Development of a multigenomic liquid biopsy (PROSTest) for prostate cancer in whole blood.

INTRODUCTION: We describe the development of a molecular assay from publicly available tumor tissue mRNA databases using machine learning and present preliminary evidence of functionality as a diagnostic and monitoring tool for prostate cancer (PCa) in whole blood. MATERIALS AND METHODS: We assessed 1055 PCas (public microarray data sets) to identify putative mRNA biomarkers. Specificity was confirmed against 32 different solid and hematological cancers from The Cancer Genome Atlas (n = 10,990). This defined a 27-gene panel which was validated by qPCR in 50 histologically confirmed PCa surgical specimens and matched blood. An ensemble classifier (Random Forest, Support Vector Machines, XGBoost) was trained in age-matched PCas (n = 294), and in 72 controls and 64 BPH. Classifier performance was validated in two independent sets (n = 263 PCas; n = 99 controls). We assessed the panel as a postoperative disease monitor in a radical prostatectomy cohort (RPC: n = 47). RESULTS: A PCa-specific 27-gene panel was identified. Matched blood and tumor gene expression levels were concordant (r = 0.72, p < 0.0001). The ensemble classifier ("PROSTest") was scaled 0%-100% and the industry-standard operating point of ≥50% used to define a PCa. Using this, the PROSTest exhibited an 85% sensitivity and 95% specificity for PCa versus controls. In two independent sets, the metrics were 92%-95% sensitivity and 100% specificity. In the RPCs (n = 47), PROSTest scores decreased from 72% ± 7% to 33% ± 16% (p < 0.0001, Mann-Whitney test). PROSTest was 26% ± 8% in 37 with normal postoperative PSA levels (<0.1 ng/mL). In 10 with elevated postoperative PSA, PROSTest was 60% ± 4%. CONCLUSION: A 27-gene whole blood signature for PCa is concordant with tissue mRNA levels. Measuring blood expression provides a minimally invasive genomic tool that may facilitate prostate cancer management.

Treatment of advanced gastroenteropancreatic neuroendocrine neoplasia, are we on the way to personalised medicine?

Gastroenteropancreatic neuroendocrine neoplasia (GEPNEN) comprises clinically as well as prognostically diverse tumour entities often diagnosed at late stage. Current classification provides a uniform terminology and a Ki67-based grading system, thereby facilitating management. Advances in the study of genomic and epigenetic landscapes have amplified knowledge of tumour biology and enhanced identification of prognostic and potentially predictive treatment subgroups. Translation of this genomic and mechanistic biology into advanced GEPNEN management is limited. 'Targeted' treatments such as somatostatin analogues, peptide receptor radiotherapy, tyrosine kinase inhibitors and mammalian target of rapamycin inhibitors are treatment options but predictive tools are lacking. The inability to identify clonal heterogeneity and define critical oncoregulatory pathways prior to therapy, restrict therapeutic efficacy as does the inability to monitor disease status in real time. Chemotherapy in the poor prognosis NEN G3 group, though associated with acceptable response rates, only leads to short-term tumour control and their molecular biology requires delineation to provide new and more specific treatment options.The future requires an exploration of the NEN tumour genome, its microenvironment and an identification of critical oncologic checkpoints for precise drug targeting. In the advance to personalised medical treatment of patients with GEPNEN, clinical trials need to be based on mechanistic and multidimensional characterisation of each tumour in order to identify the therapeutic agent effective for the individual tumour.This review surveys advances in NEN research and delineates the current status of translation with a view to laying the basis for a genome-based personalised medicine management of advanced GEPNEN.

Molecular Genomic Assessment Using a Blood-based mRNA Signature (NETest) is Cost-effective and Predicts Neuroendocrine Tumor Recurrence With 94% Accuracy.

