Early Identification of Residual Disease After Neuroendocrine Tumor Resection Using a Liquid Biopsy Multigenomic mRNA Signature (NETest).

Abstract

Surgery is the only cure for neuroendocrine tumors (NETs), with R0 resection being critical for successful tumor removal. Early detection of residual disease is key for optimal management, but both imaging and current biomarkers are ineffective post-surgery. NETest, a multigene blood biomarker, identifies NETs with >90% accuracy. We hypothesized that surgery would decrease NETest levels and that elevated scores post-surgery would predict recurrence. This was a multicenter evaluation of surgically treated primary NETs (n=153). Blood sampling was performed at day 0 and postoperative day (POD)30. Follow-up included computed tomography/magnetic resonance imaging (CT/MRI), and messenger RNA (mRNA) quantification was performed by polymerase chain reaction (PCR; NETest score: 0-100; normal ≤20). Statistical analyses were performed using the Mann-Whitney U-test, Chi-square test, Kaplan-Meier survival, and area under the receiver operating characteristic curve (AUROC), as appropriate. Data are presented as mean±standarddeviation. The NET cohort (n=153) included 57 patients with pancreatic cancer, 62 patients with small bowel cancer, 27 patients with lung cancer, 4 patients with duodenal cancer, and 3 patients with gastric cancer, while the surgical cohort comprised patients with R0 (n=102) and R1 and R2 (n=51) resection. The mean follow-up time was 14 months (range 3-68). The NETest was positive in 153/153 (100%) samples preoperatively (mean levels of 68±28). In the R0 cohort, POD30 levels decreased from 62±28 to 22±20 (p<0.0001), but remained elevated in 30% (31/102) of patients: 28% lung, 29% pancreas, 27% small bowel, and 33% gastric. By 18 months, 25/31 (81%) patients with a POD30 NETest >20 had image-identifiable recurrence. An NETest score of >20 predicted recurrence with 100% sensitivity and correlated with residual disease (Chi-square17.1, p<0.0001). AUROC analysis identified an AUC of 0.97 (p<0.0001) for recurrence-prediction. In the R1 (n=29) and R2 (n=22) cohorts, the score decreased (R1: 74±28 to 45±24, p=0.0012; R2: 72±24 to 60±28, p=non-significant). At POD30, 100% of NETest scores were elevated despite surgery (p<0.0001). The preoperative NETest accurately identified all NETs (100%). All resections decreased NETest levels and a POD30 NETest score >20 predicted radiologically recurrent disease with 94% accuracy and 100% sensitivity. R0 resection appears to be ineffective in approximately 30% of patients. NET mRNA blood levels provide early objective genomic identification of residual disease and may facilitate management.