{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T08:06:47Z","timestamp":1784102807910,"version":"3.55.0"},"reference-count":32,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:00:00Z","timestamp":1783555200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>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\u00ae is a blood-based multigene transcriptomic liquid biopsy designed to dynamically assess NET biologic activity. This study compared serial NETest2.0\u00ae 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\u00ae scores were derived from quantitative RT-PCR analysis of a 51-gene transcript panel and expressed on a 0\u2013100 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 (\u0394) between sequential measurements were evaluated using predefined NETest2.0\u00ae thresholds and compared with the conventional CgA threshold (&gt;50%). NETest2.0 \u0394 thresholds of &gt;0% and &gt;5% were evaluated a priori: &gt;0% as a high-sensitivity threshold capturing any upward transcriptomic drift, and &gt;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\u00ae changes compared with changes in CgA (AUC: 0.893 vs. 0.538; p &lt; 0.0001). In the primary surveillance analysis, NETest2.0\u00ae thresholds of &gt;0% and &gt;5% achieved AUCs of 0.860 (95% CI: 0.803\u20130.906) and 0.822 (95% CI: 0.760\u20130.873), respectively, both significantly superior to CgA (AUC: 0.553, 95% CI: 0.480\u20130.625; both p &lt; 0.0001). NETest2.0\u00ae &gt;0% demonstrated the highest sensitivity (86.4%), whereas NETest2.0\u00ae &gt;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\u00ae were the strongest independent predictor of progression (all p &lt; 0.0001; odds ratios: 52.99\u201361.26), whereas CgA did not significantly contribute to progression prediction. Conclusions: Serial NETest2.0\u00ae assessment significantly outperformed CgA for monitoring NET disease activity and progression. These findings support the integration of NETest2.0\u00ae into molecularly informed surveillance strategies to complement imaging and improve longitudinal monitoring of patients with NETs.<\/jats:p>","DOI":"10.3390\/cancers18142206","type":"journal-article","created":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T08:50:56Z","timestamp":1783587056000},"page":"2206","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["NETest2.0\u00ae Demonstrates Superior Monitoring Performance Compared with Chromogranin A in Neuroendocrine Tumor Surveillance"],"prefix":"10.3390","volume":"18","author":[{"given":"Kiarash","family":"Mashayekhi","sequence":"first","affiliation":[{"name":"Department of Surgery, University of North Dakota School of Medicine & Health Sciences, Grand Forks, ND 58203, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1525-5167","authenticated-orcid":false,"given":"Mark","family":"Kidd","sequence":"additional","affiliation":[{"name":"Wren Laboratories, Branford, CT 06405, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anthony","family":"Gulati","sequence":"additional","affiliation":[{"name":"Department of Medical Oncology, Stamford Health, Stamford, CT 06902, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1001\/jamaoncol.2017.0589","article-title":"Trends in the Incidence, Prevalence, and Survival Outcomes in Patients With Neuroendocrine Tumors in the United States","volume":"3","author":"Dasari","year":"2017","journal-title":"JAMA Oncol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s11912-021-01029-7","article-title":"Epidemiology, Incidence, and Prevalence of Neuroendocrine Neoplasms: Are There Global Differences?","volume":"23","author":"Das","year":"2021","journal-title":"Curr. 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