Glycoarrays for diagnosis and therapy of the disorders of the female reproductive system

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Abstract

The development of effective methods for prediction, diagnostics and treatment of female reproductive disorders is an urgent task. Natural antiglycan antibodies (AGAT) are of great interest in both diagnostic and therapeutic aspects, since AGATs are very diverse, and their specificities were selected in the course of natural evolution. In this work, we investigated the possibility of using glycoarray technique, as well as the signature approach to predict effectiveness of therapy in breast cancer (BC), as well as a targeted search for natural antibodies with therapeutic potential.
We studied blood serum samples of apparently healthy female donors (n = 27), and patients with established diagnosis of metastatic breast cancer prior to starting therapy (n = 29). The median age of the patients was 48 years, 41% had “ER/PR+”-status, 59% – “ER/PR-“-status. The median age of healthy subjects was 50 years. The patients received combined therapy with doxorubicin and herceptin with different outcomes: 11 patients did not respond to treatment and 18 patients showed clinical response (the tumor was not revealed). For the study with AGAT, glycoarray was used, on which more than 200 different glycans were printed. The antibodies bound to the ligands were detected using biotinylated goat antibodies against human Ig (G+M+A). To search for a combination of diagnostically significant AGATs (signatures), the previously developed calculation tool “Immunoruler” was used.
An opportunity of using glycoarray to predict efficiency of therapy was studied in breast cancer patients. The study included patients receiving combination therapy with doxirubicin and herceptin, with clinical response monitored at 18-24 weeks. A signature consisting of 10 AGATs with high sensitivity and specificity (90 and 91%, respectively) proved to predict efficiency of the administered therapy.
The possibility of breast cancer diagnosis using AGAT has been further confirmed. The specified signature included five antibodies: the level of two AGATs was significantly higher in patients than in donors, which could be adaptive antibodies developed in response to emerging malignancy. For three other antibodies, the registered signals in patients were lower than in healthy controls, thus, probably, indicating depletion of humoral immunity during the development of breast cancer. Hence, such AGATs may have some therapeutic potential, and, by usage of glycoarray screening technology, they could be searched in purposeful manner.

About the authors

N. V. Shilova

V. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology; Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences

Author for correspondence.
Email: pumatnv@gmail.com
ORCID iD: 0000-0001-6003-071X

Shilova Nadezhda V. - PhD (Chemistry), Senior Research Associate, Laboratory of Clinical Immunology; Senior Research Associate, Laboratory of Carbohydrate Chemistry

117997, Moscow, Miklukho-Maklay str., 16/10

Russian Federation

N. V. Bovin

Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences

Email: professorbovin@yandex.ru
ORCID iD: 0000-0001-8669-4477

PhD, MD (Chemistry), Professor, Head, Laboratory of Carbohydrate Chemistry

Moscow

A. Yu. Nokel

V. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology; Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences

Email: anokel@gmx.com
ORCID iD: 0000-0003-2903-2279

PhD (Chemistry), Research Associate; Research Associate

Moscow

M. M. Ziganshina

V. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology

Email: mmz@mail.ru
ORCID iD: 0000-0003-1578-8403

PhD (Biology), Leading Research Associate

Moscow

N. R. Khasbiullina

V. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology

Email: crosbreed@list.ru
ORCID iD: 0000-0001-7504-6650

PhD (Biology), Research Associate

Moscow

M. Vuskovic

San Diego State University

Email: fake@neicon.ru

Vuskovic Marko, Professor, Leading Research Associate, Department of Computer Science

San Diego

 

United States

M. E. Huflejt

Collegium Medicum, University of Warmia and Mazury

Email: fake@neicon.ru

Huflejt Margaret Elisabeth, PhD (Biology), Research Associate, Department of Public Health, Faculty of Health Sciences

Olsztyn

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Copyright (c) 2021 Shilova N.V., Bovin N.V., Nokel A.Y., Ziganshina M.M., Khasbiullina N.R., Vuskovic M., Huflejt M.E.

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