A liquid biopsy for bronchopulmonary/lung carcinoid diagnosis

Recent developments in the diagnosis of pancreatic neuroendocrine neoplasms

INTRODUCTION

Pancreatic Neuroendocrine Neoplasms (PanNENs) are characterized by a highly heterogeneous clinical and biological behavior, making their diagnosis challenging. PanNENs diagnostic work-up mainly relies on biochemical markers, pathological examination, and imaging evaluation. The latter includes radiological imaging (i.e. computed tomography [CT] and magnetic resonance imaging [MRI]), functional imaging (i.e. 68Gallium [68 Ga]Ga-DOTA-peptide PET/CT and Fluorine-18 fluorodeoxyglucose [18F]FDG PET/CT), and endoscopic ultrasound (EUS) with its associated procedures.

AREAS COVERED

This review provides a comprehensive assessment of the recent advancements in the PanNENs diagnostic field. PubMed and Embase databases were used for the research, performed from inception to October 2023.

EXPERT OPINION

A deeper understanding of PanNENs biology, recent technological improvements in imaging modalities, as well as progresses achieved in molecular and cytological assays, are fundamental players for the achievement of early diagnosis and enhanced preoperative characterization of PanNENs. A multimodal diagnostic approach is required for a thorough disease assessment.

Neuroendocrine Neoplasms: Genetics and Epigenetics

Neuroendocrine neoplasms (NENs) are a group of rare, heterogeneous tumors of neuroendocrine cell origin, affecting a range of different organs. The clinical management of NENs poses significant challenges, as tumors are often diagnosed at an advanced stage where overall survival remains poor with current treatment regimens. In addition, a host of complex and often unique molecular changes underpin the pathobiology of each NEN subtype. Exploitation of the unique genetic and epigenetic signatures driving each NEN subtype provides an opportunity to enhance the diagnosis, treatment, and monitoring of NEN in an emerging era of individualized medicine.

NETest: A Systematic Review Focusing on the Prognostic and Predictive Role

The NETest is a standardized and reproducible liquid biopsy for neuroendocrine tumors (NETs). It evaluates the expression of 51 NET genes by real-time polymerase chain reaction, providing an accurate molecular profile of the neoplasm. Diagnostic utility of NETest has been widely demonstrated, while its role in predicting prognosis and treatment response is less studied. This systematic review aims to collect and discuss the available evidence on the prognostic and predictive role of NETest, trying to answer 3 questions, frequently raised in clinical practice. Is NETest able to differentiate stable from progressive disease? Increased NETest levels (at least >40%) correlate with disease progression. Is NETest able to predict tumor progression and tumor response to treatment? Some studies demonstrated that the baseline NETest score >33-40% could predict tumor progression. Moreover, NETest performed after treatment (as peptide receptor radionuclide therapy) could predict treatment response also before radiological findings, since the decrease or stability of NETest score predicts tumor response to treatment. Is NETest able to evaluate tumor recurrence risk after surgery? NETest can predict surgical treatment outcome detecting minimal residual disease after radical surgery, which is characterized by a lower but positive NETest score (20-40%), while a higher score (>33-40%) is associated with nonradical surgery. In conclusion, in addition to its demonstrated diagnostic role, this systematic review highlights the efficacy of NETest to assess disease status at the moment of the NETest execution and to predict tumor recurrence after surgery. The efficacy for other applications should be proven by additional studies.

Mutation differences in circulating tumor DNAs from non-small cell lung cancer patients between Uygur and Han populations

BACKGROUND

The incidence of non-small cell lung cancer (NSCLC) in Uygur population is gradually increasing recently. In view of the great diagnostic and prognostic values of cell-free DNAs (cfDNA) detection, this study focus on a liquid biopsy to explore the value of cfDNA mutation in healthy and NSCLC patients in 2 ethnicities.

METHODS

The concentration and sequencing of cfDNA in NSCLC and healthy subjects was assessed with a standard information analysis procedure, including detection, annotation, and statistical analysis. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted to analyze the function of mutant genes and related pathways. Totally, 133 subjects, including 35 Uygur NSCLC patients, 10 Uygur healthy subjects, 63 cases of Han NSCLC patients and 25 Han health control, were admitted to the hospital.

