Steven M. Pollard

The paper identifies six distinct tumor microenvironment niches in glioblastoma that correlate with patient survival and immunotherapy response.

This study screens a large compound library across patient-derived GBM stem cells to identify effective drugs targeting tumor heterogeneity and presents validated hits for further exploration.

The paper uses single cell proteomic analysis to identify distinct functional states of neutrophils in human glioblastoma, revealing clusters with pathogenic and anti-tumorigenic properties not detectable by scRNA-seq.

This study shows FAK regulates glycolysis and glutamine oxidation in glioblastoma stem cells, affecting mitochondrial morphology and cell migration.

This study identifies a synergistic combination of FAK and MEK inhibitors that effectively targets glioblastoma heterogeneity and improves therapeutic outcomes.

The paper uses machine learning to identify senescent glioblastoma cells and discovers compounds that induce senescence in these cells.

This study benchmarks brain organoid gene co-expression patterns against fetal corticogenesis to assess their alignment with in vivo development.

The paper investigates oncogene expression from extrachromosomal DNA in glioblastoma and finds that copy number amplification, not spatial clustering, drives high transcriptional output.

The paper shows that Brn2 and Ascl1 differentially bind mitotic chromosomes, influencing the timing of transcriptional reactivation during the mitosis-to-G1 transition.

The paper identifies EDC mixtures linked to adverse health outcomes and shows they disrupt gene regulatory networks in vitro and in vivo.