Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes
eLife. 2018;7. DOI 10.7554/eLife.31657. PMID 29993362. PMCID PMC6075866.
How to cite
AMA
Lin JR, Izar B, Wang S, Yapp C, Mei S, Shah PM, et al. Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes. eLife. 2018;7. doi:10.7554/eLife.31657APA
Lin, J. R., Izar, B., Wang, S., Yapp, C., Mei, S., Shah, P. M., et al. (2018). Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes. eLife, 7. https://doi.org/10.7554/eLife.31657BibTeX
@article{lin2018highly,
title = {Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes},
author = {Lin, J. R. and Izar, B. and Wang, S. and Yapp, C. and Mei, S. and Shah, P. M. and Santagata, S. and Sorger, P. K.},
journal = {eLife},
volume = {7},
year = {2018},
doi = {10.7554/eLife.31657},
pmid = {29993362}
}Standard tumor pathology leans on H&E staining and single-marker immunohistochemistry, so most FFPE slides carry only a handful of measurements per cell. Single-cell sequencing adds molecular depth but has to dissociate the tissue, which erases where each cell sat.
This paper introduces tissue-based cyclic immunofluorescence (t-CyCIF), a method that builds up to 60-plex images of a single FFPE section through repeated rounds of four-channel staining, imaging and fluorophore inactivation on conventional slide scanners, including a RareCyte CyteFinder. The authors used it to image whole tumor sections at single-cell resolution across melanoma, pancreatic, renal and other cancers, keeping every cell in its spatial setting while reading dozens of proteins at once.
Key findings
- t-CyCIF reaches up to 60-plex on a single FFPE section. The method builds up to 60-plex images through successive rounds of four-channel staining, imaging and fluorophore inactivation, all on conventional slide scanners rather than specialized imaging hardware.
- A whole metastatic melanoma was imaged as 165 stitched CyteFinder fields. The authors captured a ~10 × 11 mm melanoma on a RareCyte CyteFinder and assembled 165 individual image tiles into one registered whole-slide image with the ASHLAR algorithm.
- A single run resolved hundreds of thousands of individual cells, each with a 25-protein readout. Eight-cycle t-CyCIF of a 2 × 1.5 cm pancreatic ductal adenocarcinoma resection yielded ~2 × 10⁵ single cells, each associated with a vector of 25 whole-cell fluorescence intensities.
CyteFinder in the methods
“Stained slides from each round of CyCIF were imaged with a CyteFinder slide scanning fluorescence microscope (RareCyte Inc. Seattle WA) using either a 10X (NA = 0.3) or 40X long-working distance objective (NA = 0.6). Imager5 software (RareCyte Inc.) was used to sequentially scan the region of interest in four fluorescence channels.”
— Lin et al., eLife (2018), Materials and methods, “Image acquisition”
Disclosure: RareCyte is named in the competing-interests statement of the publication cited above.
Why it matters for CyteFinder users
If your work needs many markers read across a whole tumor section rather than a single small field, this paper shows what a RareCyte CyteFinder slide-scanning fluorescence microscope can carry. The authors built t-CyCIF, a cyclic method, directly on the CyteFinder: each round stains, images four channels, and inactivates the fluorophores, and the rounds stack into images of up to 60 markers on one FFPE slide. Because the CyteFinder scans large areas at roughly one-micron resolution, they could assemble a centimeter-scale melanoma from 165 fields and quantify hundreds of thousands of cells in a single pancreatic resection, each with a full protein signature. For your own studies, that means you can keep every cell in its spatial context while building marker depth over successive cycles, instead of trading plex against field of view. When your question is how cell types and states are arranged across an intact tissue, this is the kind of whole-slide, single-cell dataset the CyteFinder is built to generate.
