Circulating tumor cell enumeration with a combination of epithelial cell adhesion molecule- and cell-surface vimentin-based methods for monitoring breast cancer therapeutic response

循环肿瘤细胞计数与基于上皮细胞粘附分子和细胞表面波形蛋白的方法相结合,用于监测乳腺癌治疗反应

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作者:Arun Satelli, Zachary Brownlee, Abhisek Mitra, Qing H Meng, Shulin Li

Background

Detection, isolation, and enumeration of circulating tumor cells (CTCs) from cancer patients has become an important modality in clinical management of patients with breast cancer. Although CellSearch, an epithelial cell adhesion molecule (EpCAM)-based method that is used to isolate epithelial CTCs, has gained prominence, its inability to detect mesenchymal CTCs from breast cancer patients raises concerns regarding its utility in clinical management.

Conclusions

The sum of CTC counts from the CellSearch and CSV methods appears to provide new insights for assessment of therapeutic response and thus provides a new approach to personalized medicine in breast cancer patients.

Methods

To address this gap in technology, we recently discovered the utility of cell-surface vimentin (CSV) as a marker for detecting mesenchymal CTCs from sarcoma tumors. In the present study, we tested the sensitivity and specificity of detecting CTCs from blood collected at a random time during therapy from each of 58 patients with metastatic breast cancer by use of 84-1 (a monoclonal antibody against CSV to detect epithelial/mesenchymal-transition CTCs) and CellSearch methods. Additionally, we tested the possibility of improving the sensitivity and specificity of detection by use of additional parameters including nuclear EpCAM localization and epithelial mesenchymal ratios.

Results

CTC counts with CSV were significant (P = 0.0053) in differentiating populations responsive and nonresponsive to treatment compared with CTC counts with CellSearch (P = 0.0564). The specificity of CTC detection was found to be highest when the sum of CTC counts from the 2 methods was above a threshold of 8 CTCs/7.5 mL. Conclusions: The sum of CTC counts from the CellSearch and CSV methods appears to provide new insights for assessment of therapeutic response and thus provides a new approach to personalized medicine in breast cancer patients.

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