Evidence map›Paper›PMID 32820256›Full record

ArticleProstate cancer and prostatic diseases2021

A novel method for detection of exfoliated prostate cancer cells in urine by RNA in situ hybridization.

Jillian N Eskra, Daniel Rabizadeh, Leslie Mangold, Elizabeth Fabian, W Nathaniel Brennen, David B Yeater, Kenneth J Pienta, Alan W Partin, William B Isaacs, Christian P Pavlovich and 1 more

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Article in Prostate cancer and prostatic diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 50% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 1 institution in 1 country.

Jillian N EskraDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-1821-8783
Daniel RabizadehDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Leslie MangoldDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Elizabeth FabianDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
W Nathaniel BrennenDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0001-9807-7433
David B YeaterDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Kenneth J PientaDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-4138-2186
Alan W PartinDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
William B IsaacsDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Christian P PavlovichDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Jun LuoDepartment of Urology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA. jluo1@jhmi.edu.ORCID http://orcid.org/0000-0002-1414-473X
Johns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the current study, we explore the feasibility of detecting exfoliated prostate cancer cells in urine using an RNA in situ hybridization (RISH) assay. We hypothesized that robust and specific labeling of prostate cancer cells could be achieved in post-digital rectal examination (DRE) urine samples using RISH.

methodsWe focused on method development, optimization, and analytical evaluation of RISH-based detection of prostate cancer in urine. We optimized a sample collection, processing, and target detection workflow for urine cytology specimens in conjunction with RNA target detection by RISH. We screened a panel of 11 prostate-specific RNA targets, and selected NKX3-1 and PRAC1 as markers for cells of prostate origin and PCA3 as a marker of prostate malignancy. Following analytical validation of a multiplexed NKX3-1/PRAC1/PCA3 assay, we evaluated whether prostate cancer cells can be detected in a pilot cohort of 19 post-DRE specimens obtained from men diagnosed with prostate cancer.

resultsUsing cytology specimens prepared from spiked urine samples, we established the analytical validity of the RISH assay for detection and visualization of prostate cells in urine. Cells of prostate origin could be readily and specifically identified and separated into benign and malignant cell populations based on the multiplex test that consisted of markers specific for prostate cells (NKX3-1, PRAC1) and prostate cancer cells (PCA3). Upon evaluation of post-DRE urine from a pilot cohort of prostate cancer patients, we identified 11 samples in which prostate cells were present, 6 of which were also positive for prostate cancer cells.

conclusionsMultiplex RISH enables the direct visualization and molecular characterization of individual exfoliated prostate cells in urine. This proof-of-principle study provides evidence supporting the application of RISH as a potential noninvasive tool for prostate cancer detection.

Indexed as

Antigens, NeoplasmBiomarkers, TumorHumansIn Situ HybridizationMaleProstatic NeoplasmsRNA, NeoplasmTumor Cells, CulturedAntigens, NeoplasmBiomarkers, Tumorprostate cancer antigen 3, humanRNA, Neoplasm

Identifiers

PMID32820256
OpenAlexW3078458936

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.