 cells which displayed 93,000 binding sites per cell.

scholarly journals Prostate Cancer Liquid Biopsy Biomarkers’ Clinical Utility in Diagnosis and Prognosis

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3373
Author(s):  
Milena Matuszczak ◽  
Jack A. Schalken ◽  
Maciej Salagierski
Keyword(s):  
Prostate Cancer ◽  
Liquid Biopsy ◽  
Current Knowledge ◽  
Prostate Gland ◽  
Specific Antigen ◽  
Transrectal Ultrasound ◽  
Digital Rectal Examination ◽  
Cost Effective ◽  
Non Invasive ◽  
Diagnosis And Prognosis

Prostate cancer (PCa) is the most common cancer in men worldwide. The current gold standard for diagnosing PCa relies on a transrectal ultrasound-guided systematic core needle biopsy indicated after detection changes in a digital rectal examination (DRE) and elevated prostate-specific antigen (PSA) level in the blood serum. PSA is a marker produced by prostate cells, not just cancer cells. Therefore, an elevated PSA level may be associated with other symptoms such as benign prostatic hyperplasia or inflammation of the prostate gland. Due to this marker’s low specificity, a common problem is overdiagnosis, which leads to unnecessary biopsies and overtreatment. This is associated with various treatment complications (such as bleeding or infection) and generates unnecessary costs. Therefore, there is no doubt that the improvement of the current procedure by applying effective, sensitive and specific markers is an urgent need. Several non-invasive, cost-effective, high-accuracy liquid biopsy diagnostic biomarkers such as Progensa PCA3, MyProstateScore ExoDx, SelectMDx, PHI, 4K, Stockholm3 and ConfirmMDx have been developed in recent years. This article compares current knowledge about them and their potential application in clinical practice.

scholarly journals Novel, non-invasive markers for detecting therapy induced neuroendocrine differentiation in castration-resistant prostate cancer patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Divya Bhagirath ◽  
Michael Liston ◽  
Theresa Akoto ◽  
Byron Lui ◽  
Barbara A. Bensing ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Patients ◽  
Neuroendocrine Differentiation ◽  
Extracellular Vesicle ◽  
Machine Learning Algorithms ◽  
Castration Resistant Prostate Cancer ◽  
Cellular Models ◽  
Non Invasive ◽  
Castration Resistant ◽  
Neuroendocrine Prostate Cancer

AbstractNeuroendocrine prostate cancer (NEPC), a highly aggressive variant of castration-resistant prostate cancer (CRPC), often emerges upon treatment with androgen pathway inhibitors, via neuroendocrine differentiation. Currently, NEPC diagnosis is challenging as available markers are not sufficiently specific. Our objective was to identify novel, extracellular vesicles (EV)-based biomarkers for diagnosing NEPC. Towards this, we performed small RNA next generation sequencing in serum EVs isolated from a cohort of CRPC patients with adenocarcinoma characteristics (CRPC-Adeno) vs CRPC-NE and identified significant dysregulation of 182 known and 4 novel miRNAs. We employed machine learning algorithms to develop an ‘EV-miRNA classifier’ that could robustly stratify ‘CRPC-NE’ from ‘CRPC-Adeno’. Examination of protein repertoire of exosomes from NEPC cellular models by mass spectrometry identified thrombospondin 1 (TSP1) as a specific biomarker. In view of our results, we propose that a miRNA panel and TSP1 can be used as novel, non-invasive tools to identify NEPC and guide treatment decisions. In conclusion, our study identifies for the first time, novel non-invasive exosomal/extracellular vesicle based biomarkers for detecting neuroendocrine differentiation in advanced castration resistant prostate cancer patients with important translational implications in clinical management of these patients that is currently extremely challenging.

scholarly journals Biofluid quantification of TWEAK/Fn14 axis in combination with a selected biomarker panel improves assessment of prostate cancer aggressiveness

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Xavier Ruiz-Plazas ◽  
Esther Rodríguez-Gallego ◽  
Marta Alves ◽  
Antonio Altuna-Coy ◽  
Javier Lozano-Bartolomé ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Biochemistry ◽  
Specific Antigen ◽  
Total Serum ◽  
Mrna Levels ◽  
Biomarker Panel ◽  
Non Invasive ◽  
Clinical Biomarkers ◽  
Cancer Aggressiveness ◽  
Aggressive Tumors

