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EP555 Biomarkers for diagnosis and prognosis of endometrial carcinoma: BioEndoCar
  1. T Knific1,
  2. Š Smrkolj2,
  3. A Romano3,
  4. A Semczuk4,
  5. A Kaminska4,
  6. A Adamiak-Godlewska4,
  7. J Vilo5,6,
  8. D Fishman5,6,
  9. C Schröder7,
  10. J Adamski8,9,10 and
  11. T Lanišnik Rižner1
  1. 1Laboratory for Molecular Basis of Hormone-Dependent Diseases and Biomarkers, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana
  2. 2Department of Obstetrics and Gynecology, University Medical Centre Ljubljana, Ljubljana, Slovenia
  3. 3Department of Gynecology, Maastricht University Medical Centre (MUMC), Maastricht, The Netherlands
  4. 4Department of Gynecology, Lublin Medical University, Lublin, Poland
  5. 5Institute of Computer Science, University of Tartu
  6. 6Quretec Ltd., Tartu, Estonia
  7. 7Sciomics GmbH, Heidelberg
  8. 8Research Unit Molecular Endocrinology and Metabolism, Genome Analysis Centre, Helmholtz Zentrum München
  9. 9Lehrstuhl fuür Experimentelle Genetik, Technische Universität Muünchen
  10. 10German Center for Diabetes Research (DZD), München, Germany

Abstract

Introduction/Background Endometrial carcinoma (EC) is the most frequent gynecological malignancy in the developed world. Currently there are no valid non-invasive diagnostic or prognostic methods available and therefore, diagnosis and treatment of EC patients is guided by histopathological and surgical findings. The lack of non-invasive diagnostic and prognostic biomarkers of EC is addressed in the current clinical study titled ‘Biomarkers for Diagnosis and Prognosis of Endometrial Carcinoma’ (BioEndoCar).

Methodology Prospective observational case - control study. Patient recruitment takes place at three medical centers (University Medical Centre Ljubljana, Slovenia; Maastricht University, The Netherlands; Lublin Medical University, Poland). Plasma samples from women with diagnosed EC and controls will be examined using non-targeted and targeted metabolomics (Helmholtz Zentrum München, Germany) and semi-targeted proteomics approaches (Sciomics GmbH, Heidelberg, Germany). Combined blood metabolome (>850 metabolites), proteome (900 different proteins), clinical and epidemiological data will be analyzed (University of Tartu, Estonia) in order to construct diagnostic/prognostic algorithms for early diagnosis of EC and to identify patients with low/high risk for cancer progression and recurrence.

Results BioEndoCar project has defined inclusion/exclusion criteria and a strict standard operating procedure for sample collection, processing and sample storage that is followed by in all three medical centers. Since the beginning of the project (April 1st 2018) we recruited nearly 100 patients in total. Great effort was put into informing the lay and expert public about the importance of the translational studies in EC. We have established an official website (https://bioendocar.eu/) and Facebook page where we post all news concerning the project.

Conclusion We expect to find different metabolic and protein profiles in patients with early stages of EC as compared to controls and in patients with poor prognosis with high risk of disease progression and recurrence as compared to those with favorable prognosis. The BioEndoCar project is currently ongoing.

Disclosure Nothing to disclose.

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