Differential assembly of mouse and human tumor microenvironments
(1) Courau T (2) Jaszczak RG (3) Samad B (4) Flynn E (5) Chew NW (6) Reeder GC (7) Tsui J (8) Teklu S (9) Pass LF (10) Edwards AW (11) Naser M (12) Ray A (13) Wismer H (14) Bunis D (15) Lupin-Jimenez L (16) Gavil NV (17) Masopust D (18) Graham JP (19) Skelly DA (20) Vesco X (21) Liu ET (22) Fragiadakis GK (23) Combes AJ (24) Krummel MF
Courau et al. profiled immune landscapes of 15 common mouse tumor models alongside human datasets. Most murine TIMEs resembled a minority subset of macrophage-rich, poorly infiltrated human tumors. Cross-species analysis showed species-specific biases in chemokine networks (including reduced CCR2/CCR5 and altered CXCL13 in mice) and altered T and myeloid cell frequencies, while conserved cell-type specific gene expression programs emerged as discriminatory. An IFN-responsive myeloid–CD8+ T cell cytotoxicity module was conserved across tumor types, and predicted clinical outcome in humans.
Contributed by Shishir Pant
(1) Courau T (2) Jaszczak RG (3) Samad B (4) Flynn E (5) Chew NW (6) Reeder GC (7) Tsui J (8) Teklu S (9) Pass LF (10) Edwards AW (11) Naser M (12) Ray A (13) Wismer H (14) Bunis D (15) Lupin-Jimenez L (16) Gavil NV (17) Masopust D (18) Graham JP (19) Skelly DA (20) Vesco X (21) Liu ET (22) Fragiadakis GK (23) Combes AJ (24) Krummel MF
Courau et al. profiled immune landscapes of 15 common mouse tumor models alongside human datasets. Most murine TIMEs resembled a minority subset of macrophage-rich, poorly infiltrated human tumors. Cross-species analysis showed species-specific biases in chemokine networks (including reduced CCR2/CCR5 and altered CXCL13 in mice) and altered T and myeloid cell frequencies, while conserved cell-type specific gene expression programs emerged as discriminatory. An IFN-responsive myeloid–CD8+ T cell cytotoxicity module was conserved across tumor types, and predicted clinical outcome in humans.
Contributed by Shishir Pant
ABSTRACT: Mouse models are frequently used to develop treatments for human cancer. However, the degree to which their tumor microenvironments (TMEs) are synonymously assembled is particularly poorly characterized. Through systematic immunoprofiling of 15 commonly used mouse models, we found that most murine TMEs recapitulate the composition of poorly infiltrated human tumors, extensively biased toward high macrophage densities. We discovered substantial species-specific biases of chemokine expression networks known to drive TMEs assembly, together with discoordinated frequencies of T and myeloid cell subtypes. Even with variable alignment, conserved cell-type-specific gene expression programs emerged across species and cohorts. Dissecting the coordinated T cell-myeloid gene expression programs revealed a conserved axis between interferon-responsive myeloid states and ongoing T cell cytotoxicity that transcends tissue of origin and predicts clinical outcome. Collectively, this work provides a practical atlas outlining both the hazards and opportunities of using mice to model human cancer.
Author Info:
(1) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. tristan.courau@ucsf.edu. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. tristan.courau@u
csf.edu. CoLabs, UCSF, San Francisco, CA, USA. tristan.courau@ucsf.edu. (2) CoLabs, UCSF, San Francisco, CA, USA. (3) ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. (4) CoLabs, UCSF, San Francisco, CA, USA. (5) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. (6) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. (7) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. (8) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. (9) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. (10) CoLabs, UCSF, San Francisco, CA, USA. (11) CoLabs, UCSF, San Francisco, CA, USA. (12) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. (13) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. (14) CoLabs, UCSF, San Francisco, CA, USA. (15) CoLabs, UCSF, San Francisco, CA, USA. (16) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (17) Department of Microbiology and Immunology, University of Minnesota Medical School, Minneapolis, MN, USA. (18) The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA. (19) The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA. (20) The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA. (21) The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA. (22) CoLabs, UCSF, San Francisco, CA, USA. Department of Medicine, Division of Rheumatology, UCSF, San Francisco, CA, USA. (23) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. CoLabs, UCSF, San Francisco, CA, USA. Department of Medicine, Division of Gastroenterology, UCSF, San Francisco, CA, USA. (24) Department of Pathology and ImmunoX Initiative, UCSF, San Francisco, CA, USA. max.krummel@ucsf.edu. ImmunoProfiler Initiative, UCSF, San Francisco, CA, USA. max.krummel@ucsf.edu.
