An unbiased in vivo functional genomics screening approach in mice identifies novel tumor cell-based regulators of immune rejection.

Published

Journal Article

The clinical successes of immune checkpoint therapies for cancer make it important to identify mechanisms of resistance to anti-tumor immune responses. Numerous resistance mechanisms have been identified employing studies of single genes or pathways, thereby parsing the tumor microenvironment complexity into tractable pieces. However, this limits the potential for novel gene discovery to in vivo immune attack. To address this challenge, we developed an unbiased in vivo genome-wide RNAi screening platform that leverages host immune selection in strains of immune-competent and immunodeficient mice to select for tumor cell-based genes that regulate in vivo sensitivity to immune attack. Utilizing this approach in a syngeneic triple-negative breast cancer (TNBC) model, we identified 709 genes that selectively regulated adaptive anti-tumor immunity and focused on five genes (CD47, TGFβ1, Sgpl1, Tex9 and Pex14) with the greatest impact. We validated the mechanisms that underlie the immune-related effects of expression of these genes in different TNBC lines, as well as tandem synergistic interactions. Furthermore, we demonstrate the impact of different genes with previously unknown immune functions (Tex9 and Pex14) on anti-tumor immunity. Thus, this innovative approach has utility in identifying unknown tumor-specific regulators of immune recognition in multiple settings to reveal novel targets for future immunotherapies.

Full Text

Duke Authors

Cited Authors

  • Shuptrine, CW; Ajina, R; Fertig, EJ; Jablonski, SA; Kim Lyerly, H; Hartman, ZC; Weiner, LM

Published Date

  • December 2017

Published In

Volume / Issue

  • 66 / 12

Start / End Page

  • 1529 - 1544

PubMed ID

  • 28770278

Pubmed Central ID

  • 28770278

Electronic International Standard Serial Number (EISSN)

  • 1432-0851

International Standard Serial Number (ISSN)

  • 0340-7004

Digital Object Identifier (DOI)

  • 10.1007/s00262-017-2047-2

Language

  • eng