RESULTS

There were a lower proportion of adenocarcinoma and higher percentage of smoking rate for Uygur patients. For cfDNA level between NSCLC and healthy subjects, Han patients exhibited sharp increase while there was no statistical difference in Uygur population. In addition, the mutation frequency of cfDNA in Han patients (72.6%) was significantly higher than Uygur patients (45.7%). There were 5 gene mutations only found in Han patients and ABCC11 showed a higher mutation frequency in Uygur population as a common one. Finally, Go and Kyoto Encyclopedia of Genes and Genomes analysis showed apprent functional enrichments and pathway changes between 2 ethnicities.

CONCLUSION

There existed distinct distributions of cancer subtypes, smoking proportion, cfDNA level, and mutation patterns between Han and Uygur patients. The results may be a useful tool in NSCLC patients' diagnosis as well as individualized therapy between ethnicities in future.

Neuroendocrine Tumor Omic Gene Cluster Analysis Amplifies the Prognostic Accuracy of the NETest

BACKGROUND

The NETest is a multigene assay comprising 51 circulating neuroendocrine tumor (NET)-specific transcripts. The quotient of the 51-gene assay is based upon an ensemble of machine learning algorithms. Eight cancer hallmarks or "omes" (apoptome, epigenome, growth factor signalome, metabolome, proliferome, plurome, secretome, SSTRome) represent 29 genes. The NETest is an accurate diagnostic (>90%) test, but its prognostic utility has not been assessed. In this study, we describe the expansion of the NETest omic cluster components and demonstrate that integration amplifies NETest prognostic accuracy.

METHODS

Group 1: n = 222; including stable disease (SD, n = 146), progressive disease (PD, n = 76), and controls (n = 139). Group 2: NET Registry NCT02270567; n = 88; prospective samples (SD, n = 54; PD, n = 34) with up to 24 months follow-up. We used PubMed literature review, interactomic analysis, nonparametric testing, Kaplan-Meier survival curves, and χ2 analyses to inform and define the prognostic significance of NET genomic "hallmarks."

RESULTS

2020 analyses: In-depth analyses of 47 -NETest genes identified a further six omes: fibrosome, inflammasome, metastasome, NEDome, neurome, and TFome. Group 1 analysis: Twelve omes, excluding the inflammasome and apoptome, were significantly (p < 0.05, 2.1- to 8.2-fold) elevated compared to controls. In the PD group, seven omes (proliferome, NEDome, epigenome, SSTRome, neurome, metastasome, and fibrosome) were elevated (both expression levels and fold change >2) versus SD. Group 2 analysis: All these seven omes were upregulated. In PD, they were significantly more elevated (p < 0.02) than in SD. The septet omic expression exhibited a 69% prognostic accuracy. The NETest alone was 70.5% accurate. A low NETest (≤40) integrated with epigenome/metastasome levels was an accurate prognostic for PD (90%). A high NETest (>40) including the fibrosome/NEDome predicted PD development within 3 months (100%). Using decision tree analysis to integrate the four omes (epigenome, metastasome, fibrosome, and NEDome) with the NETest score generated an overall prognostic accuracy of 93%.

CONCLUSIONS

Examination of NETest omic gene cluster analysis identified five additional clinically relevant cancer hallmarks. Identification of seven omic clusters (septet) provides a molecular pathological signature of disease progression. The integration of the quartet (epigenome, fibrosome, metastasome, NEDome) and the NETest score yielded a 93% accuracy in the prediction of future disease status.

IGF1R and MAPK15 Emerge as Potential Targets of Pentabromobenzylisothioureas in Lung Neuroendocrine Neoplasms

Pentabromobenzylisothioureas are antitumor agents with diverse properties, including the inhibition of MAPK15, IGF1R and PKD1 kinases. Their dysregulation has been implicated in the pathogenesis of several cancers, including bronchopulmonary neuroendocrine neoplasms (BP-NEN). The present study assesses the antitumor potential of ZKKs, a series of pentabromobenzylisothioureas, on the growth of the lung carcinoid H727 cell line. It also evaluates the expression of MAPK15, IGF1R and PKD1 kinases in different BP-NENs. The viability of the H727 cell line was assessed by colorimetric MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide) and its proliferation by BrdU (5-bromo-2′-deoxyuridine) assay. Tissue kinase expression was measured using TaqMan-based RT-PCR and immunohistochemistry. ZKKs (10⁻⁴ to 10⁻⁵ M) strongly inhibited H727 cell viability and proliferation and their antineoplastic effects correlated with their concentrations (p < 0.001). IGF1R and MAPK15 were expressed at high levels in all subtypes of BP-NENs. In addition, the SCLC (small cell lung carcinoma) patients demonstrated higher mRNA levels of IGF1R (p = 0.010) and MAPK15 (p = 0.040) than the other BP-NEN groups. BP-NENs were characterized by low PKD1 expression, and lung neuroendocrine cancers demonstrated lower PKD1 mRNA levels than carcinoids (p = 0.003). ZKKs may suppress BP-NEN growth by inhibiting protein kinase activity. Our results suggest also a possible link between high IGF1R and MAPK15 expression and the aggressive phenotype of BP-NEN tumors.

