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«Salivaomics» of Different Molecular Biological Subtypes of Breast Cancer

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Publisher MDPI
Specialty Molecular Biology
Date 2022 Jul 25
PMID 35877435
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Abstract

The aim of the study was to determine the metabolic characteristics of saliva depending on the molecular biological subtype of breast cancer, as well as depending on the expression levels of HER2, estrogen receptors (ER), and progesterone receptors (PR). The study included 487 patients with morphologically verified breast cancer and 298 volunteers without breast pathologies. Saliva samples were obtained from all patients strictly before the start of treatment and the values of 42 biochemical indicators were determined. It has been established that the saliva of healthy volunteers and patients with various molecular biological subtypes of breast cancer differs in 12 biochemical indicators: concentrations of protein, urea, nitric oxide, malondialdehyde, total amino acid content, and activity of lactate dehydrogenase, alkaline phosphatase, gamma-glutamyltransferase, catalase, amylase, superoxide dismutase, and peroxidases. The saliva composition of patients with basal-like breast cancer differs from other subtypes in terms of the maximum number of indicators. Changes in biochemical indicators indicated an increase in the processes of lipid peroxidation and endogenous intoxication and a weakening of antioxidant protection, which correlates with the severity of the disease and the least favorable prognosis for this subtype of breast cancer. An analysis was made of the individual contribution of the expression level of HER2, estrogen, and progesterone receptors to changes in the biochemical composition of saliva. The HER2 (-)/HER2 (+) group, which should be considered as a single group, as well as ER-positive breast cancer, differ statistically significantly from the control group. For ER/PR-positive breast cancer, a more favorable ratio of saliva biochemical indicators was also noted compared to ER/PR-negative breast cancer.

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References
1.
Belskaya L, Kosenok V, Sarf E . Chronophysiological features of the normal mineral composition of human saliva. Arch Oral Biol. 2017; 82:286-292. DOI: 10.1016/j.archoralbio.2017.06.024. View

2.
Cheng F, Wang Z, Huang Y, Duan Y, Wang X . Investigation of salivary free amino acid profile for early diagnosis of breast cancer with ultra performance liquid chromatography-mass spectrometry. Clin Chim Acta. 2015; 447:23-31. DOI: 10.1016/j.cca.2015.05.008. View

3.
Murata T, Yanagisawa T, Kurihara T, Kaneko M, Ota S, Enomoto A . Salivary metabolomics with alternative decision tree-based machine learning methods for breast cancer discrimination. Breast Cancer Res Treat. 2019; 177(3):591-601. DOI: 10.1007/s10549-019-05330-9. View

4.
Rapado-Gonzalez O, Martinez-Reglero C, Salgado-Barreira A, Takkouche B, Lopez-Lopez R, Suarez-Cunqueiro M . Salivary biomarkers for cancer diagnosis: a meta-analysis. Ann Med. 2020; 52(3-4):131-144. PMC: 7877992. DOI: 10.1080/07853890.2020.1730431. View

5.
Oakman C, Tenori L, Biganzoli L, Santarpia L, Cappadona S, Luchinat C . Uncovering the metabolomic fingerprint of breast cancer. Int J Biochem Cell Biol. 2010; 43(7):1010-20. DOI: 10.1016/j.biocel.2010.05.001. View