Abstract
Abstract Gliomas are diffusely invasive brain tumors with fatal outcomes and few effective treatments. Precision medicine focuses on targeting the genetics of individual tumors, but not host genetics, despite studies that have linked germline polymorphisms with glioma risk. Accordingly, glioma survival studies in mice utilize genetically variable tumors on identical host genetic backgrounds, which fails to differentiate between cancer cell-autonomous (CCA) and tumor microenvironment (TME) effects on glioma progression and host survival. The Collaborative Cross (CC) is a panel of genetically diverse mouse strains derived from both wild- and traditional inbred laboratory strains that facilitates high-resolution genetic mapping in models of complex disease. Here, we implement a novel platform to discover genetic modifiers of both CCA and TME phenotypes using genetically defined orthotopic murine allograft gliomas and CC hosts. We stereotactically injected Nf1;Trp53-/-oligodendrocyte progenitor-derived mouse tumor cells into syngeneic C57BL/6 control mice and 14 different CC strains. Seven strains survived significantly longer than controls (P<0.05), suggesting slower tumor growth (Gs, growth slow). The remaining 7 strains survived similarly to controls, suggesting fast growth (Gf, growth fast). Variable tumor growth in CC mice suggests that genetic background influences molecular processes in the TME that inhibit or potentiate tumor growth, respectively. To identify candidate genes, we performed RNA sequencing on 36 tumors from 3 Gf strains, 4 Gs strains, and controls. 134 genes were differentially expressed among Gf, Gs, and control tumors (P<0.05). Hierarchical clustering on these genes revealed that Gs strains clustered separately from Gf and controls. Gene ontology analysis using GOrilla showed 30 enriched processes, (FDR q<0.001), all of which were involved in immune responses or extracellular matrix biology. These results suggest that Gs strains activate immune and TME processes that slow tumor growth. Quantitative trait locus (QTL) analyses of host genetics and tumor data are pending and will facilitate identification of genetic variants that influence TME effects on tumor progression. Citation Format: Kasey Skinner, Martin Ferris, Ryan Bash, Abigail Shelton, Erin Smithberger, Steve Angus, Brian Golitz, Noah Sciaky, Jeremy Simon, Jason Stein, Glenn Matsushima, Quinn Ostrom, Lindsay Stetson, Jill Barnholtz-Sloan, Harshil Dhruv, Michael Berens, Fernando Pardo Manuel de Villena, C. Ryan Miller. Tumor microenvironment and host genetics impact glioma progression in a Collaborative Cross-based orthotopic allograft model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2745.
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