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Updated: Jun 2, 2025

Isolation and Functional Assessment of Human Breast Cancer Stem Cells from Cell and Tissue Samples
Published on: October 2, 2020
Rare Cell Population Analysis in Early-Stage Breast Cancer Patients
Stefan Schreier1,2,3, Prapaphan Budchart3, Suparerk Borwornpinyo3,4
1School of Bioinnovation and Bio-based Product Intelligence, Faculty of Science, Mahidol University, Bangkok, Thailand.
Background:
Circulating rare cells participate in breast cancer evolution as systemic components of the disease and thus, are a source of theranostic information. Exploration of cancer-associated rare cells is in its infancy.
Objectives:
We aimed to investigate and classify abnormalities in the circulating rare cell population among early-stage breast cancer patients using fluorescence marker identification and cytomorphology. In addition, we sought to determine the dependency of these markers on the presence of tumors.
Design:
We evaluated the validity of a multi-rare-cell detection platform and demonstrated the utility of a specific rare cell subset as a novel approach to characterize the breast cancer system. Sampling was conducted both before and after tumor resection.
Methods:
Linearity of the Rarmax platform was established using a spike-in approach. The platform includes red blood cell lysis, leukocyte depletion and high-resolution fluorescence image recording. Rare cell analysis was conducted on 28 samples (before and after surgery) from 14 patients with breast cancer, 20 healthy volunteers and 9 noncancer control volunteers. In-depth identification of rare cells, including circulating tumor cells, endothelial-like cells, erythroblasts, and inflammation-associated cells, was performed using a phenotype and morphology-based classification system.
Results:
The platform performed linearly over a range of 5 to 950 spiked cells, with an average recovery of 84.6%. Circulating epithelial and endothelial-like cell subsets have been demonstrated to be associated with or independent of cancer with tumor presence. Furthermore, certain cell profile patterns may be associated with treatment-related adverse effects. The sensitivity in detecting tumor-presence and cancer-associated abnormality before surgery was 43% and 85.7%, respectively, and the specificity was 100% and 96.6%, respectively.
Conclusion:
This study supports the idea of a cancer-associated rare cell abnormality to represent tumor entities as well as systemic cancer. The latter is independent of the apparent clinical cancer.
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