EBioMedicine | 2019

CTC phenotyping for a preoperative assessment of tumor metastasis and overall survival of pancreatic ductal adenocarcinoma patients

 
 
 
 
 
 
 
 
 
 

Abstract


Background The evaluation for surgical resectability of pancreatic ductal adenocarcinoma (PDAC) patients is not only imaging-based but highly subjective. An objective method is urgently needed. We report on the clinical value of a phenotypic circulating tumor cell (CTC)-based blood test for a preoperative prognostic assessment of tumor metastasis and overall survival (OS) of PDAC patients. Methods Venous blood samples from 46 pathologically confirmed PDAC patients were collected prospectively before surgery and immunoassayed using a specially designed TU-chip™. Captured CTCs were differentiated into epithelial (E), mesenchymal and hybrid (H) phenotypes. A further 45 non-neoplastic healthy donors provided blood for cell line validation study and CTC false positive quantification. Findings A validated multivariable model consisting of disjunctively combined CTC phenotypes: “H-CTC≥15.0 CTCs/2ml OR E-CTC≥11.0 CTCs/2ml” generated an optimal prediction of metastasis with a sensitivity of 1.000 (95% CI 0.889–1.000) and specificity of 0.886 (95% CI 0.765–0.972). The adjusted Kaplan-Meier median OS constructed using Cox proportional-hazard models and stratified for E-CTC\u202f<\u202f11.0 CTCs/2\u202fml was 16.5\u202fmonths and for E-CTC\u202f≥\u202f11.0 CTCs/2\u202fml was 5.5\u202fmonths (HR\u202f=\u202f0.050, 95% CI 0.004–0.578, P\u202f=\u202f.016). These OS results were consistent with the outcome of the metastatic analysis. Interpretation Our work suggested that H-CTC is a better predictor of metastasis and E-CTC is a significant independent predictor of OS. The CTC phenotyping model has the potential to be developed into a reliable and accurate blood test for metastatic and OS assessments of PDAC patients. Fund National Natural Science Foundation of China; Zhejiang Province Science and Technology Program; China Scholarship Council.

Volume 46
Pages 133 - 149
DOI 10.1016/j.ebiom.2019.07.044
Language English
Journal EBioMedicine

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