New tool decodes how genes control cell behavior in disease and cancer
Researchers have developed MOBILE, a computational tool that identifies which genes and pathways drive specific cell behaviors—a breakthrough that could accelerate drug discovery and personalized medicine. The method successfully mapped genetic networks controlling immune cells and cancer subtypes, offering a faster way to understand disease mechanisms that pharmaceutical and biotech companies need to develop targeted therapies.
Originaltitel: MOBILE pipeline enables identification of context-specific networks and regulatory mechanisms
<p>Robust identification of context-specific network features that control cellular phenotypes remains a challenge. We here introduce MOBILE (Multi-Omics Binary Integration via Lasso Ensembles) to nominate molecular features associated with cellular phenotypes and pathways. First, we use MOBILE to nominate mechanisms of interferon-γ (IFNγ) regulated PD-L1 expression. Our analyses suggest that IFNγ-controlled PD-L1 expression involves BST2 , CLIC2 , FAM83D , ACSL5 , and HIST2H2AA3 genes, which were supported by prior literature. We also compare networks activated by related family members transforming growth factor-beta 1 (TGFβ1) and bone morphogenetic protein 2 (BMP2) and find that differences in ligand-induced changes in cell size and clustering properties are related to differences in laminin/collagen pathway activity. Finally, we demonstrate the broad applicability and adaptability of MOBILE by analyzing publicly available molecular datasets to investigate breast cancer subtype specific networks. Given the ever-growing availability of multi-omics datasets, we envision that MOBILE will be broadly useful for identification of context-specific molecular features and pathways.</p>