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Identification of urinary biomarkers of colorectal cancer: Towards the development of a colorectal screening test in limited resource settings.
Zhang, Lun; Zheng, Jiamin; Ismond, Kathleen P; MacKay, Scott; LeVatte, Marcia; Constable, Jeremy; Isaac Alatise, Olusegun; Peter Kingham, T; Wishart, David S.
Afiliação
  • Zhang L; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
  • Zheng J; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
  • Ismond KP; Department of Medicine, University of Alberta, Edmonton, AB, Canada.
  • MacKay S; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
  • LeVatte M; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
  • Constable J; Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Isaac Alatise O; Department of Surgery, Obafemi Awolowo University and Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, Nigeria.
  • Peter Kingham T; Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Wishart DS; Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
Cancer Biomark ; 36(1): 17-30, 2023.
Article em En | MEDLINE | ID: mdl-35871322
ABSTRACT

BACKGROUND:

African colorectal cancer (CRC) rates are rising rapidly. A low-cost CRC screening approach is needed to identify CRC from non-CRC patients who should be sent for colonoscopy (a scarcity in Africa).

OBJECTIVE:

To identify urinary metabolite biomarkers that, combined with easy-to-measure clinical variables, would identify patients that should be further screened for CRC by colonoscopy. Ideal metabolites would be water-soluble and easily translated into a sensitive, low-cost point-of-care (POC) test.

METHODS:

Liquid-chromatography mass spectrometry (LC-MS/MS) was used to quantify 142 metabolites in spot urine samples from 514 Nigerian CRC patients and healthy controls. Metabolite concentration data and clinical characteristics were used to determine optimal sets of biomarkers for identifying CRC from non-CRC subjects.

RESULTS:

Our statistical analysis identified N1, N12-diacetylspermine, hippurate, p-hydroxyhippurate, and glutamate as the best metabolites to discriminate CRC patients via POC screening. Logistic regression modeling using these metabolites plus clinical data achieved an area under the receiver-operator characteristic (AUCs) curves of 89.2% for the discovery set, and 89.7% for a separate validation set.

CONCLUSIONS:

Effective urinary biomarkers for CRC screening do exist. These results could be transferred into a simple, POC urinary test for screening CRC patients in Africa.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Detecção Precoce de Câncer Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Humans Idioma: En Revista: Cancer Biomark Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Detecção Precoce de Câncer Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Humans Idioma: En Revista: Cancer Biomark Ano de publicação: 2023 Tipo de documento: Article