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Updated: May 6, 2026

Automated Multiplex Immunofluorescence Panel for Immuno-oncology Studies on Formalin-fixed Carcinoma Tissue Specimens
Published on: January 21, 2019
Applications of pathology-assisted image analysis of immunohistochemistry-based biomarkers in oncology
V Shinde1, K E Burke, A Chakravarty
1Pharmaceuticals International Co., Cambridge, MA 02139, USA.
Abstract:
Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.
Insights
Automated image analysis enhances biomarker quantification for cancer drug discovery. This approach confirms target inhibition and downstream effects with greater accuracy and efficiency in preclinical and clinical studies.
Area of Science:
- Oncology
- Biomarker Discovery
- Digital Pathology
Background:
- Immunohistochemistry (IHC) biomarkers are crucial for assessing target inhibition in cancer research.
- Advancements in automated slide scanning and image analysis enable high-throughput quantitative IHC analysis.
- Digital pathology offers enhanced tissue and cellular-level insights beyond traditional methods.
Purpose of the Study:
- To implement and evaluate automated workflows for IHC biomarker analysis in oncology drug discovery.
- To explore biomarkers for Aurora A and NEDD8-activating enzyme (NAE) targets using automated image analysis.
- To demonstrate the utility of quantitative image analysis in confirming target inhibition and downstream effects.
Main Methods:
- Developed automated staining, slide-scanning, and image analysis workflows for IHC.
- Utilized automated image analysis to assess mitotic and apoptotic indices in response to an Aurora A inhibitor (MLN8237).
- Applied a novel image algorithm to measure pathway modulation upon NAE inhibition (MLN4924) in preclinical and clinical samples.
Main Results:
- Automated image analysis confirmed target inhibition for Aurora A and NAE pathways.
- Quantitative assessment of downstream effects of target inhibition was achieved with high throughput and accuracy.
- The developed workflows successfully supported oncology drug discovery and development programs.
Conclusions:
- Automated image analysis provides a robust strategy for biomarker development in oncology.
- Combining pathologist expertise with automated tools enhances quantitative accuracy and efficiency.
- This approach is vital for confirming target engagement and understanding drug mechanisms in cancer research.

