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The Identification of Gut Neuroendocrine Tumor Disease by Multiple Synchronous Transcript Analysis in Blood

Irvin M. Modlin, Ignat Drozdov, Mark Kidd

We developed a multi-transcript molecular signature for PCR-based blood analysis. NEN transcripts were identified by computational analysis of 3 microarray datasets and examined in 130 blood samples. Gene-based classifiers detected NENs in independent sets with high sensitivity (85-98%), specificity (93-97%), PPV (95-96%) and NPV (87-98%). A panel of 51 marker genes differentiates NENs from controls with a high PPV and NPV (>90%), identifies pancreatic and gastrointestinal NENs with similar efficacy, and confirms GEP-NENs when CgA levels are low. The panel is significantly more accurate than the CgA assay. This reflects its utility to identify multiple diverse biological components of NENs. Application of this sensitive and specific PCR-based blood test to NENs will allow accurate detection of disease, and potentially define disease progress enabling monitoring of treatment efficacy.

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Gut Neuroendocrine Tumor Blood qPCR Fingerprint Assay: Characteristics and Reproducibility

Irvin M. Modlin, Ignat Drozdov, Mark Kidd

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, storage, acid suppressive medica-tion (proton pump inhibitor (PPI)), age, sex, race and food on accuracy.

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PRRT genomic signature in blood for prediction of 177Lu-octreotate efficacy

Bodei L, Kidd MS, Singh A, van der Zwan WA, Severi S, Drozdov IA, Cwikla J, Baum RP, Kwekkeboom DJ, Paganelli G, Krenning EP, Modlin IM

We validated the PRRT Prediction Quotient (PPQ) as a complementary diagnostic in two different PRRT cohorts. The accuracy of this Prediction Quotient in the validation cohorts was 95%. It was significantly more predictive and of more clinical better than either grade (70%) or elevated chromogranin A (50%). Other parameters like SUVmax and FDG were equally non-informative.

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Comparative curves for NETest (green and red) and chromogranin A (blue) demonstrating the NETest is significantly superior.


NETest gene expression histogram: demonstrates stable values after eating. Fasting is therefore not required for the test.