Cell surface proteins are widely studied in the search for new biomarkers and therapeutic targets, but there is little information available about the surfaceome of individual cells, and this is difficult to obtain experimentally, especially in heterogeneous samples. Flow cytometry is a simple and robust tool for assessing cell surface protein expression on a single-cell level in a wide variety of cell types. However, due to the cost and relative scarcity of reagents, it is typically limited to interrogating known markers, screening small curated subsets of likely candidates, or validating targets obtained via other high throughput methods such as transcriptional profiling. Given recent advances in our understanding of stem cells, tumor-initiating cells, and other rare populations in seemingly homogenous samples, and the relative lack of correlation between the transcriptome and the surfaceome, large-scale flow cytometry screens have become an appealing option. A relatively exhaustive microarray-like flow cytometry screening platform can reveal unexpected markers or sub-populations that are not readily detected by other methods. The single-cell resolution, reliability, and simplicity of flow cytometry and the additional benefit of sub-population/heterogeneity discrimination with the addition of functional and/or phenotypic co-stains allow for the rapid generation of very reliable data from a wide variety of samples at a low cost per sample. These larger datasets can be used for more elaborate bioinformatics, such as hierarchical clustering. Here we describe a method for high throughput cell surface profiling using conventional single or multicolor flow cytometry, which can be adapted to an antibody panel of any size.
Keywords: Antibody array; Biomarker; Cell surface markers; High throughput; Molecular profiling; Stem cells; Surfaceome.