{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["H Elsayed A"],"funding":["U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)","American Cancer Society","American Cancer Society (American Cancer Society, Inc.)","U.S. Department of Health &amp; Human Services | NIH | National Cancer Institute","NHGRI NIH HHS","NCI NIH HHS"],"pagination":["168"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11294346"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["8(1)"],"pubmed_abstract":["In this study, we leveraged machine-learning tools by evaluating expression of genes of pharmacological relevance to standard-AML chemotherapy (ara-C/daunorubicin/etoposide) in a discovery-cohort of pediatric AML patients (N = 163; NCT00136084 ) and defined a 5-gene-drug resistance score (ADE-RS5) that was predictive of outcome (high MRD1 positivity p = 0.013; lower EFS p < 0.0001 and OS p < 0.0001). ADE-RS5 was integrated with a previously defined leukemic-stemness signature (pLSC6) to classify patients into four groups. ADE-RS5, pLSC6 and integrated-score was evaluated for association with outcome in one of the largest assembly of ~3600 AML patients from 10 independent cohorts (1861 pediatric and 1773 adult AML). Patients with high ADE-RS5 had poor outcome in validation cohorts and the p"],"journal":["NPJ precision oncology"],"pubmed_title":["Integrated drug resistance and leukemic stemness gene-expression scores predict outcomes in large cohort of over 3500 AML patients from 10 trials."],"pmcid":["PMC11294346"],"funding_grant_id":["U10 CA098543","P30 CA247796","U10 CA180886","T32 HG008958","SAP 21-061-01","R01 CA132946","R01CA132946","U10 CA180899","U10 CA098413"],"pubmed_authors":["Rubnitz J","Ribeiro RC","Hebert J","Richard-Carpentier G","Zwaan CM","Meshinchi S","Nguyen NHK","Lamba JK","Marrero RJ","Wu H","Gamis A","Pounds S","H Elsayed A","Ni Y","Valk PJ","Cao X","Tobias H","Aplenc R","Beliveau F","Alonzo TA","Kolb EA"],"additional_accession":[]},"is_claimable":false,"name":"Integrated drug resistance and leukemic stemness gene-expression scores predict outcomes in large cohort of over 3500 AML patients from 10 trials.","description":"In this study, we leveraged machine-learning tools by evaluating expression of genes of pharmacological relevance to standard-AML chemotherapy (ara-C/daunorubicin/etoposide) in a discovery-cohort of pediatric AML patients (N = 163; NCT00136084 ) and defined a 5-gene-drug resistance score (ADE-RS5) that was predictive of outcome (high MRD1 positivity p = 0.013; lower EFS p < 0.0001 and OS p < 0.0001). ADE-RS5 was integrated with a previously defined leukemic-stemness signature (pLSC6) to classify patients into four groups. ADE-RS5, pLSC6 and integrated-score was evaluated for association with outcome in one of the largest assembly of ~3600 AML patients from 10 independent cohorts (1861 pediatric and 1773 adult AML). Patients with high ADE-RS5 had poor outcome in validation cohorts and the p","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Aug","modification":"2026-07-15T08:06:09.169Z","creation":"2024-11-08T23:09:33.678Z"},"accession":"S-EPMC11294346","cross_references":{"pubmed":["39090192"],"doi":["10.1038/s41698-024-00643-5"]}}