Evaluating gastroenteropancreatic neuroendocrine tumors through microRNA sequencing

A randomized phase II trial of Captem or Folfiri as second-line therapy in neuroendocrine carcinomas

BACKGROUND

Neuroendocrine Carcinomas (NECs) prognosis is poor.No standard second-line therapy is currently recognized after failure of platinum-based first-line treatment. FOLFIRI and CAPTEM regimens have shown promising activity in preliminary studies. We aimed to evaluate these regimens in metastatic NEC patients.

METHODS

This is an open-label, multicenter, randomized non-comparative phase II trial to evaluate the activity and safety of FOLFIRI or CAPTEM in metastatic NEC patients. Primary endpoints were the 12 weeks-Disease Control Rate (12w-DCR) by investigator assessment per RECIST v1.1 and safety per CTCAE v5.0. Additional endpoints included overall response rate (ORR), progression-free survival (PFS) and overall survival (OS). Patients' serum samples were subject to NGS miRNome profiling in comparison with healthy donors to reveal differentially expressed miRNAs as candidate circulating biomarkers.

RESULTS

The study was halted for futility at interim analysis, as the minimum 12w-DCR threshold of 10 out of 25 patients required for the first step was not reached. From 06/03/2017 to 18/01/2021, 53 out of 112 patients were enrolled. Median follow-up was 22.6 months (range: 1.4-60.4). The 12w-DCR was 39.1 % in the FOLFIRI arm and 28.0 % in the CAPTEM arm. In the FOLFIRI subgroup the 12-months OS rate was 28.4 % (95 % CI: 12.7-46.5) while in the CAPTEM subgroup it was 32.4 % (95 % CI: 14.9-51.3). The most common G3-G4 side effects were neutropenia (n = 5, 18.5 %) and anemia (n = 2, 7.4 %) for FOLFIRI and G3-G4 thrombocytopenia (n = 2, 8.0 %), G4 nausea/vomiting (n = 1, 4.0 %) for CAPTEM. Three microRNAs emerged as NEC independent predictors. High expression values were found to be significantly associated with decreased PFS and OS.

CONCLUSION

The safety profile of FOLFIRI and CAPTEM was manageable. FOLFIRI and CAPTEM chemotherapy showed comparable activity in the second-line setting after progression on etoposide/platinum.

CLINICALTRIALS

GOV IDENTIFIER

NCT03387592.

Gastroenteropancreatic neuroendocrine tumors: Epigenetic landscape and clinical implications

Neuroendocrine tumors (NETs) are a rare, heterogenous group of neoplasms arising from cells of the neuroendocrine system. Amongst solid tumor malignancies, NETs are notable for overall genetic stability and recent data supports the notion that epigenetic changes may drive NET pathogenesis. In this review, major epigenetic mechanisms of NET pathogenesis are reviewed, including changes in DNA methylation, histone modification, chromatin remodeling, and microRNA. Prognostic implications of the above are discussed, as well as the expanding diagnostic utility of epigenetic markers in NETs. Lastly, preclinical and clinical evaluations of epigenetically targeted therapies in NETs and are reviewed, with a focus on future directions in therapeutic advancement.

A neuroendocrine biomarker revolution from monoanalyte to multianalyte biomarkers in non-functioning gastro-entero-pancreatic neuroendocrine neoplasms

Neuroendocrine neoplasms (NENs) arise from neuroendocrine cells in a wide variety of organs. One of the most affected disease sites is the gastrointestinal system, which originates the gastro-entero-pancreatic NENs (GEP-NENs), a heterogenous group of malignancies that are rapidly increasing in incidence. These tumors can be functioning, with secretory activity leading to identifiable clinical syndromes, or non-functioning, with no secretory activity but with local symptoms of tumor growth and metastasis. A limitation in biomarkers is a crucial unmet need in non-secretory NEN management, as clinical decision-making is made more difficult by obstacles in tumor classification, prognostic evaluation, assessment of treatment response and surveillance. The objective of this review is to present existing and novel biomarkers for NENs that can function as prognostic factors and monitor disease progression or regression longitudinally, with a special emphasis on innovative research into novel multianalyte biomarkers.

Evaluation of a blood miRNA/mRNA signature to follow-up Lu-PRRT therapy for G1/G2 intestinal neuroendocrine tumors

Background

177Lu-oxodotreotide peptide receptor therapy (LuPRRT) is an efficient treatment for midgut neuroendocrine tumors (NETs) of variable radiological response. Several clinical, biological, and imaging parameters may be used to establish a relative disease prognosis but none is able to predict early efficacy or toxicities. We investigated expression levels for mRNA and miRNA involved in radiosensitivity and tumor progression searching for correlations related to patient outcome during LuPRRT therapy.

Methods

Thirty-five patients received LuPRRT for G1/G2 midgut NETs between May 2019 and September 2021. Peripheral blood samples were collected prior to irradiation, before and 48 h after the second and the fourth LuPRRT, and at 6-month follow-up. Multiple regression analyses and Pearson correlations were performed to identify the miRNA/mRNA signature that will best predict response to LuPRRT.

