Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface

被引:0
|
作者
Miranda V. Hunter
Reuben Moncada
Joshua M. Weiss
Itai Yanai
Richard M. White
机构
[1] Memorial Sloan Kettering Cancer Center,Cancer Biology and Genetics
[2] NYU Langone Health,Institute for Computational Medicine
[3] Memorial Sloan Kettering Cancer Center,Weill Cornell/Rockefeller/Sloan Kettering Tri
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
During tumor progression, cancer cells come into contact with various non-tumor cell types, but it is unclear how tumors adapt to these new environments. Here, we integrate spatially resolved transcriptomics, single-cell RNA-seq, and single-nucleus RNA-seq to characterize tumor-microenvironment interactions at the tumor boundary. Using a zebrafish model of melanoma, we identify a distinct “interface” cell state where the tumor contacts neighboring tissues. This interface is composed of specialized tumor and microenvironment cells that upregulate a common set of cilia genes, and cilia proteins are enriched only where the tumor contacts the microenvironment. Cilia gene expression is regulated by ETS-family transcription factors, which normally act to suppress cilia genes outside of the interface. A cilia-enriched interface is conserved in human patient samples, suggesting it is a conserved feature of human melanoma. Our results demonstrate the power of spatially resolved transcriptomics in uncovering mechanisms that allow tumors to adapt to new environments.
引用
收藏
相关论文
共 50 条
  • [1] Spatially resolved transcriptomics reveals the architecture of the tumor-microenvironment interface
    Hunter, Miranda V.
    Moncada, Reuben
    Weiss, Joshua M.
    Yanai, Itai
    White, Richard M.
    NATURE COMMUNICATIONS, 2021, 12 (01)
  • [2] Spatial transcriptomics reveals mechanically-regulated cell state transitions at the tumor-microenvironment interface
    Hunter, M. V.
    Moncada, R.
    Yanai, I.
    White, R. M.
    MOLECULAR BIOLOGY OF THE CELL, 2023, 34 (02) : 440 - 441
  • [3] Dissecting tumor microenvironment from spatially resolved transcriptomics data by heterogeneous graph learning
    Zuo, Chunman
    Xia, Junjie
    Chen, Luonan
    NATURE COMMUNICATIONS, 2024, 15 (01)
  • [4] Technique integration of single-cell RNA sequencing with spatially resolved transcriptomics in the tumor microenvironment
    Yan, Hailan
    Shi, Jinghua
    Dai, Yi
    Li, Xiaoyan
    Wu, Yushi
    Zhang, Jing
    Gu, Zhiyue
    Zhang, Chenyu
    Leng, Jinhua
    CANCER CELL INTERNATIONAL, 2022, 22 (01)
  • [5] Technique integration of single-cell RNA sequencing with spatially resolved transcriptomics in the tumor microenvironment
    Hailan Yan
    Jinghua Shi
    Yi Dai
    Xiaoyan Li
    Yushi Wu
    Jing Zhang
    Zhiyue Gu
    Chenyu Zhang
    Jinhua Leng
    Cancer Cell International, 22
  • [6] Spatially resolved transcriptomics reveals plant host responses to pathogens
    Michael Giolai
    Walter Verweij
    Ashleigh Lister
    Darren Heavens
    Iain Macaulay
    Matthew D. Clark
    Plant Methods, 15
  • [7] Spatially resolved transcriptomics reveals plant host responses to pathogens
    Giolai, Michael
    Verweij, Walter
    Lister, Ashleigh
    Heavens, Darren
    Macaulay, Iain
    Clark, Matthew D.
    PLANT METHODS, 2019, 15 (01)
  • [8] Spatially resolved transcriptomics reveals gene expression characteristics in uveal melanoma
    Jing-Ying Xiu
    Yu-Ning Chen
    Ya-Li Mao
    Jing-Ting Luo
    Hao-Wen Li
    Yang Li
    Wen-Bin Wei
    Holistic Integrative Oncology, 4 (1):
  • [9] Computational modeling for deciphering tissue microenvironment heterogeneity from spatially resolved transcriptomics
    Zhang, Chuanchao
    Wang, Lequn
    Shi, Qianqian
    COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 2024, 23 : 2109 - 2115
  • [10] Spatially resolved transcriptomics and beyond
    Nicola Crosetto
    Magda Bienko
    Alexander van Oudenaarden
    Nature Reviews Genetics, 2015, 16 : 57 - 66