Aneuploid subtypes of circulating tumor cells and circulating tumor-derived endothelial cells predict the overall survival of advanced lung cancer

Abstract

ObjectiveThis study aimed to detect circulating tumor cells (CTCs) and circulating tumor-derived endothelial cells (CTECs) in patients with advanced lung cancer, for describing the distribution characteristics of CTC and CTEC subtypes, exploring the correlation between CTC/CTEC subtypes and novel prognostic biomarkers.MethodsA total of 52 patients with advanced lung cancer were enrolled in this study. Using the subtraction enrichment-immunofluorescence in situ hybridization (SE-iFISH) system, CTCs and CTECs derived from these patients were identified.ResultsBased on cell size, there were 49.3% small and 50.7% large CTCs, and 23.0% small and 77.0% large CTECs. Triploidy, tetraploidy, and multiploidy varied in the small and large CTCs/CTECs. Besides these three aneuploid subtypes, monoploidy was found in the small and large CTECs. Triploid and multiploid small CTCs and tetraploid large CTCs were associated with shorter overall survival (OS) in patients with advanced lung cancer. However, none of the CTECs subtypes showed a significant correlation with patient prognosis. In addition, we found strong positive correlations (P<0.0001) in the four groups including triploid small cell size CTCs and multiploid small cell size CTECs, and multiploid small cell size CTCs and monoploid small cell size CTECs. Furthermore, combined detection of the specific subtypes, including triploid small CTC and monoploid small CTEC, triploid small CTC and triploid small CTEC, and multiploid small CTC and monoploid small CTEC, were associated with poor prognosis in advanced lung cancer.ConclusionsAneuploid small CTCs are associated with the outcome of patients with advanced lung cancer. In particular, the combined detection of triploid small CTCs and monoploid small CTECs, triploid small CTCs and triploid small CTECs, and multiploid small CTCs and monoploid small CTECs has clinical significance for predicting prognosis in patients with advanced lung cancer.