Data from: Cell signaling-based classifier predicts response to induction therapy in elderly patients with acute myeloid leukemia

Alessandra Cesano, Cheryl L. Willman, Kenneth J. Kopecky, Urte Gayko, Santosh Putta, Brent Louie, Matt Westfall, Norman Purvis, David C. Spellmeyer, Carol Marimpietri, Aileen C. Cohen, James Hackett, Jing Shi, Michael G. Walker, Zhuoxin Sun, Elisabeth Paietta, Martin S. Tallman, Larry D. Cripe, Susan Atwater, Frederick R. Appelbaum & Jerald P. Radich
Single-cell network profiling (SCNP) data generated from multi-parametric flow cytometry analysis of bone marrow (BM) and peripheral blood (PB) samples collected from patients >55 years old with non-M3 AML were used to train and validate a diagnostic classifier (DXSCNP) for predicting response to standard induction chemotherapy (complete response [CR] or CR with incomplete hematologic recovery [CRi] versus resistant disease [RD]). SCNP-evaluable patients from four SWOG AML trials were randomized between Training (N = 74 patients...

Registration Year

  • 2015
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Resource Types

  • Dataset
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Affiliations

  • Fred Hutchinson Cancer Research Center
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  • The Bronx Defenders
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  • Stanford University
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  • Indiana University
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  • Memorial Sloan Kettering Cancer Center
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  • Cancer Research Center
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  • Nodality (United States)
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  • University of New Mexico
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