Discrimination between circulating endothelial cells and blood cell populations with overlapping phenotype reveals distinct regulation and predictive potential in cancer therapy.
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 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 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.
Department of Surgery, Medical University of Vienna, General Hospital, Waehringer Guertel 18-20, Vienna, Austria.
Patrick
P
Starlinger
Philipp
P
Brugger
Christian
C
Reiter
Dominic
D
Schauer
Silvia
S
Sommerfeldt
Dietmar
D
Tamandl
Irene
I
Kuehrer
Sebastian F
SF
Schoppmann
Michael
M
Gnant
Christine
C
Brostjan
D000328:Adult; D000368:Aged; D061067:Antibodies, Monoclonal, Humanized / Q000008:administration & dosage; D018952:Antigens, CD34 / Q000097:blood; D000970:Antineoplastic Agents / Q000627:therapeutic use*; D000068258:Bevacizumab; D001792:Blood Platelets / Q000187:drug effects / Q000378:metabolism; D051929:CD146 Antigen / Q000097:blood; D003841:Deoxycytidine / Q000008:administration & dosage / Q000031:analogs & derivatives; D004334:Drug Administration Schedule; D042783:Endothelial Cells / Q000187:drug effects* / Q000378:metabolism; D005260:Female; D005434:Flow Cytometry; D006801:Humans; D016130:Immunophenotyping; D017493:Leukocyte Common Antigens / Q000097:blood; D008297:Male; D008875:Middle Aged; D009362:Neoplasm Metastasis; D010190:Pancreatic Neoplasms / Q000097:blood* / Q000188:drug therapy* / Q000473:pathology; D019408:Platelet Endothelial Cell Adhesion Molecule-1 / Q000097:blood; D011379:Prognosis; D012044:Regression Analysis; D013601:T-Lymphocytes / Q000187:drug effects / Q000378:metabolism; D016896:Treatment Outcome; D000093542:Gemcitabine
D061067:Antibodies, Monoclonal, Humanized; D018952:Antigens, CD34; D000970:Antineoplastic Agents; D051929:CD146 Antigen; D019408:Platelet Endothelial Cell Adhesion Molecule-1; D003841:Deoxycytidine; D000068258:Bevacizumab; D017493:Leukocyte Common Antigens; D000093542:Gemcitabine