Wren Laboratories

Branford, CT, United States

Wren Laboratories

Branford, CT, United States
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Modlin I.M.,Wren Laboratories | Drozdov I.,Bering Ltd | Bodei L.,Italian National Cancer Institute | Kidd M.,Yale University
BMC Cancer | Year: 2014

Background: Detection of neuroendocrine tumor (NET) disease progression is a key issue in determining management. Currently, assessment is by imaging (MRI/CT and Octreoscan®) and plasma Chromogranin A (CgA) measurement.Case presentation: We report use of a NET-specific multigene PCR-derived blood transcript signature (NET Index) to assess disease and correlated CgA and gene transcripts with MRI, CT, Octreoscan®, 11C-5HTP-PET/CT and 68Ga-DOTA-PET/CT in a patient with NET.Conclusions: Our results identify limitations in evaluating disease status by CgA and identify that a PCR-based test is more sensitive. Alteration in NET blood gene transcript levels prior to image-based tumor confirmation suggests this parameter may also have utility as an index of therapeutic efficacy. © 2014 Modlin et al.; licensee BioMed Central Ltd.

Modlin I.M.,Yale University | Modlin I.M.,Wren Laboratories | Kidd M.,Wren Laboratories | Bodei L.,Italian National Cancer Institute | And 2 more authors.
American Journal of Gastroenterology | Year: 2015

OBJECTIVES: Current monoanalyte blood-based biomarkers for the diagnosis and follow-up of neuroendocrine tumors (NETs) do not achieve satisfactory metrics of sensitivity and specificity. We report the sensitivity and selectivity of the PCR-based test, the NETest, to detect tumors with reference to other benign and malignant gastrointestinal diseases. METHODS: A total of 179 cases (gastrointestinal tumors: n=81; pancreatic disease: n=98) were prospectively collected and assessed using the NETest or chromogranin A (CgA) to determine metrics for detecting small intestinal and pancreatic NETs. RESULTS: For intestinal carcinoids, the accuracy of the NETest was 93% (all NETs positive and 3 (12%) colorectal tumors were positive). CgA was positive in 80%, but 29% (n=7) of colorectal cancers were CgA positive. For pancreatic disease, the NETest accuracy was 94% (96% NETs positive, 2 (6%) of intraductal papillary mucinous neoplasms (IPMNs) were positive). The accuracy of CgA was 56% (29% of pancreatic NETs were CgA positive). Overall, the NETest was significantly more sensitive than CgA for the detection of small intestinal (area under the curve 0.98 vs. 0.75 P<0.0001) and pancreatic NETs (0.94 vs. 0.52, P<0.0001). NETest scores were elevated (P<0.05) in extensive disease and were more accurate (76-80%) than CgA levels (20-32%). The metrics of the multianalyte NETest met the performance criteria proposed by the National Institutes of Health for biomarkers, whereas CgA measurement did not. CONCLUSIONS: This study demonstrates that a blood-based multianalyte NET gene transcript measurement of well-differentiated small intestinal and pancreatic neuroendocrine tumor disease is sensitive and specific and outperforms the current monoanalyte diagnostic strategy of plasma CgA measurement.

Modlin I.M.,Yale University | Bodei L.,Italian National Cancer Institute | Kidd M.,Wren Laboratories
Best Practice and Research: Clinical Endocrinology and Metabolism | Year: 2016

