Driver mutations occur frequently in metastases of well-differentiated small intestine neuroendocrine tumours

Small intestinal neuroendocrine tumors lack early genomic drivers, acquire DNA repair defects and harbor hallmarks of low REST expression

The tumorigenesis of small intestinal neuroendocrine tumors (siNETs) is not understood and comprehensive genomic and transcriptomic data sets are limited. Therefore, we performed whole genome and transcriptome analysis of 39 well differentiated siNET samples. Our genomic data revealed a lack of recurrent driver mutations and demonstrated that multifocal siNETs from individual patients can arise genetically independently. We detected germline mutations in Fanconi anemia DNA repair pathway (FANC) genes, involved in homologous recombination (HR) DNA repair, in 9% of patients and found mutational signatures of defective HR DNA repair in late-stage tumor evolution. Furthermore, transcriptomic analysis revealed low expression of the transcriptional repressor REST. Summarizing, we identify a novel common transcriptomic signature of siNETs and demonstrate that genomic alterations alone do not explain initial tumor formation, while impaired DNA repair likely contributes to tumor evolution and represents a potential pharmaceutical target in a subset of patients.

Biomarkers to Inform Prognosis and Treatment for Unresectable or Metastatic GEP-NENs

Importance

Evidence-based treatment decisions for advanced gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) require individualized patient-centered decision-making that accounts for patient and cancer characteristics.

Objective

To create an accessible guidance document to educate clinicians and patients on biomarkers informing prognosis and treatment in unresectable or metastatic GEP-NENs.

Methods

A multidisciplinary panel in-person workshop was convened to define methods. English language articles published from January 2016 to January 2023 in PubMed (MEDLINE) and relevant conference abstracts were reviewed to investigate prognostic and treatment-informing features in unresectable or metastatic GEP-NENs. Data from included studies were used to form evidence-based recommendations. Quality of evidence and strength of recommendations were determined using the Grading of Recommendations, Assessment, Development and Evaluations framework. Consensus was reached via electronic survey following a modified Delphi method.

Findings

A total of 131 publications were identified, including 8 systematic reviews and meta-analyses, 6 randomized clinical trials, 29 prospective studies, and 88 retrospective cohort studies. After 2 rounds of surveys, 24 recommendations and 5 good clinical practice statements were developed, with full consensus among panelists. Recommendations focused on tumor and functional imaging characteristics, blood-based biomarkers, and carcinoid heart disease. A single strong recommendation was made for symptomatic carcinoid syndrome informing treatment in midgut neuroendocrine tumors. Conditional recommendations were made to use grade, morphology, primary site, and urinary 5-hydroxyindoleacetic levels to inform treatment. The guidance document was endorsed by the Commonwealth Neuroendocrine Tumour Collaboration and the North American Neuroendocrine Tumor Society.

Conclusions and Relevance

The study results suggest that select factors have sufficient evidence to inform care in GEP-NENs, but the evidence for most biomarkers is weak. This article may help guide management and identify gaps for future research to advance personalized medicine and improve outcomes for patients with GEP-NENs.

Gastroenteropancreatic neuroendocrine neoplasms: epidemiology, genetics, and treatment

The incidence of gastroenteropancreatic neuroendocrine neoplasms (GEP NEN) is increasing at a rapid pace and is becoming an increasingly important consideration in clinical care. Epidemiological data from multiple countries indicate that the incidence of gastroenteropancreatic neuroendocrine neoplasms (GEP NEN) exhibits regional, site-specific, and gender-based variations. While the genetics and pathogenesis of some GEP NEN, particularly pancreatic NENs, have been investigated, there are still many mechanisms that require further investigation. The management of GEP NEN is diverse, but surgery remains the primary option for most cases. Peptide receptor radionuclide therapy (PRRT) is an effective treatment, and several clinical trials are exploring the potential of immunotherapy and targeted therapy, as well as combination therapy.

Molecular Classification of Gastrointestinal and Pancreatic Neuroendocrine Neoplasms: Are We Ready for That?

In the last two decades, the increasing availability of technologies for molecular analyses has allowed an insight in the genomic alterations of neuroendocrine neoplasms (NEN) of the gastrointestinal tract and pancreas. This knowledge has confirmed, supported, and informed the pathological classification of NEN, clarifying the differences between neuroendocrine carcinomas (NEC) and neuroendocrine tumors (NET) and helping to define the G3 NET category. At the same time, the identification genomic alterations, in terms of gene mutation, structural abnormalities, and epigenetic changes differentially involved in the pathogenesis of NEC and NET has identified potential molecular targets for precision therapy. This review critically recapitulates the available molecular features of digestive NEC and NET, highlighting their correlates with pathological aspects and clinical characteristics of these neoplasms and revising their role as predictive biomarkers for targeted therapy. In this context, the feasibility and applicability of a molecular classification of gastrointestinal and pancreatic NEN will be explored.

