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1. Integrated drug resistance and leukemic stemness gene-expression scores predict outcomes in large cohort of over 3500 AML patients from 10 trials

Author

Abdelrahman H. Elsayed, Xueyuan Cao, Richard J. Marrero, Nam H. K. Nguyen, Huiyun Wu, Yonhui Ni, Raul C. Ribeiro, Herold Tobias, Peter J. Valk, François Béliveau, Guillaume Richard-Carpentier, Josée Hébert, C. Michel Zwaan, Alan Gamis, Edward Anders Kolb, Richard Aplenc, Todd A. Alonzo, Soheil Meshinchi, Jeffrey Rubnitz, Stanley Pounds, and Jatinder K. Lamba

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

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

Published
2024
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