Cellular dynamics in tumour microenvironment along with lung cancer progression underscore spatial and evolutionary heterogeneity of neutrophil

Author:

Peng Haoxin123,Wu Xiangrong124,Liu Shaopeng56,He Miao12,Tang Chenshuo5,Wen Yaokai78,Xie Chao5,Zhong Ran1,Li Caichen1ORCID,Xiong Shan1,Liu Jun1,Zheng Hongbo9,He Jianxing1ORCID,Lu Xu56,Liang Wenhua110ORCID

Affiliation:

1. Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease the First Affiliated Hospital of Guangzhou Medical University Guangzhou China

2. Deparment of Clinical Medicine Nanshan School Guangzhou Medical University Guangzhou China

3. Department of Oncology Peking University Cancer Hospital & Institute Peking University Health Science Center, Peking University Beijing China

4. Department of Oncology Shanghai Medical College, Fudan University Shanghai China

5. Department of Computer Science Guangdong Polytechnic Normal University Guangzhou China

6. Department of Artificial Intelligence Research Pazhou Lab Guangzhou China

7. Deparment of Clinical Medicine Tongji University Shanghai China

8. Department of Medical Oncology Shanghai Pulmonary Hospital & Thoracic Cancer Institute, Tongji University, School of Medicine Shanghai China

9. Medical Department Genecast Biotechnology Co., Ltd Beijing China

10. Department of Medical Oncology The First People's Hospital of Zhaoqing Zhaoqing China

Abstract

AbstractBackgroundThe cellular dynamics in the tumour microenvironment (TME) along with non‐small cell lung cancer (NSCLC) progression remain unclear.MethodsMultiplex immunofluorescence test detecting 10 immune‐related markers on 553 primary tumour (PT) samples of NSCLC was conducted and spatial information in TME was assessed by the StarDist depth learning model. The single‐cell transcriptomic atlas of PT (n = 4) and paired tumour‐draining lymph nodes (TDLNs) (n = 5 for tumour‐invaded, n = 3 for tumour‐free) microenvironment was profiled. Various bioinformatics analyses based on Gene Expression Omnibus, TCGA and Array‐Express databases were also used to validate the discoveries.ResultsSpatial distances of CD4+ T cells–CD38+ T cells, CD4+ T cells–neutrophils and CD38+ T cells–neutrophils prolonged and they were replaced by CD163+ macrophages in PT along with tumour progression. Neutrophils showed unique stage and location‐dependent prognostic effects. A high abundance of stromal neutrophils improved disease‐free survival in the early‐stage, whereas high intratumoural neutrophil infiltrates predicted poor prognosis in the mid‐to‐late‐stage. Significant molecular and functional reprogramming in PT and TDLN microenvironments was observed. Diverse interaction networks mediated by neutrophils were found between positive and negative TDLNs. Five phenotypically and functionally heterogeneous subtypes of tumour‐associated neutrophil (TAN) were further identified by pseudotime analysis, including TAN‐0 with antigen‐presenting function, TAN‐1 with strong expression of interferon (IFN)‐stimulated genes, the pro‐tumour TAN‐2 subcluster, the classical subset (TAN‐3) and the pro‐inflammatory subtype (TAN‐4). Loss of IFN‐stimulated signature and growing angiogenesis activity were discovered along the transitional trajectory. Eventually, a robust six neutrophil differentiation relevant genes‐based model was established, showing that low‐risk patients had longer overall survival time and may respond better to immunotherapy.ConclusionsThe cellular composition, spatial location, molecular and functional changes in PT and TDLN microenvironments along with NSCLC progression were deciphered, highlighting the immunoregulatory roles and evolutionary heterogeneity of TANs.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Molecular Medicine,Medicine (miscellaneous)

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