Multi-omic dataset of patient-derived tumor organoids of neuroendocrine neoplasms

BACKGROUND

Organoids are 3-dimensional experimental models that summarize the anatomical and functional structure of an organ. Although a promising experimental model for precision medicine, patient-derived tumor organoids (PDTOs) have currently been developed only for a fraction of tumor types.

RESULTS

We have generated the first multi-omic dataset (whole-genome sequencing [WGS] and RNA-sequencing [RNA-seq]) of PDTOs from the rare and understudied pulmonary neuroendocrine tumors (n = 12; 6 grade 1, 6 grade 2) and provide data from other rare neuroendocrine neoplasms: small intestine (ileal) neuroendocrine tumors (n = 6; 2 grade 1 and 4 grade 2) and large-cell neuroendocrine carcinoma (n = 5; 1 pancreatic and 4 pulmonary). This dataset includes a matched sample from the parental sample (primary tumor or metastasis) for a majority of samples (21/23) and longitudinal sampling of the PDTOs (1 to 2 time points), for a total of n = 47 RNA-seq and n = 33 WGS. We here provide quality control for each technique and the raw and processed data as well as all scripts for genomic analyses to ensure an optimal reuse of the data. In addition, we report gene expression data and somatic small variant calls and describe how they were generated, in particular how we used WGS somatic calls to train a random forest classifier to detect variants in tumor-only RNA-seq. We also report all histopathological images used for medical diagnosis: hematoxylin and eosin-stained slides, brightfield images, and immunohistochemistry images of protein markers of clinical relevance.

CONCLUSIONS

This dataset will be critical to future studies relying on this PDTO biobank, such as drug screens for novel therapies and experiments investigating the mechanisms of carcinogenesis in these understudied diseases.

Clinicopathological and genetic characteristics of gastric neuroendocrine tumour (NET) G3 and comparisons with neuroendocrine carcinoma and NET G2

AIMS

To characterise the clinicopathological and genetic characteristics of gastric neuroendocrine tumour G3 (gNET G3) and to compare them with those of gastric neuroendocrine carcinoma (gNEC) and gNET G2.

METHODS AND RESULTS

A total of 115 gastric neuroendocrine neoplasms (NENs) were included, of which gNET G3 was different from gNET G1/G2 in terms of tumour location (P = 0.029), number (P = 0.003), size (P = 0.010), the Ki67 index (P < 0.001), lymph node metastasis (P < 0.001) and TNM stage (P = 0.011), and different from gNEC/gastric mixed neuroendocrine-non-neuroendocrine neoplasm (gMiNEN) in terms of tumour size (P = 0.010) and the Ki67 index (P = 0.001). High-resolution copy number (CN) profiling and validation experiments showed CN gains and high expression of DLL3 in gNET G3. Hierarchical clustering analysis based on CN characteristics showed that gNET G3 was separated from gNEC but mixed with gNET G2. In gene set enrichment analysis, eight pathways were significantly enriched in gNEC when comparing gNET G3 and gNEC (P < 0.05), while no pathways were enriched when comparing gNET G3 and gNET G2. Whole-exome sequencing and validation experiments showed nonsense mutation of TP53 in one gNET G3, with wild-type staining for p53. In gNEC, TP53 mutations were detected in four of eight cases, and abnormal expression of p53 was detected in all cases.

CONCLUSION

Gastric NET G3 is a distinct entity with unique genetic characteristics, which are different from those of gNEC than gNET G2. Our results provide insight into some molecular alterations that may contribute to the development and progression of gNET G3 and serve as potential therapeutic targets.

Multiomic sequencing of paired primary and metastatic small bowel carcinoids

Background: Small bowel carcinoids are insidious tumors that are often metastatic when diagnosed. Limited mutation landscape studies of carcinoids indicate that these tumors have a relatively low mutational burden. The development of targeted therapies will depend upon the identification of mutations that drive the pathogenesis and metastasis of carcinoid tumors. Methods: Whole exome and RNA sequencing of 5 matched sets of normal tissue, primary small intestine carcinoid tumors, and liver metastases were investigated. Germline and somatic variants included: single nucleotide variants (SNVs), insertions/deletions (indels), structural variants, and copy number alterations (CNAs). The functional impact of mutations was predicted using Ensembl Variant Effect Predictor. Results: Large-scale CNAs were observed including the loss of chromosome 18 in all 5 metastases and 3/5 primary tumors. Certain somatic SNVs were metastasis-specific; including mutations in ATRX, CDKN1B, MXRA5 (leading to the activation of a cryptic splice site and loss of mRNA), SMARCA2, and the loss of UBE4B. Additional mutations in ATRX, and splice site loss of PYGL, leading to intron retention observed in primary and metastatic tumors. Conclusions: We observed novel mutations in primary/metastatic carcinoid tumor pairs, and some have been observed in other types of neuroendocrine tumors. We confirmed a previously observed loss of chromosome 18 and CDKN1B. Transcriptome sequencing added relevant information that would not have been appreciated with DNA sequencing alone. The detection of several splicing mutations on the DNA level and their consequences at the RNA level suggests that RNA splicing aberrations may be an important mechanism underlying carcinoid tumors.

