Resolving the heterogeneous tumour microenvironment in cardiac myxoma through single-cell and spatial transcriptomics

被引:3
|
作者
Liu, Xuanyu [1 ,2 ]
Shen, Huayan [1 ,2 ]
Yu, Jinxing [1 ,2 ]
Luo, Fengming [1 ,2 ]
Li, Tianjiao [1 ,2 ]
Li, Qi [1 ,3 ]
Yuan, Xin [1 ,3 ]
Sun, Yang [1 ,2 ,3 ,4 ,5 ]
Zhou, Zhou [1 ,2 ,5 ]
机构
[1] Chinese Acad Med Sci & Peking Union Med Coll, Natl Ctr Cardiovasc Dis, Fuwai Hosp, State Key Lab Cardiovasc Dis, Beijing, Peoples R China
[2] Fuwai Hosp, Ctr Lab Med, Beijing Key Lab Mol Diagnost Cardiovasc Dis, Beijing, Peoples R China
[3] Fuwai Hosp, Dept Cardiovasc Surg, Beijing, Peoples R China
[4] Fuwai Hosp, Dept Pathol, Beijing, Peoples R China
[5] Chinese Acad Med Sci, Fuwai Hosp, Ctr Lab Med, Beijing, Peoples R China
来源
CLINICAL AND TRANSLATIONAL MEDICINE | 2024年 / 14卷 / 02期
关键词
cardiac myxoma; myxoma tumour cell; single-cell RNA sequencing; spatial transcriptomics; tumour microenvironment; MARKERS;
D O I
10.1002/ctm2.1581
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Cardiac myxoma (CM) is the most common (58%-80%) type of primary cardiac tumours. Currently, there is a need to develop medical therapies, especially for patients not physically suitable for surgeries. However, the mechanisms that shape the tumour microenvironment (TME) in CM remain largely unknown, which impedes the development of targeted therapies. Here, we aimed to dissect the TME in CM at single-cell and spatial resolution. Methods: We performed single-cell transcriptomic sequencing and Visium CytAssist spatial transcriptomic (ST) assays on tumour samples from patients with CM. A comprehensive analysis was performed, including unsupervised clustering, RNA velocity, clonal substructure inference of tumour cells and cell-cell communication. Results: Unsupervised clustering of 34 759 cells identified 12 clusters, which were assigned to endothelial cells (ECs), mesenchymal stroma cells (MSCs), and tumour-infiltrating immune cells. Myxoma tumour cells were found to encompass two closely related phenotypic states, namely, EC-like tumour cells (ETCs) and MSC-like tumour cells (MTCs). According to RNA velocity, our findings suggest that ETCs may be directly differentiated from MTCs. The immune microenvironment of CM was found to contain multiple factors that promote immune suppression and evasion, underscoring the potential of using immunotherapies as a treatment option. Hyperactive signals sent primarily by tumour cells were identified, such as MDK, HGF, chemerin, and GDF15 signalling. Finally, the ST assay uncovered spatial features of the subclusters, proximal cell-cell communication, and clonal evolution of myxoma tumour cells. Conclusions: Our study presents the first comprehensive characterisation of the TME in CM at both single-cell and spatial resolution. Our study provides novel insight into the differentiation of myxoma tumour cells and advance our understanding of the TME in CM. Given the rarity of cardiac tumours, our study provides invaluable datasets and promotes the development of medical therapies for CM.
引用
收藏
页数:20
相关论文
共 50 条
  • [41] Elucidating cardiomyocyte heterogeneity and maturation dynamics through integrated single-cell and spatial transcriptomics
    Wang, Xiaoying
    Cao, Lizhi
    Chang, Rui
    Shen, Junwei
    Ma, Linlin
    Li, Yanfei
    ISCIENCE, 2025, 28 (01)
  • [42] Dissecting the cellular landscape of hidradenitis suppurativa through single-cell sequencing and spatial transcriptomics
    Du-Harpur, Xinyi
    Harun, Clarisse Ganier Nasrat
    Rashidghamat, Ellie
    Luscombe, Nicholas M.
    Watt, Fiona M.
    Lynch, Magnus D.
    BRITISH JOURNAL OF DERMATOLOGY, 2022, 187 : 49 - 49
  • [43] Single-cell transcriptomics reveals an abnormal immune microenvironment in plasma cell mastitis
    Ni, Qingtao
    Han, Gaohua
    Pan, Chi
    ANNALS OF MEDICINE, 2025, 57 (01)
  • [44] Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics
    Frédéric Pont
    Juan Pablo Cerapio
    Pauline Gravelle
    Laetitia Ligat
    Carine Valle
    Emeline Sarot
    Marion Perrier
    Frédéric Lopez
    Camille Laurent
    Jean Jacques Fournié
    Marie Tosolini
    BMC Bioinformatics, 24
  • [45] Single-cell spatial explorer: easy exploration of spatial and multimodal transcriptomics
    Pont, Frederic
    Cerapio, Juan Pablo
    Gravelle, Pauline
    Ligat, Laetitia
    Valle, Carine
    Sarot, Emeline
    Perrier, Marion
    Lopez, Frederic
    Laurent, Camille
    Fournie, Jean Jacques
    Tosolini, Marie
    BMC BIOINFORMATICS, 2023, 24 (01)
  • [46] Recent advances in high-throughput single-cell transcriptomics and spatial transcriptomics
    Shen, Xiaohan
    Zhao, Yichun
    Wang, Zhuo
    Shi, Qihui
    LAB ON A CHIP, 2022, 22 (24) : 4774 - 4791
  • [47] Characterizing the tumor microenvironment of metastatic ovarian cancer by single-cell transcriptomics
    Olalekan, Susan
    Xie, Bingqing
    Back, Rebecca
    Eckart, Heather
    Basu, Anindita
    CELL REPORTS, 2021, 35 (08):
  • [48] Cardiac cellular diversity and functionality in cardiac repair by single-cell transcriptomics
    Chen, Wei
    Li, Chuling
    Chen, Yijin
    Bin, Jianping
    Chen, Yanmei
    FRONTIERS IN CARDIOVASCULAR MEDICINE, 2023, 10
  • [49] Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics
    Gulati, Gunsagar S.
    D'Silva, Jeremy Philip
    Liu, Yunhe
    Wang, Linghua
    Newman, Aaron M.
    NATURE REVIEWS MOLECULAR CELL BIOLOGY, 2025, 26 (01) : 11 - 31
  • [50] Tumour heterogeneity and personalized treatment screening based on single-cell transcriptomics
    Zhang, Xinying
    Xie, Jiajie
    Yang, Zixin
    Yu, Carisa Kwok Wai
    Hu, Yaohua
    Qin, Jing
    COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 2025, 27 : 307 - 320