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Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells
Published on: February 8, 2018
Profiling Tumor Immune Microenvironment of Non-Small Cell Lung Cancer Using Multiplex Immunofluorescence
Haoxin Peng1,2, Xiangrong Wu1,2, Ran Zhong1,2
1Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Abstract:
This study attempted to profile the tumor immune microenvironment (TIME) of non-small cell lung cancer (NSCLC) by multiplex immunofluorescence of 681 NSCLC cases. The number, density, and proportion of 26 types of immune cells in tumor nest and tumor stroma were evaluated, revealing some close interactions particularly between intrastromal neutrophils and intratumoral regulatory T cells (Treg) (r2 = 0.439, P < 0.001), intrastromal CD4+CD38+ T cells and CD20-positive B cells (r2 = 0.539, P < 0.001), and intratumoral CD8-positive T cells and M2 macrophages expressing PD-L1 (r2 = 0.339, P < 0.001). Three immune subtypes correlated with distinct immune characteristics were identified using the unsupervised consensus clustering approach. The immune-activated subtype had the longest disease-free survival (DFS) and demonstrated the highest infiltration of CD4-positive T cells, CD8-positive T cells, and CD20-positive B cells. The immune-defected subtype was rich in cancer stem cells and macrophages, and these patients had the worst prognosis. The immune-exempted subtype had the highest levels of neutrophils and Tregs. Intratumoral CD68-positive macrophages, M1 macrophages, and intrastromal CD4+ cells, CD4+FOXP3- cells, CD8+ cells, and PD-L1+ cells were further found to be the most robust prognostic biomarkers for DFS, which were used to construct and validate the immune-related risk score for risk stratification (high vs. median vs. low) and the prediction of 5-year DFS rates (23.2% vs. 37.9% vs. 43.1%, P < 0.001). In conclusion, the intricate and intrinsic structure of TIME in NSCLC was demonstrated, showing potency in subtyping and prognostication.
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