Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia.

Cell reports. Medicine - 16 Jan 2024

Pino James C, Posso Camilo, Joshi Sunil K, Nestor Michael, Moon Jamie, Hansen Joshua R, Hutchinson-Bunch Chelsea, Gritsenko Marina A, Weitz Karl K, Watanabe-Smith Kevin, Long Nicola, McDermott Jason E, Druker Brian J, Liu Tao, Tyner Jeffrey W, Agarwal Anupriya, Traer Elie, Piehowski Paul D, Tognon Cristina E, Rodland Karin D, Gosline Sara J C

Abstract excerpt

Acute myeloid leukemia is a poor-prognosis cancer commonly stratified by genetic aberrations, but these mutations are often heterogeneous and fail to consistently predict therapeutic response. Here, we combine transcriptomic, proteomic, and phosphoproteomic datasets with ex vivo drug sensitivity data to help understand the underlying pathophysiology of AML beyond mutations. We measure the proteome and...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Acute Myeloid Leukemia Research
Share to Genomics

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Leukemia, Myeloid, Acute

Share to Multiple Myeloma Research and Treatments

Share to Mutation

Share to Protein Degradation and Inhibitors

Share to Proteogenomics

Share to Proteomics

Source

Open in PubMed Open full text

Identifiers

PMID: 38232702
DOI: 10.1016/j.xcrm.2023.101359
PMCID: PMC10829797

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia.PMID 38232702Read ↗

Proteomics and Phosphoprotoemic Measurements Enhance Ability to Predict Ex Vivo Drug Response in AMLSemantic proximity Read ↗

Proteomic and phosphoproteomic measurements enhance ability to predict ex vivo drug response in AMLSemantic proximity Read ↗

Utilizing proteomics and phosphoproteomics to predict <i>ex vivo</i> drug sensitivity across genetically diverse AML patientsSemantic proximity Read ↗

Proteomic Characterization of Acute Myeloid Leukemia for Precision MedicineSemantic proximity Read ↗

Mutation Patterns Predict Drug Sensitivity in Acute Myeloid LeukemiaSemantic proximity Read ↗

Integrated proteogenomic and metabolomic profiling of acute myeloid leukemias to identify molecular subtypes and associated therapy targets.Semantic proximity Read ↗

A quantitative analysis of heterogeneities and hallmarks in acute myelogenous leukaemia.Semantic proximity Read ↗

Molecular precision medicine: Multi-omics-based stratification model for acute myeloid leukemiaSemantic proximity Read ↗

Proteomic and phosphoproteomic landscapes of acute myeloid leukemia.Semantic proximity Read ↗

Phosphoproteomics predict response to midostaurin plus chemotherapy in independent cohorts of FLT3-mutated acute myeloid leukaemia.Semantic proximity Read ↗

Proteogenetic drug response profiling elucidates targetable vulnerabilities of myelofibrosis.Semantic proximity Read ↗

Clinical Forecasting using <i>Ex Vivo</i> Drug Sensitivity Profiling of Acute Myeloid LeukemiaSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.