title: Cell signaling-based classifier predicts response to induction therapy in elderly patients with acute myeloid leukemia.
abstract: 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 with CR, CRi or RD; BM set = 43; PB set = 57) and Validation Analysis Sets (N = 71; BM set = 42, PB set = 53). Cell survival, differentiation, and apoptosis pathway signaling were used as potential inputs for DXSCNP. Five DXSCNP classifiers were developed on the SWOG Training set and tested for prediction accuracy in an independent BM verification sample set (N = 24) from ECOG AML trials to select the final classifier, which was a significant predictor of CR/CRi (area under the receiver operating characteristic curve AUROC = 0.76, p = 0.01). The selected classifier was then validated in the SWOG BM Validation Set (AUROC = 0.72, p = 0.02). Importantly, a classifier developed using only clinical and molecular inputs from the same sample set (DXCLINICAL2) lacked prediction accuracy: AUROC = 0.61 (p = 0.18) in the BM Verification Set and 0.53 (p = 0.38) in the BM Validation Set. Notably, the DXSCNP classifier was still significant in predicting response in the BM Validation Analysis Set after controlling for DXCLINICAL2 (p = 0.03), showing that DXSCNP provides information that is independent from that provided by currently used prognostic markers. Taken together, these data show that the proteomic classifier may provide prognostic information relevant to treatment planning beyond genetic mutations and traditional prognostic factors in elderly AML.
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Cesano
authors.affiliation: University of New Mexico Cancer Center, Albuquerque, New Mexico, United States of America.
authors.forename: Cheryl L
authors.initials: CL
authors.lastname: Willman
authors.affiliation: SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
authors.forename: Kenneth J
authors.initials: KJ
authors.lastname: Kopecky
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: Urte
authors.initials: U
authors.lastname: Gayko
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: Santosh
authors.initials: S
authors.lastname: Putta
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: Brent
authors.initials: B
authors.lastname: Louie
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: Matt
authors.initials: M
authors.lastname: Westfall
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: Norman
authors.initials: N
authors.lastname: Purvis
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: David C
authors.initials: DC
authors.lastname: Spellmeyer
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: Carol
authors.initials: C
authors.lastname: Marimpietri
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: Aileen C
authors.initials: AC
authors.lastname: Cohen
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: James
authors.initials: J
authors.lastname: Hackett
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: Jing
authors.initials: J
authors.lastname: Shi
authors.affiliation: Nodality, Inc., South San Francisco, California, United States of America.
authors.forename: Michael G
authors.initials: MG
authors.lastname: Walker
authors.affiliation: ECOG Coordinating Center, Frontier Science, Boston, Massachusetts, United States of America.
authors.forename: Zhuoxin
authors.initials: Z
authors.lastname: Sun
authors.affiliation: Montefiore Medical Center North Division, Bronx, New York, United States of America.
authors.forename: Elisabeth
authors.initials: E
authors.lastname: Paietta
authors.affiliation: Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
authors.forename: Martin S
authors.initials: MS
authors.lastname: Tallman
authors.affiliation: Indiana University Simon Cancer Center, Indianapolis, Indiana, United States of America.
authors.forename: Larry D
authors.initials: LD
authors.lastname: Cripe
authors.affiliation: Stanford University, Palo Alto, California, United States of America.
authors.forename: Susan
authors.initials: S
authors.lastname: Atwater
authors.affiliation: Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
authors.forename: Frederick R
authors.initials: FR
authors.lastname: Appelbaum
authors.affiliation: Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
authors.forename: Jerald P
authors.initials: JP
authors.lastname: Radich
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use*; D019540:Area Under Curve; D001773:Blood Cells / Q000166:cytology / Q000378:metabolism*; D001854:Bone Marrow Cells / Q000166:cytology / Q000378:metabolism*; D005260:Female; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000175:diagnosis / Q000188:drug therapy* / Q000473:pathology; D008297:Male; D053858:Metabolic Networks and Pathways; D008875:Middle Aged; D011379:Prognosis; D012372:ROC Curve; D012074:Remission Induction; D015398:Signal Transduction; D059010:Single-Cell Analysis