Development and validation of a 25-Gene Panel urine test for prostate cancer diagnosis and potential treatment follow-up

Abstract Background Heterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies. Methods Using a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRT-PCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy. Results The 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963–0.929) in the retrospective cohort (n = 614), AUC of 0.901 (0.929–0.873) in the prospective cohort (n = 396), and AUC of 0.936 (0.956–0.916) in the large combination cohort (n = 1010). It greatly improved diagnostic accuracy over PSA and risk factors (p < 0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980–0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947–0.909) in the combination cohort (n = 727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy. Conclusions The 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.

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Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients

Frontiers in Medicine ◽

10.3389/fmed.2021.721554 ◽

2021 ◽

Vol 8 ◽

Author(s):

Jinan Guo ◽

Xuhui Zhang ◽

Taolin Xia ◽

Heather Johnson ◽

Xiaoyan Feng ◽

...

Keyword(s):

Prostate Cancer ◽

Cancer Patients ◽

Clinical Significance ◽

Treatment Decision ◽

Urine Test ◽

Newly Diagnosed ◽

Grade Group ◽

Non Invasive ◽

Insignificant Cancer ◽

Clinically Significant

Objective: To avoid over-treatment of low-risk prostate cancer patients, it is important to identify clinically significant and insignificant cancer for treatment decision-making. However, no accurate test is currently available.Methods: To address this unmet medical need, we developed a novel gene classifier to distinguish clinically significant and insignificant cancer, which were classified based on the National Comprehensive Cancer Network risk stratification guidelines. A non-invasive urine test was developed using quantitative mRNA expression data of 24 genes in the classifier with an algorithm to stratify the clinical significance of the cancer. Two independent, multicenter, retrospective and prospective studies were conducted to assess the diagnostic performance of the 24-Gene Classifier and the current clinicopathological measures by univariate and multivariate logistic regression and discriminant analysis. In addition, assessments were performed in various Gleason grades/ISUP Grade Groups.Results: The results showed high diagnostic accuracy of the 24-Gene Classifier with an AUC of 0.917 (95% CI 0.892–0.942) in the retrospective cohort (n = 520), AUC of 0.959 (95% CI 0.935–0.983) in the prospective cohort (n = 207), and AUC of 0.930 (95% 0.912-CI 0.947) in the combination cohort (n = 727). Univariate and multivariate analysis showed that the 24-Gene Classifier was more accurate than cancer stage, Gleason score, and PSA, especially in the low/intermediate-grade/ISUP Grade Group 1–3 cancer subgroups.Conclusions: The 24-Gene Classifier urine test is an accurate and non-invasive liquid biopsy method for identifying clinically significant prostate cancer in newly diagnosed cancer patients. It has the potential to improve prostate cancer treatment decisions and active surveillance.

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Establishing a Urine-Based Biomarker Assay for Prostate Cancer Risk Stratification

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2020.597961 ◽

2020 ◽

Vol 8 ◽

Author(s):

Jinan Guo ◽

Dale Liu ◽

Xuhui Zhang ◽

Heather Johnson ◽

Xiaoyan Feng ◽

...

Keyword(s):

Prostate Cancer ◽

Risk Stratification ◽

Gleason Score ◽

Prospective Cohort ◽

Lower Risk ◽

Treatment Decision ◽

Gene Panel ◽

Urine Test ◽

Non Invasive ◽

Lower Accuracy

One of the major features of prostate cancer (PCa) is its heterogeneity, which often leads to uncertainty in cancer diagnostics and unnecessary biopsies as well as overtreatment of the disease. Novel non-invasive tests using multiple biomarkers that can identify clinically high-risk cancer patients for immediate treatment and monitor patients with low-risk cancer for active surveillance are urgently needed to improve treatment decision and cancer management. In this study, we identified 14 promising biomarkers associated with PCa and tested the performance of these biomarkers on tissue specimens and pre-biopsy urinary sediments. These biomarkers showed differential gene expression in higher- and lower-risk PCa. The 14-Gene Panel urine test (PMP22, GOLM1, LMTK2, EZH2, GSTP1, PCA3, VEGFA, CST3, PTEN, PIP5K1A, CDK1, TMPRSS2, ANXA3, and CCND1) was assessed in two independent prospective and retrospective urine study cohorts and showed high diagnostic accuracy to identify higher-risk PCa patients with the need for treatment and lower-risk patients for surveillance. The AUC was 0.897 (95% CI 0.939–0.855) in the prospective cohort (n = 202), and AUC was 0.899 (95% CI 0.964–0.834) in the retrospective cohort (n = 97). In contrast, serum PSA and Gleason score had much lower accuracy in the same 202 patient cohorts [AUC was 0.821 (95% CI 0.879–0.763) for PSA and 0.860 (95% CI 0.910–0.810) for Gleason score]. In addition, the 14-Gene Panel was more accurate at risk stratification in a subgroup of patients with Gleason scores 6 and 7 in the prospective cohort (n = 132) with AUC of 0.923 (95% CI 0.968–0.878) than PSA [AUC of 0.773 (95% CI 0.852–0.794)] and Gleason score [AUC of 0.776 (95% CI 0.854–0.698)]. Furthermore, the 14-Gene Panel was found to be able to accurately distinguish PCa from benign prostate with AUC of 0.854 (95% CI 0.892–0.816) in a prospective urine study cohort (n = 393), while PSA had lower accuracy with AUC of 0.652 (95% CI 0.706–0.598). Taken together, the 14-Gene Panel urine test represents a promising non-invasive tool for detection of higher-risk PCa to aid treatment decision and lower-risk PCa for active surveillance.

