Neuroendocrine Neoplasms: Historical Background and Terminologies

PURPOSE Neuroendocrine tumors (NETs) are considered rare tumors and can produce a variety of hormones. In this study, we examined the epidemiology of and prognostic factors for NETs, because a thorough examination of neither had previously been performed. METHODS The Surveillance, Epidemiology, and End Results (SEER) Program registries were searched to identify NET cases from 1973 to 2004. Associated population data were used for incidence and prevalence analyses. Results We identified 35,618 patients with NETs. We observed a significant increase in the reported annual age-adjusted incidence of NETs from 1973 (1.09/100,000) to 2004 (5.25/100,000). Using the SEER 9 registry data, we estimated the 29-year limited-duration prevalence of NETs on January 1, 2004, to be 9,263. Also, the estimated 29-year limited-duration prevalence in the United States on that date was 103,312 cases (35/100,000). The most common primary tumor site varied by race, with the lung being the most common in white patients, and the rectum being the most common in Asian/Pacific Islander, American Indian/Alaskan Native, and African American patients. Additionally, survival duration varied by histologic grade. In multivariate analysis of patients with well-differentiated to moderately differentiated NETs, disease stage, primary tumor site, histologic grade, sex, race, age, and year of diagnosis were predictors of outcome (P < .001). CONCLUSION We observed increased reported incidence of NETs and increased survival durations over time, suggesting that NETs are more prevalent than previously reported. Clinicians need to be become familiar with the natural history and patterns of disease progression, which are characteristic of these tumors.

The classification of neuroendocrine neoplasms (NENs) differs between organ systems and currently causes considerable confusion. A uniform classification framework for NENs at any anatomical location may reduce inconsistencies and contradictions among the various systems currently in use. The classification suggested here is intended to allow pathologists and clinicians to manage their patients with NENs consistently, while acknowledging organ-specific differences in classification criteria, tumor biology, and prognostic factors. The classification suggested is based on a consensus conference held at the International Agency for Research on Cancer (IARC) in November 2017 and subsequent discussion with additional experts. The key feature of the new classification is a distinction between differentiated neuroendocrine tumors (NETs), also designated carcinoid tumors in some systems, and poorly differentiated NECs, as they both share common expression of neuroendocrine markers. This dichotomous morphological subdivision into NETs and NECs is supported by genetic evidence at specific anatomic sites as well as clinical, epidemiologic, histologic, and prognostic differences. In many organ systems, NETs are graded as G1, G2, or G3 based on mitotic count and/or Ki-67 labeling index, and/or the presence of necrosis; NECs are considered high grade by definition. We believe this conceptual approach can form the basis for the next generation of NEN classifications and will allow more consistent taxonomy to understand how neoplasms from different organ systems inter-relate clinically and genetically.

We report a comprehensive molecular characterization of pheochromocytomas and paragangliomas (PCCs/PGLs), a rare tumor type. Multi-platform integration revealed that PCCs/PGLs are driven by diverse alterations affecting multiple genes and pathways. Pathogenic germline mutations occurred in eight PCC/PGL susceptibility genes. We identified CSDE1 as a somatically mutated driver gene, complementing four known drivers (HRAS, RET, EPAS1, and NF1). We also discovered fusion genes in PCCs/PGLs, involving MAML3, BRAF, NGFR, and NF1. Integrated analysis classified PCCs/PGLs into four molecularly defined groups: a kinase signaling subtype, a pseudohypoxia subtype, a Wnt-altered subtype, driven by MAML3 and CSDE1, and a cortical admixture subtype. Correlates of metastatic PCCs/PGLs included the MAML3 fusion gene. This integrated molecular characterization provides a comprehensive foundation for developing PCC/PGL precision medicine.