English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The characterization of the immune landscape of glioblastoma multiforme (GBM) is rapidly emerging. Current immunotherapeutic efforts for GBM would benefit from a comprehensive and mechanistic understanding of the relationship between distinct driver gene mutations and the composition and function of the immune tumor microenvironment. The majority of GBM tumors overexpress EGFR and EGFRvIII and ~40% are mutated for PTEN. Using genetically engineered and accurate preclinical mouse models of GBM built on combinations of these driver genes, we demonstrate that the compositions of the immune landscape and the response to checkpoint blockade immunotherapy vary according to the genotype of the GBM. Mechanistically, we show that signaling networks downstream of EGFR and PTEN establish chemokine and cytokine profiles that parallel the levels of intra-tumoral polymorphonuclear myeloid-derived suppressor cells and regulatory T cells. Additionally, tumor-associated microglia/macrophages number, function and polarization are heavily influenced by specific driver-gene mutation combinations. Furthermore, we demonstrate that efficacy of checkpoint blockade therapy using anti PD-1 as a single agent or in combination with anti CTLA-4 is dependent on EGFR and PTEN status. Taken together, our findings demonstrate that important components of the tumor immune microenvironment are influenced by specific driver gene mutations. Our results suggest that stratifying patients based on tumor genotype or signaling events may be informative for selection of appropriate candidates for checkpoint blockade therapy and present an opportunity to pharmacologically modulate GBM signaling with targeted therapeutics to sensitize patients to immunotherapy.

IMMU-31. DRIVER GENE MUTATIONS DICTATE THE COMPOSITION OF THE IMMUNE LANDSCAPE OF GLIOBLASTOMA AND CONFER SELECTIVE RESPONSE TO IMMUNOTHERAPY