Sensitive and easy screening for circulating tumor cells by flow cytometry
Alexia Lopresti, Fabrice Malergue, François Bertucci, Maria Lucia Liberatoscioli, Severine Garnier, Quentin DaCosta, Pascal Finetti, Marine Gilabert, Jean Luc Raoul, Daniel Birnbaum, Claire Acquaviva, Emilie Mamessier
Alexia Lopresti, Fabrice Malergue, François Bertucci, Maria Lucia Liberatoscioli, Severine Garnier, Quentin DaCosta, Pascal Finetti, Marine Gilabert, Jean Luc Raoul, Daniel Birnbaum, Claire Acquaviva, Emilie Mamessier
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Resource and Technical Advance Oncology

Sensitive and easy screening for circulating tumor cells by flow cytometry

Abstract

Circulating tumor cells (CTCs) provide easy, repeatable, and representative access to information regarding solid tumors. However, their detection remains difficult because of their paucity, their short half-life, and the lack of reliable surface biomarkers. Flow cytometry (FC) is a fast, sensitive, and affordable technique, ideal for rare-cell detection. Adapted to CTC detection (i.e., extremely rare cells), most FC-based techniques require a time-consuming pre-enrichment step, followed by a 2-hour staining procedure, impeding the efficiency of CTC detection. We overcame these caveats and reduced the procedure to less than 1 hour, with minimal manipulation. First, cells were simultaneously fixed, permeabilized, and then stained. Second, using low-speed FC acquisition conditions and 2 discriminators (cell size and pan-cytokeratin expression), we suppressed the pre-enrichment step. Applied to blood from donors with or without known malignant diseases, this protocol ensures a high recovery of the cells of interest independently of their epithelial-mesenchymal plasticity and can predict which samples are derived from cancer donors. This proof-of-concept study lays the bases of a sensitive tool to detect CTCs from a small amount of blood upstream of in-depth analyses.

Authors

Alexia Lopresti, Fabrice Malergue, François Bertucci, Maria Lucia Liberatoscioli, Severine Garnier, Quentin DaCosta, Pascal Finetti, Marine Gilabert, Jean Luc Raoul, Daniel Birnbaum, Claire Acquaviva, Emilie Mamessier

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Figure 5

CTC detection in peripheral blood samples from individuals with or without known malignant diseases.

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CTC detection in peripheral blood samples from individuals with or witho...
(A) Detection of CTCs in donor with or without malignant disease. The y axis represents the number of CTCs found per milliliter of blood by flow cytometry according to the disease status, as noted on the x axis. The median with interquartile range are shown for each group. The number of CTCs was significantly lower in donors without malignant disease (n = 20) compared with donors with malignant disease at diagnosis: metastatic colon cancer at diagnosis (mColon n = 15) (P < 0.0001) or with advanced malignant disease progressing under treatment (mBreast, n = 46) (P < 0.0001). The number of CTCs in the different groups was compared using the nonparametric unpaired Mann–Whitney U test (2-tailed, confidence interval of 95%). (B) Cut-off value for true positive CTC detection in untreated metastatic patients. ROC curve in the learning set of 31 donors with malignant disease and 10 donors without malignant disease. Optimal cut-off in red was defined as the highest area under the curve (AUC) value across CTC count values. The high AUC (AUC = 0.997) reflects the strong and expected positive correlation between the cancer and normal samples. Significance of AUC was defined using bootstrap across 1000 iterations. (C) Dot plot of CTC count set between donors with or without known malignant disease in the learning set with optimal cut-off represented by the orange line. Significance between groups was defined by Student’s t test. (D) Dot plot of CTC count set between donors with malignant disease (n = 30) and donors without malignant disease (n = 10) in the validation set with optimal cut-off represented by the orange line. Significance between groups was defined by Student’s t test. For all analyses, only P values < 0.05 were considered statistically significant.