Identification of the genetic landscape of neuroendocrine neoplasms to improve differential diagnosis and identify a signature for tumor aggressiveness

Ranallo, Nicoletta (2026) Identification of the genetic landscape of neuroendocrine neoplasms to improve differential diagnosis and identify a signature for tumor aggressiveness, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Oncologia, ematologia e patologia, 38 Ciclo.
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Abstract

Background Neuroendocrine neoplasms (NENs) are rare and heterogeneous tumors, most commonly arising in the gastroenteropancreatic (GEP) tract and the lung. They vary widely in clinical behaviour. Although WHO classification separates well-differentiated neuroendocrine tumors (NET G1–G3) from poorly differentiated neuroendocrine carcinomas (NECs), the distinction between G3 NET and NEC remains challenging. Molecular markers that refine this taxonomy are needed. Aims This project aimed to identify oncogenic alterations associated with tumor aggressiveness; evaluate DLL3 and RB1 expression as prognostic markers; integrate Whole-Exome Sequencing (WES) and RNA-seq data to improve molecular classification. Material and Methods A retrospective multicentre study enrolled 104 patients across three Italian centres: IRST, CROB and CSS. Clinical and pathological data were collected. DLL3 and RB1 were evaluated by immunohistochemistry. WES was performed on FFPE samples, while RNA-seq was applied to fresh-frozen tissue. Data were analysed using standard bioinformatics pipelines. Results DLL3 was expressed in NECs only and correlated with worse overall survival. RB1 loss was observed in a subset of NECs but was not statistically significant. WES on NETs revealed recurrent mutations in TTN, MUC19, MUC17, MUC4, OBSCN, RYR1, SYNE1, TSC2 and MKI67. Pathway analysis implicated RTK–RAS, PI3K/mTOR, NOTCH, WNT and Hippo signalling. RNA-seq of 37 samples identified 28 pathways upregulated in metastatic tumors, particularly immune response, extracellular matrix remodelling and vesicle transport. Conclusions DLL3 represents a marker of aggressiveness in NENs. TSC2 mutations and immune-related transcriptional signatures provide insights into NET progression. Integrating genomic and transcriptomic data refines the molecular classification of NENs and highlights potential biomarkers for patient stratification.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Ranallo, Nicoletta
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
38
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Neuroendocrine tumors; Neuroendocrine carcinoma; NET; NEC; Prognostic biomarkers; DLL3; Whole-Exome Sequencing; RNA sequencing; Tumour aggressiveness; Molecular classification
Data di discussione
1 Aprile 2026
URI

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