Nanoscale imaging of clinical specimens using pathology-optimized expansion microscopy
Name
nihms872468.pdf
Description
Accepted version
Size
1.33 MB
Format
Adobe PDF
Checksum (MD5)
7c48efbb0d3e83326cd967ee223fdf71
Author(s)
Zhao, Yongxin
Bucur, Octavian
Irshad, Humayun
Chen, Fei
Weins, Astrid
Stancu, Andreea L
Oh, Eun-Young
DiStasio, Marcello
Torous, Vanda
Glass, Benjamin
Date Issued
2017
Journal
Nature Biotechnology
Publisher
Springer Science and Business Media LLC
Version
Author's final manuscript
Abstract
Expansion microscopy (ExM), a method for improving the resolution of light microscopy by physically expanding a specimen, has not been applied to clinical tissue samples. Here we report a clinically optimized form of ExM that supports nanoscale imaging of human tissue specimens that have been fixed with formalin, embedded in paraffin, stained with hematoxylin and eosin, and/or fresh frozen. The method, which we call expansion pathology (ExPath), converts clinical samples into an ExM-compatible state, then applies an ExM protocol with protein anchoring and mechanical homogenization steps optimized for clinical samples. ExPath enables ~70-nm-resolution imaging of diverse biomolecules in intact tissues using conventional diffraction-limited microscopes and standard antibody and fluorescent DNA in situ hybridization reagents. We use ExPath for optical diagnosis of kidney minimal-change disease, a process that previously required electron microscopy, and we demonstrate high-fidelity computational discrimination between early breast neoplastic lesions for which pathologists often disagree in classification. ExPath may enable the routine use of nanoscale imaging in pathology and clinical research.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Massachusetts Institute of Technology. Department of Biological Engineering
McGovern Institute for Brain Research at MIT
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1038/NBT.3892
