NETest2.0^® Demonstrates Superior Monitoring Performance Compared with Chromogranin A in Neuroendocrine Tumor...

Background/Objectives: Reliable biomarkers for longitudinal surveillance of neuroendocrine tumors (NETs) remain an unmet clinical need. Chromogranin A (CgA), the most widely used circulating biomarker, is limited by low sensitivity, substantial biologic variability, and poor concordance with radiologic progression. NETest2.0^® is a blood-based multigene transcriptomic liquid biopsy designed to dynamically assess NET biologic activity. This study compared serial NETest2.0^® measurements with CgA for monitoring disease progression in a real-world registry cohort. Methods: Patients with histologically confirmed NETs enrolled in the RegisterNET program (NCT02270567) who had paired blood samples and contemporaneous clinical assessment were included. NETest2.0^® scores were derived from quantitative RT-PCR analysis of a 51-gene transcript panel and expressed on a 0-100 scale. Serum CgA levels were measured using standard clinical immunoassays. Imaging-based disease assessment was performed using CT, MRI, and/or ⁶⁸Ga-somatostatin receptor PET/CT with RECIST 1.1 criteria applied where appropriate. Longitudinal percentage changes (Δ) between sequential measurements were evaluated using predefined NETest2.0^® thresholds and compared with the conventional CgA threshold (>50%). NETest2.0 Δ thresholds of >0% and >5% were evaluated a priori: >0% as a high-sensitivity threshold capturing any upward transcriptomic drift, and >5% as a more conservative threshold intended to reduce minor biological or analytical fluctuation. Receiver operating characteristic (ROC) analysis, operating characteristics, multivariable analysis (MVA), and logistic regression analysis (LRA) were performed. Results: A total of 191 patients were analyzed. Exploratory ROC analysis demonstrated superior discrimination for progression using serial NETest2.0^® changes compared with changes in CgA (AUC: 0.893 vs. 0.538; p < 0.0001). In the primary surveillance analysis, NETest2.0^® thresholds of >0% and >5% achieved AUCs of 0.860 (95% CI: 0.803-0.906) and 0.822 (95% CI: 0.760-0.873), respectively, both significantly superior to CgA (AUC: 0.553, 95% CI: 0.480-0.625; both p < 0.0001). NETest2.0^® >0% demonstrated the highest sensitivity (86.4%), whereas NETest2.0^® >5% achieved the optimal balance of sensitivity (70.5%), specificity (93.9%), and overall accuracy (88.5%). In multivariable and logistic regression analyses, changes in NETest2.0^® were the strongest independent predictor of progression (all p < 0.0001; odds ratios: 52.99-61.26), whereas CgA did not significantly contribute to progression prediction. Conclusions: Serial NETest2.0^® assessment significantly outperformed CgA for monitoring NET disease activity and progression. These findings support the integration of NETest2.0^® into molecularly informed surveillance strategies to complement imaging and improve longitudinal monitoring of patients with NETs.