Abstract Background Conventional clinical biomarkers cannot accurately differentiate indolent from aggressive prostate cancer (PCa). We investigated the usefulness of a biomarker panel measured exclusively in biofluids for assessment of PCa aggressiveness. Methods We collected biofluid samples (plasma/serum/semen/post-prostatic massage urine) from 98 patients that had undergone radical prostatectomy. Clinical biochemistry was performed and several cytokines/chemokines including soluble(s) TWEAK, sFn14, sCD163, sCXCL5 and sCCL7 were quantified by ELISA in selected biofluids. Also, the expression of KLK2, KLK3, Fn14, CD163, CXCR2 and CCR3 was quantified by real-time PCR in semen cell sediment. Univariate, logistic regression, and receiver operating characteristic (ROC) analyses were used to assess the predictive ability of the selected biomarker panel in conjunction with clinical and metabolic variables for the evaluation of PCa aggressiveness. Results Total serum levels of prostate-specific antigen (PSA), semen levels of sTWEAK, fasting glycemia and mRNA levels of Fn14, KLK2, CXCR2 and CCR3 in semen cell sediment constituted a panel of markers that was significantly different between patients with less aggressive tumors [International Society of Urological Pathology (ISUP) grade I and II] and those with more aggressive tumors (ISUP grade III, IV and V). ROC curve analysis showed that this panel could be used to correctly classify tumor aggressiveness in 90.9% of patients. Area under the curve (AUC) analysis revealed that this combination was more accurate [AUC = 0.913 95% confidence interval (CI) 0.782–1] than a classical non-invasive selected clinical panel comprising age, tumor clinical stage (T-classification) and total serum PSA (AUC = 0.721 95% CI 0.613–0.830). Conclusions TWEAK/Fn14 axis in combination with a selected non-invasive biomarker panel, including conventional clinical biochemistry, can improve the predictive power of serum PSA levels and could be used to classify PCa aggressiveness.

scholarly journals Integration of Urinary EN2 Protein & Cell-Free RNA Data in the Development of a Multivariable Risk Model for the Detection of Prostate Cancer Prior to Biopsy

Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 2102
Author(s):  
Shea Connell ◽  
Robert Mills ◽  
Hardev Pandha ◽  
Richard Morgan ◽  
Colin Cooper ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Model ◽  
Action Plan ◽  
Digital Rectal Examination ◽  
Standards Of Care ◽  
Net Benefit ◽  
Protein Levels ◽  
Non Invasive ◽  
Trus Biopsy ◽  
Diagnostic Potential

The objective is to develop a multivariable risk model for the non-invasive detection of prostate cancer prior to biopsy by integrating information from clinically available parameters, Engrailed-2 (EN2) whole-urine protein levels and data from urinary cell-free RNA. Post-digital-rectal examination urine samples collected as part of the Movember Global Action Plan 1 study which has been analysed for both cell-free-RNA and EN2 protein levels were chosen to be integrated with clinical parameters (n = 207). A previously described robust feature selection framework incorporating bootstrap resampling and permutation was applied to the data to generate an optimal feature set for use in Random Forest models for prediction. The fully integrated model was named ExoGrail, and the out-of-bag predictions were used to evaluate the diagnostic potential of the risk model. ExoGrail risk (range 0–1) was able to determine the outcome of an initial trans-rectal ultrasound guided (TRUS) biopsy more accurately than clinical standards of care, predicting the presence of any cancer with an area under the receiver operator curve (AUC) = 0.89 (95% confidence interval(CI): 0.85–0.94), and discriminating more aggressive Gleason ≥ 3 + 4 disease returning an AUC = 0.84 (95% CI: 0.78–0.89). The likelihood of more aggressive disease being detected significantly increased as ExoGrail risk score increased (Odds Ratio (OR) = 2.21 per 0.1 ExoGrail increase, 95% CI: 1.91–2.59). Decision curve analysis of the net benefit of ExoGrail showed the potential to reduce the numbers of unnecessary biopsies by 35% when compared to current standards of care. Integration of information from multiple, non-invasive biomarker sources has the potential to greatly improve how patients with a clinical suspicion of prostate cancer are risk-assessed prior to an invasive biopsy.

scholarly journals Identification of non-invasive miRNAs biomarkers for prostate cancer by deep sequencing analysis of urinary exosomes

2017 ◽  
Vol 16 (1) ◽  
Author(s):  
Marta Rodríguez ◽  
Cristina Bajo-Santos ◽  
Nina P. Hessvik ◽  
Susanne Lorenz ◽  
Bastian Fromm ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Deep Sequencing ◽  
Sequencing Analysis ◽  
Non Invasive ◽  
Urinary Exosomes ◽  
Deep Sequencing Analysis

Circulating microRNAs combined with PSA for accurate and non-invasive prostate cancer detection

2018 ◽  
Vol 40 (2) ◽  
pp. 246-253 ◽  
Author(s):  
Maurizia Mello-Grand ◽  
Ilaria Gregnanin ◽  
Lidia Sacchetto ◽  
Paola Ostano ◽  
Andrea Zitella ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Detection ◽  
Circulating Micrornas ◽  
Prostate Cancer Detection ◽  
Non Invasive

scholarly journals Plasma ghrelin O-acyltransferase (GOAT) enzyme levels: A novel non-invasive diagnosis tool for patients with significant prostate cancer

2018 ◽  
Vol 22 (11) ◽  
pp. 5688-5697 ◽  
Author(s):  
Enrique Gómez-Gómez ◽  
Juan M. Jiménez-Vacas ◽  
Julia Carrasco-Valiente ◽  
Vicente Herrero-Aguayo ◽  
Ana M. Blanca-Pedregosa ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Non Invasive ◽  
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