James Hackett
5 Papers
24 Citations
James Hackett is an academic researcher. The author has contributed to research in topics: Induction chemotherapy & Receiver operating characteristic. The author has an hindex of 3, co-authored 5 publications.
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Papers
Development and validation of a single‐cell network profiling assay‐based classifier to predict response to induction therapy in paediatric patients with de novo acute myeloid leukaemia: a report from the Children's Oncology Group
Norman J. Lacayo,Norman J. Lacayo,Todd A. Alonzo,Todd A. Alonzo,Urte Gayko,David B. Rosen,Matt Westfall,Norman Purvis,Santosh Putta,Brent Louie,James Hackett,Aileen Cohen,Alessandra Cesano,Robert B. Gerbing,Yaddanapudi Ravindranath,Yaddanapudi Ravindranath,Gary V. Dahl,Gary V. Dahl,Alan S. Gamis,Alan S. Gamis,Soheil Meshinchi +20 more
TL;DR: This is the first validation of an SCNP classifier to predict response to induction chemotherapy, demonstrating the usefulness of quantitative SCNP under modulated conditions to provide independent information on AML disease biology and induction response.
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Single-Cell Network Profiliing (SCNP) Signatures Independently Predict Response to Induction Therapy In Older Patients with Acute Myeloid Leukemia (AML)
Alessandra Cesano,Santosh Putta,Urte Gayko,James Hackett,David B. Rosen,Larry D. Cripe,Zhuoxin Sun,Hajime Uno,Mark R. Litzow,Martin S. Tallman,Elisabeth Paietta +10 more
TL;DR: A set of classifiers that predict for likelihood of response to anthracycline/cytarabine-based induction therapy in older patients with AML and several promising models with high area under the operator/receiver curve (AUROC) values were developed.
3
Single Cell Network Profiling (SCNP)-Based Classifier to Predict Response to Induction Therapy in Pediatric Patients with De Novo Acute Myeloid Leukemia (AML): Validation Study Results,
Norman J. Lacayo,Todd A. Alonzo,Urte Gayko,Matt Westfall,Norman Purvis,Santosh Putta,James Hackett,Aileen Cohen,Robert B. Gerbing,Gary V Dahl,Alan S. Gamis,Soheil Meshinchi +11 more
TL;DR: This study is the first validation of a SCNP-based classifier that predicts response to induction Rx, and shows that performing quantitative SCNP under modulated conditions can serve as the basis for developing biologically based tests in leukemia.
3
Single-Cell Network Profiling (SCNP)-Based Classifier to Predict Response to Induction Therapy in Elderly Patients with Acute Myeloid Leukemia (AML): Validation in Two Independent Sample Sets From ECOG and SWOG Trials.
Alessandra Cesano,Cheryl L. Willman,Kenneth J. Kopecky,Urte Gayko,Santosh Putta,Brent Louie,Matt Westfall,Norman Purvis,David C. Spellmeyer,Carol Marimpietri,James Hackett,Jing Shi,Elisabeth Paietta,Martin S. Tallman,Larry D. Cripe,Susan K. Atwater,Frederick R. Appelbaum,Jerald P. Radich +17 more
TL;DR: DX SCNP was a significant predictor of CR/CRi in BM samples and a classifier of response to induction therapy in a Training Set of cryopreserved diagnostic samples collected from 74 non-M3 AML pts, aged 56+ treated with 3+7-based regimens on 4 SWOG clinical trials.
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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 Cohen,James Hackett,Jing Shi,Michael G. Walker,Zhuoxin Sun,Elisabeth Paietta,Martin S. Tallman,Larry D. Cripe,Susan K. Atwater,Frederick R. Appelbaum,Jerald P. Radich +20 more
TL;DR: Data show that the proteomic classifier may provide prognostic information relevant to treatment planning beyond genetic mutations and traditional prognostic factors in elderly AML.