Optimized Bioinformatic Strategy for the Analysis of Clinical Proteomic Data of the Endometrium in Chronic Endometritis

The aim of the study is to analyze the entire set of proteins (proteome) expressed in the endometrial tissue and to identify protein markers specific for carcinogenesis.

Materials and Methods. Tissue samples were obtained using endometrial pipelle biopsy in women with chronic endometritis. After homogenization the samples were subjected to protein electrophoresis in polyacrylamide gel in the presence of sodium dodecyl sulfate according to the Lamley method. The proteins separated according to their molecular weights were digested by modified trypsin using the standard method. Obtained tryptic peptides were analyzed and identified by high-performance liquid chromatography coupled with tandem mass spectrometry.

The Human Protein Atlas and Tissue-Specific Gene Expression and Regulation databases were used to analyze the tissue-specific protein expression.

Functional protein annotation and gene set enrichment analysis were performed using the Database for Annotation, Visualization and Integrated Discovery bioinformatics resource.

Results. In the obtained endometrial tissue samples, 103 proteins were identified by tandem mass spectrometry. Analysis of tissue specificity showed that 83 proteins were expressed in the tissues of the female reproductive system. Functional annotation followed by clustering revealed that 51 proteins (49.5% of the identified ones) were encoded by the genes differentially expressed in cell cultures of the female reproductive organs. Along with that, 4 groups of proteins were expressed both in tumors (serous ovarian adenocarcinoma, immortalized ovarian cystadenoma, ovarian carcinoma) and in the immortalized normal ovarian surface epithelium.

Conclusion. Endometrial tissue proteins were identified using a clinical proteomic analysis. The bioinformatic approach allowed us to annotate the functional clusters of the identified proteins based on their potential involvement in carcinogenesis. The obtained data can serve as the starting point for further in-depth studies of the endometrium using the proteomic approach, as well as other OMICS technologies. Subsequent application of bioinformatic tools will allow revealing of molecular mechanisms of relationship between inflammation and endometrium tissue malignant transformation.

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Gainullin M.R., Yazykova A.B., Motovilova T.M., Klemente Apumaita H.M., Khodosova T.G., Gagaeva Y.A., Kolomina E.S., Kovaleva M.M., Militskaya A.A., Shcherina A.N., Boyko E.L., Zgoda V.G., Grechkanev G.O. Optimized Bioinformatic Strategy for the Analysis of Clinical Proteomic Data of the Endometrium in Chronic Endometritis. Sovremennye tehnologii v medicine 2019; 11(2): 50, https://doi.org/10.17691/stm2019.11.2.07