A multitranscript blood neuroendocrine tumor molecular signature to identify treatment efficacy and disease progress.

Abstract

4137 Background: Gastroenteropancreatic (GEP) neuroendocrine neoplasms (NENs) or NETs (also called “carcinoids”) are problematic since they present with advanced disease and have limited treatment options. Imaging has proved to be insensitive in identifying treatment effect. Similarly, the currently used biomarker, a neurosectory peptide, Chromogranin A (CgA) is of limited value as a predictor of treatment efficacy. We have developed a multi-transcript (n=51 genes) molecular signature for PCR-based blood analysis which exhibits a high sensitivity (85-98%), specificity (93-97%), positive predictive value (95-96%) and negative predictive value (87-98%) for the identification of GEP-NENs. This test significantly outperforms (p<0005) plasma CgA (measured by ELISA). Methods: The candidate gene signature was examined by a 2-step PCR method in a training set of 130 blood samples (GEP-NENs: n=63, treatment-naïve (n=28)) and validated in an independent set ([n=182, GEP-NENs: n=133, including complete remission (n=4), clinically stable disease (n=82) and non-responders/clinically progressive disease (n=47). Results: The PCR score was significantly elevated (p<0.0001) in the treatment-naïve group compared to treated GEP-NENs, while levels were significantly reduced (p<0.004) in 11 matched samples (pre- and post-treatment – surgical removal (n=10), RFA (n=1)). In the independent set, the scores for complete remission were not different to controls (0.5±0.25 vs. 0.4±0.16), while scores for stable disease (0.63±0.12) were significantly lower than for non-responders (5.85±0.34, p<0.002). Stable disease could be differentiated from clinically progressive disease since the latter exhibited a high score (85% vs. 10%, p<0.0001). The performance metrics for differentiation were: sensitivity (91%), specificity (91%), PPV (86%), NPV (95%). Conclusions: This study demonstrated that the multi-transcript molecular signature is both sensitive and specific for the detection of neuroendocrine tumor disease and is capable of differentiating clinically stable from progressive disease. It therefore has potential utility as a measure for monitoring treatment efficacy for GEP-NENs.