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In this study, we found that the anti\u2010leukemic effect of mTOR inhibition was mediated in part through the TP53 pathway. mTOR inhibition by rapamycin and TP53 activation by DS\u20105272 collaboratively induced the downregulation of MYC and MCL1 partly through miR\u201034a, thereby inducing cell cycle arrest and apoptosis in AML cells. Joint non\u2010negative matrix factorization (JNMF) and statistical regression analysis using public AML databases revealed that monocytic AMLs with distinctive gene expression profiles were highly sensitive to mTOR inhibition, leading to the generation of an 11\u2010gene score (Rapa\u201011) to predict the rapamycin sensitivity of each monocytic AML. Consistent with our\n                    <jats:italic>in silico<\/jats:italic>\n                    prediction, mouse AML cells expressing MLL\u2010AF9, the monocytic AML with a low Rapa\u201011 score, were highly sensitive to rapamycin, whereas those expressing RUNX1\u2010ETO or SETBP1\/ASXL1 mutations were not. Co\u2010treatment with rapamycin and DS\u20105272 had a dramatic in\u00a0vivo effect on MLL\u2010AF9\u2010driven AML, curing 85% of the leukemic mice. Thus, machine learning\u2010based predictive approaches identified monocytic AML with wild\u2010type TP53 and low Rapa\u201011 score as a rapamycin\u2010sensitive AML subtype and an ideal target for mTOR\/p53 co\u2010targeting therapy.\n                  <\/jats:p>","DOI":"10.1111\/cas.70170","type":"journal-article","created":{"date-parts":[[2025,8,11]],"date-time":"2025-08-11T10:25:00Z","timestamp":1754907900000},"page":"3040-3051","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Machine Learning\u2010Based Predictive Modeling Maximizes the Efficacy of\n                    <scp>mTOR<\/scp>\n                    \/p53 Co\u2010Targeting Therapy Against\n                    <scp>AML<\/scp>"],"prefix":"10.1111","volume":"116","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3078-5770","authenticated-orcid":false,"given":"Jingmei","family":"Li","sequence":"first","affiliation":[{"name":"Department of Computational 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