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Targeted Proteomics Identifies Proteomic Signatures in Liquid Biopsies of the Endometrium to Diagnose Endometrial Cancer and Assist in the Prediction of the Optimal Surgical Treatment.
Martinez-Garcia, Elena; Lesur, Antoine; Devis, Laura; Cabrera, Silvia; Matias-Guiu, Xavier; Hirschfeld, Marc; Asberger, Jasmin; van Oostrum, Jan; Casares de Cal, María de Los Ángeles; Gómez-Tato, Antonio; Reventos, Jaume; Domon, Bruno; Colas, Eva; Gil-Moreno, Antonio.
Afiliación
  • Martinez-Garcia E; Biomedical Research Group in Gynecology, Vall Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, CIBERONC, Barcelona, Spain.
  • Lesur A; Luxembourg Clinical Proteomics Center (LCP), Luxembourg Institute of Health (LIH), Strassen, Luxembourg.
  • Devis L; Biomedical Research Group in Gynecology, Vall Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, CIBERONC, Barcelona, Spain.
  • Cabrera S; Gynecology Department, Vall Hebron University Hospital, Barcelona, Spain.
  • Matias-Guiu X; Pathological Oncology Group and Pathology Department, University Hospital Arnau de Vilanova, and University Hospital Bellvitge, IRBLLEIDA and Idibell, University of Lleida, CIBERONC, Barcelona, Spain.
  • Hirschfeld M; Department of Obstetrics and Gynecology, University Medical Center, Albert-Ludwigs-University, Freiburg, Germany.
  • Asberger J; Institute of Veterinary Medicine, Georg-August-University Goettingen, Germany.
  • van Oostrum J; Department of Obstetrics and Gynecology, University Medical Center, Albert-Ludwigs-University, Freiburg, Germany.
  • Casares de Cal MLÁ; Luxembourg Clinical Proteomics Center (LCP), Luxembourg Institute of Health (LIH), Strassen, Luxembourg.
  • Gómez-Tato A; Faculty of Mathematics, University of Santiago de Compostela (USC), Santiago de Compostela, Spain.
  • Reventos J; Faculty of Mathematics, University of Santiago de Compostela (USC), Santiago de Compostela, Spain.
  • Domon B; Biomedical Research Group in Gynecology, Vall Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, CIBERONC, Barcelona, Spain.
  • Colas E; Basic Sciences Department, International University of Catalonia, CIBERONC, Barcelona, Spain.
  • Gil-Moreno A; Luxembourg Clinical Proteomics Center (LCP), Luxembourg Institute of Health (LIH), Strassen, Luxembourg.
Clin Cancer Res ; 23(21): 6458-6467, 2017 Nov 01.
Article en En | MEDLINE | ID: mdl-28790116
ABSTRACT

Purpose:

Endometrial cancer (EC) diagnosis relies on the observation of tumor cells in endometrial biopsies obtained by aspiration (i.e., uterine aspirates), but it is associated with 22% undiagnosed patients and up to 50% of incorrectly assigned EC histotype and grade. We aimed to identify biomarker signatures in the fluid fraction of these biopsies to overcome these limitations.Experimental

Design:

The levels of 52 proteins were measured in the fluid fraction of uterine aspirates from 116 patients by LC-PRM, the latest generation of targeted mass-spectrometry acquisition. A logistic regression model was used to assess the power of protein panels to differentiate between EC and non-EC patients and between EC histologic subtypes. The robustness of the panels was assessed by the "leave-one-out" cross-validation procedure performed within the same cohort of patients and an independent cohort of 38 patients.

Results:

The levels of 28 proteins were significantly higher in patients with EC (n = 69) compared with controls (n = 47). The combination of MMP9 and KPYM exhibited 94% sensitivity and 87% specificity for detecting EC cases. This panel perfectly complemented the standard diagnosis, achieving 100% of correct diagnosis in this dataset. Nine proteins were significantly increased in endometrioid EC (n = 49) compared with serous EC (n = 20). The combination of CTNB1, XPO2, and CAPG achieved 95% sensitivity and 96% specificity for the discrimination of these subtypes.

Conclusions:

We developed two uterine aspirate-based signatures to diagnose EC and classify tumors in the most prevalent histologic subtypes. This will improve diagnosis and assist in the prediction of the optimal surgical treatment. Clin Cancer Res; 23(21); 6458-67. ©2017 AACR.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Proteínas Nucleares / Biomarcadores de Tumor / Neoplasias Endometriales / Carioferinas / Alfa Catenina / Biopsia Líquida / Proteínas de Microfilamentos Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Aged80 / Female / Humans / Middle aged Idioma: En Revista: Clin Cancer Res Asunto de la revista: NEOPLASIAS Año: 2017 Tipo del documento: Article País de afiliación: España

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Proteínas Nucleares / Biomarcadores de Tumor / Neoplasias Endometriales / Carioferinas / Alfa Catenina / Biopsia Líquida / Proteínas de Microfilamentos Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Aged80 / Female / Humans / Middle aged Idioma: En Revista: Clin Cancer Res Asunto de la revista: NEOPLASIAS Año: 2017 Tipo del documento: Article País de afiliación: España