Peripheral blood immune cell dynamics reflect antitumor immune responses and predict clinical response to immunotherapy

免疫检查点 免疫疗法 免疫系统 背景(考古学) 医学 肿瘤微环境 免疫学 癌症免疫疗法 T细胞 无容量 癌症研究 肿瘤科 生物 古生物学
作者
Michael S. Hwang,Jenna VanLiere Canzoniero,Samuel Rosner,Guangfan Zhang,James R. White,Zineb Belcaid,Christopher Cherry,Archana Balan,Gavin Pereira,Alexandria Curry,Noushin Niknafs,Jiajia Zhang,Kellie N. Smith,Lavanya Sivapalan,Jamie E. Chaft,Joshua E. Reuss,Kristen A. Marrone,Joseph C. Murray,Qing Kay Li,Vincent K. Lam
出处
期刊:Journal for ImmunoTherapy of Cancer [BMJ]
卷期号:10 (6): e004688-e004688 被引量:96
标识
DOI:10.1136/jitc-2022-004688
摘要

Background Despite treatment advancements with immunotherapy, our understanding of response relies on tissue-based, static tumor features such as tumor mutation burden (TMB) and programmed death-ligand 1 (PD-L1) expression. These approaches are limited in capturing the plasticity of tumor–immune system interactions under selective pressure of immune checkpoint blockade and predicting therapeutic response and long-term outcomes. Here, we investigate the relationship between serial assessment of peripheral blood cell counts and tumor burden dynamics in the context of an evolving tumor ecosystem during immune checkpoint blockade. Methods Using machine learning, we integrated dynamics in peripheral blood immune cell subsets, including neutrophil-lymphocyte ratio (NLR), from 239 patients with metastatic non-small cell lung cancer (NSCLC) and predicted clinical outcome with immune checkpoint blockade. We then sought to interpret NLR dynamics in the context of transcriptomic and T cell repertoire trajectories for 26 patients with early stage NSCLC who received neoadjuvant immune checkpoint blockade. We further determined the relationship between NLR dynamics, pathologic response and circulating tumor DNA (ctDNA) clearance. Results Integrated dynamics of peripheral blood cell counts, predominantly NLR dynamics and changes in eosinophil levels, predicted clinical outcome, outperforming both TMB and PD-L1 expression. As early changes in NLR were a key predictor of response, we linked NLR dynamics with serial RNA sequencing deconvolution and T cell receptor sequencing to investigate differential tumor microenvironment reshaping during therapy for patients with reduction in peripheral NLR. Reductions in NLR were associated with induction of interferon-γ responses driving the expression of antigen presentation and proinflammatory gene sets coupled with reshaping of the intratumoral T cell repertoire. In addition, NLR dynamics reflected tumor regression assessed by pathological responses and complemented ctDNA kinetics in predicting long-term outcome. Elevated peripheral eosinophil levels during immune checkpoint blockade were correlated with therapeutic response in both metastatic and early stage cohorts. Conclusions Our findings suggest that early dynamics in peripheral blood immune cell subsets reflect changes in the tumor microenvironment and capture antitumor immune responses, ultimately reflecting clinical outcomes with immune checkpoint blockade.
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