{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["9(12)"],"submitter":["Li T"],"pubmed_abstract":["Endometrial cancer (EC) is a frequently diagnosed gynecologic cancer. Identifying reliable prognostic genes for predicting EC onset is crucial for reducing patient morbidity and mortality. Here, a comprehensive strategy with transcriptomic and proteomic data was performed to measure EC's characteristics. Based on the publicly available RNA-seq data, death-associated protein kinase 3, recombination signal-binding protein for the immunoglobulin kappa J region, and myosin light chain 9 were screened out as potential biomarkers that affect the EC patients' prognosis. A linear model was further constructed by multivariate Cox regression for the prediction of the risk of being malignant. From further integrative analysis, exosomes were found to have a highly enriched role that might participate in EC occurrence. The findings were validated by qRT-polymerase chain reaction (PCR) and western blotting. Collectively, we constructed a prognostic-gene-based model for EC prediction and found that exosomes participate in EC incidents, revealing significantly promising support for the diagnosis of EC."],"journal":["ACS omega"],"pagination":["14489-14499"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10975631"],"repository":["biostudies-literature"],"pubmed_title":["Integrative Analysis of Multi-Omic Data for the Characteristics of Endometrial Cancer."],"pmcid":["PMC10975631"],"pubmed_authors":["Ruan Z","Lu L","Shi L","Yin F","Zhang T","Li T","Wang R","Song C","An Y","Zuo M","Ye X"],"additional_accession":[]},"is_claimable":false,"name":"Integrative Analysis of Multi-Omic Data for the Characteristics of Endometrial Cancer.","description":"Endometrial cancer (EC) is a frequently diagnosed gynecologic cancer. Identifying reliable prognostic genes for predicting EC onset is crucial for reducing patient morbidity and mortality. Here, a comprehensive strategy with transcriptomic and proteomic data was performed to measure EC's characteristics. Based on the publicly available RNA-seq data, death-associated protein kinase 3, recombination signal-binding protein for the immunoglobulin kappa J region, and myosin light chain 9 were screened out as potential biomarkers that affect the EC patients' prognosis. A linear model was further constructed by multivariate Cox regression for the prediction of the risk of being malignant. From further integrative analysis, exosomes were found to have a highly enriched role that might participate in EC occurrence. The findings were validated by qRT-polymerase chain reaction (PCR) and western blotting. Collectively, we constructed a prognostic-gene-based model for EC prediction and found that exosomes participate in EC incidents, revealing significantly promising support for the diagnosis of EC.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Mar","modification":"2025-04-22T08:18:06.796Z","creation":"2025-04-05T22:32:48.15Z"},"accession":"S-EPMC10975631","cross_references":{"pubmed":["38559975"],"doi":["10.1021/acsomega.4c00375"]}}