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Abstract B033: T-cell-induced tumor vulnerability discovery in an IFNγ-independent genomic landscape

Authors: Daniel S. Peeper; David Vredevoogd; Thomas Kuilman;

Abstract B033: T-cell-induced tumor vulnerability discovery in an IFNγ-independent genomic landscape

Abstract

Abstract New clinical opportunities are needed to increase immunotherapy (IT) benefit. Whereas IFNγ-pathway mutations cause IT resistance, we find that IFNγ receptor-deficient tumors remain remarkably susceptible to T-cell elimination. By integrating transcriptomics, proteomics and genome-wide CRISPR-Cas9 screening with clinical data, we defined the IFNγ-independent tumor landscape and uncovered an immunotherapeutic opportunity. Ablation of TRAF2 enhanced T-cell elimination of both melanoma and lung cancer cells by redirecting TNF signaling to favor RIPK1-dependent apoptosis. TRAF2 loss greatly enhanced the therapeutic potential of pharmacologic inhibition of its interaction partner cIAP. Corroborating these observations clinically, we identified recurring TRAF2 mutations that reduced T-cell sensitivity of tumor cells. Furthermore, both IT response duration and overall survival were lower for tumors that had acquired TNF pathway mutations on IT, suggesting immune-editing by TNF pressure. These results functionally annotate the tumor genome landscape of IFNγ-independent T-cell cytotoxicity, and merit clinical exploration of TRAF2 for cancer immunotherapy. Citation Format: Daniel S. Peeper, David Vredevoogd, Thomas Kuilman. T-cell-induced tumor vulnerability discovery in an IFNγ-independent genomic landscape [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B033.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Cancer Research