Targeting the Atf7ip-Setdb1 Complex Augments Antitumor Immunity by Boosting Tumor Immunogenicity.

Substantial progress has been made in understanding how tumors escape immune surveillance. However, few measures to counteract tumor immune evasion have been developed. Suppression of tumor antigen expression is a common adaptive mechanism that cancers use to evade detection and destruction by the immune system. Epigenetic modifications play a critical role in various aspects of immune invasion, including the regulation of tumor antigen expression. To identify epigenetic regulators of tumor antigen expression, we established a transplantable syngeneic tumor model of immune escape with silenced antigen expression and used this system as a platform for a CRISPR-Cas9 suppressor screen for genes encoding epigenetic modifiers. We found that disruption of the genes encoding either of the chromatin modifiers activating transcription factor 7-interacting protein (Atf7ip) or its interacting partner SET domain bifurcated histone lysine methyltransferase 1 (Setdb1) in tumor cells restored tumor antigen expression. This resulted in augmented tumor immunogenicity concomitant with elevated endogenous retroviral (ERV) antigens and mRNA intron retention. ERV disinhibition was associated with a robust type I interferon response and increased T-cell infiltration, leading to rejection of cells lacking intact Atf7ip or Setdb1. ATF7IP or SETDB1 expression inversely correlated with antigen processing and presentation pathways, interferon signaling, and T-cell infiltration and cytotoxicity in human cancers. Our results provide a rationale for targeting Atf7ip or Setdb1 in cancer immunotherapy.

Transcriptomic immunologic signature associated with favorable clinical outcome in basal-like breast tumors.

BACKGROUND: Most patients with early stage triple negative breast cancer (TNBC) receive adjuvant chemotherapy. Activation of the immune system is associated with tumor response and may help identify TNBC with favorable outcome. METHODS: Gene expression data were obtained from the GEO Dataset GDS2250/GSE3744. Affymetrix CEL files were downloaded and analyzed with Affymetrix Transcriptome Analysis Console 3.0. Functional genomics was implemented with David Bioinformatics Resources 6.8. Data contained at Oncomine were used to identify genes upregulated in basal-like cancer compared to normal breast tissue. Data contained at cBioportal were used to assess for molecular alterations. The KMPlotter online tool, METABRIC and GSE25066 datasets were used to associate gene signatures with clinical outcome. RESULTS: 1564 upregulated genes were identified as differentially expressed between normal and basal-like tumors. Of these, 16 genes associated with immune function were linked with clinical outcome. HLA-C, HLA-F, HLA-G and TIGIT were associated with both improved relapse-free survival (RFS) and overall survival (OS). The combination of HLA-F/TIGIT and HLA-C/HLA-F/TIGIT showed the most favorable outcome (HR for RFS 0.44, p<0.001; HR for OS 0.22, p<0.001; and HR for RFS 0.46, p<0.001; HR for OS 0.15, p<0.001; respectively). The association of HLA-C/HLA-F with outcome was confirmed using the METABRIC and GSE25066 datasets. No copy number alterations of these genes were identified. CONCLUSION: We describe a gene signature associated with immune function and favorable outcome in basal-like breast cancer. Incorporation of this signature in prospective studies may help to stratify risk of early stage TNBC.