No effective blood biomarker exists to detect and clinically manage bronchopulmonary (BP) neuroendocrine tumors (NET). This research evaluates the blood-based 51 NET-specific transcript set for diagnosis, monitoring and evaluating clinical performance metrics in BPNETs.

We developed a multi-transcript molecular signature for PCR-based blood analysis. NEN transcripts were identified by analysis of 3 microarray datasets and examined in 130 blood samples. Gene-based classifiers detected NENs in independent sets with high sensitivity (85-98%) and specificity (93-97%).

We have developed a PCR-based tool that measures a 51-gene panel for identification of gastro-enteropancreatic (GEP) neuroendocrine neoplasms (NENs) in peripheral blood. This manuscript assesses the robustness (performance metrics) of this tool with a specific focus on the effects of individual parameters including collection.

This research demonstrates that expression of genes in the NETest captured the biology of NET neoplasia, and that integrating these measurements of circulating gene expression could accurately define clinical status. Based on these data, which indicate that measurement of circulating gene expression is clinically informative, we have built an algorithm – the NETEst – that not only accurately diagnoses GEP–NETs but also provides a measure of their biological activity.