Pancreastatin plasma levels in patients with primary hyperparathyroidism

Neuroendocrine tumor biomarkers: From monoanalytes to transcripts and algorithms

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.

A multianalyte PCR blood test outperforms single analyte ELISAs (chromogranin A, pancreastatin, neurokinin A) for neuroendocrine tumor detection

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 χ(2), 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 outperformed 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 =0.98 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.

Neuroendocrine tumor biomarkers: current status and perspectives

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.

The granin family of uniquely acidic proteins of the diffuse neuroendocrine system: comparative and functional aspects

The chromogranins A (CgA) and B (CgB) and secretogranin II (SgII) constitute the main members of a family of uniquely acidic secretory proteins in elements of the diffuse neuroendocrine system. These genetically distinct proteins, CgA, CgB, SgII and the less well known secretogranins III-VII are collectively referred to as 'granins' and characterised by numerous pairs of basic amino acids as potential cleavage sites for processing by the co-stored prohormone converting enzymes PC 1/3 and PC2. This review is directed towards comparative and functional aspects of the granins with emphasis on their phylogenetically conserved sequences. Recent developments provide ample evidence of widely different effects and targets for the intact granins and their derived peptides, intracellularly in the directed trafficking of storage components during granule maturation and extracellularly in autocrine, paracrine and endocrine interactions. Most of the effects assigned to the granin derived peptides fit into patterns of direct or indirect inhibitory modulations of major functions. So far, peptides derived from CgA (vasostatins, chromacin, pancreastatin, WE-14, catestatin and parastatin), CgB (secretolytin) and SgII (secretoneurin) are the most likely candidates for granin-derived regulatory peptides, of postulated relevance not only for homeostatic processes, but also for tissue assembly and repair, inflammatory responses and the first line of defence against invading microorganisms.