Multiplexed immunohistochemistry, imaging, and quantitation: A review, with an assessment of Tyramide signal amplification, multispectral imaging and multiplex analysis

• Published in: Methods (San Diego, Calif.) Vol. 70; no. 1; pp. 46 - 58
• Main Authors: Stack, Edward C., Wang, Chichung, Roman, Kristin A., Hoyt, Clifford C.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.11.2014
• Subjects: Animals; Automation; Biomarkers; Biomarkers, Tumor; Breast Neoplasms - metabolism; Cancer; computer software; DNA; DNA - chemistry; Female; Fluorescent Dyes - chemistry; Humans; image analysis; Image Processing, Computer-Assisted - methods; immunohistochemistry; Immunohistochemistry - methods; Keratins - chemistry; Multiplexed; Multispectral; multispectral imagery; Neoplasms - metabolism; Pathology; patients; Pattern Recognition, Automated; Perception; Precision Medicine; proteins; Quantitative; RNA; RNA - chemistry; Software; TSA; Tyramine - chemistry; visual perception; Pathology; TSA; Multiplexed; Biomarkers; Quantitative; Multispectral; Cancer
• ISSN: 1046-2023; 1095-9130; 1095-9130
• DOI: 10.1016/j.ymeth.2014.08.016

Tissue sections offer the opportunity to understand a patient’s condition, to make better prognostic evaluations and to select optimum treatments, as evidenced by the place pathology holds today in clinical practice. Yet, there is a wealth of information locked up in a tissue section that is only partially accessed, due mainly to the limitations of tools and methods. Often tissues are assessed primarily based on visual analysis of one or two proteins, or 2–3 DNA or RNA molecules. Even while analysis is still based on visual perception, image analysis is starting to address the variability of human perception. This is in contrast to measuring characteristics that are substantially out of reach of human perception, such as parameters revealed through co-expression, spatial relationships, heterogeneity, and low abundance molecules. What is not routinely accessed is the information revealed through simultaneous detection of multiple markers, the spatial relationships among cells and tissue in disease, and the heterogeneity now understood to be critical to developing effective therapeutic strategies. Our purpose here is to review and assess methods for multiplexed, quantitative, image analysis based approaches, using new multicolor immunohistochemistry methods, automated multispectral slide imaging, and advanced trainable pattern recognition software. A key aspect of our approach is presenting imagery in a workflow that engages the pathologist to utilize the strengths of human perception and judgment, while significantly expanding the range of metrics collectable from tissue sections and also provide a level of consistency and precision needed to support the complexities of personalized medicine.