Neuroendocrine Neoplasm CNV

Classification of neuroendocrine neoplasm (NEN) shows high clinical relevance, but remains difficult and controversial. NEN grading is routinely assessed using Ki-67 index, or neuroendocrine carcinomas (NEC)/neuroendocrine tumor (NET) classification; however, neither fully captures the patient’s treatment response or prognosis. In this study, we used allele-specific copy number analysis from whole exome sequencing (WES) to cluster NEN patients into subgroups. Majority of the samples clinically annotated as NEC cluster together, and exhibit highly altered genomic properties; meanwhile certain NEC samples also cluster together with NET, indicating that the clinical severity differences may exist within NEC subtype. Furthermore, clusters enriched for NEC were stratified into subgroups showing different overall survival and cell morphologies, and patients classified within the same Ki-67 category also have significant different survival time. Overall, we demonstrate that NENs can be molecularly classified based on their copy number stability, and it can complement current classification systems in practice.