The NETest liquid biopsy is diagnostic for gastric neuroendocrine tumors: observations on the blood-based identification of microscopic and macroscopic residual diseaseOK

Background

NETest, a novel multi-gene liquid biopsy has utility in neuroendocrine tumor (NET) diagnosis and identification of residual disease. We independently assessed utility of the NETest to diagnose gastric neuroendocrine neoplasms (GNENs) and identify micro- and macroscopic residual disease.

Methods

Cohorts comprised histologically confirmed GNENs at biopsy, n = 46; GNETs Type 1: 42 (32 NET G1, 10 NET G2), a GNET Type 3: 1 well-differentiated NET G3, neuroendocrine carcinomas (NECs) (n = 3), and controls (n = 63). Disease status at sampling was assessed by gastroscopy, histology (resection margin [R] positivity of polypectomy or biopsy), EUS, CT or MRI, and/or ⁶⁸Ga-DOTA-TATE PET/CT. Groups included image- (gastroscopy, EUS, and anatomical and/or functional imaging) positive or image negative disease. NETest assay by PCR (spotted plates, normal cut-off: 20). Data: mean ± SD.

Results

Disease extent: Image-negative (n = 30) (21 R0, 9 R1); Image-positive, n = 16.

Diagnosis: NETest was increased in GNETs (23 ± 11) vs. controls (7 ± 4, p < 0.0001). In histology-positive, the NETest accuracy was 100% (25/25).

Microscopic disease: In image-negative but R1, NETest was elevated in 100% (9/9; 28 ± 9). Levels were elevated vs. controls (7 ± 4, p < 0.0001), or R0 (16 ± 11, p = 0.02). Eight of 21 R0, exhibited positive NETest.

Macroscopic disease: Gastric lesions were multiple: 38%, single: 62%, submucosal: 13%, or ulcerated: 13%. Lesions size was ≤5 mm (50%), > 5–9.9 mm (17%), 10–19.9 mm (17%), ≥20 mm (17%) [≥10 mm: 34%). The NETest accuracy was 100% (16/16). Levels (28 ± 7) were higher than controls (7 ± 4, p < 0.0001) or R0 (16 ± 11, p = 0.002) but not to R1 (28 ± 9, p = 0.5).

Conclusions

NETest is diagnostic for gastric NETs. Elevated levels identify both microscopic and macroscopic residual disease. In histology/image-negative disease, elevated NETest may reflect early evidence of increased neuroendocrine gene expression of hypergastrinemia-induced neoplastic transformation of enterochromaffin-like (ECL) cells to tumor status. A sensitive liquid biopsy has utility in the management and surveillance of gastric NET disease.

Biomarkers for Pancreatic Neuroendocrine Neoplasms (PanNENs) Management-An Updated Review

Pancreatic neuroendocrine tumors (PanNENs) are rare sporadic cancers or develop as part of hereditary syndromes. PanNENs can be both functioning and non-functioning based on whether they produce bioactive peptides. Some PanNENs are well differentiated while others-poorly. Symptoms, thus, depend on both oncological and hormonal causes. PanNEN diagnosis and treatment benefit from and in some instances are guided by biomarker monitoring. However, plasmatic monoanalytes are only suggestive of PanNEN pathological status and their positivity is typically followed by deepen diagnostic analyses through imaging techniques. There is a strong need for new biomarkers and follow-up modalities aimed to improve the outcome of PanNEN patients. Liquid biopsy follow-up, i.e., sequential analysis on tumor biomarkers in body fluids offers a great potential, that need to be substantiated by additional studies focusing on the specific markers and the timing of the analyses. This review provides the most updated panorama on PanNEN biomarkers.

