PXD053618-1

PXD053618 is an original dataset announced via ProteomeXchange.

Title	Phosphoproteomics predict response to midostaurin plus chemotherapy in independent cohorts of FLT3-mutated acute myeloid leukaemia
Description	Acute myeloid leukaemia (AML) is a blood malignancy with poor prognosis and a limited number of first-line treatments, one of which is midostaurin combined with intensive chemotherapy (MIC). MIC is approved for FLT3 mutation-positive (FLT3-MP) AML, yet many eligible patients are refractory or experience an early relapse. Development of a MIC stratification method that outperforms FLT3 mutational status would thus benefit a large number of patients with AML. We employed phosphoproteomics, a mass spectrometry technique that quantifies thousands of cellular signalling events in a single sample, to analyse 71 diagnosis samples of 47 FLT3-MP patients with AML who subsequently received MIC. We then used machine learning to identify biomarkers of response to MIC, and validated the resulting predictive model in two independent validation cohorts. We identified three distinct phosphoproteomic subtypes amongst long-term AML survivors. The subtypes showed similar duration of MIC response, but different modulation of AML-implicated pathways, and exhibited distinct, highly-predictive biomarkers of MIC response. Using these biomarkers, we built a phosphoproteomics-based predictive model of MIC response, called MPhos. When applied to two retrospective real-world patient test cohorts (n=20), MPhos predicted MIC response with 100% sensitivity and 87.5% specificity (log-rank p<3.0e-4, HR=0.04 [95% CI:0-0.39]). In validation, MPhos outperformed the currently-used FLT3-based stratification method. Thus, it has the potential to transform clinical decision-making, with important implications for the role of phosphoproteomics in precision medicine beyond AML.
HostingRepository	PRIDE
AnnounceDate	2025-05-09
AnnouncementXML	Submission_2025-05-09_15:19:37.577.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Nazrath Nawaz
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	2-pyrrolidone-5-carboxylic acid (Gln); phosphorylated residue; monohydroxylated residue
Instrument	Orbitrap Exploris 240; Q Exactive Plus

Revision	Datetime	Status	ChangeLog Entry
0	2024-07-03 14:52:12	ID requested
⏵ 1	2025-05-09 15:19:38	announced

10.1016/j.ebiom.2024.105316;

Borek WE, Nobre L, Pedicona SF, Campbell AE, Christopher JA, Nawaz N, Perkins DN, Moreno-Cardoso P, Kelsall J, Ferguson HR, Patel B, Gallipoli P, Arruda A, Ambinder AJ, Thompson A, Williamson A, Ghiaur G, Minden MD, Gribben JG, Britton DJ, Cutillas PR, Dokal AD, Phosphoproteomics predict response to midostaurin plus chemotherapy in independent cohorts of FLT3-mutated acute myeloid leukaemia. EBioMedicine, 108():105316(2024) [pubmed]

submitter keyword: phosphoproteomics, machine learning, drug response prediction, midostaurin plus chemotherapy, acute myeloid leukemialeukaemia, precision medicine

Arran D. Dokal
contact affiliation	Kinomica Ltd, Alderley Park, SK104TG Macclesfield, United Kingdom
contact email	a.dokal@kinomica.com
lab head
Nazrath Nawaz
contact affiliation	Kinomica Ltd
contact email	n.nawaz@kinomica.com
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD053618
     1. Label: PRIDE project
     2. Name: Phosphoproteomics predict response to midostaurin plus chemotherapy in independent cohorts of FLT3-mutated acute myeloid leukaemia