Circulating tumor cell detection: A direct comparison between negative and unbiased enrichment in lung cancer

Xu,Yan; Liu,Biao; Ding,Fengan; Zhou,Xiaodie; Tu,Pin; Yu,Bo; He,Yan; Huang,Peilin

doi:10.3892/ol.2017.6046

Circulating tumor cell detection: A direct comparison between negative and unbiased enrichment in lung cancer

Authors:
- Yan Xu
- Biao Liu
- Fengan Ding
- Xiaodie Zhou
- Pin Tu
- Bo Yu
- Yan He
- Peilin Huang
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Affiliations: Department of Internal Medicine, Affiliated Zhongda Hospital, Southeast University School of Medicine, Nanjing, Jiangsu 210009, P.R. China, Department of Pathology, Nanjing Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu 210093, P.R. China
Published online on: April 19, 2017 https://doi.org/10.3892/ol.2017.6046
Pages: 4882-4886

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Abstract

Circulating tumor cells (CTCs), isolated as a ‘liquid biopsy’, may provide important diagnostic and prognostic information. Therefore, rapid, reliable and unbiased detection of CTCs are required for routine clinical analyses. It was demonstrated that negative enrichment, an epithelial marker‑independent technique for isolating CTCs, exhibits a better efficiency in the detection of CTCs compared with positive enrichment techniques that only use specific anti‑epithelial cell adhesion molecules. However, negative enrichment techniques incur significant cell loss during the isolation procedure, and as it is a method that uses only one type of antibody, it is inherently biased. The detection procedure and identification of cell types also relies on skilled and experienced technicians. In the present study, the detection sensitivity of using negative enrichment and a previously described unbiased detection method was compared. The results revealed that unbiased detection methods may efficiently detect >90% of cancer cells in blood samples containing CTCs. By contrast, only 40‑60% of CTCs were detected by negative enrichment. Additionally, CTCs were identified in >65% of patients with stage I/II lung cancer. This simple yet efficient approach may achieve a high level of sensitivity. It demonstrates a potential for the large‑scale clinical implementation of CTC‑based diagnostic and prognostic strategies.

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