{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T08:31:57Z","timestamp":1786350717100,"version":"build-2736575974"},"reference-count":8,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Cancer Inform"],"published-print":{"date-parts":[[2026,8]]},"abstract":"\n Objectives<\/jats:title>\n Acute myeloid leukemia (AML) exhibits substantial biological heterogeneity that is not fully captured by current prognostic systems. We aimed to identify transcriptome-wide gene expression markers associated with overall survival in newly diagnosed AML patients.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Gene expression and clinical data from 399 newly diagnosed AML patients in the OHSU cohort were obtained via cBioPortal. Cox proportional hazards regression was performed independently for 22,836 genes to evaluate associations with overall survival. Analyses were restricted to genes with sufficient observations, and Bonferroni correction was applied to account for multiple testing.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n A total of 46 genes were significantly associated with overall survival after multiple testing correction. Higher expression of\n FAM213A<\/jats:italic>\n (hazard ratio [HR] 1.240) and\n TJP2<\/jats:italic>\n (HR 1.439) was associated with increased mortality risk, whereas higher expression of\n PJA2<\/jats:italic>\n (HR 0.381),\n MICALL2<\/jats:italic>\n (HR 0.779), and\n LTK<\/jats:italic>\n (HR 0.828) was associated with improved survival. Several identified genes, including\n FAM213A, MICALL2<\/jats:italic>\n , and\n PJA2<\/jats:italic>\n , have known roles in cancer biology, supporting the biological plausibility of these findings.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n This transcriptome-wide analysis identified multiple genes associated with survival in newly diagnosed AML, highlighting candidate prognostic biomarkers that may complement existing risk stratification frameworks. Further validation in independent cohorts is warranted.<\/jats:p>\n <\/jats:sec>","DOI":"10.1177\/11769351261478087","type":"journal-article","created":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T11:24:24Z","timestamp":1786188264000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Transcriptome-Wide Cox Regression Identifies Candidate Survival-Associated Genes in Newly Diagnosed Acute Myeloid Leukemia"],"prefix":"10.1177","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-9910-6563","authenticated-orcid":false,"given":"Songphol","family":"Tungjitviboonkun","sequence":"first","affiliation":[{"name":"University of California San Francisco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5786-1035","authenticated-orcid":false,"given":"Nikhil","family":"Mullapudi","sequence":"additional","affiliation":[{"name":"University of California San Francisco"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0838-3982","authenticated-orcid":false,"given":"Elly","family":"Gardev","sequence":"additional","affiliation":[{"name":"University of California San Francisco"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,8,8]]},"reference":[{"key":"e_1_3_6_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/hon.2728"},{"key":"e_1_3_6_3_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12964-022-00984-3"},{"key":"e_1_3_6_4_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijms25010518"},{"key":"e_1_3_6_5_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12885-022-09614-0"},{"key":"e_1_3_6_6_2","doi-asserted-by":"publisher","DOI":"10.1002\/advs.202401964"},{"key":"e_1_3_6_7_2","doi-asserted-by":"publisher","DOI":"10.18632\/aging.202356"},{"key":"e_1_3_6_8_2","doi-asserted-by":"publisher","DOI":"10.1007\/s44313-026-00123-8"},{"key":"e_1_3_6_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00277-024-05963-x"}],"container-title":["Cancer Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/11769351261478087","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/11769351261478087","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/11769351261478087","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T08:16:16Z","timestamp":1786349776000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/11769351261478087"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":8,"alternative-id":["10.1177\/11769351261478087"],"URL":"https:\/\/doi.org\/10.1177\/11769351261478087","relation":{},"ISSN":["1176-9351","1176-9351"],"issn-type":[{"value":"1176-9351","type":"print"},{"value":"1176-9351","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8]]},"article-number":"11769351261478087"}}