Targeted Genomic Profiling and Chemotherapy Outcomes in Grade 3 Gastro-Entero-Pancreatic Neuroendocrine Tumors (G3 GEP-NET)

BACKGROUND

Grade 3 gastro-entero-pancreatic neuroendocrine tumors (G3 GEP-NET) are poorly characterized in terms of molecular features and response to treatments.

METHODS

Patients with G3 GEP-NET were included if they received capecitabine and temozolomide (CAPTEM) or oxaliplatin with either 5-fluorouracile (FOLFOX) or capecitabine (XELOX) as first-line treatment (chemotherapy cohort). G3 NET which successfully undergone next-generation sequencing (NGS) were included in the NGS cohort.

RESULTS

In total, 49 patients were included in the chemotherapy cohort: 15 received CAPTEM and 34 received FOLFOX/XELOX. Objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were 42.9%, 9.0 months, and 33.6 months, respectively. Calculating a Ki67 cutoff using ROC curve analysis, tumors with Ki67 ≥ 40% had lower ORR (51.2% vs. 0%; p = 0.007) and shorter PFS (10.6 months vs. 4.4 months; p < 0.001) and OS (49.4 months vs. 10.0 months; p = 0.023). In patients who received FOLFOX/XELOX as a first-line treatment, ORR, PFS, and OS were 38.2%, 7.9 months, and 30.0 months, respectively. In the NGS cohort (N = 13), the most mutated genes were DAXX/ATRX (N = 5, 38%), MEN1 (N = 4, 31%), TP53 (N = 4, 31%), AKT1 (N = 2, 15%), and PIK3CA (N = 1, 8%).

CONCLUSIONS

FOLFOX/XELOX chemotherapy is active as the first-line treatment of patients with G3 GEP-NET. The mutational landscape of G3 NET is more similar to well-differentiated NETs than NECs.

Systematic Evaluation of the Immune Environment of Small Intestinal Neuroendocrine Tumors

PURPOSE

The immune tumor microenvironment and the potential therapeutic opportunities for immunotherapy in small intestinal neuroendocrine tumors (siNET) have not been fully defined.

EXPERIMENTAL DESIGN

Herein, we studied 40 patients with primary and synchronous metastatic siNETs, and matched blood and normal tissue obtained during surgery. We interrogated the immune checkpoint landscape using multi-parametric flow cytometry. In addition, matched FFPE tissue was obtained for multi-parametric IHC to determine the relative abundance and distribution of T-cell infiltrate. Tumor mutational burden (TMB) was also assessed and correlated with immune infiltration.

RESULTS

Effector tumor-infiltrating lymphocytes (TIL) had a higher expression of PD-1 in the tumor microenvironment compared with the periphery. In addition, CD8+ TILs had a significantly higher co-expression of PD-1/ICOS and PD-1/CTLA-4 (cytotoxic T lymphocyte antigen-4) and higher levels of PD-1 expression compared with normal tissue. IHC revealed that the majority of cases have ≤10% intra-tumoral T cells but a higher number of peri-tumoral T cells, demonstrating an "exclusion" phenotype. Finally, we confirmed that siNETs have a low TMB compared with other tumor types in the TCGA database but did not find a correlation between TMB and CD8/Treg ratio.

CONCLUSIONS

Taken together, these results suggest that a combination therapy approach will be required to enhance the immune response, using PD-1 as a checkpoint immunomodulator backbone in combination with other checkpoint targeting molecules (CTLA-4 or ICOS), or with drugs targeting other pathways to recruit "excluded" T cells into the tumor microenvironment to treat patients with siNETs.

Metastatic Neuroendocrine Neoplasms of Unknown Primary: Clues from Pathology Workup

Simple Summary

While most neuroendocrine neoplasms are indolent and slow-growing tumors, subsets of cases will spread beyond the tissue of origin. Given the rather slow progress, some lesions are incidentally discovered as metastatic deposits rather than primary masses. In these cases, a biopsy is often taken to allow the pathologist to identify the tumor type and possibly the primary tumor site via microscopic examination. In this review, the authors present a simplified guide on how to approach metastatic neuroendocrine tumors from a pathologist’s perspective.

