{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T23:34:12Z","timestamp":1788564852873,"version":"build-2803163510"},"reference-count":33,"publisher":"SAGE Publications","issue":"10","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Guangzhou Innovation Leadership Team","award":["CXLJTD-201602"],"award-info":[{"award-number":["CXLJTD-201602"]}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2018YFC1106300, 2017YFC1105000"],"award-info":[{"award-number":["2018YFC1106300, 2017YFC1105000"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"Joint Funds of the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["U1501245"],"award-info":[{"award-number":["U1501245"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51672088"],"award-info":[{"award-number":["51672088"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"UK-China (Guangzhou) Healthtech Open Innovation","award":["2014Q-P037"],"award-info":[{"award-number":["2014Q-P037"]}]},{"name":"Guangzhou 2024 Annual Agricultural and Social Development Science and Technology Special Topics","award":["2024B03J1332"],"award-info":[{"award-number":["2024B03J1332"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Cancer Biomarkers"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Autoantibodies against tumor-associated antigens (TAAs) are promising noninvasive cancer biomarkers due to their specificity and stability. Gastric cancer (GC) diagnosis often requires invasive procedures, emphasizing the need for reliable blood-based biomarkers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study assessed whether serum IgG and IgA autoantibodies, individually or combined, could serve as noninvasive biomarkers for gastric cancer.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Experimental design<\/jats:title>\n                    <jats:p>We analyzed 27 autoantibodies in serum from 265 healthy controls, 296 GC patients, and 195 gastritis patients using protein microarray. Autoantibody levels and the IgG\/IgA ratio were calculated. Diagnostic accuracy was evaluated using receiver operating characteristic (ROC) curves.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We identified 24 differentially expressed autoantibodies (DEAs) for IgA and 17 for IgG between GC patients and controls. In distinguishing GC from gastritis, 20 DEAs for IgA and 23 for IgG were significant. The IgG\/IgA ratio of MIP1 beta had the highest diagnostic performance between atrophic gastritis and GC, while MMP7 was the most effective between chronic gastritis and GC. The gbm model with 14 autoantibodies had the highest Youden's index for GC versus controls, and a 13-autoantibody model performed best for GC versus all gastritis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Specific panels of autoantibodies could serve as noninvasive diagnostic tools for distinguishing GC from controls and gastritis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/18758592251363414","type":"journal-article","created":{"date-parts":[[2025,10,6]],"date-time":"2025-10-06T12:57:27Z","timestamp":1759755447000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Combination detection of IgG- and IgA-related autoantibodies for the early diagnosis of gastric cancer"],"prefix":"10.1177","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0133-1381","authenticated-orcid":false,"given":"Congcong","family":"Fu","sequence":"first","affiliation":[{"name":"RayBiotech Guangzhou Co. 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