Prognostic transcriptome classes of duodenopancreatic neuroendocrine tumors

Abstract

Duodenopancreatic neuroendocrine tumors (DPNETs) aggressiveness is heterogeneous. Tumor grade and extension are commonly used for prognostic determination. Yet, grade classes are empirically defined, with regular updates changing the definition of classes. Genomic screening may provide more objective classes and reflect tumor biology. The aim of this study was to provide a transcriptome classification of DPNETs. We included 66 DPNETs, covering the entire clinical spectrum of the disease in terms of secretion, grade, and stage. Three distinct molecular groups were identified, associated with distinct outcomes (log-rank P < 0.01): (i) better-outcome DPNETs with pancreatic beta-cell signature. This group was mainly composed of well-differentiated, grade 1 insulinomas; (ii) poor-outcome DPNETs with pancreatic alpha-cell and hepatic signature. This group included all neuroendocrine carcinomas and grade 3 DPNETs, but also some grade 1 and grade 2 DPNETs and (iii) intermediate-outcome DPNETs with pancreatic exocrine and progenitor signature. This group included grade 1 and grade 2 DPNETs, with some insulinomas. Fibrinogen gene FGA expression was one of the topmost expressed liver genes. FGA expression was associated with disease-free survival (HR = 1.13, P = 0.005) and could be validated on two independent cohorts. This original pathophysiologic insight provides new prognostic classification perspectives.

Keywords: ARX; FGA; PDX1; RNA-Seq; dedifferentiation; duodenopancreatic neuroendocrine tumors.