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Quantification of Rare Cancer Cells in Patients With Gastrointestinal Cancer by Nanostructured Substrate
Authors:Boran Cheng  Haibin Song  Shuyi Wang  Chunxiao Zhang  Bibo Wu  Yuanyuan Chen  Fangfang Chen  Bin Xiong
Institution:Department of Oncology, Zhongnan Hospital of Wuhan University, Hubei Key Laboratory of Tumor Biological Behaviors, Hubei Cancer Clinical Study Center, Wuhan, Hubei, 430071, P. R. China
Abstract:Detecting the cancer cells in the peripheral blood, i.e. circulating tumor cell (CTC), have been considered as the “liquid biopsy” and become a particular area of focus. A deep insight into CTC provides a potential alternative method for early diagnosis of solid tumor. Previous studies showed that CTC counts could be regarded as an indicator in tumor diagnosis, predicting clinical outcomes and monitoring treatment responses. In this report, we utilize our facile and efficient CTC detection device made of hydroxyapatite/chitosan (HA/CTS) for rare cancer cells isolation and enumeration in clinical use. A biocompatible and surface roughness controllable nanofilm was deposited onto a glass slide to achieve enhanced topographic interactions with nanoscale cellular surface components, anti-EpCAM (epithelial cell adhesion molecule, EpCAM) were then coated onto the surface of nanosubstrate for specific capture of CTCs. This device performed a considerable and stable capture yields. We evaluated the relationship performance between serial CTC changes and the changes of tumor volume/serum tumor marker in gastrointestinal cancer patients undergoing anti-cancer treatments. The present study results showed that changes in the number of CTC were associated with tumor burden and progression. Enumeration of CTCs in cancer patients may predict clinical response. Longitudinal monitoring of individual patients during the therapeutic process showed a close correlation between CTC quantity and clinical response to anti-cancer therapy. Effectively capture of this device is capable of CTCs isolation and quantification for monitoring of cancer and predicting treatment response.
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