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Related Experiment Video

Updated: May 8, 2025

Manual Construction of a Tissue Microarray using the Tape Method and a Handheld Microarrayer

Manual Construction of a Tissue Microarray using the Tape Method and a Handheld Microarrayer

Published on: June 10, 2022

AI-Assisted High-Throughput Tissue Microarray Workflow.

Konrad Kurowski^1,2,3, Sylvia Timme¹, Melanie Christine Föll¹

¹Institute for Surgical Pathology, Medical Center, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany.

Methods and Protocols

|December 27, 2024

Summary

This summary is machine-generated.

This study introduces an efficient, AI-assisted workflow for immunohistochemistry (IHC) biomarker research on large patient cohorts. The high-throughput method significantly reduces time and resource consumption for tumor characterization.

Keywords:

AI FFPE tissue immunohistochemistry tissue microarrays workflow

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A Next-generation Tissue Microarray ngTMA Protocol for Biomarker Studies

A Next-generation Tissue Microarray ngTMA Protocol for Biomarker Studies

Published on: September 23, 2014

Related Experiment Videos

Last Updated: May 8, 2025

Manual Construction of a Tissue Microarray using the Tape Method and a Handheld Microarrayer

Manual Construction of a Tissue Microarray using the Tape Method and a Handheld Microarrayer

Published on: June 10, 2022

Author Spotlight: Introducing the Tile/SED/Array Interface for Rapid Field of View Positioning in Tissue Imaging

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Published on: September 15, 2023

A Next-generation Tissue Microarray ngTMA Protocol for Biomarker Studies

A Next-generation Tissue Microarray ngTMA Protocol for Biomarker Studies

Published on: September 23, 2014

Area of Science:

Oncology
Pathology
Biomarker Discovery

Background:

Immunohistochemistry (IHC) is crucial for oncology tumor characterization and biomarker identification.
Archived formalin-fixed paraffin-embedded (FFPE) samples are underutilized due to labor-intensive IHC processes.
There is a need for high-throughput methods to analyze large patient cohorts.

Purpose of the Study:

To develop a high-throughput workflow for IHC biomarker studies using modern technologies.
To facilitate efficient analysis of large patient groups and archived FFPE samples.
To correlate antibody expression with clinicopathological data and patient survival.

Main Methods:

Construction of semiautomatic tissue microarrays (TMAs) from two tumor patient cohorts.
Immunohistochemical staining for seven antibodies (ABs).
AI-supported image analysis (QuPath) for quantifying AB expression and correlation with clinicopathological data using R-script.

Main Results:

The workflow reduced labor time by 92.3% compared to whole-slide studies.
Significantly decreased human and material resource consumption.
Successfully correlated AB expression with overall patient survival and clinicopathological data, generating publication-ready reports.

Conclusions:

The AI-assisted high-throughput TMA workflow streamlines histopathological research.
This method offers cost and time efficiency compared to traditional whole-slide studies.
It is ideal for high-throughput research centers and collaborations, maintaining research quality while reducing resource use.