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
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
View: Text | PDF
Clinical Research and Public Health Immunology Oncology

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

Abstract

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.FUNDING AMED under grant numbers 18cm0106302h0003, 18gm0710012h0105, and 18lk1403006h0002; the Tang Prize Foundation; and JSPS KAKENHI grant numbers JP16H06149, 17K19593, and 19K17673.

Authors

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

×

Figure 6

Modest correlation between particular cellular and metabolite markers excludes metabolite makers from the combinatorial candidate biomarker.

Options: View larger image (or click on image) Download as PowerPoint
Modest correlation between particular cellular and metabolite markers ex...
(A) Scatter plots between cellular markers (x axis) and metabolite markers (y axis). The dots represent the responders and the circles indicate the nonresponders. r, Spearman’s correlation coefficients. Generally, |r| of more than 0.4 in Spearman’s is considered to have a modest to strong correlation. (B) A clustered heatmap of absolute correlation coefficients over all marker pairs detected in A (using Spearman’s correlation distance and complete linkage). Dark denotes higher correlation (|r| close to 1) and light lower correlation (|r| close to 0). The markers clustered into 3 groups, which were designated as metabolic categories I, II, and III.