INTRODUCTION: Identification of residual disease after neuroendocrine tumor (NET) resection is critical for management. Post-surgery imaging is insensitive, expensive, and current biomarkers ineffective. We evaluated whether the NETest, a multigene liquid biopsy blood biomarker, correlated with surgical resection and could predict recurrence. METHODS: Multicenter evaluation of NET resections over 24 months (n = 103): 47 pancreas, 26 small bowel, 26 lung, 2 appendix, 1 duodenum, 1 stomach. Surgery: R0 (83), R1/R2 (20). One millilitre of blood was collected at D0 and posroperative day (POD) 30. Transcript quantification by polymerase chain reaction (normal: ≤20), CgA by NEOLISA (normal ≤108 ng/mL). Standard-of-care (SoC) follow-up costs were calculated and compared to POD30 NETest-stratification approach. Analyses: Wilcoxon-paired test, Chi-square test. D BIOMARKERS: NETest: 103 of 103 (100%)-positive, whereas 23 of 103 (22%) were CgA-positive (Chi-square = 78, P < 0.0001).In the R0 group, the NETest decreased 59 ± 28 to 26 ± 23 (P < 0.0001); 36% (30/83) remained elevated. No significant decrease was evident for CgA. In the R1/R2 group the NETest decreased but 100% remained elevated. CgA levels did not decrease.An elevated POD30 NETest was present in R0 and 25 (83%) developed radiological recurrences. Normal score R0 s (n = 53) did not develop recurrence (Chi-square = 56, P < 0.0001). Recurrence prediction was 94% accurate with the NETest. COST EVALUATION: Using the NETest to stratify postoperative imaging resulted in a cost-savings of 42%. CONCLUSION: NETest diagnosis is more accurate than CgA (100% vs 22%). Surgery significantly decreased NETest. An elevated POD30 NETest predicted recurrence with 94% accuracy and post-surgical POD30 NETest follow-up stratification decreased costs by 42%. CgA had no surgical utility. Further studies would define the accuracy and cost-effectiveness of the NETest in the detection of postoperative recurrent disease.

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

INTRODUCTION: 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. METHODS: 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 ± standard deviation. RESULTS: 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-square 17.1, 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). CONCLUSION: 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.

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.

A combination of surgery, theranostics, and liquid biopsy - a personalised oncologic approach to treatment of patients with advanced metastatic neuroendocrine neoplasms.

Rationale: Neuroendocrine neoplasia (NEN) of small bowel (SBNEN) frequently present with metastatic disease. Theranostics (molecular imaging followed by targeting therapy) allow for personalised medicine. Liquid biopsies enable precise identification of residual disease and real-time monitoring of therapeutic response. Our aim was to determine the clinical utility of a combination of surgery, theranostics, and a multigene blood measurement in metastasised SBNEN. Methods: Inclusion criteria were SBNEN, G1/G2 NEN, initial tumour diagnosis, stage IV NEN, positivity on 68Ga somatostatin analogue PET/CT, eligible for surgery, and 177Lu peptide receptor radionuclide therapy (PRRT). Blood samples for NETest were collected longitudinally. Progression-free survival (PFS) and overall survival (OS) were calculated. NETest results were assessed prior to surgery and during clinical follow-up. Results: A surgical cohort of 39 SBNEN patients met eligibility criteria. Thirty-two patients underwent ileal resection and 7 right hemicolectomy. The mean number of 177Lu PRRT cycles was 4. Mortality was nil. Surgical morbidity was 10.3%. Transient grade 1/2 toxicity occurred in 41% (PRRT). NETest scores (n=9 patients) decreased in 100% following treatment and correlated with diminished tumour volume and disease stabilization following surgery and PRRT. Median follow-up: 78 months. Median PFS and OS: 42.7 and 110 months, respectively. Progression-free survival at 1-, 3-, and 5-years was 79.4%, 57.1% and 40.5%, respectively. Overall survival at 1-, 3-, and 5-years was 97.4%, 97.4%, and 94.1%, respectively. Conclusions: Surgery combined with 177Lu PRRT is safe and provides favourable PFS and OS in selected patients with advanced SBNEN. Liquid biopsy (NETest) has the potential to accurately delineate disease status.