The management of neuroendocrine neoplasia remains a perplexing problem because of the lack of knowledge of the biology of the disease, its late presentation, the relative insensitivity of imaging modalities and a paucity of predictably effective treatment options. A critical limitation is posed by the lack of accurate biomarkers to guide management, monitor the efficacy of therapy and provide a prognostic assessment of disease progress. Currently utilized monoanalyte biomarkers (e.g. chromogranin, serotonin, pancreastatin etc.) exhibit variable metrics, poor sensitivity, specificity, and predictive ability and are rarely used to guide clinical decision making. A National Cancer Institute Neuroendocrine Tumor summit conference held in 2007 noted biomarker limitations to be a crucial unmet need in the management of neuroendocrine tumors. Nevertheless little progress has been made in this field until recently with the consideration of blood transcript analysis, circulating tumor cells and miRNA measurement.Given the complexity and multidimensionality of the neoplastic process itself, the heterogeneity of neuroendocrine tumors (NET) as well as the interaction of the tumor microenvironment, it is not unexpected that no single (monoanalyte) biomarker has proven to be effective. This deduction reflects the growing recognition that use of a monoanalyte to define a multidimensional disease process has inherent flaws. Logic dictates that no single measured parameter can capture the pathobiological diversity of neoplasia and monoanalytes cannot define the multiple variables (proliferation, metabolic activity, invasive potential and metastatic propensity) that constitute tumor growth.Thus far, most biomarkers whether in tissue or blood/urine have been single analytes with varying degrees of sensitivity and specificity and in general have failed to exhibit robust metrics or lacked methodological rigor. Neuroendocrine (NE) disease represents an area of biomarker paucity since the individual biomarkers (gastrin, insulin etc) are not widely applicable to the diverse types of NE neoplasia (NEN). Broad spectrum markers such as CgA have limitations in sensitivity, specificity and reproducibility.This review serves to provide a general background of the evolution of NET biomarkers. It provides an assessment of their current and past usage and limitations in assessing their diagnostic, pathologic and prognostic aspects in respect of NET. It provides a view of the changing methodology of biomarker development and the application of biomathematical analyses to redefining detection and treatment. Finally, it presents a description and consensus on current advances in transcript analysis, miRNA measurement and circulating tumor cell identification. © 2016 Elsevier Ltd.

Bodei L.,Italian National Cancer Institute | Kidd M.,Wren Laboratories | Modlin I.M.,Wren Laboratories | Prasad V.,Charite University Hospital | And 7 more authors.
European Journal of Nuclear Medicine and Molecular Imaging | Year: 2015

Purpose: Precise determination of neuroendocrine tumor (NET) disease status and response to therapy remains a rate-limiting concern for disease management. This reflects limitations in biomarker specificity and resolution capacity of imaging. In order to evaluate biomarker precision and identify if combinatorial blood molecular markers and imaging could provide added diagnostic value, we assessed the concordance between 68Ga-somatostatin analog (SSA) positron emission tomography (PET), circulating NET gene transcripts (NETest), chromogranin A (CgA), and Ki-67 in NETs. Methods: We utilized two independent patient groups with positive 68Ga-SSA PET: data set 1 (68Ga-SSA PETs undertaken for peptide receptor radionuclide therapy (PRRT), as primary or salvage treatment, n = 27) and data set 2 (68Ga-SSA PETs performed in patients referred for initial disease staging or restaging after various therapies, n = 22). We examined the maximum standardized uptake value (SUVmax), circulating gene transcripts, CgA levels, and baseline Ki-67. Regression analyses, generalized linear modeling, and receiver-operating characteristic (ROC) analyses were undertaken to determine the strength of the relationships. Results: SUVmax measured in two centers were mathematically evaluated (regression modeling) and determined to be comparable. Of 49 patients, 47 (96 %) exhibited a positive NETest. Twenty-six (54 %) had elevated CgA (χ2 = 20.1, p < 2.5×10−6). The majority (78 %) had Ki-67 < 20 %. Gene transcript scores were predictive of imaging with >95 % concordance and significantly correlated with SUVmax (R2 = 0.31, root-mean-square error = 9.4). The genes MORF4L2 and somatostatin receptors SSTR1, 3, and 5 exhibited the highest correlation with SUVmax. Progressive disease was identified by elevated levels of a quotient of MORF4L2 expression and SUVmax [ROC-derived AUC (R2 = 0.7, p < 0.05)]. No statistical relationship was identified between CgA and Ki-67 and no relationship with imaging parameters was evident. Conclusion: 68Ga-SSA PET imaging parameters (SUVmax) correlated with a circulating NET transcript signature. Disease status could be predicted by an elevated quotient of gene expression (MORF4L2) and SUVmax. These observations provide the basis for further exploration of strategies that combine imaging parameters and disease-specific molecular data for the improvement of NET management. © 2015, Springer-Verlag Berlin Heidelberg.

