Created by: Jesse Morris

Issue 212: Glioblastoma is a complex disease that is difficult to treat. In our study, we applied a host of data theoretic techniques to gene expression patterns from pediatric and adult glioblastoma, and adult glioma-derived stem cells (GSCs) to identify the key molecular regulators of the networks driving glioblastoma/GSCs and predict their cell fate dynamics along differentiation landscapes illustrated here. Our results provide strong evidence of complex systems approaches for inferring complex dynamics by reverse-engineering gene networks. In the figure, we see a visualization of the Waddington landscape with more or less differentiated cells. Identifying the programs regulating this differentiation will bolster the search for new clinically relevant targets in glioblastoma and other cancers.