A multi-transcript blood signature for detection and assessment of gut neuroendocrine tumors.

Abstract

216 Background: Gut neuroendocrine tumors (NETs or “carcinoids”) are difficult to manage since they present with advanced disease and limited treatment options are available. Imaging is relatively insensitive in identifying treatment efficacy and the current biomarker, a neurosecretory peptide, Chromogranin A (CgA), has limited value. There is a lack of specific blood biomarker tests both to detect tumors and measure treatment responsiveness. We report the utility of a 51 marker peripheral blood signature (NETest) in comparison to CgA. Methods: The signature was validated using a 2-step qPCR method for detecting NETs in two sets (n=115; n=120) and for measuring treatment responses in a third set (n=133, including complete remission: n=4, clinically stable disease: n=82 and non-responders/clinically progressive disease: n=47). Comparison with CgA (DAKO-ELISA) was undertaken. The confounding effects of PPIs, age, sex and race were also determined for the PCR test. Results: The PCR NETest detected NETs with high sensitivity (85-98%) and specificity (93-97%). It identified pancreatic and gastrointestinal NETs with similar efficacy (>85%) as well as metastatic and non-metastatic lesions. NETest score was significantly reduced (p<0.004) following surgery or RFA and significantly higher in clinically progressive disease compared to stable disease (5.8±0.3 versus 0.6±0.1, p<0.002). The performance metrics for differentiating stable and progressive disease were sensitivity: 91% and specificity: 91%. The score was robust (reproducibility: Coefficient of Variation<2%).Long-term PPI use (>1yr), did not alter the NETest values, neither did age, sex or ethnicity. The PCR score was significantly (p<0.0005) more accurate than CgA for identifying NETs and was elevated in 91% of NETs when CgA was normal. Conclusions: This study demonstrates that a multi (51)-gene NET panel is both sensitive and specific for detecting NETs and is capable of differentiating clinically stable from progressive disease. The test is robust and significantly more sensitive and specific (accurate) than CgA. The NETest thus facilitates both accurate disease detection, and disease progress thereby permitting assessment of treatment efficacy.