Research Report on Comprehensive Genomic and Transcriptomic Characteristics of High-Grade Gastro-Entero-Pancreatic Neuroendocrine Tumors

Research Background

High-grade gastro-entero-pancreatic neuroendocrine neoplasms (HG GEP-NENs) are a heterogeneous group of malignant tumors characterized by neuroendocrine differentiation. According to WHO 2019 [1] and 2022 [2] standards, GEP-NENs are currently classified into three categories: neuroendocrine tumors (NETs), neuroendocrine carcinomas (NECs), and mixed neuroendocrine-non-neuroendocrine neoplasms. International clinical guidelines [3, 4] acknowledge GEP-NET G3 and GEP-NECs under the overarching concept of HG GEP-NENs but emphasize differences in prognosis and treatment between GEP-NET G3 and GEP-NECs. The prognosis of GEP-NECs is poor, with a median overall survival (OS) of less than 1 year in advanced patients, and the first-line treatment is platinum-based chemotherapy (PBC) [5, 6].

In previous studies, the Ki-67 index has been considered an important marker for distinguishing high-grade GEP-NENs subtypes. The Nordic NEC study [5] and other studies have shown that a Ki-67 cutoff of 55% helps better stratify HG GEP-NENs patients [7, 9, 10]. This study aims to explore the genomic and transcriptomic characteristics of these high-grade GEP-NENs and their impact on prognosis and potential therapeutic predictions.

Research Origin

This article was written by Valentina Angerilli, Giovanna Sabella, Michele Simbolo, Vincenzo Lagano, Giovanni Centonze, Marco Gentili, Alessandro Mangogna, Jorgelina Coppa, Giada Munari, Gianluca Businello, Chiara Borga, Francesca Schiavi, Sara Pusceddu, Rita Leporati, Simone Oldani, Matteo Fassan, and Massimo Milione. The authors are affiliated with the Department of Medicine at the University of Padova, the National Cancer Institute in Milan, the University and Hospital of Verona, the University of Udine, and the National Cancer Institute in Milan, Italy. The paper was published in the British Journal of Cancer on May 10, 2024.

Research Process

Pathological and Sample Analysis

This study included 49 cases of high-grade GEP-NENs from 2010 to 2020. Samples were analyzed using histopathology, immunohistochemistry, genomic and transcriptomic sequencing. Exclusion criteria included: mixed neuroendocrine and non-neuroendocrine components, insufficient material for next-generation sequencing (NGS) analysis, and non-GEP origin tumors.

Immunohistochemical Analysis

Markers detected included: common neuroendocrine markers (chromogranin-A and synaptophysin), Ki-67 labeling index, RB1, p53, SSTR-2A, and PD-L1. Detailed immunohistochemical data of these high-grade GEP-NENs were provided through the combined assessment of three pathologists.

Genomic and Transcriptomic Sequencing

Detailed genomic analysis was performed on samples using the NGS method. The Trusight Oncology 500 (TSO500) platform was used to sequence 120 ng of DNA and 200 ng of RNA for each sample. For RNA sequencing, the Smarter Stranded Total RNA-Seq Kit V3 - Pico Input Mammalian library preparation was conducted and sequenced.

Data Processing and Analysis

Tools like FASTQC were used to check the quality of sequencing reads. Various bioinformatics software and methods, including Star, RSeQC, DEseq2, and GSEA, were utilized in data analysis. The analysis focused on differential gene expression and pan-cancer characteristics related to cancer and biological features.

Main Results

Case Characteristics and Distribution

Among the 49 patients, there were 21 cases of GEP-NET G3, 12 cases of GEP-NEC <55%, and 16 cases of GEP-NEC ≥55%. These tumors primarily occurred in the pancreas (44.9%), colorectal (24.4%), and stomach (14.3%). GEP-NET G3 patients had a higher incidence of pancreatic primary tumors.

Immunohistochemical Results

Immunohistochemical analysis showed abnormal expression of p53 in 55.1% of tumors, RB1 loss in 50% of GEP-NEC ≥55%. SSTR-2A expression was higher in GEP-NET G3, while SSTR-2A deficiency was more common in GEP-NEC <55% and GEP-NEC ≥55%.

Genomic Analysis

Genomic analysis revealed common mutations in genes such as TP53, APC, KRAS, and MEN1. GEP-NEC ≥55% and GEP-NEC <55% shared many mutations, including TP53 and APC, but more mutations in MEN1 and VHL were concentrated in GEP-NET G3. In addition, GEP-NET G3 showed genomic features similar to pancreatic NETs G1/G2.

Transcriptomic Analysis

RNA sequencing and differential gene expression analysis showed significant gene expression differences between GEP-NET G3 and GEP-NECs, but no significant differences in gene expression between GEP-NEC <55% and GEP-NEC ≥55%. Gene set enrichment analysis indicated that WNT-β-catenin and MYC signaling pathways were more common in GEP-NECs, while pancreatic β-cell characteristics were associated with GEP-NET G3.

Conclusion

This study demonstrates significant genomic and transcriptomic differences between GEP-NET G3 and GEP-NECs. However, GEP-NEC <55% and GEP-NEC ≥55% may belong to the same spectrum at the molecular level, despite differences in clinical manifestations and chemotherapy responses. Furthermore, the research provides molecular discoveries with prognostic and potential therapeutic value, offering new perspectives for precision medicine in high-grade GEP-NENs patients.

Research Highlights

1. Genomic Heterogeneity: Revealed significant genomic heterogeneity in high-grade GEP-NENs, with different subgroups showing different gene expression and mutation profiles.
2. Transcriptomic Data: Conducted an in-depth analysis of the transcriptome of high-grade GEP-NENs for the first time, highlighting differences in pathomechanisms among subgroups.
3. Prognostic Markers: Established the prognostic value of molecular markers like RB1 loss and TP53 mutations and pointed out their association with specific immune microenvironments.

Research Significance

This study provides new insights into the molecular characteristics of high-grade GEP-NENs and proposes new recommendations and directions for better clinical classification and treatment of these tumors. Future research can build on these findings to further validate them and explore new therapeutic strategies.