Resolving the spatial distribution of RNA and protein in tissues at subcellular resolution is a challenge in the field of spatial biology. We describe spatial molecular imaging, a system that measures RNAs and proteins in intact biological samples at subcellular resolution by performing multiple cycles of nucleic acid hybridization of fluorescent molecular barcodes. We demonstrate that spatial molecular imaging has high sensitivity (one or two copies per cell) and very low error rate (0.0092 false calls per cell) and background (~0.04 counts per cell). The imaging system generates three-dimensional, super-resolution localization of analytes at ~2 million cells per sample. Cell segmentation is morphology based using antibodies, compatible with formalin-fixed, paraffin-embedded samples. We measured multiomic data (980 RNAs and 108 proteins) at subcellular resolution in formalin-fixed, paraffin-embedded tissues (nonsmall cell lung and breast cancer) and identified >18 distinct cell types, ten unique tumor microenvironments and 100 pairwise ligand–receptor interactions. Data on >800,000 single cells and ~260 million transcripts can be accessed at http://nanostring.com/CosMx-dataset.
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Genome Biology Open Access 13 December 2022
Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding
Nature Communications Open Access 10 December 2022
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The full RNA NSCLC dataset used in this study is available at http://nanostring.com/CosMx-dataset.
Data from this publication (the full RNA NSCLC dataset) has been placed in the public domain in a format that can be analyzed and visualized using a variety of open-source packages, such as Seurat (https://github.com/satijalab/seurat) and Giotto (https://github.com/RubD/Giotto). Nearly all of the analyses performed in this paper can be accomplished using these open-source packages. For any of the specialized code/analyses performed in this manuscript that are not available through open-source packages, requests can be made through email to the corresponding author.
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Research and development reported in this publication was supported in part through a strategic development collaboration between NanoString Technologies and Lam Research (Fremont, CA). The authors thank B. Birditt, B. Filanoski, J. Jenkins and E. Zhao from NanoString Technologies for provision of technical support.
All authors are employees of NanoString Technologies and hold NanoString stock or stock options. D.K. is an employee of Dxome Co.
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He, S., Bhatt, R., Brown, C. et al. High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging. Nat Biotechnol 40, 1794–1806 (2022). https://doi.org/10.1038/s41587-022-01483-z
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