BACKGROUND: Circulating endothelial cells (CECs) have been proposed to predict patient response to antiangiogenic cancer therapy. However, contradictory reports and inconsistency in the phenotypic identification of CECs have led us to compare three cell populations with partially overlapping phenotype in cancer patients receiving chemotherapy and the antiangiogenic agentbevacizumab. METHODS:Patients (n = 20) with locally advanced pancreatic cancer were monitored during 16 weeks of neoadjuvant treatment with gemcitabine and bevacizumab. Detection of circulating cell populations was based on the marker combination CD45, CD31, and CD146; levels of viable and dead (7-aminoactinomycin D-positive) cells were evaluated by flow cytometry in 2-week intervals. RESULTS: We were able to discriminate and concomitantly monitor three cell populations elevated in cancer patients. Whereas CECs were defined as CD45(-) CD31(+) CD146(+), the distinct populations of CD45(-) CD31(-) CD146(+) and CD45(-) CD31(high) CD146(-) cells were partly positive for CD3 and CD41, respectively. CECs and CD45(-) CD31(-) CD146(+) cells increased during therapy; the rise in dead cells was positively correlated with patient response or survival. Conversely, CD45(-) CD31(high) CD146(-) cells decreased in neoadjuvant treatment. A highly significant correlation was established for improved patient response and a minor decrease in viable cell counts. CONCLUSIONS: Flow cytometric CEC analysis based on CD45, CD31, and CD146 requires careful discrimination between blood cell populations with overlapping phenotype showing hallmarks of activated T cells and large platelets. However, these three cell populations show distinct regulation during cancer therapy, and their concomitant analysis may offer extended prognostic and predictive information.
RCT Entities:
BACKGROUND: Circulating endothelial cells (CECs) have been proposed to predict patient response to antiangiogenic cancer therapy. However, contradictory reports and inconsistency in the phenotypic identification of CECs have led us to compare three cell populations with partially overlapping phenotype in cancerpatients receiving chemotherapy and the antiangiogenic agent bevacizumab. METHODS:Patients (n = 20) with locally advanced pancreatic cancer were monitored during 16 weeks of neoadjuvant treatment with gemcitabine and bevacizumab. Detection of circulating cell populations was based on the marker combination CD45, CD31, and CD146; levels of viable and dead (7-aminoactinomycin D-positive) cells were evaluated by flow cytometry in 2-week intervals. RESULTS: We were able to discriminate and concomitantly monitor three cell populations elevated in cancerpatients. Whereas CECs were defined as CD45(-) CD31(+) CD146(+), the distinct populations of CD45(-) CD31(-) CD146(+) and CD45(-) CD31(high) CD146(-) cells were partly positive for CD3 and CD41, respectively. CECs and CD45(-) CD31(-) CD146(+) cells increased during therapy; the rise in dead cells was positively correlated with patient response or survival. Conversely, CD45(-) CD31(high) CD146(-) cells decreased in neoadjuvant treatment. A highly significant correlation was established for improved patient response and a minor decrease in viable cell counts. CONCLUSIONS: Flow cytometric CEC analysis based on CD45, CD31, and CD146 requires careful discrimination between blood cell populations with overlapping phenotype showing hallmarks of activated T cells and large platelets. However, these three cell populations show distinct regulation during cancer therapy, and their concomitant analysis may offer extended prognostic and predictive information.
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