<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Monasta L</submitter><funding>Italian Ministry of Health</funding><pagination>11498</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12691889</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>26(23)</volume><pubmed_abstract>Endometrial cancers (ECs) are mainly adenocarcinomas arising from the uterine endometrium. In this work, we employed data-independent acquisition (DIA) mass spectrometry (MS)-based label-free quantification (LFQ-MS) proteomics to analyze the proteome of tissue washings collected from 25 control (CTRL) subjects, 25 patients with low-grade type 1 endometrial cancer (EC), and 24 patients with high-grade type 1 EC. Following quantification and statistical analysis, we identified 42 proteins able to discriminate CTRL from EC patients, and 151 proteins differentiating high-grade EC cases from low-grade EC cases. Notably, &lt;i>PRRC2A&lt;/i> and &lt;i>SYDE2&lt;/i> effectively distinguished both EC patients from controls and advanced EC cases from low-grade EC cases. Validation by Western blot analysis in an </pubmed_abstract><journal>International journal of molecular sciences</journal><pubmed_title>Data-Independent Acquisition (DIA)-Based Proteomics for the Identification of Biomarkers in Tissue Washings of Endometrial Cancer.</pubmed_title><pmcid>PMC12691889</pmcid><funding_grant_id>5x1000 SD 18\19</funding_grant_id><pubmed_authors>Monasta L</pubmed_authors><pubmed_authors>Kharrat F</pubmed_authors><pubmed_authors>Capaci V</pubmed_authors><pubmed_authors>Aloisio M</pubmed_authors><pubmed_authors>Balasan N</pubmed_authors><pubmed_authors>Ura B</pubmed_authors><pubmed_authors>Romano F</pubmed_authors><pubmed_authors>Golino V</pubmed_authors><pubmed_authors>Ciampechini M</pubmed_authors><pubmed_authors>Ricci G</pubmed_authors><pubmed_authors>Conti A</pubmed_authors><pubmed_authors>Licastro D</pubmed_authors><pubmed_authors>Di Lorenzo G</pubmed_authors><pubmed_authors>Campiglia P</pubmed_authors></additional><is_claimable>false</is_claimable><name>Data-Independent Acquisition (DIA)-Based Proteomics for the Identification of Biomarkers in Tissue Washings of Endometrial Cancer.</name><description>Endometrial cancers (ECs) are mainly adenocarcinomas arising from the uterine endometrium. In this work, we employed data-independent acquisition (DIA) mass spectrometry (MS)-based label-free quantification (LFQ-MS) proteomics to analyze the proteome of tissue washings collected from 25 control (CTRL) subjects, 25 patients with low-grade type 1 endometrial cancer (EC), and 24 patients with high-grade type 1 EC. Following quantification and statistical analysis, we identified 42 proteins able to discriminate CTRL from EC patients, and 151 proteins differentiating high-grade EC cases from low-grade EC cases. Notably, &lt;i>PRRC2A&lt;/i> and &lt;i>SYDE2&lt;/i> effectively distinguished both EC patients from controls and advanced EC cases from low-grade EC cases. Validation by Western blot analysis in an </description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Nov</publication><modification>2026-05-26T14:03:39.574Z</modification><creation>2026-05-24T03:11:45.521Z</creation></dates><accession>S-EPMC12691889</accession><cross_references><pubmed>41373651</pubmed><doi>10.3390/ijms262311498</doi></cross_references></HashMap>