Models in Pancreatic Neuroendocrine Neoplasms: Current Perspectives and Future Directions

SIMPLE SUMMARY: Pancreatic neuroendocrine neoplasms (pNENs) are a rare and understudied cancer. Some of this low knowledge base is due to a historical lack of study models. Study models have tremendous implications for validating data for a range of cancer research topics, including treatment development. Therefore, correctly choosing a model is imperative and needs to consider a range of factors pertinent to the research question. In this review, we summarized the current field of models in pNENs. We considered factors, including complexity, accuracy, and cost, in models ranging from cell line cultures, 3D cultures, and whole organismal models, including mice and zebrafish. Improving the number and quality of models available will lead to new breakthroughs in treating pNENs and may lead to findings beneficial for other cancers. ABSTRACT: Pancreatic neuroendocrine neoplasms (pNENs) are a heterogeneous group of tumors derived from multiple neuroendocrine origin cell subtypes. Incidence rates for pNENs have steadily risen over the last decade, and outcomes continue to vary widely due to inability to properly screen. These tumors encompass a wide range of functional and non-functional subtypes, with their rarity and slow growth making therapeutic development difficult as most clinically used therapeutics are derived from retrospective analyses. Improved molecular understanding of these cancers has increased our knowledge of the tumor biology for pNENs. Despite these advances in our understanding of pNENs, there remains a dearth of models for further investigation. In this review, we will cover the current field of pNEN models, which include established cell lines, animal models such as mice and zebrafish, and three-dimensional (3D) cell models, and compare their uses in modeling various disease aspects. While no study model is a complete representation of pNEN biology, each has advantages which allow for new scientific understanding of these rare tumors. Future efforts and advancements in technology will continue to create new options in modeling these cancers.