UMBI Research Spotlight No.3/2026
Decoding AML: Graph-Based Method for Potential Gene Discovery
UMBI is pleased to share a recent publication from our researchers, led by Dr. Muhammad-Redha Abdullah-Zawawi, exploring novel genes associated with acute myeloid leukemia (AML) using a graph-based clustering approach and protein-protein interaction network analysis.
By analysing complex molecular interaction networks, the team identified 16 potential AML-associated genes showing significant differential expression across multiple AML subtypes, including PML-RARα and CD34-positive AML. The findings revealed that these genes are strongly linked to ribosome biogenesis, translational control, chromatin organization, and key pathways such as PI3K/AKT signalling and hematopoietic dysregulation.
Importantly, this systems-level approach provides new insights into the molecular mechanisms underlying AML progression and highlights several candidate genes that may serve as future biomarkers or therapeutic targets for this aggressive blood cancer. The study also demonstrates the potential of graph-based computational biology in advancing precision diagnostics and personalised treatment strategies in hematological malignancies.
These findings further reflect UMBI’s growing strength in molecular oncology, bioinformatics, systems biology, and translational cancer research aimed at improving disease understanding and patient outcomes.
We invite colleagues and collaborators to explore the full review:
Muhamad Azuan et al. Oncologie (2026)
https://doi.org/10.1515/oncologie-2025-0509
#UMBI #UKM #UMBIResearchSpotlight #AcuteMyeloidLeukemia #AML #CancerResearch #MolecularOncology #PrecisionMedicine #Biomarkers #Hematology #ComputationalBiology
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