IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v578y2020i7796d10.1038_s41586-019-1876-x.html
   My bibliography  Save this article

The single-cell pathology landscape of breast cancer

Author

Listed:
  • Hartland W. Jackson

    (University of Zurich
    University of Zurich)

  • Jana R. Fischer

    (University of Zurich
    University of Zurich
    ETH Zurich and University of Zurich)

  • Vito R. T. Zanotelli

    (University of Zurich
    University of Zurich
    ETH Zurich and University of Zurich)

  • H. Raza Ali

    (University of Zurich
    University of Zurich
    University of Cambridge)

  • Robert Mechera

    (University of Basel and University Hospital Basel)

  • Savas D. Soysal

    (University of Basel
    Clarunis University Center for Gastrointestinal and Liver Diseases Basel)

  • Holger Moch

    (University Hospital Zurich)

  • Simone Muenst

    (University Hospital Basel)

  • Zsuzsanna Varga

    (University Hospital Zurich)

  • Walter P. Weber

    (University of Basel and University Hospital Basel)

  • Bernd Bodenmiller

    (University of Zurich
    University of Zurich)

Abstract

Single-cell analyses have revealed extensive heterogeneity between and within human tumours1–4, but complex single-cell phenotypes and their spatial context are not at present reflected in the histological stratification that is the foundation of many clinical decisions. Here we use imaging mass cytometry5 to simultaneously quantify 35 biomarkers, resulting in 720 high-dimensional pathology images of tumour tissue from 352 patients with breast cancer, with long-term survival data available for 281 patients. Spatially resolved, single-cell analysis identified the phenotypes of tumour and stromal single cells, their organization and their heterogeneity, and enabled the cellular architecture of breast cancer tissue to be characterized on the basis of cellular composition and tissue organization. Our analysis reveals multicellular features of the tumour microenvironment and novel subgroups of breast cancer that are associated with distinct clinical outcomes. Thus, spatially resolved, single-cell analysis can characterize intratumour phenotypic heterogeneity in a disease-relevant manner, with the potential to inform patient-specific diagnosis.

