A targeted phosphoproteomic assay to enable the prediction of response to intensive chemotherapy in acute myeloid leukemia.

G Gabriel Ghiaur (1Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, United States) J Josie A. Christopher W Weronika E. Borek (Kinomica Limited, Macclesfield, United Kingdom) L Luis Veiga Nobre (Kinomica Limited, Macclesfield, United Kingdom) F Federico Pedicona (Kinomica Limited, Macclesfield, United Kingdom) A Amy E. Campbell (Kinomica Limited, Macclesfield, United Kingdom) J Janet Kelsall (Kinomica Limited, Macclesfield, United Kingdom) O Olga Ramirez Diaz (Kinomica Limited, Macclesfield, United Kingdom) K Krystyna J. Sykes (Kinomica Limited, Macclesfield, United Kingdom) D David M. Ross (21Haematology Directorate, SA Pathology, Royal Adelaide Hospital and Flinders Medical Centre, Adelaide, Australia) D Derek L. Stirewalt (Fred Hutchinson Cancer Research Center, Seattle, WA) I Ian Francis Thomas (Cardiff University, School of Medicine, Cardiff, United Kingdom) H Heinz Sill (34Division of Hematology, Medical University of Graz, Graz, Austria) B Brian Huntly P Paolo Gallipoli M Mark D. Minden (Princess Margaret Cancer Centre, University Health Network) J John G. Gribben (6Barts Cancer Institute, Queen Mary University of London, London, United Kingdom) A Arran David Dokal (Kinomica Limited, Macclesfield, United Kingdom) E Edmund H. Wilkes (Kinomica Limited, Macclesfield, United Kingdom)

Abstract

6521 Background: Intensive chemotherapy (IC; cytarabine plus an anthracycline) remains a standard first-line therapy for fit patients with acute myeloid leukemia (AML), a heterogeneous hematologic malignancy with poor long-term survival. IC induces composite complete remission (cCR) in ~60–70% of cases, and IC response variability persists within genetic/ELN risk strata. As emerging regimens increasingly challenge IC as a default therapy, biology-informed predictors are needed to identify patients unlikely to benefit from IC to avoid unnecessary toxicity. Mass spectrometry (MS)-based phosphoproteomics enables quantitative profiling of phosphopeptides (PPs) from patient samples, providing a functional readout of tumor biology. Thus, we sought to develop a PP-based clinically-deployable assay, orthogonal to genetic risk stratification, to predict response to IC in AML. Methods: 261 retrospective samples were collected from patients with newly-diagnosed AML (Table) treated with standard “7+3” IC in 9 centers in Europe, Australia, and North America. Response was assessed at the end of induction by the treating physician. Samples underwent phosphoproteomics using: 1) global MS for biomarker discovery or 2) targeted, clinically-compatible MS for validation. Predictive model performance was evaluated using rebalanced leave-one-out cross-validation. Results: During discovery, 3205 PPs were detected. Using Bayesian approaches, we identified an 80-PP multi-analyte signature of IC response (refractory vs cCR), and achieved an AUROC of 0.68 (95% CI 0.54-0.83). The signature was enriched for DNA damage signalling and repair (DNA-PK-S2612, ATM/cohesin, nucleotide excision and double-strand break repair proteins), and cellular stress pathways (phospho-p38, IL-16, AP-1/c-Jun). In an independent validation cohort, the targeted assay reliably detected the biomarker set and preserved its association with outcome (AUROC 0.69; 95% CI 0.53-0.84). Biomarker-based classification was associated with improved event-free survival (HR 0.45; 95% CI 0.26-0.78). Conclusions: We identified and validated a signature of response to IC in AML, and translated it into a targeted, clinically-deployable assay. This approach captures signaling states relevant to IC mechanisms of action that are not directly inferred from standard clinical or genetic variables. Ongoing analyses are evaluating its relationship to established genetic and ELN risk stratification. These findings support diagnostic phosphoproteomics and suggest functional biomarkers may complement existing approaches for treatment selection in AML. Cohort characteristics. Cohort Discovery Validation Median age at diagnosis (years, quartiles) 54 (23, 65) 59 (47, 68) Median diagnosis year (range) 2014 (1999, 2023) 2013 (2001, 2024) No of patients/samples 135/165 102/106 No of cCR/Refractory 94/41 79/23 PPs 3205 80

Article Details

Volume / Issue Vol. 44, Issue 16_suppl
Published June 01, 2026
Pages 6521-6521
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (19)

G

Gabriel Ghiaur

1Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, United States

J

Josie A. Christopher

W

Weronika E. Borek

Kinomica Limited, Macclesfield, United Kingdom

L

Luis Veiga Nobre

Kinomica Limited, Macclesfield, United Kingdom

F

Federico Pedicona

Kinomica Limited, Macclesfield, United Kingdom

A

Amy E. Campbell

Kinomica Limited, Macclesfield, United Kingdom

J

Janet Kelsall

Kinomica Limited, Macclesfield, United Kingdom

O

Olga Ramirez Diaz

Kinomica Limited, Macclesfield, United Kingdom

K

Krystyna J. Sykes

Kinomica Limited, Macclesfield, United Kingdom

D

David M. Ross

21Haematology Directorate, SA Pathology, Royal Adelaide Hospital and Flinders Medical Centre, Adelaide, Australia

D

Derek L. Stirewalt

Fred Hutchinson Cancer Research Center, Seattle, WA

I

Ian Francis Thomas

Cardiff University, School of Medicine, Cardiff, United Kingdom

H

Heinz Sill

34Division of Hematology, Medical University of Graz, Graz, Austria

B

Brian Huntly

P

Paolo Gallipoli

M

Mark D. Minden

Princess Margaret Cancer Centre, University Health Network

J

John G. Gribben

6Barts Cancer Institute, Queen Mary University of London, London, United Kingdom

A

Arran David Dokal

Kinomica Limited, Macclesfield, United Kingdom

E

Edmund H. Wilkes

Kinomica Limited, Macclesfield, United Kingdom