Kidd M.,Wren Laboratories | Bodei L.,Italian National Cancer Institute | Modlin I.M.,Yale University
Current Opinion in Endocrinology, Diabetes and Obesity | Year: 2016

Purpose of review The review summarizes the utility and limitations of chromogranin A (CgA) as a circulating biomarker for neuroendocrine tumors (NETs). Recent findings Blood CgA measurement has numerous clinical limitations including poor assay reproducibility, low sensitivity (meta-analysis: 73%, 95% confidence interval: 0.71-0.76), and a paucity of prospective validation studies. A recent study noted elevation in 27% of NETs with a predictive value of 50% for metastases. These findings are consistent with its efficacy primarily as a monoanalyte secretory rather than multidimensional neoplastic marker. An automated CgA assay (KRYPTOR) exhibits similar metrics to the DAKO assay but is only useful in serum and routine storage diminishes its accuracy. Current studies indicate that CgA is more effective as a biomarker for cardiac disease. Given the diverse limitations of CgA, NET biomarker focus has evolved toward measurement of multiple analytes, for example, transcripts. Multianalyte algorithmic analyses perform significantly better as diagnostic (>95%) and prognostic markers (>90%) than CgA (30-74 and ∼50%, respectively) since they delineate different aspects of the biological behavior of NETs, (e.g., proliferome and metabolome). Summary CgA is neither a reliable nor robust NET biomarker. As a monoanalyte, it is restricted by poor metrics and has limited predictive value. Its current clinical utility appears optimal in cardiovascular disease. The significance of CgA in NET disease is diminishing as other analytical approaches, particularly transcript multianalyte assays or other strategies, evolve to supersede it. Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.

Modlin I.M.,Wren Laboratories | Modlin I.M.,Yale University | Oberg K.,Uppsala University Hospital | Taylor A.,Wren Laboratories | And 4 more authors.
Neuroendocrinology | Year: 2014

The identification of accurate harbingers of disease status and therapeutic efficacy are critical requirements in precise diagnosis and effective management. Initially, tissue analysis was regarded as ideal but invasive strategies represent risk compared with peripheral blood sampling. Thus far, most biomarkers, whether in tissue or blood/urine, have been single analytes with varying degrees of sensitivity and specificity. Some analytes have not exhibited robust metrics or have lacked methodological rigor. Neuroendocrine disease represents an area of dire biomarker paucity since the individual biomarkers (gastrin, insulin, etc.) are not widely applicable to the diverse types of neuroendocrine neoplasia. Broad-spectrum markers such as chromogranin A have limitations in sensitivity, specificity and reproducibility. Monoanalytes cannot define the multiple variables (proliferation, metabolic activity, invasive potential, metastatic propensity) that constitute tumor growth. The restricted status of the neuroendocrine neoplasia field has resulted in a lack of comprehensive knowledge of the molecular and cellular biology of the disease, with tardy application of innovative technology. This overview examines limitations in current practice and describes contemporary viable strategies under evaluation, including the identification of novel analytes (gene transcripts, microRNA), circulating tumor cells and metabolic imaging agents that identify disease. Novel requirements are necessary to develop biomathematical algorithms for synchronous calibration of multiple molecular markers and predictive nomograms that interface biological variables to delineate disease progress or treatment efficacy. Optimally, the application of novel techniques and amalgamations of multianalyte assessment will provide a personalized molecular disease signature extrapolative of neuroendocrine neoplasia status and likelihood of progression and predictive of therapeutic opportunity. © 2014 S. Karger AG, Basel.

