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Usage Information

IFN-γ–related mRNA profile predicts clinical response to PD-1 blockade
Mark Ayers, … , Antoni Ribas, Terrill K. McClanahan
Mark Ayers, … , Antoni Ribas, Terrill K. McClanahan
Published June 26, 2017
Citation Information: J Clin Invest. 2017;127(8):2930-2940. https://doi.org/10.1172/JCI91190.
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Research Article Immunology Oncology Article has an altmetric score of 90

IFN-γ–related mRNA profile predicts clinical response to PD-1 blockade

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Abstract

Programmed death-1–directed (PD-1–directed) immune checkpoint blockade results in durable antitumor activity in many advanced malignancies. Recent studies suggest that IFN-γ is a critical driver of programmed death ligand-1 (PD-L1) expression in cancer and host cells, and baseline intratumoral T cell infiltration may improve response likelihood to anti–PD-1 therapies, including pembrolizumab. However, whether quantifying T cell–inflamed microenvironment is a useful pan-tumor determinant of PD-1–directed therapy response has not been rigorously evaluated. Here, we analyzed gene expression profiles (GEPs) using RNA from baseline tumor samples of pembrolizumab-treated patients. We identified immune-related signatures correlating with clinical benefit using a learn-and-confirm paradigm based on data from different clinical studies of pembrolizumab, starting with a small pilot of 19 melanoma patients and eventually defining a pan-tumor T cell–inflamed GEP in 220 patients with 9 cancers. Predictive value was independently confirmed and compared with that of PD-L1 immunohistochemistry in 96 patients with head and neck squamous cell carcinoma. The T cell–inflamed GEP contained IFN-γ–responsive genes related to antigen presentation, chemokine expression, cytotoxic activity, and adaptive immune resistance, and these features were necessary, but not always sufficient, for clinical benefit. The T cell–inflamed GEP has been developed into a clinical-grade assay that is currently being evaluated in ongoing pembrolizumab trials.

Authors

Mark Ayers, Jared Lunceford, Michael Nebozhyn, Erin Murphy, Andrey Loboda, David R. Kaufman, Andrew Albright, Jonathan D. Cheng, S. Peter Kang, Veena Shankaran, Sarina A. Piha-Paul, Jennifer Yearley, Tanguy Y. Seiwert, Antoni Ribas, Terrill K. McClanahan

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ISSN: 0021-9738 (print), 1558-8238 (online)

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