Molecular profiling of neuroendocrine tumours to predict response and toxicity to peptide receptor radionuclide therapy.

Peptide receptor radionuclide therapy (PRRT) is a type of radiotherapy that targets peptide receptors and is typically used for neuroendocrine tumours (NETs). Some of the key challenges in its use are the prediction of efficacy and toxicity, patient selection, and response optimisation. In this Review, we assess current knowledge on the molecular profile of NETs and the strategies and tools used to predict, monitor, and assess the toxicity of PRRT. The few mutations in tumour genes that can be evaluated (eg, ATM and DAXX) are limited to pancreatic NETs and are most likely not informative. Assays that are transcriptomic or based on genes are effective in the prediction of radiotherapy response in other cancers. A blood-based assay for eight genes (the PRRT prediction quotient [PPQ]) has an overall accuracy of 95% for predicting responses to PRRT in NETs. No molecular markers exist that can predict the toxicity of PRRT. Candidate molecular targets include seven single nucleotide polymorphisms (SNPs) that are susceptible to radiation. Transcriptomic evaluations of blood and a combination of gene expression and specific SNPs, assessed by machine learning with algorithms that are tumour-specific, might yield molecular tools to enhance the efficacy and safety of PRRT.

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.

An Assessment of Circulating Chromogranin A as a Biomarker of Bronchopulmonary Neuroendocrine Neoplasia: A Systematic Review and Meta-Analysis.

BACKGROUND: Management of bronchopulmonary neuroendocrine neoplasia (NEN; pulmonary carcinoids [PCs], small-cell lung cancer [SCLC], and large cell neuroendocrine carcinoma) is hampered by the paucity of biomarkers. Chromogranin A (CgA), the default neuroendocrine tumor biomarker, has undergone wide assessment in gastroenteropancreatic neuroendocrine tumors. OBJECTIVES: To evaluate CgA in lung NEN, define its clinical utility as a biomarker, assess its diagnostic, prognostic, and predictive efficacy, as well as its accuracy in the identification of disease recurrence. METHODS: A systematic review of PubMed was undertaken using the preferred reporting items for systematic reviews and meta-analyses guidelines. No language restrictions were applied. Overall, 33 original scientific papers and 3 case reports, which met inclusion criteria, were included in qualitative analysis, and meta-analysis thereafter. All studies, except 2, were retrospective. Meta-analysis statistical assessment by generic inverse variance methodology. RESULTS: Ten different CgA assay types were reported, without consistency in the upper limit of normal (ULN). For PCs (n = 16 studies; median patient inclusion 21 [range 1-200, total: 591 patients]), the CgA diagnostic sensitivity was 34.5 ± 2.7% with a specificity of 93.8 ± 4.7. CgA metrics were not available separately for typical or atypical carcinoids. CgA >100 ng/mL (2.7 × ULN) and >600 ng/mL (ULN unspecified) were anecdotally prognostic for overall survival (n = 2 retrospective studies). No evidence was presented for predicting treatment response or identifying post-surgery residual disease. For SCLC (n = 19 studies; median patient inclusion 23 [range 5-251, total: 1,241 patients]), the mean diagnostic sensitivity was 59.9 ± 6.8% and specificity 79.4 ± 3.1. Extensive disease typically exhibited higher CgA levels (diagnostic accuracy: 61 ± 2.5%). An elevated CgA was prognostic for overall survival (n = 4 retrospective studies). No prospective studies evaluating predictive benefit or prognostic utility were identified. CONCLUSION: The available data are scarce. An assessment of all published data showed that CgA exhibits major limitations as an effective and accurate biomarker for either PC or SCLC. Its utility especially for localized PC/limited SCLC (when surgery is potentially curative), is limited. The clinical value of CgA remains to be determined. This requires validated, well-constructed, multicenter, prospective, randomized studies. An assessment of all published data indicates that CgA does not exhibit the minimum required metrics to function as a clinically useful biomarker for lung NENs.

