Neuroendocrine tumor biomarkers: Current status and perspectives

Irvin M. Modlin, Kjell Oberg, Andrew Taylor, Ignat Drozdov, Lisa Bodei, Mark Kidd

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)265-277
Number of pages13
Issue number4
Publication statusPublished - Feb 17 2014


  • Algorithmic analyses
  • Biomarker
  • Chromogranin A
  • Circulating tumor cells
  • MicroRNA
  • Monoanalytes
  • Multianalyte assays
  • Neuroendocrine tumor
  • Pancreastatin
  • Serotonin
  • Transcript

ASJC Scopus subject areas

  • Endocrinology
  • Endocrinology, Diabetes and Metabolism
  • Endocrine and Autonomic Systems
  • Cellular and Molecular Neuroscience
  • Medicine(all)


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