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


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.

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Fig. 5



Bicinchoninic acid assay


Carcinoembryonic antigen related cell adhesion molecule 2




C-C motif chemokine ligand 4


Carbon dioxide


Clustered regularly interspaced short palindromic repeats


Ectonucleotide pyrophosphatase/phosphodiesterase 2


False discovery rate


Glyceraldehyde 3-phosphate dehydrogenase


Hydrogen chloride


Indoleamine-pyrrole 2,3 dioxygenase


Immunoglobulin G


Interleukin 4


Interleukin 13 receptor subunit alpha 1


Knocked down


Linear models for microarray data


Multiplicity of infection


NOD-SCID-IL2 gamma chain knock-out


Sodium chloride




Tumor necrosis factor (ligand) superfamily, member 4


Tumor protein P53


Peroxisomal membrane protein 14


RNA interference




System biosciences


Semaphorin 7a


Sphingosine-1-phosphate ligase 1


Short harpin RNA


SMAD family member 3


S1P transporter spinster homologue 2


Testis expressed gene 9


T-Cell lymphoma invasion and metastasis 1


Tumor microenvironment


Triple-negative breast cancer


Thrombospondin 1




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This research was supported by the following Shared Resources at Lombardi Comprehensive Cancer Center: The Genomics and Epigenomics Shared Resource, the Flow Cytometry and Cell Sorting Shared Resource, and the Tissue Culture Shared Resource. All Lombardi Comprehensive Cancer Center Shared Resources are partially supported by National Institutes of Health (NIH)/National Cancer Institute (NCI) Grant P30-CA051008. An antibody to CD47 was kindly provided by Dr. Robert Karr, Tioma Therapeutics, Inc (St. Louis, MO).

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Correspondence to Louis M. Weiner.

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This manuscript was supported by NIH Grants CA50633 (Louis M Weiner) and CA51880 (Louis M Weiner), and Susan G. Komen Career Catalyst Research Grant CCR14299200 (Zachary C Hartman).

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The authors have no conflicts of interest to report or disclose.

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Shuptrine, C.W., Ajina, R., Fertig, E.J. et al. An unbiased in vivo functional genomics screening approach in mice identifies novel tumor cell-based regulators of immune rejection. Cancer Immunol Immunother 66, 1529–1544 (2017).

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  • In Vivo Genome-wide RNAi Screen
  • Triple-negative breast cancer
  • Cancer-derived resistance to immunotherapy
  • Functional genomics