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Increased vessel perfusion predicts the efficacy of immune checkpoint blockade
Xichen Zheng, … , Qingyu Wu, Yuhui Huang
Xichen Zheng, … , Qingyu Wu, Yuhui Huang
Published April 16, 2018
Citation Information: J Clin Invest. 2018;128(5):2104-2115. https://doi.org/10.1172/JCI96582.
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Research Article Immunology Vascular biology Article has an altmetric score of 9

Increased vessel perfusion predicts the efficacy of immune checkpoint blockade

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Abstract

Immune checkpoint blockade (ICB) has demonstrated curative potential in several types of cancer, but only for a small number of patients. Thus, the identification of reliable and noninvasive biomarkers for predicting ICB responsiveness is an urgent unmet need. Here, we show that ICB increased tumor vessel perfusion in treatment-sensitive EO771 and MMTV-PyVT breast tumor as well as CT26 and MCA38 colon tumor models, but not in treatment-resistant MCaP0008 and 4T1 breast tumor models. In the sensitive tumor models, the ability of anti–cytotoxic T lymphocyte–associated protein 4 or anti–programmed cell death 1 therapy to increase vessel perfusion strongly correlated with its antitumor efficacy. Moreover, globally enhanced tumor vessel perfusion could be detected by Doppler ultrasonography before changes in tumor size, which predicted final therapeutic efficacy with more than 90% sensitivity and specificity. Mechanistically, CD8+ T cell depletion, IFN-γ neutralization, or implantation of tumors in IFN-γ receptor knockout mice abrogated the vessel perfusion enhancement and antitumor effects of ICB. These results demonstrated that ICB increased vessel perfusion by promoting CD8+ T cell accumulation and IFN-γ production, indicating that increased vessel perfusion reflects the successful activation of antitumor T cell immunity by ICB. Our findings suggest that vessel perfusion can be used as a novel noninvasive indicator for predicting ICB responsiveness.

Authors

Xichen Zheng, Zhaoxu Fang, Xiaomei Liu, Shengming Deng, Pei Zhou, Xuexiang Wang, Chenglin Zhang, Rongping Yin, Haitian Hu, Xiaolan Chen, Yijie Han, Yun Zhao, Steven H. Lin, Songbing Qin, Xiaohua Wang, Betty Y.S. Kim, Penghui Zhou, Wen Jiang, Qingyu Wu, Yuhui Huang

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

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