PubMed | Erasmus Medical Center, Wren Laboratories, Yale University and European Institute of Oncology
Type: Journal Article | Journal: Seminars in nuclear medicine | Year: 2016

Peptide receptor radionuclide therapy (PRRT) has been utilized for more than two decades and has been accepted as an effective therapeutic modality in the treatment of inoperable or metastatic gastroenteropancreatic neuroendocrine neoplasms (NENs) or neuroendocrine tumors (NETs). The two most commonly used radiopeptides for PRRT, (90)Y-octreotide and (177)Lu-octreotate, produce disease-control rates of 68%-94%, with progression-free survival rates that compare favorably with chemotherapy, somatostatin analogues, and newer targeted therapies. In addition, biochemical and symptomatic responses are commonly observed. In general, PRRT is well tolerated with only low to moderate toxicity in most individuals. In line with the need to place PRRT in the therapeutic sequence of gastroenteropancreatic NENs, a recently sponsored phase III randomized trial in small intestine NENs treated with (177)Lu-octreotate vs high-dose octreotide long-acting release demonstrated that (177)Lu-octreotate significantly improved progression-free survival. Other strategies that are presently being developed include combinations with targeted therapies or chemotherapy, intra-arterial PRRT, and salvage treatments. Sophisticated molecular tools need to be incorporated into the management strategy to more effectively define therapeutic efficacy and for an early identification of adverse events. The strategy of randomized controlled trials is a key issue to standardize the treatment and establish the position of PRRT in the therapeutic algorithm of NENs.

Kidd M.,Wren Laboratories | Modlin I.M.,Wren Laboratories | Bodei L.,Wren Laboratories | Drozdov I.,Wren Laboratories
CMGH Cellular and Molecular Gastroenterology and Hepatology | Year: 2015

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN), considered a heterogeneous neoplasia, exhibit ill-defined pathobiology and protean symptomatology and are ubiquitous in location. They are difficult to diagnose, challenging to manage, and outcome depends on cell type, secretory product, histopathologic grading, and organ of origin. A morphologic and molecular genomic review of these lesions highlights tumor characteristics that can be used clinically, such as somatostatin-receptor expression, and confirms features that set them outside the standard neoplasia paradigm. Their unique pathobiology is useful for developing diagnostics using somatostatin-receptor targeted imaging or uptake of radiolabeled amino acids specific to secretory products or metabolism. Therapy has evolved via targeting of protein kinase B signaling or somatostatin receptors with drugs or isotopes (peptide-receptor radiotherapy). With DNA sequencing, rarely identified activating mutations confirm that tumor suppressor genes are relevant. Genomic approaches focusing on cancer-associated genes and signaling pathways likely will remain uninformative. Their uniquely dissimilar molecular profiles mean individual tumors are unlikely to be easily or uniformly targeted by therapeutics currently linked to standard cancer genetic paradigms. The prevalence of menin mutations in pancreatic NEN and P27KIP1 mutations in small intestinal NEN represents initial steps to identifying a regulatory commonality in GEP-NEN. Transcriptional profiling and network-based analyses may define the cellular toolkit. Multianalyte diagnostic tools facilitate more accurate molecular pathologic delineations of NEN for assessing prognosis and identifying strategies for individualized patient treatment. GEP-NEN remain unique, poorly understood entities, and insight into their pathobiology and molecular mechanisms of growth and metastasis will help identify the diagnostic and therapeutic weaknesses of this neoplasia. © 2015 The Authors.

