Profiling Tumor Immune Microenvironment of Non-Small Cell Lung Cancer Using Multiplex Immunofluorescence

Author:

Peng Haoxin,Wu Xiangrong,Zhong Ran,Yu Tao,Cai Xiuyu,Liu Jun,Wen Yaokai,Ao Yiyuan,Chen Jiana,Li Yutian,He Miao,Li Caichen,Zheng Hongbo,Chen Yanhui,Pan Zhenkui,He Jianxing,Liang Wenhua

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.

Publisher

Frontiers Media SA

Subject

Immunology,Immunology and Allergy

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

全球学者库

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"全球学者库"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前全球学者库共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-88110370

www.globalauthorid.com

TOP

Copyright © 2019-2021 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3