Background: Defining therapeutic efficacy in NETs is problematic. We have identified circulating NET transcripts that accurately reflect tumor tissue levels and are sensitive measures of tumor biology. We also identified gene clusters that define NET activity e.g., proliferation. We hypothesized that targeted treatment would alter cluster expression and these could predict treatment response. We evaluated this using somatostatin analogs since they effectively ameliorate symptoms and inhibit tumor growth. Methods: We prospectively evaluated GEP-NETs (n=35) [M:F 12:23; median age: 58 years, small intestine: n=29, pancreas n=3, rectum n=3]. Circulating NET gene expression was assessed (qRT-PCR, normalized gene expression) and imaging (CT/MRI: disease status–RECIST criteria) undertaken. Treatments included: sandostatin (n=32), octreotide (n=2) and pasireotide (n=1); median dose 20mg (range 20-60mg). Gene clusters e.g., proliferation (Ki67, NAP1L1, NOL3, TECPR2) were evaluated as predictive “neoplasia hallmarks” using 2-tailed non-parametric and ROC analyses. Cluster expression is expressed as mean±SEM. Results: Imagery identified25 (71%) patients with stable disease; 10 were progressing. Expression of genes associated with secretory regulation, the “secretome” was significantly down-regulated in the disease-stabilized versus progressive group (2±0.5 vs. 30±25, p<0.001). Individuals with disease progression on SSA therapy exhibited both a significantly elevated proliferation-associated gene cluster (65±15 vs. 16±1, p<0.001) and an epigenetic remodeling cluster (44±6 vs. 32±10, p<0.005). ROC analysis confirmed these accurately identified therapy response (AUC: 0.86-0.97, p<0.0001). Other gene clusters e.g., metabolism (10±1.2 vs. 15.4±3) and apoptosis (1.3±0.2 vs. 1.1±0.8) were not different. Conclusions: SSA therapy alters circulating transcript measurements. Disease stabilization is associated with downregulation of genes linked to tumor secretion while progression is associated with elevation in gene clusters that define tumor proliferation and epigenetic reprogramming. Blood transcript measurements provide an accurate tool to predict the efficacy of SSA therapy.