Detection of circulating tumor cells in patients with non-small cell lung cancer using a size-based platform
- Authors:
- Published online on: February 23, 2017 https://doi.org/10.3892/ol.2017.5772
- Pages: 2717-2722
Metrics: Total
Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )
Abstract
The detection of circulating tumor cells (CTCs) is limited by the rarity of these cells in the peripheral blood of patients with cancer. Understanding tumor biology may be useful in the development of novel therapeutic strategies for patients with lung cancer. The present study evaluated a novel size‑based filtration platform for enriching CTCs from patients with lung cancer. Blood samples were obtained from 82 patients with lung cancer for CTC analysis. CTC enrichment by size‑based filtration was performed on 5‑ml blood samples. The collected cells were detected by immunofluorescence using monoclonal anti‑human antibodies against protein tyrosine phosphatase, receptor type C (CD45) and epithelial cell adhesion molecule (EpCAM; an epithelial cell marker), as well as a DAPI nucleic acid stain. CTCs were detected in 57 patients (69.5%) using the size‑based filtration platform. The mean CTC counts, defined as the number of cells with DAPI‑positive, CD45‑negative and EpCAM‑positive staining, were 1.48±1.71 per 5 ml blood for the 66 stage I‑III patients and 8.00±9.95 per 5 ml blood for the 16 stage IV patients. The presence of ≥1 CTCs per 5-ml blood sample was significantly associated with pathological stage (stage IV vs. stage I‑III, P=0.009), but not with patient age or gender, tumor histology, tumor size or lymphovascular invasion. The mean CTC count of healthy donors was 0.25±0.55 per 5 ml blood. In summary, CTCs from the blood of patients with lung cancer were enriched using a size-based filtration platform and immunofluorescent staining with DAPI, CD45 and EpCAM. The CTC counts of patients with stage IV cancer were higher than those of patients with stages I‑III cancer. These results suggest that this novel platform may be a useful tool for determining the prognosis of patients with lung cancer.