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High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis

Author

Listed:
  • Amanda Janesick

    (10x Genomics Inc.)

  • Robert Shelansky

    (10x Genomics Inc.)

  • Andrew D. Gottscho

    (10x Genomics Inc.)

  • Florian Wagner

    (10x Genomics Inc.)

  • Stephen R. Williams

    (10x Genomics Inc.)

  • Morgane Rouault

    (10x Genomics Inc.)

  • Ghezal Beliakoff

    (10x Genomics Inc.)

  • Carolyn A. Morrison

    (10x Genomics Inc.)

  • Michelli F. Oliveira

    (10x Genomics Inc.)

  • Jordan T. Sicherman

    (10x Genomics Inc.)

  • Andrew Kohlway

    (10x Genomics Inc.)

  • Jawad Abousoud

    (10x Genomics Inc.)

  • Tingsheng Yu Drennon

    (10x Genomics Inc.)

  • Seayar H. Mohabbat

    (10x Genomics Inc.)

  • Sarah E. B. Taylor

    (10x Genomics Inc.)

Abstract

Single-cell and spatial technologies that profile gene expression across a whole tissue are revolutionizing the resolution of molecular states in clinical samples. Current commercially available technologies provide whole transcriptome single-cell, whole transcriptome spatial, or targeted in situ gene expression analysis. Here, we combine these technologies to explore tissue heterogeneity in large, FFPE human breast cancer sections. This integrative approach allowed us to explore molecular differences that exist between distinct tumor regions and to identify biomarkers involved in the progression towards invasive carcinoma. Further, we study cell neighborhoods and identify rare boundary cells that sit at the critical myoepithelial border confining the spread of malignant cells. Here, we demonstrate that each technology alone provides information about molecular signatures relevant to understanding cancer heterogeneity; however, it is the integration of these technologies that leads to deeper insights, ushering in discoveries that will progress oncology research and the development of diagnostics and therapeutics.

Suggested Citation

  • Amanda Janesick & Robert Shelansky & Andrew D. Gottscho & Florian Wagner & Stephen R. Williams & Morgane Rouault & Ghezal Beliakoff & Carolyn A. Morrison & Michelli F. Oliveira & Jordan T. Sicherman &, 2023. "High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43458-x
    DOI: 10.1038/s41467-023-43458-x
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    References listed on IDEAS

    as
    1. Clare A. Rebbeck & Jian Xian & Susanne Bornelöv & Joseph Geradts & Amy Hobeika & Heather Geiger & Jose Franco Alvarez & Elena Rozhkova & Ashley Nicholls & Nicolas Robine & Herbert K. Lyerly & Gregory , 2022. "Gene expression signatures of individual ductal carcinoma in situ lesions identify processes and biomarkers associated with progression towards invasive ductal carcinoma," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
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    Cited by:

    1. Jingyang Qian & Hudong Bao & Xin Shao & Yin Fang & Jie Liao & Zhuo Chen & Chengyu Li & Wenbo Guo & Yining Hu & Anyao Li & Yue Yao & Xiaohui Fan & Yiyu Cheng, 2024. "Simulating multiple variability in spatially resolved transcriptomics with scCube," Nature Communications, Nature, vol. 15(1), pages 1-21, December.
    2. Leonardo D. Garma & Lisbeth Harder & Juan M. Barba-Reyes & Sergio Marco Salas & Mónica Díez-Salguero & Mats Nilsson & Alberto Serrano-Pozo & Bradley T. Hyman & Ana B. Muñoz-Manchado, 2024. "Interneuron diversity in the human dorsal striatum," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    3. Bohan Li & Feng Bao & Yimin Hou & Fengji Li & Hongjue Li & Yue Deng & Qionghai Dai, 2024. "Tissue characterization at an enhanced resolution across spatial omics platforms with deep generative model," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    4. Haoyang Li & Yingxin Lin & Wenjia He & Wenkai Han & Xiaopeng Xu & Chencheng Xu & Elva Gao & Hongyu Zhao & Xin Gao, 2024. "SANTO: a coarse-to-fine alignment and stitching method for spatial omics," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    5. Arezou Rahimi & Luis A. Vale-Silva & Maria Fälth Savitski & Jovan Tanevski & Julio Saez-Rodriguez, 2024. "DOT: a flexible multi-objective optimization framework for transferring features across single-cell and spatial omics," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    6. A. S. Eisele & M. Tarbier & A. A. Dormann & V. Pelechano & D. M. Suter, 2024. "Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    7. Xiaohang Fu & Yingxin Lin & David M. Lin & Daniel Mechtersheimer & Chuhan Wang & Farhan Ameen & Shila Ghazanfar & Ellis Patrick & Jinman Kim & Jean Y. H. Yang, 2024. "BIDCell: Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data," Nature Communications, Nature, vol. 15(1), pages 1-17, December.

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