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Development of Internet-Accessible Prediction Models for Prostate Cancer Diagnosis, Treatment, and Follow-Up

10.21236/ada413542 ◽

2003 ◽

Author(s):

Leon Sun ◽

Judd W. Moul ◽

Hongyu Wu ◽

Fatiha Bensouda ◽

Holly Wu

Keyword(s):

Prostate Cancer ◽

Cancer Diagnosis ◽

Prediction Models ◽

Prostate Cancer Diagnosis

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Risk Factors for Prostate Cancer Detection After a Negative Biopsy: A Novel Multivariable Longitudinal Approach

Journal of Clinical Oncology ◽

10.1200/jco.2008.20.3422 ◽

2010 ◽

Vol 28 (10) ◽

pp. 1714-1720 ◽

Cited By ~ 50

Author(s):

Peter H. Gann ◽

Angela Fought ◽

Ryan Deaton ◽

William J. Catalona ◽

Edward Vonesh

Keyword(s):

Prostate Cancer ◽

Risk Factors ◽

Specific Antigen ◽

Time Dependent ◽

Negative Biopsy ◽

Gland Volume ◽

Piecewise Exponential ◽

Over Time ◽

Negative Biopsies

Purpose To introduce a novel approach for the time-dependent quantification of risk factors for prostate cancer (PCa) detection after an initial negative biopsy. Patients and Methods Data for 1,871 men with initial negative biopsies and at least one follow-up biopsy were available. Piecewise exponential regression models were developed to quantify hazard ratios (HRs) and define cumulative incidence curves for PCa detection for subgroups with specific patterns of risk factors over time. Factors evaluated included age, race, serum prostate-specific antigen (PSA) concentration, PSA slope, digital rectal examination, dysplastic glands or prostatitis on biopsy, ultrasound gland volume, urinary symptoms, and number of negative biopsies. Results Four hundred sixty-five men had PCa detected, after a mean follow-up time of 2.8 years. All of the factors were independent predictors of PCa detection except for PSA slope, as a result of its correlation with time-dependent PSA level, and race. PSA (HR = 3.90 for > 10 v 2.5 to 3.9 ng/mL), high-grade prostatic intraepithelial neoplasia/atypical glands (HR = 2.97), gland volume (HR = 0.39 for > 50 v < 25 mL), and number of repeat biopsies (HR = 0.36 for two v zero repeat biopsies) were the strongest predictors. Men with high-risk versus low-risk event histories had a 20-fold difference in PCa detection over 5 years. Conclusion Piecewise exponential models provide an approach to longitudinal analysis of PCa risk that allows clinicians to see the interplay of risk factors as they unfold over time for individual patients. With these models, it is possible to identify distinct subpopulations with dramatically different needs for monitoring and repeat biopsy.

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A prospective randomized study comparing MRI-based and standard pathway for prostate cancer diagnosis: Three years follow up

European Urology Supplements ◽

10.1016/s1569-9056(18)33058-6 ◽

2018 ◽

Vol 17 (8) ◽

pp. 176-177

Author(s):

M. Manfredi ◽

C. Fiori ◽

I. Morra ◽

M. Cossu ◽

S. De Luca ◽

...

Keyword(s):

Prostate Cancer ◽

Cancer Diagnosis ◽

Randomized Study ◽

Prospective Randomized Study ◽

Prostate Cancer Diagnosis

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Predictors of the development of takotsubo cardiomyopathy in aneurysmal subarachnoid hemorrhage and outcomes in patients with intra-aortic balloon pumps

Journal of Neurosurgery ◽

10.3171/2020.5.jns20536 ◽

2020 ◽

pp. 1-6

Author(s):

Joshua S. Catapano ◽

Andrew F. Ducruet ◽

Fabio A. Frisoli ◽

Candice L. Nguyen ◽

Christopher E. Louie ◽

...

