Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response

Abstract

Cancer treatment by immune checkpoint blockade (ICB) can bring long-lasting clinical benefits, but only a fraction of patients respond to treatment. To predict ICB response, we developed TIDE, a computational method to model two primary mechanisms of tumor immune evasion: the induction of T cell dysfunction in tumors with high infiltration of cytotoxic T lymphocytes (CTL) and the prevention of T cell infiltration in tumors with low CTL level. We identified signatures of T cell dysfunction from large tumor cohorts by testing how the expression of each gene in tumors interacts with the CTL infiltration level to influence patient survival. We also modeled factors that exclude T cell infiltration into tumors using expression signatures from immunosuppressive cells. Using this framework and pre-treatment RNA-Seq or NanoString tumor expression profiles, TIDE predicted the outcome of melanoma patients treated with first-line anti-PD1 or anti-CTLA4 more accurately than other biomarkers such as PD-L1 level and mutation load. TIDE also revealed new candidate ICB resistance regulators, such as SERPINB9, demonstrating utility for immunotherapy research.

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Fig. 1: The interaction test identifies gene signatures of T cell dysfunction.
Fig. 2: T cell dysfunction signatures are consistent with published signatures of tumor immune evasion.
Fig. 3: Immunosuppressive cell expression models gene signatures of T cell exclusion.
Fig. 4: TIDE signatures predict ICB immunotherapy response.
Fig. 5: Validation of SERPINB9 as a regulator of tumor immune escape.

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Acknowledgements

The research was supported by the Cancer Immunologic Data Commons (1U24CA224316-01) grant of the National Cancer Institute (NCI), the Pathway to Independence Award (1K99CA218900-01) grant of NCI (to P.J.), the Specialized Center (1P50CA206963-01) grant of NCI (to G.J.F.), and the Breast Cancer Research Foundation (to X.S.L.). D.P. is a Cancer Research Institute/Robertson Foundation Fellow.

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P.J., K.W.W. and X.S.L. designed the study and wrote the manuscript. P.J. carried out the computational works. S.G., D.P., Z.L. and N.T. carried out the experimental validation. P.J. and J.F. developed the website. A.S., X.H., X.B., B.L, J.L., G.J.F. and M.A.B. participated in discussions.

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Correspondence to Kai W. Wucherpfennig or X. Shirley Liu.

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Competing interests

X.S.L. is a cofounder and board member of GV20 Oncotherapy, a scientific advisor of 3DMedCare and a paid consultant for Genentech. K.W.W. is a member of the scientific advisory board for TCR2 and Nextech; he serves as a consultant for Novartis. The laboratory of K.W.W. received sponsored research funding from Astellas Pharma Inc.

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Jiang, P., Gu, S., Pan, D. et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med 24, 1550–1558 (2018). https://doi.org/10.1038/s41591-018-0136-1

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