Gettinger, S. | Search bioRxiv

bioRxiv2022

Autologous humanized PDX modeling for immuno-oncology recapitulates the human tumor microenvironment

Interactions between immune and tumor cells are critical to determining cancer progression and response. In addition, preclinical prediction of immune-related drug efficacy is limited by inter-species differences between human and mouse, as well as inter-person germline and somatic variation. Here we develop an autologous system that models the TME in individual patients. With patient-derived bone marrow, we engrafted a patients hematopoietic system in MISTRG6 mice followed by patient-derived xenograft (PDX) tissue, providing a genetically matched autologous model. We used this system to prospectively study tumor-immune interactions in solid tumor patients. Autologous PDX mice generated innate and adaptive immune populations; these cells populated the TME; and tumors from autologously engrafted mice grew larger than tumors from non-engrafted littermate controls. Single-cell transcriptomics revealed a prominent VEGF-A signature in TME myeloid cells, and inhibition of human VEGF-A abrogated enhanced growth, demonstrating the utility of the autologous PDX system for pre-clinical testing.

cancer biology↗

bioRxiv2020

Genetic determinants of EGFR-Driven Lung Cancer Growth and Therapeutic Response In Vivo

Cancer genome sequencing has uncovered substantial complexity in the mutational landscape of tumors. Given this complexity, experimental approaches are necessary to establish the impact of combinations of genetic alterations on tumor biology and to uncover genotype-dependent effects on drug sensitivity. In lung adenocarcinoma, EGFR mutations co-occur with many putative tumor suppressor gene alterations, however the extent to which these alterations contribute to tumor growth and their response to therapy in vivo has not been explored experimentally. By integrating a novel mouse model of oncogenic EGFR-driven Trp53-deficient lung adenocarcinoma with multiplexed CRISPR-Cas9-mediated genome editing and tumor barcode sequencing, we quantified the effects of inactivation of ten putative tumor suppressor genes. Inactivation of Apc, Rb1, or Rbm10 most strongly promoted tumor growth. Unexpectedly, inactivation of Lkb1 or Setd2 - which are the strongest drivers of tumor growth in an oncogenic Kras-driven model - reduced EGFR-driven tumor growth. These results are consistent with the relative frequency of these tumor suppressor gene alterations in human EGFR- and KRAS-driven lung adenocarcinomas. Furthermore, Keap1 inactivation reduces the sensitivity of EGFR-driven Trp53-deficient tumors to the EGFR inhibitor osimertinib. Importantly, in human EGFR/TP53 mutant lung adenocarcinomas, mutations in the KEAP1 pathway correlated with decreased time on tyrosine kinase inhibitor treatment. Our study highlights how genetic alterations can have dramatically different biological consequences depending on the oncogenic context and that the fitness landscape can shift upon drug treatment.

cancer biology↗