Comprehensive immune cell analysis from lung cancer patients with PD-1 inhibitor neoadjuvant immunotherapy using single cell sequencing.

Abstract

e21001 Background: Single-cell RNA sequencing (scRNA-seq) is a powerful tool to investigate the tumor microenvironment including infiltration of different types of immune cells. However, there is limited study utilizing scRNA-seq technology to investigate patient response to immunotherapy using a comprehensive set of samples. In this study, we used scRNA-seq approach to study tumor infiltrating immune cells in lung cancer patients receiving PD-1 inhibitor neoadjuvant immunotherapy. Methods: CD45 cells were collected from the tumor tissues, the adjacent normal tissues, peripheral blood, lymph nodes, and normal lung tissues for three lung cancer patients receiving PD-1 inhibitor neoadjuvant immunotherapy and four treatment naive lung cancer patients, followed by single cell library construction using 10x Genomics technology and sequenced on Illumina HiSeq X-Ten platform. CellRanger was used to generate expression matrices, and Seurat was used to identify cell subpopulations. Results: From a total of 62,970 single cells, we identified 23 clusters that belonged to different types of immune cells including myeloid cells, T cells, NK cells, mast cells, and B cells. Compared with the adjacent normal tissues, the tumor tissues had lower proportion of NK cells and higher percentage of B cells in all but one patient, and higher percentage of Treg cells for all the seven patients. We observed that patients treated with neoadjuvant immunotherapy had higher proportion of tumor-infiltrating T cells and lower percentage of myeloid cells compared with the treatment naive patients. Patients in the two groups showed differential gene expression in categories including leukocyte cell-cell adhesion, and cell-cycle arrest. Furthermore, the three patients undergoing immunotherapy had different response; the gene expression pattern for the patients differed in functional groups including regulation of inflammatory response, leukocyte migration, and regulation of immune effector process. These results support the potential application for scRNA-Seq in monitoring patient response to neoadjuvant immunotherapy. Conclusions: scRNA-Seq technology can detect the composition of tumor-infiltrating immune cells after neoadjuvant immunotherapy, which provides new tool for predicting the efficacy of treatment. We will next focus on the gene expression of tumor-infiltrating Treg cells and its effect on the therapeutic response.