Neuroendocrine Neoplasms of the Small Bowel and Pancreas.

The traditionally promulgated perspectives of neuroendocrine neoplasms (NEN) as rare, indolent tumours are blunt and have been outdated for the last 2 decades. Clear increments in their incidence over the past decades render them increasingly clinically relevant, and at initial diagnosis many present with nodal and/or distant metastases (notably hepatic). The molecular pathogenesis of these tumours is increasingly yet incompletely understood. Those arising from the small bowel (SB) or pancreas typically occur sporadically; the latter may occur within the context of hereditary tumour predisposition syndromes. NENs can also be associated with endocrinopathy of hormonal hypersecretion. Tangible advances in the development of novel biomarkers, functional imaging modalities and therapy are especially applicable to this sub-set of tumours. The management of SB and pancreatic neuroendocrine tumours (NET) may be challenging, and often comprises a multidisciplinary approach wherein surgical, medical, interventional radiological and radiotherapeutic modalities are implemented. This review provides a comprehensive overview of the epidemiology, pathophysiology, diagnosis and treatment of SB and pancreatic NETs. Moreover, we provide an outlook of the future in these tumour types which will include the development of precision oncology frameworks for individualised therapy, multi-analyte predictive biomarkers, artificial intelligence-derived clinical decision support tools and elucidation of the role of the microbiome in NEN development and clinical behaviour.

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 genomic signature in blood for prediction of 177Lu-octreotate efficacy.

BACKGROUND: Peptide receptor radionuclide therapy (PRRT) utilizes somatostatin receptor (SSR) overexpression on neuroendocrine tumors (NET) to deliver targeted radiotherapy. Intensity of uptake at imaging is considered related to efficacy but has low sensitivity. A pretreatment strategy to determine individual PRRT response remains a key unmet need. NET transcript expression in blood integrated with tumor grade provides a PRRT predictive quotient (PPQ) which stratifies PRRT "responders" from "non-responders". This study clinically validates the utility of the PPQ in NETs. METHODS: The development and validation of the PPQ was undertaken in three independent 177Lu-PRRT treated cohorts. Specificity was tested in two separate somatostatin analog-treated cohorts. Prognostic value of the marker was defined in a cohort of untreated patients. The developmental cohort included lung and gastroenteropancreatic [GEP] NETs (n = 72) from IRST Meldola, Italy. The majority were GEP (71%) and low grade (86% G1-G2). Prospective validation cohorts were from Zentralklinik Bad Berka, Germany (n = 44), and Erasmus Medical Center, Rotterdam, Netherlands (n = 42). Each cohort included predominantly well differentiated, low grade (86-95%) lung and GEP-NETs. The non-PRRT comparator cohorts included SSA cohort I, n = 28 (100% low grade, 100% GEP-NET); SSA cohort II, n = 51 (98% low grade; 76% GEP-NET); and an untreated cohort, n = 44 (64% low grade; 91% GEP-NET). Baseline evaluations included clinical information (disease status, grade, SSR) and biomarker (CgA). NET blood gene transcripts (n = 8: growth factor signaling and metabolism) were measured pre-therapy and integrated with tumor Ki67 using a logistic regression model. This provided a binary output: "predicted responder" (PPQ+); "predicted non-responder" (PPQ-). Treatment response was evaluated using RECIST criteria [Responder (stable, partial and complete response) vs Non-Responder)]. Sample measurement and analyses were blinded to study outcome. Statistical evaluation included Kaplan-Meier survival and standard test evaluation analyses. RESULTS: In the developmental cohort, 56% responded to PRRT. The PPQ predicted 100% of responders and 84% of non-responders (accuracy: 93%). In the two validation cohorts (response: 64-79%), the PPQ was 95% accurate (Bad Berka: PPQ + =97%, PPQ- = 93%; Rotterdam: PPQ + =94%, PPQ- = 100%). Overall, the median PFS was not reached in PPQ+ vs PPQ- (10-14 months; HR: 18-77, p < 0.0001). In the comparator cohorts, the predictor (PPQ) was 47-50% accurate for SSA-treatment and 50% as a prognostic. No differences in PFS were respectively noted (PPQ+: 10-12 months vs. PPQ-: 9-15 months). CONCLUSION: The PPQ derived from circulating NET specific genes and tumor grade prior to the initiation of therapy is a highly specific predictor of the efficacy of PRRT with an accuracy of 95%.

