Combination of host immune metabolic biomarkers for the PD-1 blockade cancer immunotherapy

Ryusuke Hatae, Kenji Chamoto, Young Hak Kim, Kazuhiro Sonomura, Kei Taneishi, Shuji Kawaguchi, Hironori Yoshida, Hiroaki Ozasa, Yuichi Sakamori, Maryam Akrami, Sidonia Fagarasan, Izuru Masuda, Yasushi Okuno, Fumihiko Matsuda, Toyohiro Hirai, Tasuku Honjo

研究成果: ジャーナルへの寄稿学術誌査読

25 被引用数 (Scopus)


BACKGROUND. Current clinical biomarkers for the programmed cell death 1 (PD-1) blockade therapy are insufficient because they rely only on the tumor properties, such as programmed cell death ligand 1 expression frequency and tumor mutation burden. Identifying reliable, responsive biomarkers based on the host immunity is necessary to improve the predictive values. METHODS. We investigated levels of plasma metabolites and T cell properties, including energy metabolism markers, in the blood of patients with non-small cell lung cancer before and after treatment with nivolumab (n = 55). Predictive values of combination markers statistically selected were evaluated by cross-validation and linear discriminant analysis on discovery and validation cohorts, respectively. Correlation between plasma metabolites and T cell markers was investigated. RESULTS. The 4 metabolites derived from the microbiome (hippuric acid), fatty acid oxidation (butyrylcarnitine), and redox (cystine and glutathione disulfide) provided high response probability (AUC = 0.91). Similarly, a combination of 4 T cell markers, those related to mitochondrial activation (PPARγ coactivator 1 expression and ROS), and the frequencies of CD8+PD-1hi and CD4+ T cells demonstrated even higher prediction value (AUC = 0.96). Among the pool of selected markers, the 4 T cell markers were exclusively selected as the highest predictive combination, probably because of their linkage to the abovementioned metabolite markers. In a prospective validation set (n = 24), these 4 cellular markers showed a high accuracy rate for clinical responses of patients (AUC = 0.92). CONCLUSION. Combination of biomarkers reflecting host immune activity is quite valuable for responder prediction.

ジャーナルJCI Insight
出版ステータス出版済み - 1月 30 2020

All Science Journal Classification (ASJC) codes

  • 医学(全般)


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