Serum Proteomic Profiles of Patients with High and Low Risk of Endometrial Cancer Recurrence

Author:

Pietkiewicz Dagmara1ORCID,Zaborowski Mikołaj Piotr23,Jaz Kamila2ORCID,Matuszewska Eliza1ORCID,Światły-Błaszkiewicz Agata4,Kluz Tomasz5,Kokot Zenon J.6,Nowak-Markwitz Ewa2,Matysiak Jan1ORCID

Affiliation:

1. Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 3 Rokietnicka Street, 60-806 Poznan, Poland

2. Gynecologic Oncology Department, Poznan University of Medical Sciences, 33 Polna Street, 60-535 Poznan, Poland

3. Institute of Bioorganic Chemistry, Polish Academy of Sciences, Zygmunta Noskowskiego 12/14, 61-704 Poznan, Poland

4. Department of Inorganic and Analytical Chemistry, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, Jurasza 2, 85-089 Bydgoszcz, Poland

5. Department of Gynaecology, Gynaecologic Oncology and Obstetrics, Institute of Medical Sciences, Medical College of Rzeszow University, Rejtana 16c Street, 35-959 Rzeszow, Poland

6. Faculty of Health Sciences, Calisia University, 13 Kaszubska Street, 62-800 Kalisz, Poland

Abstract

Endometrial cancer is the most common gynecological cancer worldwide. Classifying endometrial cancer into low- or high-risk groups based on the following features is recommended: tumor grade, lymphovascular space invasion, myometrial involvement, and non-endometrioid histology. Despite the recent progress in molecular profiling of endometrial cancer, a substantial group of patients are misclassified based on the current criteria. This study aimed to identify proteins that could be used as biomarkers for the stratification of endometrial cancer patients into low- or high-risk groups. The proteomic analysis of serum samples from endometrial cancer patients was performed using matrix-assisted laser desorption/ionization–time of flight mass spectrometry (MALDI-TOF MS). The data were then analyzed using chemometric algorithms to identify potential biomarkers. Nineteen precursor ions were identified as fragments of eighteen proteins which included (1) connective tissue matrix proteins, (2) cytoskeletal proteins, and (3) innate immune system molecules and stress proteins. These biomarkers could be used to stratify the high- and low-risk patients, thus enabling more precise treatment decisions.

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

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