Decoding meningioma heterogeneity and neoplastic cell—macrophage interaction through single-cell transcriptome profiling across pathological grades

Journal of Translational Medicine

Research

Jian Hu¹  Zhen Wu²  Lairong Song²  Junpeng Ma²  Liang Wang²  Xiaojie Li²  Junting Zhang²  Jian Fan³  Hailang Fan⁴  Dake Zhang⁴ 

[1] Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, 77054-1901, Houston, TX, USA;MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, 77225-0334, Houston, TX, USA;Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China;Department of Urology, Peking University First Hospital, Institute of Urology, National Urological Cancer Center, Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, Peking University, 100871, Beijing, China;Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Engineering Medicine, Beihang University, 100191, Beijing, China;

关键词: Meningiomas;    scRNA-seq;    Heterogeneity;    MIF;    CD74;   

DOI  :  10.1186/s12967-023-04445-4

 received in 2023-05-23, accepted in 2023-08-16,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundAnalyzing meningioma of distinct pathological types at the single-cell level can provide new and valuable insights into the specific biological mechanisms of each cellular subpopulation, as well as their vital interplay within the tumor microenvironment.MethodsWe recruited patients diagnosed with four distinct types of meningioma and performed single-cell RNA sequencing on their tumor samples, concurrently analyzing a publicly available dataset for comparison. Next, we separated the cells into discrete clusters and identified their unique identities. Using pseudotime analysis, we demonstrated cellular differentiation and dynamics. To investigate biological function, we employed weighted gene co-expression network analysis, gene regulatory network, and gene set enrichment analysis. Additionally, we conducted cell–cell communication analyses to characterize interactions among different clusters and validated a crucial interaction using multiple immunofluorescence staining.ResultsThe single-cell transcriptomic profiles for five meningioma of different pathological types demonstrated that neoplastic cells exhibited high inter-sample heterogeneity and diverse biological functions featured by metabolic regulation. A small cluster of neoplastic cells (N5 cluster, < 3%) was most proliferative, indicated by high expression of MKI67 and TOP2A. They were primarily observed in our atypical and transitional meningioma samples and located at the beginning of the pseudotime differentiation branch for neoplastic cells. Macrophages, the most abundant immune cells present, showed two distinct developmental trajectories, one promoting and the other suppressing meningioma growth, with the MIF-CD74 interaction serving as the primary signaling pathway for MIF signals in the tumor environment. Unexpectedly, despite its small cluster size, the N5 cluster demonstrated a significant contribution in this interaction. By staining pathological sections of more samples, we found that this interaction was widely present in different types of meningiomas.ConclusionsMeningioma neoplastic cells' diverse types cause inter-sample heterogeneity and a wide range of functions. Some proliferative neoplastic cell may educate macrophages, which promotes tumorigenesis possibly through the MIF-CD74 interaction. It provides novel clues for future potential therapeutic avenues.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

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