Programming-free Image-Analysis Workflows for IHC, IF and Spatial Proteomics: More than just Cell Counting

Abstract

Quantitative analysis of cells using a specific protein marker is one of the most frequently performed tasks in both preclinical and clinical histopathology. The primary alternatives include immunohistochemistry and immunofluorescence. This article will briefly shed some light on the pros and cons of both methods, the main ones being that immunohistochemistry is widely available, but in many laboratories, it is limited to only one marker per image. Utilizing more than one marker can be achieved through methods such as establishing duplex or triplex stains, serial sections, or re-staining. However, immunofluorescence excels where a deep multi-marker characterization of single cells is required. Spatial proteomics systems have recently increased the plexity to as many as 100 parallel markers, allowing advanced co-expression, rare cells, and spatial neighbourhood analyses. Bioinformatic analysis aspects for both modalities are discussed, outlining two generic workflows as they are realised in a professional image analysis software used by biomedical researchers. While cell segmentation and typing are at the core, a number of pre- and post-processing steps, such as tissue detection, comparison of ROIs, hotspot search, spatial clustering or neighbourhood analysis should be performed to provide more comprehensive read-outs.