The clinical applications of a multigene liquid biopsy (NETest) in neuroendocrine tumors

PURPOSE

There are few effective biomarkers for neuroendocrine tumors. Precision oncology strategies have provided liquid biopsies for real-time and tailored decision-making. This has led to the development of the first neuroendocrine tumor liquid biopsy (the NETest). The NETest represents a transcriptomic signature of neuroendocrine tumor (NETs) that captures tumor biology and disease activity. The data have direct clinical application in terms of identifying residual disease, disease progress and the efficacy of treatment. In this overview we assess the available published information on the metrics and clinical efficacy of the NETest.

MATERIAL AND METHODS

Published data on the NETest have been collated and analyzed to understand the clinical application of this multianalyte biomarker in NETs.

RESULTS

NETest assay has been validated as a standardized and reproducible clinical laboratory measurement. It is not affected by demographic characteristics, or acid suppressive medication. Clinical utility of the NETest has been documented in gastroenteropancreatic, bronchopulmonary NETs, in paragangliomas and pheochromocytomas. The test facilitates accurate diagnosis of a NET disease, and real-time monitoring of the disease status (stable/progressive disease). It predicts aggressive tumor behavior, identifies operative tumor resection, and efficacy of the medical treatment (e.g. somatostatin analogues), or peptide receptor radionuclide therapy (PRRT). NETest metrics and clinical applications out-perform standard biomarkers like chromogranin A.

CONCLUSIONS

The NETest exhibits clinically competent metrics as an effective biomarker for neuroendocrine tumors. Measurement of NET transcripts in blood is a significant advance in neuroendocrine tumor management and demonstrates that blood provides a viable source to identify and monitor tumor status.

Blood Chromogranin A Is Not Effective as a Biomarker for Diagnosis or Management of Bronchopulmonary Neuroendocrine Tumors/Neoplasms

BACKGROUND

Identification of circulating tumor markers for clinical management in bronchopulmonary (BP) neuroendocrine tumors/neoplasms (NET/NEN) is of considerable clinical interest. Chromogranin A (CgA), a "universal" NET biomarker, is considered controversial as a circulating biomarker of BPNEN.

AIM

Assess utility of CgA in the diagnosis and management of BPNEN in a multicentric study.

MATERIAL AND METHODS

CgA diagnostic metrics were assessed in lung NET/NENs (n = 200) and controls (n = 140), randomly assigned to a Training and Test set (100 BPC and 70 controls in each). Assay specificity was evaluated in neoplastic lung disease (n = 137) and nonneoplastic lung disease (n = 77). CgA efficacy in predicting clinical status was evaluated in the combined set of 200 NET/NENs. CgA levels in bronchopulmonary neuroendocrine tumor (BPNET) subtypes (atypical [AC] vs. typical [TC]) and grade was examined. The clinical utility of an alteration of CgA levels (±25%) was evaluated in a subset of 49 BPNET over 12 months. CgA measurement was by NEOLISATM kit (EuroDiagnostica).

RESULTS

Sensitivity and specificity in the training set were 41/98%, respectively. Test set data were 42/87%. Training set area under receiver operator characteristic analysis differentiated BPC from control area under the curve (AUC) 0.61 ± 0.05 p = 0.015. Test set the data were AUC 0.58 ± 0.05, p = 0.076. In the combined set (n = 200), 67% BPNET/NEN (n = 134) had normal CgA levels. CgA levels did not distinguish histological subtypes (TC vs. AC, AUC 0.56 ± 0.04, p = 0.21), grade (p = 0.45-0.72), or progressive from stable disease (AUC 0.53 ± 0.05 p = 0.47). There was no correlation of CgA with Ki-67 index (Pearson r = 0.143, p = 0.14). For nonneoplastic diseases (chronic obstructive pulmonary disorder and idiopathic pulmonary fibrosis), CgA was elevated in 26-37%. For neoplastic disease (NSCLC, squamous cell carcinoma), CgA was elevated in 11-16%. The neuroendocrine SCLC also exhibited elevated CgA (50%). Elevated CgA was not useful for differentiating BPNET/NEN from these other pathologies. Monitoring BPNET/NEN over a 12-month period identified neither CgA levels per se nor changes in CgA were reflective of somatostatin analog treatment outcome/efficacy or the natural history of the disease (progression).

