Dataset Information

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?ConclusionsThe 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.

SUBMITTER: Johnson H

PROVIDER: S-EPMC7706045 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

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

Johnson Heather H Guo Jinan J Zhang Xuhui X Zhang Heqiu H Simoulis Athanasios A Wu Alan H B AHB Xia Taolin T Li Fei F Tan Wanlong W Johnson Allan A Dizeyi Nishtman N Abrahamsson Per-Anders PA Kenner Lukas L Feng Xiaoyan X Zou Chang C Xiao Kefeng K Persson Jenny L JL Chen Lingwu L

BMC medicine 20201201 1

<h4>Background</h4>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.<h4>Methods</h4>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) w ...[more]

PMID: 33256740

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Project description:Background:One of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high-as the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood test (FOBT) have low compliance (~ 40%) and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (≥ 97%), if they can at least match the sensitivity and specificity of FOBTs. However, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin). Methods:A combination of high abundance protein ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasma samples (i.e., pools of 20 healthy and 20 stages I-IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p < 0.05; fold-change > 1.5), and further examined with a neural network classification method using in silico augmented 5000 patient datasets. Results:Ultradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, 7 candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC. Conclusion:MS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature.

Project description:BackgroundOver one million men undergo prostate biopsies annually in the United States, a majority of whom due to elevated serum PSA. More than half of the biopsies turn out to be negative for prostate cancer (CaP). The limitations of both the PSA test and the biopsy procedure have led to the development for more precise CaP detection assays in urine (e.g., PCA3, TMPRSS2-ERG) or blood (e.g., PHI, 4K). Here, we describe the development and evaluation of the Urine CaP Marker Panel (UCMP) assay for sensitive and reproducible detection of CaP cells in post-digital rectal examination (post-DRE) urine.MethodsThe cellular content of the post-DRE urine was captured on a translucent filter membrane, which is placed on Cytoclear slides for direct evaluation by microscopy and immuno-cytochemistry (ICC). Cells captured on the membrane were assayed for PSA and Prostein expression to identify prostate epithelial cells, and for ERG and AMACR to identify prostate tumor cells. Immunostained cells were analyzed for quantitative and qualitative features and correlated with biopsy positive and negative status for malignancy.ResultsThe assay was optimized for single cell capture sensitivity and downstream evaluations by spiking a known number of cells from established CaP cell lines, LNCaP and VCaP, into pre-cleared control urine. The cells captured from the post-DRE urine of subjects, obtained prior to biopsy procedure, were co-stained for ERG, AMACR (CaP specific), and Prostein or PSA (prostate epithelium specific) rendering a whole cell based analysis and characterization. A feasibility cohort of 63 post-DRE urine specimens was assessed. Comparison of the UCMP results with blinded biopsy results showed an assay sensitivity of 64% (16 of 25) and a specificity of 68.8% (22 of 32) for CaP detection by biopsy.ConclusionsThis pilot study assessing a minimally invasive CaP detection assay with single cell sensitivity cell-capture and characterization from the post-DRE urine holds promise for further development of this novel assay platform. Prostate 75: 969-975, 2015. © 2015 The Authors. The Prostate, published by Wiley Periodicals, Inc.

Dataset Information

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

Background

Methods

Results

Publications

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

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