In recent years, many new anti-cancer agents have been developed and introduced into clinical care. While these new agents have led to substantial gains in response rates and life expectancies, they have also increased the need for tools to select those patients benefitting from said therapies. Once patients develop metastatic disease, treatment is aimed at improving quality of life and prolonging life expectancy, but is always a trade-off against the side-effects that are inevitably associated with anti-tumor therapy, underscoring the need to select only those patients who are likely to respond to a particular drug. However, there is still an unmet need for such an array of reliable predictive factors, a need that can be met by designing studies in which patient subgroups are defined and stratified based on rational, biology-driven but feasible tumor characteristics. An increasing number of studies is being designed in which, for example, only patients with a specific gain-of-function mutation are subjected to a monoclonal antibody therapy aimed at the activated pathway this gene is involved in. While substantial progress is being made with this approach, patient selection has thus far been far from perfect. Even a powerful predictor such as a KRAS mutation for EGFR-inhibiting therapy results in a response in just 20% of patients who are deemed sensitive based on their KRAS wild-type status. One of the reasons for the disappointing performance of predictive factors could be the fact that they are most often based on primary tumor characteristics, while at the time of metastatic disease, a patients’ prognosis is determined by their metastatic tumor load and its biological phenotype. Through processes such as clonal selection and the inherent genomic instability of the tumor or as a consequence of therapy pressure, metastatic tumor cells can differ substantially and vitally from primary tumor cells. Analysis of metastatic tissue would thus probably be better indicative of the actual tumor load and its underlying biology, and lead to better response prediction. Unfortunately, repetitive metastatic biopsies are invasive and painful, understandably limiting their use in clinical practice. Circulating tumor cells (CTCs) provide a very promising solution for this problem, as they can be obtained and characterized repetitively and non-invasively through venipunctures, and thus serve as a surrogate ‘liquid biopsy’ of metastases.

Additional Metadata
Keywords cancer, metastatic tumor cells, oncology, tumor cells
Promotor S. Sleijfer (Stefan) , J.A. Foekens (John)
Publisher Erasmus University Rotterdam
Sponsor This research project was in part financially supported by Veridex LLC, Raritan, NJ, the Netherlands Genomic Initiative (NGI)/Netherlands Organization for Scientific Research (NWO) and the Coolsingel Foundation. Publication of this thesis was financially supported by kind contributions from: Department of Medical Oncology, Erasmus MC, Erasmus University Rotterdam, ChipSoft BV, Amgen BV, Pfizer BV, Boehringer Ingelheim BV, Sanofi-Aventis BV, Novartis Pharma BV, Bayer BV, Roche Nederland BV, and BD Biosciences.
ISBN 978-90-90-26816-3
Persistent URL hdl.handle.net/1765/37262
Citation
Mostert, B. (2012, September 21). Circulation Tumor Cells: counts and characteristics. Erasmus University Rotterdam. Retrieved from http://hdl.handle.net/1765/37262