A Comprehensive Assessment of the Role of miRNAs as Biomarkers in Gastroenteropancreatic Neuroendocrine Tumors.

BACKGROUND/AIMS: A key issue in neuroendocrine neoplasia management is the identification of blood signatures that specifically define the activity of a cancer or local tumor microenvironment. MicroRNAs (miRNAs) may represent such a candidate. To evaluate their clinical utility as biomarkers in gastroenteropancreatic neuroendocrine tumors (GEP-NETs), we assessed their expression in tissue and blood. METHODS: A systematic review of PubMed was undertaken to identify studies investigating miRNAs in GEP-NETs and their utility as blood or tissue biomarkers. RESULTS: Twenty-two studies using a range of methodologies with different normalization protocols were identified: tumor - gastric NET type 1 (n = 1 study: MiR-222, regulates p27KIP1), pancreatic (n = 6: MiR-21 [inflammatory marker, oncogene] and MiR-144 [PI3K/AKT signaling], both up- and downregulated depending on the method), small intestinal (n = 7: no consistent signature), and colorectal (n = 3: no consistent signature); blood - gastric NET type 1 (n = 1: MiR-222), pancreatic (n = 3: MiR-21), and small intestinal (n = 3: no consistent signature). The studies all included heterogeneous cohorts, were insufficiently powered, and utilized different methodologies, and age- and gender-matched controls were not used. Different miRNA isolation methods and detection protocols resulted in inconsistent expression comparing tumor and blood. A scientific discrepancy was the downregulated expression of some circulating candidates compared to tissue levels, suggesting methodological issues or physiological responses to the tumor. Both are of concern in defining the biometrics of a marker. CONCLUSIONS: A potential biomarker for GEP-NETs included MiR-21 (small bowel and pancreas), but this epithelial tumor marker requires prospective validation. Overall, significant scientific investigation remains to identify and demonstrate neuroendocrine specificity and to validate candidate miRNA biomarkers.

Measurement of circulating transcript levels (NETest) to detect disease recurrence and improve follow-up after curative surgical resection of well-differentiated pancreatic neuroendocrine tumors.

BACKGROUND: Recurrence of pancreatic neuroendocrine tumors (pNET) after surgery is common. Strategies to detect recurrence have limitations. We investigated the role of clinical criteria and the multigene polymerase chain reaction-based NETest during post-operative follow-up of pNET. METHODS: We studied 3 groups of resections: R0 with no recurrence (n = 11), R0 with recurrence (n = 12), and R1 with no recurrence (n = 12). NETest levels (>40%) were compared with chromogranin A (CgA) and clinicopathological criteria (CC; grade, lymph node metastases, size). Nonparametric, receiver operating characteristics, logistic regression, and predictive feature importance analyses were performed. RESULTS: NETest was higher in R0 with recurrence (56 ± 8%) compared with R1 with no recurrence (39 ± 6%) and R0 with no recurrence (28 ± 6%, P < .005). NETest positively correlated with recurrence (area under the curve: 0.82), CgA was not (area under the curve: 0.51 ± 0.09). Multiple regression analysis defined factor impact as highest for NETest (P < .005) versus CC (P < .03) and CgA (P = .23). NETest gave false positive or negative recurrence in 18% using a 40% cutoff. Logistic regression modeling of CC was 83% accurate; it was 91% when the NETest was included. Combining CC and NETest was approximately 2× more effective than individual CC alone (increase in R 2 value from 43% to 80%). CONCLUSIONS: A multigene blood test facilitates effective identification of pNET recurrence, prediction of disease relapse, and outperforms CgA.

