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- Single-cell tumor-immune microenvironment of BRCA1/2 mutated high-grade serous ovarian cancer

# Single-cell tumor-immune microenvironment of BRCA1/2 mutated high-grade serous ovarian cancer

Launonen IM, Lyytikäinen N, Casado J, Anttila EA, Szabó A, Haltia UM, et al.

Nature Communications . 2022;13(1):835. DOI [10.1038/s41467-022-28389-3](https://doi.org/10.1038/s41467-022-28389-3). PMID 35149709. PMCID PMC8837628.

How to cite

### AMA

Launonen IM, Lyytikäinen N, Casado J, Anttila EA, Szabó A, Haltia UM, et al. Single-cell tumor-immune microenvironment of BRCA1/2 mutated high-grade serous ovarian cancer. Nat Commun . 2022;13(1):835. doi:10.1038/s41467-022-28389-3

### APA

Launonen, I. M., Lyytikäinen, N., Casado, J., Anttila, E. A., Szabó, A., Haltia, U. M., et al. (2022). Single-cell tumor-immune microenvironment of BRCA1/2 mutated high-grade serous ovarian cancer. Nature Communications , 13(1), 835. https://doi.org/10.1038/s41467-022-28389-3

### BibTeX

@article{launonen2022singlecell,
title = {Single-cell tumor-immune microenvironment of BRCA1/2 mutated high-grade serous ovarian cancer},
author = {Launonen, I. M. and Lyytikäinen, N. and Casado, J. and Anttila, E. A. and Szabó, A. and Haltia, U. M. and others},
journal = {Nature Communications},
volume = {13},
number = {1},
pages = {835},
year = {2022},
doi = {10.1038/s41467-022-28389-3},
pmid = {35149709}
}

Most high-grade serous ovarian cancers are deficient in homologous-recombination DNA repair, frequently through BRCA1/2 mutations, yet how those mutations reshape the tumor's cellular makeup and the spatial arrangement of immune cells has been hard to read from bulk measurements.

Here the authors ran cyclic high-plex immunofluorescence (tCyCIF) on a RareCyte CyteFinder scanner to measure 21 markers in 124,623 single cells across a 112-core tissue microarray from 44 high-grade serous ovarian cancers. BRCA1/2-mutated tumors carried a distinct, more immunosurveilled microenvironment, and a proliferative tumor-cell subpopulation that engaged CD8+ and CD4+ T-cells tracked with a better platinum-free interval.

[Read publication at Nature Communications](https://pmc.ncbi.nlm.nih.gov/articles/PMC8837628/)

## Key findings

- 21-marker single-cell spatial proteomics across a 112-core tumor microarray. Cyclic immunofluorescence (tCyCIF) on a RareCyte CyteFinder scanner quantified 124,623 single cells from 44 high-grade serous ovarian cancers, 31 BRCA1/2-mutated and 13 without homologous-recombination gene alterations.

- BRCA1/2-mutated tumors showed a distinct, more immunosurveilled microenvironment. Patients with BRCA1/2-mutated tumors had a significantly longer platinum-free interval than homologous-recombination-wildtype patients (p = 0.02; hazard ratio 0.30, 95% CI 0.13 to 0.70).

- A proliferative tumor-cell subpopulation was prognostic in BRCA1/2-mutated disease. Across the 31 BRCA1/2-mutated tumors, enhanced spatial interactions between this subpopulation and CD8+ and CD4+ T-cells associated with a better platinum-free interval.

## CyteFinder in the methods

“The samples were stained sequentially with the validated antibodies (Supplementary Table 1 ) and scanned with RareCyte CyteFinder scanner following the tCycIF protocol 29 . Scanned image files were corrected using the BaSiC tool and stitched and registered using the ASHLAR algorithm ( https://github.com/labsyspharm/ashlar ) to align image tiles and successive images of tiles from all cycles to one another.”

— Launonen et al., Nature Communications (2022), Methods, “Highly multiplexed imaging, and image processing”

Disclosure: RareCyte is named in the competing-interests statement of the publication cited above.

## Why it matters for CyteFinder users

If you are planning high-plex tissue imaging, this study shows what a RareCyte CyteFinder scanner supports in practice. The authors read 21 markers on a single tissue microarray by running cyclic immunofluorescence (tCyCIF), sequential rounds of staining, CyteFinder scanning, and signal removal, then registered every cycle back to one coordinate frame, so each of 124,623 cells carried a full 21-marker profile in its spatial context. That is the CyteFinder's role here, a flexible whole-slide and tissue-microarray scanner that lets you build marker depth over cycles rather than commit to one fixed panel. Because the readout is single-cell and spatially resolved, the team could move past average marker levels to the arrangement of cells, which tumor cells sit near which T-cells, and connect a proliferative, CD8+/CD4+-engaged subpopulation to the platinum-free interval in BRCA1/2-mutated disease. When your question is which cell types are present, where they sit, and whether that geometry forecasts outcome, this is the spatial-proteomic dataset the CyteFinder was built to generate.

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