Circulating tumor cell capture and analysis in a multicenter SWOG-coordinated prostate cancer trial.

Abstract

TPS342 Background: Prostate cancer biomarkers are urgently needed to better inform treatment decisions. Recent studies have demonstrated that quantification of peripheral blood circulating tumor cells (CTCs) predicts response to therapy and overall survival in advanced prostate cancer. However, present methods for CTC collection are limited by low yield, complex techniques, and expensive equipment, and they provide little phenotypic information about the CTCs themselves. We have developed a new microfilter platform that simply and reliably traps and enriches the CTC population from peripheral blood, enabling enumeration and further study of these cells. To test whether our microfilter can serve as a simple yet reliable new predictive platform for CTC collection, quantification, and phenotypic analysis, we have activated a correlative CTC biomarker study that “piggybacks” onto S0421, a SWOG cooperative group national protocol studying atrasentan in combination with docetaxel in castration resistant prostate cancer. Methods: In this ongoing multicenter trial, blood samples are drawn at 3 time points before and during treatment. Each sample is processed through the microfilter, and the captured CTCs are analyzed in three ways: 1. Absolute and post-treatment changes in microfilter CTC counts with parallel analysis on the FDA-approved Cell Search platform. 2. Expression of relevant biomarkers on microfilter- trapped CTCs; specifically, endothelin receptor A for atrasentan response, type III β-tubulin for docetaxel response, and CD44 for an aggressive progenitor/metastatic phenotype. 3. Telomerase activity in microfilter-enriched cells. Data is relayed to SWOG Statistical Center for analysis and correlation with clinical outcomes and therapy response in S0421. As of 12/2009, 131 patients have been accrued, with a final goal of 600 samples from 200 patients. This large-scale correlative biomarker study will determine if the quantity and characteristics of CTCs captured on our novel platform can predict clinical outcome and response to therapy, thus enhancing our ability to assess therapeutic efficacy in real time and contributing to optimized, evidence-based, individualized patient management. No significant financial relationships to disclose.