Influencing Factors on the Oncuria™ Urinalysis Assay: An Experimental Model.

biomarkers bladder cancer multiplex protein urinalysis

Journal

Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402

Informations de publication

Date de publication:
03 Jun 2021
Historique:
received: 31 03 2021
revised: 20 05 2021
accepted: 01 06 2021
entrez: 2 7 2021
pubmed: 3 7 2021
medline: 3 7 2021
Statut: epublish

Résumé

The Oncuria™ urine test for the detection of bladder cancer measures a multiplex protein signature. In this study, we investigated the influence of urinary cellularity, protein, and hematuria on the performance of the Oncuria™ test in an ex vivo experimental model. Pooled urine from healthy subjects was spiked with cultured benign (UROtsa) or malignant cells (T24), cellular proteins, or whole blood. The resulting samples were analyzed using the Oncuria™ test following the manufacturer's instructions. Urine samples obtained from healthy subjects were negative for bladder cancer by Oncuria™ test criteria. The majority of the manipulated conditions did not result in a false-positive test. The addition of whole blood (high concentration) did result in a false-positive result, but this was abrogated by sample centrifugation prior to analysis. The addition of cellular proteins (high concentration) resulted in a positive Oncuria™ test, and this was unaffected by pre-analysis sample centrifugation. The Oncuria™ multiplex test performed well in the ex vivo experimental model and shows promise for clinical application. The identification of patients who require additional clinical evaluation could reduce the need to subject patients who do not have bladder cancer to frequent, uncomfortable and expensive cystoscopic examinations, thus benefiting both patients and the healthcare system.

Sections du résumé

BACKGROUND BACKGROUND
The Oncuria™ urine test for the detection of bladder cancer measures a multiplex protein signature. In this study, we investigated the influence of urinary cellularity, protein, and hematuria on the performance of the Oncuria™ test in an ex vivo experimental model.
MATERIALS AND METHODS METHODS
Pooled urine from healthy subjects was spiked with cultured benign (UROtsa) or malignant cells (T24), cellular proteins, or whole blood. The resulting samples were analyzed using the Oncuria™ test following the manufacturer's instructions.
RESULTS RESULTS
Urine samples obtained from healthy subjects were negative for bladder cancer by Oncuria™ test criteria. The majority of the manipulated conditions did not result in a false-positive test. The addition of whole blood (high concentration) did result in a false-positive result, but this was abrogated by sample centrifugation prior to analysis. The addition of cellular proteins (high concentration) resulted in a positive Oncuria™ test, and this was unaffected by pre-analysis sample centrifugation.
CONCLUSIONS CONCLUSIONS
The Oncuria™ multiplex test performed well in the ex vivo experimental model and shows promise for clinical application. The identification of patients who require additional clinical evaluation could reduce the need to subject patients who do not have bladder cancer to frequent, uncomfortable and expensive cystoscopic examinations, thus benefiting both patients and the healthcare system.

Identifiants

pubmed: 34204951
pii: diagnostics11061023
doi: 10.3390/diagnostics11061023
pmc: PMC8229062
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NCI NIH HHS
ID : R01 CA1988887
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA206584
Pays : United States

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Auteurs

Kaoru Murakami (K)

Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.

Ian Pagano (I)

Cancer Prevention and Control Program, University of Hawaii Cancer Center, Honolulu, HI 96813, USA.

Runpu Chen (R)

Department of Microbiology and Immunology, The State University of New York at Buffalo, Buffalo, NY 14260, USA.

Yijun Sun (Y)

Department of Microbiology and Immunology, The State University of New York at Buffalo, Buffalo, NY 14260, USA.
Department of Computer Science and Engineering, The State University of New York at Buffalo, Buffalo, NY 14260, USA.
Department of Biostatistics, The State University of New York at Buffalo, Buffalo, NY 14260, USA.

Steve Goodison (S)

Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL 32224, USA.

Charles J Rosser (CJ)

Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
Nonagen Bioscience Corporation, Los Angeles, CA 90010, USA.

Hideki Furuya (H)

Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.

Classifications MeSH