TY - JOUR AU - Hatae, Ryusuke AU - Chamoto, Kenji AU - Kim, Young Hak AU - Sonomura, Kazuhiro AU - Taneishi, Kei AU - Kawaguchi, Shuji AU - Yoshida, Hironori AU - Ozasa, Hiroaki AU - Sakamori, Yuichi AU - Akrami, Maryam AU - Fagarasan, Sidonia AU - Masuda, Izuru AU - Okuno, Yasushi AU - Matsuda, Fumihiko AU - Hirai, Toyohiro AU - Honjo, Tasuku T1 - Combination of host immune metabolic biomarkers for the PD-1 blockade cancer immunotherapy PY - 2020/01/30/ AB - 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 (PPARĪ³ 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.FUNDING AMED under grant numbers 18cm0106302h0003, 18gm0710012h0105, and 18lk1403006h0002; the Tang Prize Foundation; and JSPS KAKENHI grant numbers JP16H06149, 17K19593, and 19K17673. JF - JCI Insight JA - JCI Insight SN - 2379-3708 DO - 10.1172/jci.insight.133501 VL - 5 IS - 2 UR - https://doi.org/10.1172/jci.insight.133501 PB - The American Society for Clinical Investigation ER -