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Immune landscape of a genetically engineered murine model of glioma compared with human glioma

Authors :
Daniel B. Zamler
Takashi Shingu
Laura M. Kahn
Kristin Huntoon
Cynthia Kassab
Martina Ott
Katarzyna Tomczak
Jintan Liu
Yating Li
Ivy Lai
Rocio Zorilla-Veloz
Cassian Yee
Kunal Rai
Betty Y.S. Kim
Stephanie S. Watowich
Amy B. Heimberger
Giulio F. Draetta
Jian Hu
Source :
JCI Insight, Vol 7, Iss 12 (2022)
Publication Year :
2022
Publisher :
American Society for Clinical investigation, 2022.

Abstract

Novel therapeutic strategies targeting glioblastoma (GBM) often fail in the clinic, partly because preclinical models in which hypotheses are being tested do not recapitulate human disease. To address this challenge, we took advantage of our previously developed spontaneous Qk/Trp53/Pten (QPP) triple-knockout model of human GBM, comparing the immune microenvironment of QPP mice with that of patient-derived tumors to determine whether this model provides opportunity for gaining insights into tumor physiopathology and preclinical evaluation of therapeutic agents. Immune profiling analyses and single-cell sequencing of implanted and spontaneous tumors from QPP mice and from patients with glioma revealed intratumoral immune components that were predominantly myeloid cells (e.g., monocytes, macrophages, and microglia), with minor populations of T, B, and NK cells. When comparing spontaneous and implanted mouse samples, we found more neutrophils and T and NK cells in the implanted model. Neutrophils and T and NK cells were increased in abundance in samples derived from human high-grade glioma compared with those derived from low-grade glioma. Overall, our data demonstrate that our implanted and spontaneous QPP models recapitulate the immunosuppressive myeloid-dominant nature of the tumor microenvironment of human gliomas. Our model provides a suitable tool for investigating the complex immune compartment of gliomas.

Subjects

Subjects :
Neuroscience
Oncology
Medicine

Details

Language :
English
ISSN :
23793708
Volume :
7
Issue :
12
Database :
Directory of Open Access Journals
Journal :
JCI Insight
Publication Type :
Academic Journal
Accession number :
edsdoj.f2d1aec989ba484691463ec5f1531b0b
Document Type :
article
Full Text :
https://doi.org/10.1172/jci.insight.148990