Single-cell RNA-sequencing methods have become a mainstay tool for cancer researchers. Techniques like CITE-Seq can analyze the expression patterns of large sets of mRNAs and proteins in hundreds or thousands of cells at a time. However, these techniques are hampered by high running costs and incompatibility with FFPE tissues for full transcriptome analysis. Crucially, these techniques also come at the loss of spatial context, and hence do not characterize the tissue microenvironment.
A TSNE plot created with the Multiplex Analysis Viewer (MAV) Software. Learn more about MAV’s capabilities in this webinar.
On the other end of the spectrum are conventional histopathology techniques, like H&E staining or chromogenic immunohistochemistry. These methods provide excellent spatial resolution but have low dimensionality, meaning that they can only be used to detect the expression of one biomarker at a time.
The CODEX® technology combines the advantages of single-cell biology with histology at single-cell spatial resolution. Capable of imaging 40+ biomarkers on a single tissue, CODEX enables analysis with both high dimensionality and spatial context.
CODEX imaging data are analyzed with the Multiplex Analysis Viewer (MAV) software suite. Cells are identified, segmented based on nuclear staining and each biomarker signal is then quantified on a per-cell basis. Spatial coordinates are preserved, and data are generated in a widely compatible tabular format.
CODEX data are multi-dimensional in that they contain single cell antibody labeling intensities for up to 40 biomarkers, along with spatial coordinates for thousands of cells per dataset. MAV therefore has sophisticated built-in analysis tools that enable researchers to analyze their data sets. For instance, via unbiased K-means clustering, the user can extract complex phenotypic information about each cell in an imaged population.
Phenotypic relationships can then be analyzed with interactive T-SNE plots, which allow the user to toggle back into the original morphological data, and to simultaneously examine spatial context and associations between cells. The combination of phenotypic information and spatial context provided by the MAV software suite is a powerful means for researchers to investigate rare cell types and discover new cell populations in FFPE tissues.
Click below to register for our on-demand webinar where we’ll look at an example of a breast cancer FFPE sample stained with a 36-antibody CODEX panel and demonstrate how it can be analyzed with single-cell, spatial resolution using the MAV software.