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Published on: August 25, 2020
Principles of deep immunohistochemistry for 3D histology
Chun Ngo Yau1,2,3, Hei Ming Lai1,2,3,4,5, Krit Lee1
1Department of Psychiatry, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Insights
Deep immunohistochemistry (IHC) offers detailed 3D tissue visualization for biological insights and clinical diagnostics. This framework unifies deep IHC methods, guiding researchers to adopt this powerful technique for diverse applications.
Area of Science:
- Biomedical Imaging
- Histology
- Molecular Biology
Background:
- Deep immunohistochemistry (IHC) is an emerging technique for 3D tissue analysis.
- It enables visualization of microscopic architectures and molecular compositions in intact tissues.
- Current methodologies vary, potentially limiting widespread adoption.
Purpose of the Study:
- To provide a unified framework for deep IHC techniques.
- To guide researchers in customizing immunolabeling pipelines.
- To facilitate the adoption of deep IHC for various research questions.
Main Methods:
- Discussion of theoretical physicochemical processes in deep IHC.
- Summary of principles in contemporary deep IHC methods.
- Advocacy for a standardized benchmarking scheme.
Main Results:
- A comprehensive overview of deep IHC methodologies.
- Identification of unaddressed issues and future research directions.
- Guidance for customizing immunolabeling pipelines.
Conclusions:
- Deep IHC has significant potential in biological research and clinical diagnostics.
- A unified framework and standardization are crucial for broader application.
- This work aims to empower researchers to utilize deep IHC effectively.
Abstract:
Deep immunohistochemistry (IHC) is a nascent field in three-dimensional (3D) histology that seeks to achieve thorough, homogeneous, and specific staining of intact tissues for visualization of microscopic architectures and molecular compositions at large spatial scales. Despite the tremendous potential of deep IHC in revealing molecule-structure-function relationships in biology and establishing diagnostic and prognostic features for pathological samples in clinical practice, the complexities and variations in methodologies may hinder its use by interested users. We provide a unified framework of deep immunostaining techniques by discussing the theoretical considerations of the physicochemical processes involved, summarizing the principles applied in contemporary methods, advocating a standardized benchmarking scheme, and highlighting unaddressed issues and future directions. By providing the essential information to guide investigators in customizing immunolabeling pipelines, we also seek to facilitate the adoption of deep IHC for researchers to address a wide range of research questions.
