Proteomic Profiling Identifies Candidate Diagnostic Biomarkers of Hydrosalpinx in Endometrial Fluid

Description

This proteomic profiling study applied sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) to study hydrosalpinx cyst fluid and pre- and post-salpingectomy endometrial fluid. In this exploratory pilot study, HCF and EF samples were collected from 10 women with hydrosalpinx, diagnosed according to standard clinical protocol, at the time of sal-pingectomy. In addition, endometrial fluid samples were collected from seven of these women one month after surgery. Samples were not obtained from three participants be-cause they failed to attend the post-surgical examination visit. The hydrosalpinx cyst fluid was obtained directly from the removed surgical speci-men by puncturing the dilated area of the fallopian tube by aspiration of the contents with a syringe (approx. 200 μL) once out of the patient. To maximize the number of identified proteins, all HCF and pre- and post-salpingectomy EF samples were pooled (2 μg of each) to build a spectral library con-taining a total of 50 μg of protein extracts for proteomic characterization. Pooled protein extracts were loaded onto a one-dimensional SDS-polyacrylamide gel and separated by electrophoresis to determine the protein profiles of each condition. The gel was digested to construct the library for label-free quantification analysis of the study samples using SWATH-MS. Once the spectral library of the proteins present in the different types of fluids was generated, the individualized identification of the quantitative profile of each type of fluid was carried out. RAW data about protein areas, Spectral library, Spectral library search results and Spectral library protein identification are contained in this dataset.

Steps to reproduce

Approximately 300 μL of endometrial fluid was aspirated from the endometrial cavity via a cannula inserted through the cervix immediately prior to salpingectomy (pre-salpingectomy EF; n = 10) and at a follow-up examination one month after the inter-vention (post-salpingectomy; n = 7 because three patients did not return for their fol-low-up). Samples were stored at −80 °C until they were sent to the proteomics service. Once in the proteomics facility of the SCSIE at the University of Valencia, the HCF and EF samples were dried in a speed vacuum, resuspended in 100 μL of Laemmli sample buffer (BioRad, Madrid, Spain), and vortexed for 5 min. Samples were then sonicated for 5 min to lyse cells, heated at 95 °C for 5 min to denature proteins, and vortexed again for 5 min prior to centrifugation at 15,000 rpm and 10 °C for 20 min. The resulting supernatant of each sample was transferred to a sterile Eppendorf tube, and proteins were quantified using a quantification assay by Macherey-Nagel (Cultek, Madrid, Spain). To maximize the number of identified proteins, all HCF and pre- and post-salpingectomy EF samples were pooled (2 μg of each) to build a spectral library con-taining a total of 50 μg of protein extracts for proteomic characterization. Pooled protein extracts were loaded onto a one-dimensional SDS-polyacrylamide gel and separated by electrophoresis to determine the protein profiles of each condition. The gel was digested to construct the library for label-free quantification analysis of the study samples using SWATH-MS. Once the spectral library of the proteins present in the different types of fluids was generated, the individualized identification of the quantitative profile of each type of fluid was carried out. SWATH-MS data were analyzed using PeakView® software (v2.2, AB SCIEX, Madrid, SpainSCIEX). Only peptides annotated with at least 95% confidence and an FDR-adjusted p-value ≤ 0.01 were selected for analysis. The maximum number of analyzed peptides is set to 20 for each protein. For every peptide meeting these conditions, the chromatographic area of 6 transitions (or MS/MS fragments) was integrated. The chromatographic area of the transitions was then converted into a value for the corresponding peptide, and with the peptide areas, the total protein area was estimated. Retention times of the detected pep-tides were alienated using major proteins identified. Protein expression trends were visualized and analyzed with MarkerView (SCIEX, Framingham, MA, USASCIEX). Estimated protein areas were normalized by the sum of all quantified proteins areas. Principal component analysis and discriminant analysis, both with Pareto scaling, were applied to reduce dimensionality of proteomic profiles. Finally, differential expression of protein abundance was evaluated using t-tests followed by pair-wise comparisons. In all cases, FDR-adjusted p-values < 0.05 were considered statis-tically significant.

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