Profiling tumor immune microenvironment of non-small cell lung cancer using multiplex immunofluorescence

Abstract

PurposeWe attempt to profile the tumor immune microenvironment (TIME) of non-small cell lung cancer (NSCLC) by multiplex immunofluorescence (MIF). Experimental DesignMIF test was performed on 681 NSCLC cases in our center between 2009 and 2011. The number, density, proportion and correlation of 26 types of immune cells in tumor nest and tumor stroma were evaluated. An unsupervised consensus clustering approach was utilized to identify robust clusters of patients. Immune-related risk score (IRRS) was constructed for prognosis prediction for disease-free survival (DFS). ResultsThe landscape of TIME was illustrated, 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 intrastromal CD20-positive B cells (r2 = 0.539, P < 0.001), and intratumoral CD8-positive T cells and intratumoral M2 macrophages expressing PD-L1 (r2 = 0.339, P < 0.001). Three immune subtypes correlated with distinct immune characteristics and clinical outcomes were identified. The immune-activated subtype had the longest DFS and demonstrated the highest infiltration of CD4-positive T cells and CD20-positive B cells. The immune-defected subtype had the highest levels of cancer stem cells and macrophages. The immune-exempted subtype had the highest levels of neutrophils and Treg. The IRRS based on six robust prognostic biomarkers showed potential ability for risk stratification (high vs. median vs. low) and prediction of five-year DFS rates (43.1% vs. 37.9% vs. 23.2%, P<0.001). ConclusionsOur study profiled the intricate and intrinsic structure of TIME in NSCLC, which showed potency in subtyping and prognostication. Translational RelevanceSignificant unmet need exists in understanding the tumor immune microenvironment (TIME) of non-small cell lung cancer (NSCLC) and its correlation with prognosis. In this retrospective cohort study (n = 681), we profiled the immune landscape of NSCLC in situ and identified a novel stratification of TIME by three immune subtypes: immune-activated, immune-exempted, and immune-defected using multiplex immunofluorescence for testing 26 kinds of immune cells. Each of the immune subtypes was correlated with distinct composition, spatial distribution, and functional orientation of immune cells, and accordingly indicating significantly different disease-free survival (DFS). Close interactions were observed for several kinds of immune cells, including neutrophils and regulatory T cells, CD4+CD38+ T cells and CD20-positive B cells, and CD8-positive T cells and M2 macrophages. We also developed the immune-related risk score (IRRS) with different immune characteristics based on six robust immune biomarkers in TIME and evaluated its role in risk stratification and prognosis prediction of DFS. This study might bring potential clinical implementations for the design of novel immunotherapies and the optimization of combined strategies.