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Quantifying HER-2 expression on circulating tumor cells by ACCEPT.

Leonie Zeune1,2, Guus van Dalum2, Charles Decraene3,4

  • 1Department of Applied Mathematics, MIRA Institute, University of Twente, Enschede, The Netherlands.

Plos One
|October 31, 2017
PubMed
Summary

An open-source image analysis tool, ACCEPT, improved the reproducible quantification of HER-2 expression on circulating tumor cells (CTCs). This advancement is crucial for using CTCs as biomarkers in metastatic breast cancer treatment.

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Area of Science:

  • Biomedical Engineering
  • Oncology
  • Medical Imaging Analysis

Background:

  • Circulating tumor cells (CTCs) are valuable biomarkers for monitoring cancer progression and treatment response.
  • Accurate assessment of treatment target expression on CTCs is essential for personalized medicine.
  • Current methods for quantifying target expression on CTCs can lack reproducibility.

Purpose of the Study:

  • To evaluate the utility of the open-source image analysis program ACCEPT for quantifying HER-2 expression on CTCs.
  • To assess the impact of ACCEPT on the reproducibility of HER-2 scoring by independent investigators.
  • To determine the prevalence of HER-2 expression in CTCs from metastatic breast cancer patients.

Main Methods:

  • Development and application of the ACCEPT image analysis tool for quantifying HER-2 on CTCs.
  • Retrospective analysis of 132 metastatic breast cancer patients' blood samples processed by CellSearch®.
  • Comparison of HER-2 scoring concordance with and without ACCEPT among six independent investigators.

Main Results:

  • The concordance rate for HER-2 scoring on CTCs increased from 30% to 51% when using the ACCEPT tool.
  • Automated assessment by ACCEPT revealed varying HER-2 expression levels across CTCs in 83.3% of patients.
  • Out of 4084 identified CTCs, 1576 were determined to be HER-2 positive.

Conclusions:

  • Image analysis tools like ACCEPT significantly enhance the reproducibility of quantifying treatment targets on CTCs.
  • ACCEPT facilitates a more standardized and potentially automated approach for CTC biomarker analysis.
  • This technology holds promise for advancing the clinical utility of CTCs in precision oncology.