PET Scans Might Allow Early Prediction of Response to Targeted Therapy of Thyroid Cancer

"For the most part, clinical trials have been measuring the effectiveness of vandetanib by changes in tumor size. Based on the activating effects of mutated RET and other protein kinases on numerous intracellular metabolic pathways, we hypothesized that PET imaging could play a role in the early evaluation of response to vandetanib,” said Martin A. Walter, MD, from the department of molecular and medical pharmacology, the University of California, Los Angeles (UCLA) David Geffen School of Medicine (Los Angeles, CA, USA) and lead author of the study.

The study evaluated the usefulness of metabolic imaging to determine response to vandetanib in three ways. First, medullary thyroid cancer cells were used to create an in vitro model. After cultivation, the cells were treated with vandetanib, and changes in the metabolic profile of the cells were successfully monitored by transcriptional profiling and by radiotracer uptake studies.

Using the same untreated cells, the researchers then created an in vivo model by injecting mice with the cancerous cells and treating them with vandetanib. Small animal PET/computed tomography (CT) imaging was performed and was found to reproduce the in vitro findings of metabolic activity after three days. Ultimately, a 43-year old patient with biopsy-proven metastasized medullary thyroid cancer was treated with vandetanib. PET scans taken at 12 and 24 weeks after treatment were able to detect metabolic response to vandetanib, consistent with the in vitro and in vivo samples.

"With the increasing number of available treatment options, careful patient selection is necessary to ensure targeted therapy is administered to those most likely to gain clinical benefit,” concluded Dr. Walter. "The identification of markers of treatment efficacy is a key factor for the success of these novel treatment approaches. Furthermore, relating in-vivo PET imaging metabolic data with transcriptional profiling data using cluster analysis is an innovative concept that allows much potential in the field of molecular imaging.”

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UCLA David Geffen School of Medicine