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.

Veterinary Pathology
|November 16, 2013
PubMed

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.