Literature DB >> 28790116

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.

Elena Martinez-Garcia1, Antoine Lesur2, Laura Devis1, Silvia Cabrera3, Xavier Matias-Guiu4, Marc Hirschfeld5,6, Jasmin Asberger5, Jan van Oostrum2, María de Los Ángeles Casares de Cal7, Antonio Gómez-Tato7, Jaume Reventos1,8, Bruno Domon2, Eva Colas9, Antonio Gil-Moreno9,3.   

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. ©2017 American Association for Cancer Research.

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Year:  2017        PMID: 28790116     DOI: 10.1158/1078-0432.CCR-17-0474

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


  7 in total

1.  Multiplex targeted mass spectrometry assay for one-shot flavivirus diagnosis.

Authors:  Sheena Wee; Asfa Alli-Shaik; Relus Kek; Hannah L F Swa; Wei-Ping Tien; Vanessa W Lim; Yee-Sin Leo; Lee-Ching Ng; Hapuarachchige C Hapuarachchi; Jayantha Gunaratne
Journal:  Proc Natl Acad Sci U S A       Date:  2019-03-18       Impact factor: 11.205

Review 2.  Clinical potential of mass spectrometry-based proteogenomics.

Authors:  Bing Zhang; Jeffrey R Whiteaker; Andrew N Hoofnagle; Geoffrey S Baird; Karin D Rodland; Amanda G Paulovich
Journal:  Nat Rev Clin Oncol       Date:  2019-04       Impact factor: 66.675

3.  Tailored Use of Targeted Proteomics in Plant-Specific Applications.

Authors:  Anja Rödiger; Sacha Baginsky
Journal:  Front Plant Sci       Date:  2018-08-17       Impact factor: 5.753

4.  EV-associated miRNAs from peritoneal lavage as potential diagnostic biomarkers in colorectal cancer.

Authors:  Berta Roman-Canal; Jordi Tarragona; Cristian Pablo Moiola; Sònia Gatius; Sarah Bonnin; Maria Ruiz-Miró; José Enrique Sierra; Maria Rufas; Esperanza González; José M Porcel; Antonio Gil-Moreno; Juan M Falcón-Pérez; Julia Ponomarenko; Xavier Matias-Guiu; Eva Colas
Journal:  J Transl Med       Date:  2019-06-20       Impact factor: 5.531

Review 5.  Exosomes on Endometrial Cancer: A Biomarkers Treasure Trove?

Authors:  Alexandros G Sykaras; Konstantinos Christofidis; Ekaterini Politi; Stamatios Theocharis
Journal:  Cancers (Basel)       Date:  2022-03-29       Impact factor: 6.639

Review 6.  Liquid Biopsy in Endometrial Cancer: New Opportunities for Personalized Oncology.

Authors:  Laura Muinelo-Romay; Carlos Casas-Arozamena; Miguel Abal
Journal:  Int J Mol Sci       Date:  2018-08-07       Impact factor: 5.923

Review 7.  Proteomic Biomarkers for the Detection of Endometrial Cancer.

Authors:  Kelechi Njoku; Davide Chiasserini; Anthony D Whetton; Emma J Crosbie
Journal:  Cancers (Basel)       Date:  2019-10-16       Impact factor: 6.639

  7 in total

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