Kidd M.,Wren Laboratories | Drozdov I.,Wren Laboratories | Modlin I.,Wren Laboratories
Endocrine-Related Cancer | Year: 2015

A multianalyte algorithmic assay (MAAA) identifies circulating neuroendocrine tumor (NET) transcripts (n=51) with a sensitivity/specificity of 98%/97%.We evaluated whether blood measurements correlated with tumor tissue transcript analysis. The latter were segregated into gene clusters (GC) that defined clinical 'hallmarks' of neoplasia. A MAAA/cluster integrated algorithm (CIA) was developed as a predictive activity index to define tumor behavior and outcome.We evaluated three groups. Group 1: publically available NET transcriptome databases (n=15; GeneProfiler). Group 2: prospectively collected tumors and matched blood samples (n=22; qRT-PCR).Group 3: prospective clinical blood samples, n=159: stable disease (SD): n=111 and progressive disease (PD): n=48. Regulatory network analysis, linear modeling, principal component analysis (PCA), and receiver operating characteristic analyses were used to delineate neoplasia 'hallmarks' and assess GC predictive utility. Our results demonstrated: group 1: NET transcriptomes identified (92%) genes elevated. Group 2: 98% genes elevated by qPCR (fold change >2, P<0.05). Correlation analysis of matched blood/tumor was highly significant (R2=0.7, P<0.0001), and 58% of genes defined nine omic clusters (SSTRome, proliferome, signalome, metabolome, secretome, epigenome, plurome, and apoptome). Group 3: six clusters (SSTRome, proliferome, metabolome, secretome, epigenome, and plurome) differentiated SD fromPD(areaunder thecurve (AUC)=0.81). Integrationwith blood-algorithmamplified theAUC to 0.92±0.02 for differentiating PD and SD. The CIA defined a significantly lower SD score (34.1± 2.6%) than in PD (84±2.8%, P<0.0001). In conclusion, circulating transcripts measurements reflect NET tissue values. Integration of biologically relevant GC differentiate SD from PD. Combination of GC data with the blood-algorithm predicted disease status in >92%. Blood transcript measurement predicts NET activity. © 2015 Society for Endocrinology.

Modlin I.M.,Wren Laboratories | Drozdov I.,Wren Laboratories | Alaimo D.,Wren Laboratories | Callahan S.,Wren Laboratories | And 3 more authors.
Endocrine-Related Cancer | Year: 2014

A critical requirement in neuroendocrine tumor (NET) management is a sensitive, specific and reproducible blood biomarker test. We evaluated a PCR-based 51 transcript signature (NETest) and compared it to chromogranin A (CgA), pancreastatin (PST) and neurokinin A (NKA). The multigene signature was evaluated in two groups: i) a validation set of 40 NETs and controls and ii) a prospectively collected group of NETs (n=41, 61% small intestinal, 50% metastatic, 44% currently treated and 41 age-sex matched controls). Samples were analyzed by a two-step PCR (51 marker genes) protocol and ELISAs for CgA, PST and NKA. Sensitivity comparisons included χ2, non-parametric measurements, ROC curves and predictive feature importance (PFAI) analyses. NETest identified 38 of 41 NETs. Performance metrics were: sensitivity 92.8%, specificity 92.8%, positive predictive value 92.8% and negative predictive value 92.8%. Single analyte ELISA metrics were: CgA 76, 59, 65, and 71%; PST 63, 56, 59, and 61% and NKA 39, 93, 84, and 60%. The AUCs (ROC analysis) were: NETest: 0.96±0.025, CgA: 0.67±0.06, PST 0.56±0.06, NKA: 0.66±0.06. NETest significantly out-performed single analyte tests (area differences: 0.284-0.403, Z-statistic 4.85-5.9, P<0.0001). PFAI analysis determined NETest had most value (69%) in diagnosis (CgA (13%), PST (9%), and NKA (9%)). Test data were consistent with the validation set (NETest >95% sensitivity and specificity, AUC Z0.98 vs single analytes: 59-67% sensitivity, AUCs: 0.58-0.63). The NETest is significantly more sensitive and efficient (>93%) than single analyte assays (CgA, PST or NKA) in NET diagnosis. Blood-based multigene analytic measurement will facilitate early detection of disease recurrence and can predict therapeutic efficacy. © 2014 Society for Endocrinology. Published by Bioscientifica Ltd.

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