NET Blood Transcript Analysis Defines the Crossing of the Clinical Rubicon: When Stable Disease Becomes Progressive.

BACKGROUND/AIMS: A key issue in gastroenteropancreatic neuroendocrine tumors (GEP-NETs) is early identification and prediction of disease progression. Clinical evaluation and imaging are limited due to the lack of sensitivity and disease indolence. We assessed the NETest as a predictive and prognostic marker of progression in a long-term follow-up study. METHODS: GEP-NETs (n = 34) followed for a median 4 years (2.2-5.4) were evaluated. WHO tumor grade/stage grade 1: n = 17, grade 2: n = 14, grade 3: n = 1 (for 2, no grade was available); 31 (91%) were stage IV. Baseline and longitudinal imaging and blood biomarkers were available in all, and progression was defined per standard clinical protocols (RECIST 1.0). The NETest was measured by quantitative PCR of blood and multianalyte algorithmic analysis (disease activity scaled 0-100% with low <40% and high activity risk cutoffs >80%); chromogranin A (CgA) was measured by radioimmunoassay (normal <150 µg/l); progression-free survival (PFS) was analyzed by Cox proportional-hazard regression and Kaplan-Meier analysis. RESULTS: At baseline, 100% were NETest positive, and CgA was elevated in 50%. The only baseline variable (Cox modeling) associated with PFS was NETest (hazard ratio = 1.022, 95% confidence interval = 1.005-1.04; p < 0.012). Using Kaplan-Meier analyses, the baseline NETest (>80%) was significantly associated (p = 0.01) with disease progression (median PFS 0.68 vs. 2.78 years with <40% levels). The NETest was more informative (96%) than CgA changes (>25%) in consistently predicting disease alterations (40%, p < 2 × 10-5, χ2 = 18). The NETest had an earlier time point change than imaging (1.02 ± 0.15 years). Baseline NETest levels >40% in stable disease were 100% prognostic of disease progression versus CgA (χ2 = 5, p < 0.03). Baseline NETest values <40% accurately (100%) predicted stability over 5 years (p = 0.05, χ2 = 3.8 vs. CgA). CONCLUSION: The NETest correlated with a well-differentiated GEP-NET clinical status. The NETest has predictive and prognostic utility for GEP-NETs identifying clinically actionable alterations ∼1 year before image-based evidence of progression.

Consensus on biomarkers for neuroendocrine tumour disease.

Management of neuroendocrine neoplasia represents a clinical challenge because of its late presentation, lack of treatment options, and limitations in present imaging modalities and biomarkers to guide management. Monoanalyte biomarkers have poor sensitivity, specificity, and predictive ability. A National Cancer Institute summit, held in 2007, on neuroendocrine tumours noted biomarker limitations to be a crucial unmet need in the management of neuroendocrine tumours. A multinational consensus meeting of multidisciplinary experts in neuroendocrine tumours assessed the use of current biomarkers and defined the perquisites for novel biomarkers via the Delphi method. Consensus (at >75%) was achieved for 88 (82%) of 107 assessment questions. The panel concluded that circulating multianalyte biomarkers provide the highest sensitivity and specificity necessary for minimum disease detection and that this type of biomarker had sufficient information to predict treatment effectiveness and prognosis. The panel also concluded that no monoanalyte biomarker of neuroendocrine tumours has yet fulfilled these criteria and there is insufficient information to support the clinical use of miRNA or circulating tumour cells as useful prognostic markers for this disease. The panel considered that trials measuring multianalytes (eg, neuroendocrine gene transcripts) should also identify how such information can optimise the management of patients with neuroendocrine tumours.

Stathmin in pancreatic neuroendocrine neoplasms: a marker of proliferation and PI3K signaling.