CONCLUSIONS

Blood CgA levels are not clinically useful as a biomarker for lung BPNET/NEN. The low specificity and elevations in both nonneoplastic as well as other common neoplastic lung diseases identified limited clinical utility for this biomarker.

PRRT neuroendocrine tumor response monitored using circulating transcript analysis: the NETest

PURPOSE

Peptide receptor radionuclide therapy (PRRT) is effective for metastatic/inoperable neuroendocrine tumors (NETs). Imaging response assessment is usually efficient subsequent to treatment completion. Blood biomarkers such as PRRT Predictive Quotient (PPQ) and NETest are effective in real-time. PPQ predicts PRRT efficacy; NETest monitors disease. We prospectively evaluated: (1) NETest as a surrogate biomarker for RECIST; (2) the correlation of NETest levels with PPQ prediction.

METHODS

Three independent ¹⁷⁷Lu-PRRT-treated GEP-NET and lung cohorts (Meldola, Italy: n = 72; Bad-Berka, Germany: n = 44; Rotterdam, Netherlands: n = 41). Treatment response: RECIST1.1 (responder (stable, partial, and complete response) vs non-responder). Blood sampling: pre-PRRT, before each cycle and follow-up (2-12 months). PPQ (positive/negative) and NETest (0-100 score) by PCR. Stable < 40; progressive > 40). CgA (ELISA) as comparator. Samples de-identified, measurement and analyses blinded. Kaplan-Meier survival and standard statistics.

RESULTS

One hundred twenty-two of the 157 were evaluable. RECIST stabilization or response in 67%; 33% progressed. NETest significantly (p < 0.0001) decreased in RECIST "responders" (- 47 ± 3%); in "non-responders," it remained increased (+ 79 ± 19%) (p < 0.0005). NETest monitoring accuracy was 98% (119/122). Follow-up levels > 40 (progressive) vs stable (< 40) significantly correlated with mPFS (not reached vs. 10 months; HR 0.04 (95%CI, 0.02-0.07). PPQ response prediction was accurate in 118 (97%) with a 99% accurate positive and 93% accurate negative prediction. NETest significantly (p < 0.0001) decreased in PPQ-predicted responders (- 46 ± 3%) and remained elevated or increased in PPQ-predicted non-responders (+ 75 ± 19%). Follow-up NETest categories stable vs progressive significantly correlated with PPQ prediction and mPFS (not reached vs. 10 months; HR 0.06 (95%CI, 0.03-0.12). CgA did not reflect PRRT treatment: in RECIST responders decrease in 38% and in non-responders 56% (p = NS).

CONCLUSIONS

PPQ predicts PRRT response in 97%. NETest accurately monitors PRRT response and is an effective surrogate marker of PRRT radiological response. NETest decrease identified responders and correlated (> 97%) with the pretreatment PPQ response predictor. CgA was non-informative.

Utility of a ready-to-use PCR system for neuroendocrine tumor diagnosis

BACKGROUND

Multigene-based PCR tests are time-consuming and limiting aspects of the protocol include increased risk of operator-based variation. In addition, such protocols are complex to transfer and reproduce between laboratories.

AIMS

Evaluate the clinical utility of a pre-spotted PCR plate (PSP) for a novel multigene (n = 51) blood-based gene expression diagnostic assay for neuroendocrine tumors (NETs).

METHODS

A pilot study (n = 44; 8 controls and 36 NETs) was undertaken to compare CQ, normalized gene expression and algorithm-based output (NETest score). Gene expression was then evaluated between matched blood:tumor tissue samples (n = 7). Thereafter, two prospective sets (diagnostic: n = 167; clinical validation: n = 48, respectively) were evaluated for diagnostic and clinical utility value. Two independent molecular diagnostics facilities were used to assess assay reproducibility and inter-laboratory metrics. Samples were collected (per CLIA protocol) processed to mRNA and cDNA and then either run per standard assay (liquid primers) or on PSPs. Separately, matching plasma samples were analyzed for chromogranin A (CgA). Statistics included non-parametric testing, Pearson-concordance, Predictive Modeling and AUROC analyses.

