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Updated: Jun 22, 2026
A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer
Published on: March 6, 2018
Circulating tumor cells in patients with castration-resistant prostate cancer baseline values and correlation with
Oscar B Goodman1, Louis M Fink, James T Symanowski
1Department of Clinical Oncology, Nevada Cancer Institute, One Breakthrough Way, Las Vegas, Nevada 89135, USA.
Purpose:
Circulating tumor cells (CTC) have been recently accepted by the Food and Drug Administration of the United States as a prognostic tool in advanced prostate cancer. However, a number of questions remain about the use of the test. The optimal clinical cut-off has never been determined. Also, the predictive value of CTCs in the setting of low-burden advanced prostate cancer has not been evaluated. Herein we describe our experience with the CellSearch method of CTC enumeration.
Experimental Design:
CTCs enumerated from 100 patients with castration-resistant prostate cancer were correlated with clinicopathologic characteristics and conventional biomarkers, such as prostate-specific antigen and lactate dehydrogenase. Patients received ongoing medical oncologic follow-up for up to 26 months, and overall survival status was documented.
Results:
Forty-nine of the patients (49%) were alive at the end of the study. CTC counts correlate well with overall survival (P < 0.001) but are also tightly interrelated to other biomarkers. Threshold analysis identified 4 CTC/7.5 cc (compared with the approved value of 5) as an optimal cut-off value with respect to correlation with survival outcomes as well as predictive of metastatic disease. Univariate analysis confirmed a tight interrelationship between cut-off CTC values and biomarkers. Multivariate analysis with bootstrap sampling validation identified lactate dehydrogenase (P = 0.002) and CTCs (P = 0.001) as independently prognostically significant.
Conclusions:
Baseline CTC values provide important prognostic information and specific prediction of metastatic disease. Their presence correlates with classic biomarkers.
