{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T13:56:37Z","timestamp":1791467797278,"version":"4.3.4"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100003392","name":"Natural Science Foundation of Fujian Province","doi-asserted-by":"publisher","award":["2022J011444"],"award-info":[{"award-number":["2022J011444"]}],"id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Acute myeloid leukemia (AML) features high biological heterogeneity and unfavorable prognoses, demanding reliable prognostic biomarkers. Dysregulated post-translational modifications (PTMs) drive AML progression by disrupting protein function and cellular signaling. This work constructed a PTM-based risk signature to predict AML survival and dissect the tumor immune microenvironment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>RNA-seq and clinical data of TCGA-Acute Myeloid Leukemia (LAML) AML patients and normal genotype-tissue expression samples were analyzed. Limma identified differentially expressed genes (DEGs), and overlapping PTM-related DEGs were screened. Unsupervised consensus clustering stratified patients into molecular subgroups, whose overall survival (OS) was compared via Kaplan\u2013Meier curves. A prognostic score model was built through univariate Cox screening, least absolute shrinkage and selection operator dimension reduction and multivariate Cox regression, validated by time-dependent receiver operating characteristic curves. Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and single-sample gene set enrichment analysis quantified immune infiltration, while tumor mutation burden (TMB) was calculated to characterize genomic features. The GSE71014 cohort served as external validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A four-gene signature (ITGAX, DOCK1, CPNE8, and GABRE) was established and validated. High-risk patients had markedly shorter OS, with 1-, 3-, and 5-year AUC values of 0.79, 0.79, and 0.90, consistent with external cohort results. The two risk groups displayed divergent immune landscapes; high-risk patients overexpressed multiple immune checkpoints. Though TMB was similar across groups, high-risk patients with low TMB had the worst survival. Low-risk patients showed greater cytarabine susceptibility, confirming the model\u2019s clinical value.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This PTM-associated signature accurately stratifies AML patients and reveals immune microenvironment disparities. It enables precise personalized prognosis and identifies PTM-related genes as promising therapeutic targets for AML immunotherapy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/jjco\/hyag111","type":"journal-article","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T17:59:46Z","timestamp":1784829586000},"page":"1215-1233","source":"Crossref","is-referenced-by-count":0,"title":["Identification of a prognostic signature based on expression of post-translational modification-related genes in acute myeloid leukemia"],"prefix":"10.1093","volume":"56","author":[{"given":"Donghui","family":"Gan","sequence":"first","affiliation":[{"name":"The Graduate School of Fujian Medical University , Fuzhou 350122, Fujian ,","place":["China"]},{"name":"Department of Hematology, The Affiliated Hospital of Putian University , Putian 351100, Fujian 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Affiliated Hospital of Putian University , Putian 351100, Fujian ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengting","family":"Huang","sequence":"additional","affiliation":[{"name":"The Graduate School of Fujian Medical University , Fuzhou 350122, Fujian ,","place":["China"]},{"name":"Department of Hematology, The Affiliated Hospital of Putian University , Putian 351100, Fujian ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Weng","sequence":"additional","affiliation":[{"name":"The Graduate School of Fujian Medical University , Fuzhou 350122, Fujian ,","place":["China"]},{"name":"Department of Hematology, The Affiliated Hospital of Putian University , Putian 351100, Fujian 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