Chromosome 1p35-36, which encodes tumor suppressors and mitotic checkpoint control genes, is commonly altered in human malignancies. One gene at this locus, stathmin 1 (STMN1), is involved in cell cycle progression and metastasis. We hypothesized that increased STMN1 expression may play a role in pancreatic neuroendocrine neoplasm (pNEN) malignancy. We investigated stathmin copy number variation, mRNA, and protein expression using PCR-Taqman Copy Number Assays, Q-PCR, Western blot, and immunohistochemistry. A mechanistic role for stathmin in proliferation was assessed in the BON cell line under growth-restrictive conditions and siRNA silencing. Furthermore, its role in PI3K signaling pathway activation was evaluated using pharmacological inhibitors. mRNA (p = 0.0001) and protein (p < 0.05) were overexpressed in pNENs. Expression was associated with pNEN tumor extension (p < 0.05), size (p < 0.01), and Ki67 expression (p < 0.01). Serum depletion decreased Ki67 expression (p < 0.01) as well as Ser38 phosphorylation (p < 0.05) in BON cells. STMN1 knockdown (siRNA) decreased proliferation (p < 0.05), and PI3K inhibitors directly inhibited proliferation via stathmin inactivation (dephosphorylation p < 0.01). We identified that stathmin was overexpressed and associated with pathological parameters in pancreatic NENs. We postulate that STMN1 overexpression and phosphorylation result in a loss of cell cycle mitotic checkpoint control and may render tumors amenable to PI3K inhibitory therapy.

Long-term tolerability of PRRT in 807 patients with neuroendocrine tumours: the value and limitations of clinical factors.

PURPOSE: Peptide receptor radionuclide therapy (PRRT) with (90)Y and (177)Lu provides objective responses in neuroendocrine tumours, and is well tolerated with moderate toxicity. We aimed to identify clinical parameters predictive of long-term renal and haematological toxicity (myelodysplastic syndrome and acute leukaemia). METHODS: Of 807 patients studied at IEO-Milan (1997-2013), 793 (98 %) received (177)Lu (278, 34.4 %), (90)Y (358, 44.4 %) or (177)Lu and (90)Y combined (157. 19.5 %), and 14 (2 %) received combinations of PRRT and other agents. Follow-up was 30 months (1-180 months). The parameters evaluated included renal risk factors, bone marrow toxicity and PRRT features. Data analysis included multiple regression, random forest feature selection, and recursive partitioning and regression trees. RESULTS: Treatment with (90)Y and (90)Y + (177)Lu was more likely to result in nephrotoxicity than treatment with (177)Lu alone (33.6 %, 25.5 % and 13.4 % of patients, respectively; p < 0.0001). Nephrotoxicity (any grade), transient and persistent, occurred in 279 patients (34.6 %) and was severe (grade 3 + 4) in 12 (1.5 %). In only 20-27 % of any nephrotoxicity was the disease modelled by risk factors and codependent associations (p < 0.0001). Hypertension and haemoglobin toxicity were the most relevant factors. Persistent toxicity occurred in 197 patients (24.3 %). In only 22-34 % of affected patients was the disease modelled by the clinical data (p < 0.0001). Hypertension (regression coefficient 0.14, p < 0.0001) and haemoglobin toxicity (regression coefficient 0.21, p < 0.0001) were pertinent factors. Persistent toxicity was associated with shorter PRRT duration from the first to the last cycle (mean 387 vs. 658 days, p < 0.004). Myelodysplastic syndrome occurred in 2.35 % of patients (modelled by the clinical data in 30 %, p < 0.0001). Platelet toxicity grade (2.05 ± 1.2 vs. 0.58 ± 0.8, p < 0.0001) and longer PRRT duration (22.6 ± 24 vs. 15.5 ± 9 months, p = 0.01) were relevant. Acute leukaemia occurred in 1.1 % of patients (modelled by the clinical data in 18 %, p < 0.0001). CONCLUSION: Identified risk factors provide a limited (<30 %) risk estimate even with target tissue dosimetry. These data strongly suggest the existence of unidentified individual susceptibilities to radiation-associated disease.