Anastasiia Marchuk and Felicitas Mungenast present applications of spatial tissue cytometry
In-depth phenotyping within tissue sections is gaining more importance in research and clinics. It is no longer enough to perform H&E or single-marker staining but to capture and analyse the complexity of multiple cellular sub-populations, including their spatial context in the tissue microenvironment. These evolving needs present many challenges, such as multiplexed imaging due to the high number of stained markers, quantification of multiple markers to determine tissue structures and cellular and molecular phenotypes, as well as high-content data mining.
These and other challenges raise questions about appropriate equipment, which should be both precise enough to generate reliable data and able to process the samples as quickly as possible. This comes together with the emerging crisis of reproducibility in science, which is an obstacle to the correct interpretation of research and thus research in general.[1] For these reasons scientists/clinicians look for solutions that allow for the standardisation of their studies and reducing the prevailing bias. In the case of image processing, slide-based cytometry and computational pathology, this can be achieved by using a more robust and observer independent methodology.
High-End Tissue Cytometry In Cancer Research
The basic process of conducting cellular phenotyping involves the preparation and staining of samples for multiple markers. Classically, flow cytometry is used to gain information on expression patterns and the percentage of cells expressing certain markers, but it does not offer any data on the spatial distribution of cellular subpopulations. Tissue cytometry, however, allows the reaching of several aims: gene and biomarker expression patterns; cell population locations; and spatial interactions and cell dynamics within the native tissue microenvironment. These questions are particularly important in the fields of immunology and oncology.
TissueGnostics’ (TG) tissue cytometry solutions, including the TissueFAXS platform (modular slide imaging solution) and StrataQuest (contextual imaging analysis solution), have been used in hundreds of projects covering cutting-edge topics within cancer research. For example, a recent paper showed that a distinct subpopulation of CD8+ T cells is present at higher levels in colorectal cancer with liver metastases relative to adjacent liver tissue.[2] This subset of CD8+ cells has now been evaluated in detail using the TissueFaxs Chroma imaging platform and StrataQuest image analysis software.
Another application of tissue cytometry in cancer research concerns tumour vasculature, which is crucial for keeping the tumour alive and facilitating its often-extensive growth. (Fig. 1). One relevant aim is to assess the number of tumour and non-tumour nuclei, the number of blood vessels, and to evaluate the distance of tumour cells from blood vessels within the tumour area in combination with the distribution of individual cancer foci in multi-focal tumours. Automated analysis workflows can be established using the IF Tumor Foci Angio App, a separate add-on solution for StrataQuest.
Additionally, TG’s tissue cytometry workflow can be adapted to the scanning/analysis of tissue microarrays. In the example shown in Fig. 2. the samples are stained with multiple markers for immune checkpoint relevant targets. Multispectral imaging combined with spectral unmixing technology, available in TissueFaxs Spectra, is useful to increase the number of markers visualised in the same sample. StrataQuest was further used within the study to decipher the immune microenvironment through the detection of single cells, in-depth phenotyping of the subpopulations, assessment of epithelium and stroma, and spatial analysis of histological entities and corresponding cellular subpopulations.
Streamlined Solutions For Spatial Phenotyping
TG’s products include advanced solutions for contextual tissue cytometry and quantitative/computational pathology. The instruments are available in multiple configurations for brightfield, fluorescence, multispectral and confocal, as well as high-throughput scanning/whole slide imaging. In terms of image analysis, StrataQuest is capable of performing phenotypic and functional characterisation of cellular sub-populations in spatial contexts using antibody labelling, FISH, CISH, RNA-ISH, RNAScope, or any other staining technique. The company’s multiplexing and spectral unmixing solutions allow for the visualisation of multiple markers without channel bleed through, which is important for follow-up precise image analysis.
TG’s tissue cytometry solutions provide data that perfectly matches the current trend of exploring multiple markers within tissue sections on the level of individual cells to better understand interactions as well as spatial relationships among and between different tissue compartments, cell types, and cellular subpopulations.
REFERENCES:
1. Ioannidis JP. Why most published research findings are false. PLoS Med. 2005 Aug;2(8):e124. doi: 10.1371/journal.pmed.0020124. Epub 2005 Aug 30. Erratum in: PLoS Med. 2022 Aug 25;19(8):e1004085. PMID: 16060722; PMCID: PMC1182327.
2. Liang, F.; Nilsson, L.M.; Byvald, F.; Rezapour, A.; Taflin, H.; Nilsson, J.A.; Yrlid, U. A Fraction of CD8+ T Cells from Colorectal Liver Metastases Preferentially Repopulate Autologous Patient-Derived Xenograft Tumors as Tissue-Resident Memory T Cells. Cancers 2022, 14, 2882. https://doi.org/10.3390/cancers14122882
Anastasiia Marchuk and Felicitas Mungenas are with TissueGnostics
