Circulating Tumor Cells in Patients with Castration-Resistant Prostate Cancer Baseline Values and Correlation with Prognostic Factors
- 1 June 2009
- journal article
- Published by American Association for Cancer Research (AACR) in Cancer Epidemiology, Biomarkers & Prevention
- Vol. 18 (6), 1904-1913
- https://doi.org/10.1158/1055-9965.epi-08-1173
Abstract
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. (Cancer Epidemiol Biomarkers Prev 2009;18(6):1904–13)Keywords
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