Altered miRNAs Expression Correlates With Gastroenteropancreatic Neuroendocrine Tumors Grades.

Elisabetta Cavalcanti,Marcello Chieppa,Sergio Coletta,Raffaele Armentano,Elisa Stasi,Grazia Serino,Vanessa Galleggiante

doi:10.3389/fonc.2020.01187

Elisabetta Cavalcanti, Marcello Chieppa + Show 5 more

Open Access

https://doi.org/10.3389/fonc.2020.01187

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Abstract

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare and heterogeneous tumors that present a wide spectrum of different clinical and biological characteristics. Currently, tumor grading, determined by Ki-67 staining and mitotic counts, represents the most reliable predictor of prognosis. This time-consuming approach fails to reach high reproducibility standards thus requiring novel approaches to support histological evaluation and prognosis. In this study, starting from a microarray analysis of paraffin-embedded tissue specimens, we defined the miRNAs signature for poorly differentiated NETs (G3) compared to well-differentiated NETs (G1 and G2) consisting of 56 deregulated miRNAs. We identified 8 miRNAs that were expressed in all GEP-NETs grades but at different level. Among these miRNAs, miR-96-5p expression level was progressively higher from grade 1 to grade 3; inversely, its target FoxO1 expression decreased from grade 1 to grade 3. Our results reveal that the miRNAs expression profile of GEP-NET is correlated with the tumor grade, showing a potential advantage of miRNA quantification that could aid clinicians in the classification of common GEP-NETs subtypes. These findings could reliably support the histological evaluation of GEP-NETs paving the way toward personalized treatment approaches.

Highlights

Neuroendocrine Tumors (NETs) are rare and heterogeneous tumors that present with a wide spectrum of different clinical and biological characteristics [1]
For the first time we provide the specific miRNA signature for each Gastroenteropancreatic Neuroendocrine Neoplasms (GEPNETs) grade identifying miRNAs differently expressed in grade 1 to grade 3
Ki-67 staining and mitotic counts, is considered the most reliable predictor for tumor grading [46]. This scoring method is poorly reproducible and time-consuming [47], there is an urgent need for novel approaches to support histological evaluation and prognosis

Summary

Introduction

Neuroendocrine Tumors (NETs) are rare and heterogeneous tumors that present with a wide spectrum of different clinical and biological characteristics [1]. Regardless of the new classification (2010/2017 WHO), the low incidence, tumor heterogeneity, non-specific symptoms at presentation, undefined nomenclatures and classifications, NETs remain an unpredictable disease often difficult to be diagnosed, when the disease is still at an early stage. According to the latest WHO classification, NETs are classified by morphological characteristics and the assessment of proliferation in two miRNAs in GEP-NETs Grading main categories: well-differentiated (WD) and poorly differentiated (PD), called G1/G2 and G3, respectively. Since well-differentiated, high-grade NETs clearly exist (mostly in the pancreas) and it were not considered a homogeneous entity, the WHO described a new classification in 2017 that discriminates the well-differentiated (low-grade, intermediate-grade, or highgrade) pNETs and poorly differentiated (high-grade) pancreatic NECs (pNECs) [8]; but this term is currently limited to patients with pancreatic NETs (pNETs). A more recent classification was made to the histological and cytology pattern, in particular NECs are no longer graded, as they are recognized to be uniformly high grade by definition, but continue to be separated into small-and large-cell types [9, 10]

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