A High-Throughput ImmunoHistoFluorescence (IHF) Method for Sub-Nuclear Protein Analysis in Tissue
Kezia Catharina Oxe1, Kristoffer Staal Rohrberg2, Ulrik Lassen2
1Nucleolar Stress and Disease Group, Danish Cancer Institute, Danish Cancer Society, 2100 Copenhagen, Denmark.
Insights
We developed a high-throughput ImmunoHistoFluorescence (IHF) method for precise analysis of cellular protein distribution in patient tissues. This AI-powered approach enhances biomarker discovery and translational research for precision medicine.
Area of Science:
- Biomedical Engineering
- Molecular Pathology
- Computational Biology
Background:
- Current methods like immunohistochemistry (IHC) offer limited insights into cellular protein distribution due to tissue complexity and manual scoring.
- Immunofluorescence (IF) is effective in cell models but faces challenges in tissue application, including poor antibody penetration and signal detection.
- Scalable protein analysis techniques are crucial for advancing precision medicine and integrating biological findings into diagnostics.
Purpose of the Study:
- To develop a high-throughput ImmunoHistoFluorescence (IHF) method for detailed sub-nuclear protein distribution analysis in human tissues.
- To enable the transfer of in vitro findings into clinically relevant tissue contexts.
- To facilitate the identification of novel biomarkers and accelerate translational research.
Main Methods:
- Generation of a high-throughput ImmunoHistoFluorescence (IHF) workflow.
- Application of IF techniques to tissue samples.
- Automated image acquisition and artificial intelligence (AI)-based analysis of sub-nuclear protein localization patterns.
Main Results:
- Successful implementation of IHF for precise investigation of complex protein localization patterns in tissues.
- Demonstration of AI-driven analysis for high-throughput assessment of protein distribution.
- Establishment of a scalable method for analyzing protein localization in physiologically relevant contexts.
Conclusions:
- The developed IHF approach overcomes limitations of traditional methods for analyzing protein distribution in clinical samples.
- This technique allows for a deeper understanding of disease mechanisms at the molecular level in patients.
- IHF is a promising tool for biomarker discovery, diagnostics, and accelerating precision medicine research.
Abstract:
The current understanding of cellular protein distribution in clinical samples is limited. This is partially due to the complexity and heterogeneity of tissues combined with the qualitative nature of analysis by immunohistochemistry (IHC). The common use of manual assessment in the clinic is time-consuming and restricts both the complexity of scoring and the scale of patient tissue analysis. This has limited the transfer of biological observations into pathology and their integration into diagnostics. Immunofluorescence (IF) techniques allow detailed and high-throughput investigation of proteins in cell models, but their application to tissues has been hindered by poor antibody penetration, autofluorescence artefacts, and weak signals. With a growing focus on precision medicine, scalable techniques to investigate and analyse proteins are critically important. To address this, we generated a high-throughput ImmunoHistoFluorescence (IHF) approach, applying IF to tissue samples followed by automated acquisition and artificial intelligence (AI)-based analysis of sub-nuclear protein distribution to enable precise investigation of complex protein localization patterns. This advancement offers a method to transfer in vitro findings into human tissues to analyse protein localization patterns in physiologically relevant contexts for improved understanding of disease-driving mechanisms in patients, identification of new biomarkers, and acceleration of translational research.
