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Non-invasive Urine Test for Molecular Classification of Clinical Significance in Newly Diagnosed Prostate Cancer Patients.
Guo, Jinan; Zhang, Xuhui; Xia, Taolin; Johnson, Heather; Feng, Xiaoyan; Simoulis, Athanasios; Wu, Alan H B; Li, Fei; Tan, Wanlong; Johnson, Allan; Dizeyi, Nishtman; Abrahamsson, Per-Anders; Kenner, Lukas; Xiao, Kefeng; Zhang, Heqiu; Chen, Lingwu; Zou, Chang; Persson, Jenny L.
Afiliação
  • Guo J; Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, China.
  • Zhang X; Shenzhen Urology Minimally Invasive Engineering Center, Shenzhen, China.
  • Xia T; Shenzhen Public Service Platform on Tumor Precision Medicine and Molecular Diagnosis, Clinical Medicine Research Centre, Shenzhen, China.
  • Johnson H; Department of Bio-diagnosis, Institute of Basic Medical Sciences, Beijing, China.
  • Feng X; Department of Urology, Foshan First People's Hospital, Foshan, China.
  • Simoulis A; Olympia Diagnostics, Inc., Sunnyvale, CA, United States.
  • Wu AHB; Department of Bio-diagnosis, Institute of Basic Medical Sciences, Beijing, China.
  • Li F; Department of Clinical Pathology and Cytology, Skåne University Hospital, Malmö, Sweden.
  • Tan W; Clinical Laboratories, San Francisco General Hospital, San Francisco, CA, United States.
  • Johnson A; Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Dizeyi N; Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Abrahamsson PA; Kinetic Reality, Santa Clara, CA, United States.
  • Kenner L; Department of Translational Medicine, Clinical Research Centre, Lund University, Malmö, Sweden.
  • Xiao K; Department of Translational Medicine, Clinical Research Centre, Lund University, Malmö, Sweden.
  • Zhang H; Department of Experimental Pathology, Medical University Vienna & Unit of Laboratory Animal Pathology, University of Veterinary Medicine, Vienna, Austria.
  • Chen L; Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, China.
  • Zou C; Shenzhen Urology Minimally Invasive Engineering Center, Shenzhen, China.
  • Persson JL; Shenzhen Public Service Platform on Tumor Precision Medicine and Molecular Diagnosis, Clinical Medicine Research Centre, Shenzhen, China.
Front Med (Lausanne) ; 8: 721554, 2021.
Article em En | MEDLINE | ID: mdl-34595190
ABSTRACT

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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Diagnostic_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Med (Lausanne) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Diagnostic_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Med (Lausanne) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China
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