Clark, H. Brent

Abstract Glioblastoma (GBM) remains a deadly cancer driven in part by invasion of tumor cells into the brain. Transcriptomic analyses have identified distinct molecular subtypes, but mechanistic differences that account for clinical differences are not clear. In this study, we show that, as predicted by the motor-clutch model of cell migration, mesenchymal glioma cells are more spread, generate larger traction forces, and migrate faster in brain tissue compared with proneural cells. Despite their rapid migration and comparable proliferation rates in vitro, mice with mesenchymal tumors survive longer than those with proneural tumors. This improved survival correlated with an immune response in mesenchymal tumors, including T cell–mediated. Consistently, inducing mesenchymal tumors in immunodeficient mice resulted in shorter survival, supporting a protective immune role in mesenchymal tumors. Thus, mesenchymal tumors have aggressive migration but are immunologically “hot,” which suppresses net proliferation. These two features counteract each other and may explain the lack of a strong survival difference between subtypes clinically, while also opening up new opportunities for subtype-specific therapies. Significance: This study highlights new mechanical and immunologic insights into GBM molecular subtypes using an integrated modeling–genome engineering strategy, which can potentially facilitate GBM subtype-specific therapeutic strategies.

Many autoimmune diseases can affect the central nervous system, and their varying clinical presentations often confound a straightforward diagnosis. In this report, we describe a unique presentation of CLIPPERS syndrome. To our knowledge, this is the first case to demonstrate significant supratentorial involvement with symmetric and non-confluent lesions in the medial orbitofrontal cortex; additionally, this is the second case to describe an association between diagnoses of hypothyroidism and CLIPPERS.

Abstract In Glioblastoma (GBM), tumor spreading is driven by tumor cells’ ability to infiltrate healthy brain parenchyma, which prevents complete surgical resection and contributes to tumor recurrence. GBM molecular subtypes, classical, proneural and mesenchymal, were shown to strongly correlate with specific genetic alterations (Mesenchymal: NF1; Classical: EGFRVIII; Proneural: PDGFRA). Here we tested the hypothesis that a key mechanistic difference between GBM molecular subtypes is that proneural cells are slow migrating and mesenchymal cells are fast migrating. Using Sleeping Beauty transposon system, immune-competent murine brain tumors were induced by SV40-LgT antigen in combination with either NRASG12V (NRAS) or PDGFB (PDGF) overexpression. Cross-species transcriptomic analysis revealed NRAS and PDGF-driven tumors correlate with human mesenchymal and proneural GBM, respectively. Similar to human GBM, CD44 expression was higher in NRAS tumors and, consistent with migration simulations of varying CD44 levels, ex vivo brain slice live imaging showed NRAS tumors cells migrate faster than PDGF tumors cells (random motility coefficient = 30µm2/hr vs. 2.5µm2/hr, p < 0.001). Consistent with CD44 function as an adhesion molecule, migration phenotype was independent of the tumor microenvironment. NRAS and human PDX/MES tumor cells were found to migrate faster and have larger cell spread area than PDGF and human PDX/PN tumors cells, respectively, in healthy mouse brain slices. Furthermore, traction force microscopy revealed NRAS tumor cells generate larger traction forces than PDGF tumors cells which further supports our theoretical mechanism driving glioma migration. Despite increased migration, NRAS cohort had better survival than PDGF which was attributed to enhanced antitumoral immune response in NRAS tumors, consistent with increased immune cell infiltration found in human mesenchymal GBM. Overall our work identified a potentially actionable difference in migration mechanics between GBM subtypes and establishes an integrated biophysical modeling and experimental approach to mechanically parameterize and simulate distinct molecular subtypes in preclinical models of cancer.