Keyword(s):

Risk Factors ◽

Subarachnoid Hemorrhage ◽

Takotsubo Cardiomyopathy ◽

Aneurysmal Subarachnoid Hemorrhage ◽

Multivariate Logistic Regression Analysis ◽

High Morbidity ◽

Female Patients ◽

Neurological Outcomes ◽

Poor Outcomes

OBJECTIVETakotsubo cardiomyopathy (TC) in patients with aneurysmal subarachnoid hemorrhage (aSAH) is associated with high morbidity and mortality. Previous studies have shown that female patients presenting with a poor clinical grade are at the greatest risk for developing TC. Intra-aortic balloon pumps (IABPs) are known to support cardiac function in severe cases of TC, and they may aid in the treatment of vasospasm in these patients. In this study, the authors investigated risk factors for developing TC in the setting of aSAH and outcomes among patients requiring IABPs.METHODSThe authors retrospectively reviewed the records of 1096 patients who had presented to their institution with aSAH. Four hundred five of these patients were originally enrolled in the Barrow Ruptured Aneurysm Trial, and an additional 691 patients from a subsequent prospectively maintained aSAH database were analyzed. Medical records were reviewed for the presence of TC according to the modified Mayo Clinic criteria. Outcomes were determined at the last follow-up, with a poor outcome defined as a modified Rankin Scale (mRS) score > 2.RESULTSTC was identified in 26 patients with aSAH. Stepwise multivariate logistic regression analysis identified female sex (OR 8.2, p = 0.005), Hunt and Hess grade > III (OR 7.6, p < 0.001), aneurysm size > 7 mm (OR 3, p = 0.011), and clinical vasospasm (OR 2.9, p = 0.037) as risk factors for developing TC in the setting of aSAH. TC patients, even with IABP placement, had higher rates of poor outcomes (77% vs 47% with an mRS score > 2, p = 0.004) and mortality at the last follow-up (27% vs 11%, p = 0.018) than the non-TC patients. However, aggressive intra-arterial endovascular treatment for vasospasm was associated with good outcomes in the TC patients versus nonaggressive treatment (100% with mRS ≤ 2 at last follow-up vs 53% with mRS > 2, p = 0.040).CONCLUSIONSTC after aSAH tends to occur in female patients with large aneurysms, poor clinical grades, and clinical vasospasm. These patients have significantly higher rates of poor neurological outcomes, even with the placement of an IABP. However, aggressive intra-arterial endovascular therapy in select patients with vasospasm may improve outcome.

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Radiotracers Used in Nuclear Medicine for Prostate Cancer Diagnosis and Follow-Up

Gaceta Mexicana de Oncolog�a ◽

10.24875/j.gamo.17000007 ◽

2019 ◽

Vol 16 (1) ◽

Author(s):

Francisco O. García-Pérez ◽

Sevastián S. Medina-Ornelas

Keyword(s):

Prostate Cancer ◽

Nuclear Medicine ◽

Cancer Diagnosis ◽

Prostate Cancer Diagnosis

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Biomarkers for Bladder Cancer Diagnosis and Surveillance: A Comprehensive Review

Diagnostics ◽

10.3390/diagnostics10010039 ◽

2020 ◽

Vol 10 (1) ◽

pp. 39 ◽

Cited By ~ 10

Author(s):

Rui Batista ◽

Nuno Vinagre ◽

Sara Meireles ◽

João Vinagre ◽

Hugo Prazeres ◽

...

Keyword(s):

Bladder Cancer ◽

Treatment Response ◽

Cancer Diagnosis ◽

Complex Disease ◽

Molecular Biomarkers ◽

Clinical Staging ◽

Response Monitoring ◽

High Morbidity ◽

Non Invasive

Bladder cancer (BC) ranks as the sixth most prevalent cancer in the world, with a steady rise in its incidence and prevalence, and is accompanied by a high morbidity and mortality. BC is a complex disease with several molecular and pathological pathways, thus reflecting different behaviors depending on the clinical staging of the tumor and molecular type. Diagnosis and monitoring of BC is mainly performed by invasive tests, namely periodic cystoscopies; this procedure, although a reliable method, is highly uncomfortable for the patient and it is not exempt of comorbidities. Currently, there is no formal indication for the use of molecular biomarkers in clinical practice, even though there are several tests available. There is an imperative need for a clinical non-invasive testing for early detection, disease monitoring, and treatment response in BC. In this review, we aim to assess and compare different tests based on molecular biomarkers and evaluate their potential role as new molecules for bladder cancer diagnosis, follow-up, and treatment response monitoring.

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