Suggested Citation

  • Hartland W. Jackson & Jana R. Fischer & Vito R. T. Zanotelli & H. Raza Ali & Robert Mechera & Savas D. Soysal & Holger Moch & Simone Muenst & Zsuzsanna Varga & Walter P. Weber & Bernd Bodenmiller, 2020. "The single-cell pathology landscape of breast cancer," Nature, Nature, vol. 578(7796), pages 615-620, February.
  • Handle: RePEc:nat:nature:v:578:y:2020:i:7796:d:10.1038_s41586-019-1876-x
    DOI: 10.1038/s41586-019-1876-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-019-1876-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41586-019-1876-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alastair Magness & Emma Colliver & Katey S. S. Enfield & Claudia Lee & Masako Shimato & Emer Daly & David A. Moore & Monica Sivakumar & Karishma Valand & Dina Levi & Crispin T. Hiley & Philip S. Hobso, 2024. "Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    2. Darci Phillips & Magdalena Matusiak & Belén Rivero Gutierrez & Salil S. Bhate & Graham L. Barlow & Sizun Jiang & Janos Demeter & Kimberly S. Smythe & Robert H. Pierce & Steven P. Fling & Nirasha Ramch, 2021. "Immune cell topography predicts response to PD-1 blockade in cutaneous T cell lymphoma," Nature Communications, Nature, vol. 12(1), pages 1-18, December.
    3. Hugo Croizer & Rana Mhaidly & Yann Kieffer & Geraldine Gentric & Lounes Djerroudi & Renaud Leclere & Floriane Pelon & Catherine Robley & Mylene Bohec & Arnaud Meng & Didier Meseure & Emanuela Romano &, 2024. "Deciphering the spatial landscape and plasticity of immunosuppressive fibroblasts in breast cancer," Nature Communications, Nature, vol. 15(1), pages 1-28, December.
    4. Stefanie Hiltbrunner & Lena Cords & Sabrina Kasser & Sandra N. Freiberger & Susanne Kreutzer & Nora C. Toussaint & Linda Grob & Isabelle Opitz & Michael Messerli & Martin Zoche & Alex Soltermann & Mar, 2023. "Acquired resistance to anti-PD1 therapy in patients with NSCLC associates with immunosuppressive T cell phenotype," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    5. Nastaran Mohammadi Ghahhari & Magdalena K. Sznurkowska & Nicolas Hulo & Lilia Bernasconi & Nicola Aceto & Didier Picard, 2022. "Cooperative interaction between ERα and the EMT-inducer ZEB1 reprograms breast cancer cells for bone metastasis," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    6. Thomas Hu & Mayar Allam & Shuangyi Cai & Walter Henderson & Brian Yueh & Aybuke Garipcan & Anton V. Ievlev & Maryam Afkarian & Semir Beyaz & Ahmet F. Coskun, 2023. "Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    7. Michael J. Geuenich & Dae-won Gong & Kieran R. Campbell, 2024. "The impacts of active and self-supervised learning on efficient annotation of single-cell expression data," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    8. Anissa El Marrahi & Fabio Lipreri & Ziqi Kang & Louise Gsell & Alper Eroglu & David Alber & Jean Hausser, 2023. "NIPMAP: niche-phenotype mapping of multiplex histology data by community ecology," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    9. Candace C. Liu & Noah F. Greenwald & Alex Kong & Erin F. McCaffrey & Ke Xuan Leow & Dunja Mrdjen & Bryan J. Cannon & Josef Lorenz Rumberger & Sricharan Reddy Varra & Michael Angelo, 2023. "Robust phenotyping of highly multiplexed tissue imaging data using pixel-level clustering," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    10. Michele Bortolomeazzi & Lucia Montorsi & Damjan Temelkovski & Mohamed Reda Keddar & Amelia Acha-Sagredo & Michael J. Pitcher & Gianluca Basso & Luigi Laghi & Manuel Rodriguez-Justo & Jo Spencer & Fran, 2022. "A SIMPLI (Single-cell Identification from MultiPLexed Images) approach for spatially-resolved tissue phenotyping at single-cell resolution," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    11. Juan Du & Junlei Zhang & Lin Wang & Xun Wang & Yaxing Zhao & Jiaoying Lu & Tingmin Fan & Meng Niu & Jie Zhang & Fei Cheng & Jun Li & Qi Zhu & Daoqiang Zhang & Hao Pei & Guang Li & Xingguang Liang & He, 2023. "Selective oxidative protection leads to tissue topological changes orchestrated by macrophage during ulcerative colitis," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    12. Sandra Tietscher & Johanna Wagner & Tobias Anzeneder & Claus Langwieder & Martin Rees & Bettina Sobottka & Natalie Souza & Bernd Bodenmiller, 2023. "A comprehensive single-cell map of T cell exhaustion-associated immune environments in human breast cancer," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    13. Yunhao Bai & Bokai Zhu & John-Paul Oliveria & Bryan J. Cannon & Dorien Feyaerts & Marc Bosse & Kausalia Vijayaragavan & Noah F. Greenwald & Darci Phillips & Christian M. Schürch & Samuel M. Naik & Edw, 2023. "Expanded vacuum-stable gels for multiplexed high-resolution spatial histopathology," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    14. Vincent Geldhof & Laura P. M. H. Rooij & Liliana Sokol & Jacob Amersfoort & Maxim Schepper & Katerina Rohlenova & Griet Hoste & Adriaan Vanderstichele & Anne-Marie Delsupehe & Edoardo Isnaldi & Naima , 2022. "Single cell atlas identifies lipid-processing and immunomodulatory endothelial cells in healthy and malignant breast," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    15. Yael Amitay & Yuval Bussi & Ben Feinstein & Shai Bagon & Idan Milo & Leeat Keren, 2023. "CellSighter: a neural network to classify cells in highly multiplexed images," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    16. Peng Lu & Karolyn A. Oetjen & Diane E. Bender & Marianna B. Ruzinova & Daniel A. C. Fisher & Kevin G. Shim & Russell K. Pachynski & W. Nathaniel Brennen & Stephen T. Oh & Daniel C. Link & Daniel L. J., 2023. "IMC-Denoise: a content aware denoising pipeline to enhance Imaging Mass Cytometry," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    17. Vázquez López, Raul, 2023. "La competitividad de las exportaciones del sector químico mexicano en los Estados Unidos de América y la Unión Europea, 1994-2015," Apuntes del Cenes, Universidad Pedagógica y Tecnológica de Colombia, vol. 42(75), pages 83-109, January.
    18. Junyoung Seo & Yeonbo Sim & Jeewon Kim & Hyunwoo Kim & In Cho & Hoyeon Nam & Young-Gyu Yoon & Jae-Byum Chang, 2022. "PICASSO allows ultra-multiplexed fluorescence imaging of spatially overlapping proteins without reference spectra measurements," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    19. Kaiwen Wang & Yuqiu Yang & Fangjiang Wu & Bing Song & Xinlei Wang & Tao Wang, 2023. "Comparative analysis of dimension reduction methods for cytometry by time-of-flight data," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    20. Zhiyuan Yuan & Yisi Li & Minglei Shi & Fan Yang & Juntao Gao & Jianhua Yao & Michael Q. Zhang, 2022. "SOTIP is a versatile method for microenvironment modeling with spatial omics data," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    21. Rui Chen & Jiasu Xu & Boqian Wang & Yi Ding & Aynur Abdulla & Yiyang Li & Lai Jiang & Xianting Ding, 2024. "SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:578:y:2020:i:7796:d:10.1038_s41586-019-1876-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.