Translational research in neuroendocrine tumors: pitfalls and opportunities
Oncogene. 2017 Apr 6;36(14):1899-1907. doi: 10.1038/onc.2016.316. Epub 2016 Sep 19.
ABSTRACT
Interest in research on neuroendocrine tumors (NETs) has grown in the past 10 years, coinciding with improvements in our understanding of the molecular pathogenesis of NETs. In addition, NETs have become one of the most exciting settings for drug development. Two targeted agents for the management of advanced pancreatic NETs have been approved, but the development of targeted agents for NETs is limited by problems with both patient selection and demonstration of activity. In this review, we analyze these limitations and discuss ways to increase the predictive value of preclinical models for target discovery and drug development. The role of translational research and ‘omics’ methodologies is emphasized, with the final aim of developing personalized medicine. Because NETs usually grow slowly and metastatic tumors are found at easily accessible locations, and owing to improvements in techniques for liquid biopsies, NETs provide a unique opportunity to obtain tumor samples at all stages of the evolution of the disease and to adapt treatment to changes in tumor biology. Combining clinical and translational research is essential to achieve progress in the NET field. Slow growth and genetic stability limit and challenge both the availability and further development of preclinical models of NETs, one of the most crucial unmet research needs in the field. Finally, we suggest some useful approaches for improving clinical drug development for NETs: moving from classical RECIST-based response end points to survival parameters; searching for different criteria to define response rates (for example, antiangiogenic effects and metabolic responses); implementing randomized phase II studies to avoid single-arm phase II studies that produce limited data on drug efficacy; and using predictive biomarkers for patient selection.
PMID:27641330 | DOI:10.1038/onc.2016.316
