{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Sun G"],"funding":["Zhengzhou Major Project for Collaborative Innovation","the Major Project of Science and Technology in Henan Province","the Program of Natural Science Foundation of Henan Province","the National Science and Technology Major Project of China","the Key Project of Tackling Key Problems in Science and Technology of Henan Province"],"pagination":["1814515"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7781740"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["9(1)"],"pubmed_abstract":["The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAbs) and explore the optimal diagnosis model based on the protein chip for detecting esophageal squamous cell carcinoma (ESCC). The human protein chip based on cancer-driving genes was customized to discover candidate TAAbs. Enzyme-linked immunosorbent assay was applied to verify and validate the expression levels of candidate TAAbs in the training cohort (130 ESCC and 130 normal controls) and the validation cohort (125 ESCC and 125 normal controls). Logistic regression analysis was adopted to construct the diagnostic model based on the expression levels of autoantibodies with diagnostic value. Twelve candidate autoantibodies were identified based on the protein chip according to the corresp"],"journal":["Oncoimmunology"],"pubmed_title":["Identification of novel autoantibodies based on the protein chip encoded by cancer-driving genes in detection of esophageal squamous cell carcinoma."],"pmcid":["PMC7781740"],"funding_grant_id":["18XTZX12007","182300410009","192102310042","161100311400","2018ZX10302205"],"pubmed_authors":["Dai L","Wang P","Zhang J","Ren P","Cheng L","Sun G","Wang X","Shi J","Ye H"],"additional_accession":[]},"is_claimable":false,"name":"Identification of novel autoantibodies based on the protein chip encoded by cancer-driving genes in detection of esophageal squamous cell carcinoma.","description":"The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAbs) and explore the optimal diagnosis model based on the protein chip for detecting esophageal squamous cell carcinoma (ESCC). The human protein chip based on cancer-driving genes was customized to discover candidate TAAbs. Enzyme-linked immunosorbent assay was applied to verify and validate the expression levels of candidate TAAbs in the training cohort (130 ESCC and 130 normal controls) and the validation cohort (125 ESCC and 125 normal controls). Logistic regression analysis was adopted to construct the diagnostic model based on the expression levels of autoantibodies with diagnostic value. Twelve candidate autoantibodies were identified based on the protein chip according to the corresp","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020 Sep","modification":"2025-04-19T08:15:44.768Z","creation":"2021-02-20T22:55:16Z"},"accession":"S-EPMC7781740","cross_references":{"pubmed":["33457096"],"doi":["10.1080/2162402X.2020.1814515"]}}