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

A parsimonious 3-gene signature predicts clinical outcomes in an acute myeloid leukemia multicohort study

23 Apr 2019

Abstract excerpt

Abstract Acute myeloid leukemia (AML) is a genetically heterogeneous hematological malignancy with variable responses to chemotherapy. Although recurring cytogenetic abnormalities and gene mutations are important predictors of outcome, 50% to 70% of AMLs harbor normal or risk-indeterminate karyotypes. Therefore, identifying more effective biomarkers predictive of treatment success and failure is essential for...

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 Chronic Myeloid Leukemia Treatments
Share to Myeloproliferative Neoplasms: Diagnosis and Treatment

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 31015209
DOI: 10.1182/bloodadvances.2018030726

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 4 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A parsimonious 3-gene signature predicts clinical outcomes in an acute myeloid leukemia multicohort studyPMID 31015209Read ↗

Integration of a 4-gene risk score model enhances prognostic accuracy in acute myeloid leukemia.Semantic proximity Read ↗

A novel 4‐mRNA signature predicts the overall survival in acute myeloid leukemiaSemantic proximity Read ↗

Precision survival estimation in acute myeloid leukemia using evolutionary learning-derived microRNA signatureSemantic proximity Read ↗

Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction valueSemantic proximity Read ↗

Integrating clinical features and genetic lesions in the risk assessment of patients with chronic myelomonocytic leukemia.Semantic proximity Read ↗

Personalized Survival Prediction of Patients With Acute Myeloblastic Leukemia Using Gene Expression ProfilingSemantic proximity Read ↗

A 4‐gene prognostic index for enhancing acute myeloid leukaemia survival predictionSemantic proximity Read ↗

A Novel 85-Gene Expression Signature Predicts Unfavorable Prognosis in Acute Myeloid Leukemia.Semantic proximity Read ↗

Multiple machine-learning tools identifying prognostic biomarkers for acute Myeloid LeukemiaSemantic proximity Read ↗

Molecular Characterization of the Highest Risk Adult Patients with Acute Myeloid Leukemia (AML) through Multi-omics ClusteringSemantic proximity Read ↗

An mRNA expression signature for prognostication inde novoacute myeloid leukemia patients with normal karyotypeSemantic proximity Read ↗

Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia.Semantic proximity Read ↗

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