RESULTS

In the pilot study (n = 44), CQ values were highly concordant (r: 0.82, p<0.0001) and normalized gene expression data significantly related (p<0.0001) (Pearson-pairwise correlation). NETest values were not different (49.7±33 standard vs. 48.5±31.5 PSP) and the overall concordance in output 96%. Predictive modelling confirmed this concordance (F1 score = 0.95). Gene expression levels were highly correlated between blood and tumor tissue (R: 0.71-0.83). In the diagnostic cohort (n = 30 controls, n = 87 non-NET controls, n = 50 NET), NETest was significantly lower (p<0.0001) in controls (11±6.5) and non-NET controls (13±18) than NETs (61±31). The AUROCs were 0.93-0.97 and the diagnostic accuracy was 90-97.5%. As a diagnostic, the PSP-NETest was significantly better than CgA (accuracy: 56%, p<0.0001). For clinical samples, the PSP generated robust and accurate (>96%) scores and was significantly better (p<0.0001) than CgA. The assay protocol was consistent (r: 0.97) and reproducible (co-efficient of variation: 1.3-4.2%) across the two facilities.

CONCLUSION

The PSP protocol for the NETest has been established and prospectively tested in clinical samples. It is highly reproducible, has similar metrics (CV, categorization by control or NET) to the standard PCR assay and generates clinically concordant (>96%) NETest results. Moreover, it functions significantly more accurately than CgA.

NETest Liquid Biopsy Is Diagnostic of Lung Neuroendocrine Tumors and Identifies Progressive Disease

BACKGROUND

There are no effective biomarkers for the management of bronchopulmonary carcinoids (BPC). We examined the utility of a neuroendocrine multigene transcript "liquid biopsy" (NETest) in BPC for diagnosis and monitoring of the disease status.

AIM

To independently validate the utility of the NETest in diagnosis and management of BPC in a multicenter, multinational, blinded study.

MATERIAL AND METHODS

The study cohorts assessed were BPC (n = 99), healthy controls (n = 102), other lung neoplasia (n = 101) including adenocarcinomas (ACC) (n = 41), squamous cell carcinomas (SCC) (n = 37), small-cell lung cancer (SCLC) (n = 16), large-cell neuroendocrine carcinoma (LCNEC) (n = 7), and idiopathic pulmonary fibrosis (IPF) (n = 50). BPC were histologically classified as typical (TC) (n = 62) and atypical carcinoids (AC) (n = 37). BPC disease status determination was based on imaging and RECIST 1.1. NETest diagnostic metrics and disease status accuracy were evaluated. The upper limit of normal (NETest) was 20. Twenty matched tissue-blood pairs were also evaluated. Data are means ± SD.

RESULTS

NETest levels were significantly increased in BPC (45 ± 25) versus controls (9 ± 8; p < 0.0001). The area under the ROC curve was 0.96 ± 0.01. Accuracy, sensitivity, and specificity were: 92, 84, and 100%. NETest was also elevated in SCLC (42 ± 32) and LCNEC (28 ± 7). NETest accurately distinguished progressive (61 ± 26) from stable disease (35.5 ± 18; p < 0.0001). In BPC, NETest levels were elevated in metastatic disease irrespective of histology (AC: p < 0.02; TC: p = 0.0006). In nonendocrine lung cancers, ACC (18 ± 21) and SCC (12 ± 11) and benign disease (IPF) (18 ± 25) levels were significantly lower compared to BPC level (p < 0.001). Significant correlations were evident between paired tumor and blood samples for BPC (R: 0.83, p < 0.0001) and SCLC (R: 0.68) but not for SCC and ACC (R: 0.25-0.31).

CONCLUSIONS

Elevated -NETest levels are indicative of lung neuroendocrine neoplasia. NETest levels correlate with tumor tissue and imaging and accurately define clinical progression.

The NETest: The Clinical Utility of Multigene Blood Analysis in the Diagnosis and Management of Neuroendocrine Tumors

The neuroendocrine neoplasms test (NETest) is a multianalyte liquid biopsy that measures neuroendocrine tumor gene expression in blood. This unique signature precisely defines the biological activity of an individual tumor in real time. The assay meets the 3 critical requirements of an optimal biomarker: diagnostic accuracy, prognostic value, and predictive therapeutic assessment. NETest performance metrics are sensitivity and specificity and in head-to-head comparison are 4-fold to 10-fold more accurate than chromogranin A. NETest accurately identifies completeness of surgery and response to somatostatin analogs. Clinical registry data demonstrate significant clinical utility in watch/wait programs.