Abstract

Neuroendocrine neoplasms (NENs) are diverse tumors arising in various anatomical locations and may therefore cause a variety of symptoms leading to their discovery. However, there are instances in which a NEN first presents clinically as a metastatic deposit, while the associated primary tumor is not easily identified using conventional imaging techniques because of small primary tumor sizes. In this setting (which is referred to as a “NEN of unknown primary”; NEN-UP), a tissue biopsy is often procured to allow the surgical pathologist to diagnose the metastatic lesion. If indeed a metastatic NEN-UP is found, several clues can be obtained from morphological assessment and immunohistochemical staining patterns that individually or in concert may help identify the primary tumor site. Herein, histological and auxiliary analyses of value in this context are discussed in order to aid the pathologist when encountering these lesions in clinical practice.

An update on the development of concepts, diagnostic criteria, and challenging issues for neuroendocrine neoplasms across different digestive organs

Digestive neuroendocrine neoplasms (NENs) are a group of heterogeneous neoplasms found throughout the digestive tract, with different behaviour and genetic background. In the last few years, nomenclature and WHO/UICC classifications of digestive NENs have changed, and molecular classifications have emerged, especially in pancreatic locations. Increasing patho-molecular details are needed to diagnose the different categories of NEN, including the use of helpful immunohistochemical markers. In this review, we address these topics in three successive chapters. We first briefly review recent updates in classifications, discuss important grading and proliferating issues and advances in the molecular understanding of NEN. Then, we provide an update on diagnosis, including the most important differential diagnoses of NEN, with a focus on high-grade neoplasms and mixed tumours. Finally, we highlight a variety of currently used and next-generation predictive and prognostic biomarkers as well as biomarkers of tumour origin and describe some site specificities of gastrointestinal NEN. We specifically focus on biomarkers available to pathologists with the potential to change the way patients with NEN are diagnosed and treated.

Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning

Over the past years, large consortia have been established to fuel the sequencing of whole genomes of many cancer patients. Despite the increased abundance in tools to study the impact of SNVs, non-coding SVs have been largely ignored in these data. Here, we introduce svMIL2, an improved version of our Multiple Instance Learning-based method to study the effect of somatic non-coding SVs disrupting boundaries of TADs and CTCF loops in 1646 cancer genomes. We demonstrate that svMIL2 predicts pathogenic non-coding SVs with an average AUC of 0.86 across 12 cancer types, and identifies non-coding SVs affecting well-known driver genes. The disruption of active (super) enhancers in open chromatin regions appears to be a common mechanism by which non-coding SVs exert their pathogenicity. Finally, our results reveal that the contribution of pathogenic non-coding SVs as opposed to driver SNVs may highly vary between cancers, with notably high numbers of genes being disrupted by pathogenic non-coding SVs in ovarian and pancreatic cancer. Taken together, our machine learning method offers a potent way to prioritize putatively pathogenic non-coding SVs and leverage non-coding SVs to identify driver genes. Moreover, our analysis of 1646 cancer genomes demonstrates the importance of including non-coding SVs in cancer diagnostics.

CD3+, CD8+, CD4+ and FOXP3+ T Cells in the Immune Microenvironment of Small Bowel Neuroendocrine Tumors

The role of inflammation in neuroendocrine tumors is poorly known. The purpose of this study was to characterize the densities of CD3⁺, CD8⁺, CD4⁺ and FOXP3⁺ T cells in small bowel neuroendocrine tumors (SB-NETs), SB-NET lymph node metastases and gastric neuroendocrine tumors (G-NETs) to assess the prognostic role of immune cell infiltrates in SB-NETs. The final cohort included 113 SB-NETs, 75 SB-NET lymph node metastases and 19 G-NETs from two Finnish hospitals. CD3⁺- and CD8⁺-based immune cell score (ICS), and other T cell densities were evaluated. Survival analyses of SB-NETs and SB-NET lymph node metastases were performed with the Kaplan-Meier method and Cox regression adjusted for confounders. The primary outcome was disease-specific survival (DSS). No significant difference in DSS was seen between low and high ICS groups in SB-NETs at 5 years (92.6% vs. 87.8%) or 10 years (53.8% vs. 79.4%), p = 0.507, or in SB-NET lymph node metastases at 5 years (88.9% vs. 90.4%) or 10 years (71.1% vs. 59.8%), p = 0.466. Individual densities of the examined T cell types showed no correlation with prognosis either. SB-NETs and lymph node metastases had similar inflammatory cell profiles, whereas in G-NETs CD3⁺ and CD8⁺ T cells were particularly more abundant. In SB-NETs, ICS or T cell densities showed no correlation with prognosis.