Results

Focusing on four mRNAs and three miRNAs, we identified a miRNA/mRNA signature enabling the early identification of responders to LuPRRT with significant reduced miRNA/mRNA expression after the first LuPRRT administration for patients with progressive disease at 1 year (p < 0.001). The relevance of this signature was reinforced by studying its evolution up to 6 months post-LuPRRT. Moreover, nadir absolute lymphocyte count within the first 2 months after the first LuPRRT administration was significantly related to low miRNA/mRNA expression level (p < 0.05) for patients with progressive disease.

Conclusion

We present a pilot study exploring a miRNA/mRNA signature that correlates with early hematologic toxicity and therapeutic response 12 months following LuPRRT. This signature will be tested prospectively in a larger series of patients.

Recent developments in the diagnosis of pancreatic neuroendocrine neoplasms

INTRODUCTION

Pancreatic Neuroendocrine Neoplasms (PanNENs) are characterized by a highly heterogeneous clinical and biological behavior, making their diagnosis challenging. PanNENs diagnostic work-up mainly relies on biochemical markers, pathological examination, and imaging evaluation. The latter includes radiological imaging (i.e. computed tomography [CT] and magnetic resonance imaging [MRI]), functional imaging (i.e. 68Gallium [68 Ga]Ga-DOTA-peptide PET/CT and Fluorine-18 fluorodeoxyglucose [18F]FDG PET/CT), and endoscopic ultrasound (EUS) with its associated procedures.

AREAS COVERED

This review provides a comprehensive assessment of the recent advancements in the PanNENs diagnostic field. PubMed and Embase databases were used for the research, performed from inception to October 2023.

EXPERT OPINION

A deeper understanding of PanNENs biology, recent technological improvements in imaging modalities, as well as progresses achieved in molecular and cytological assays, are fundamental players for the achievement of early diagnosis and enhanced preoperative characterization of PanNENs. A multimodal diagnostic approach is required for a thorough disease assessment.

Spatial profiling reveals tissue-specific neuro-immune interactions in gastroenteropancreatic neuroendocrine tumors

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are heterogeneous malignancies that arise from complex cellular interactions within the tissue microenvironment. Here, we sought to decipher tumor-derived signals from the surrounding microenvironment by applying digital spatial profiling (DSP) to hormone-secreting and non-functional GEP-NETs. By combining this approach with in vitro studies of human-derived organoids, we demonstrated the convergence of cell autonomous immune and pro-inflammatory proteins that suggests their role in neuroendocrine differentiation and tumorigenesis. DSP was used to evaluate the expression of 40 neural- and immune-related proteins in surgically resected duodenal and pancreatic NETs (n = 20) primarily consisting of gastrinomas (18/20). A total of 279 regions of interest were examined between tumors, adjacent normal and abnormal-appearing epithelium, and the surrounding stroma. The results were stratified by tissue type and multiple endocrine neoplasia I (MEN1) status, whereas protein expression was validated by immunohistochemistry (IHC). A tumor immune cell autonomous inflammatory signature was further evaluated by IHC and RNAscope, while functional pro-inflammatory signaling was confirmed using patient-derived duodenal organoids. Gastrin-secreting and non-functional pancreatic NETs showed a higher abundance of immune cell markers and immune infiltrate compared with duodenal gastrinomas. Compared with non-MEN1 tumors, MEN1 gastrinomas and preneoplastic lesions showed strong immune exclusion and upregulated expression of neuropathological proteins. Despite a paucity of immune cells, duodenal gastrinomas expressed the pro-inflammatory and pro-neural factor IL-17B. Treatment of human duodenal organoids with IL-17B activated NF-κB and STAT3 signaling and induced the expression of neuroendocrine markers. In conclusion, multiplexed spatial protein analysis identified tissue-specific neuro-immune signatures in GEP-NETs. Duodenal gastrinomas are characterized by an immunologically cold microenvironment that permits cellular reprogramming and neoplastic transformation of the preneoplastic epithelium. Moreover, duodenal gastrinomas cell autonomously express immune and pro-inflammatory factors, including tumor-derived IL-17B, that stimulate the neuroendocrine phenotype. © 2024 The Pathological Society of Great Britain and Ireland.

Prioritization of Fluorescence In Situ Hybridization (FISH) Probes for Differentiating Primary Sites of Neuroendocrine Tumors with Machine Learning

Determining neuroendocrine tumor (NET) primary sites is pivotal for patient care as pancreatic NETs (pNETs) and small bowel NETs (sbNETs) have distinct treatment approaches. The diagnostic power and prioritization of fluorescence in situ hybridization (FISH) assay biomarkers for establishing primary sites has not been thoroughly investigated using machine learning (ML) techniques. We trained ML models on FISH assay metrics from 85 sbNET and 59 pNET samples for primary site prediction. Exploring multiple methods for imputing missing data, the impute-by-median dataset coupled with a support vector machine model achieved the highest classification accuracy of 93.1% on a held-out test set, with the top importance variables originating from the ERBB2 FISH probe. Due to the greater interpretability of decision tree (DT) models, we fit DT models to ten dataset splits, achieving optimal performance with k-nearest neighbor (KNN) imputed data and a transformation to single categorical biomarker probe variables, with a mean accuracy of 81.4%, on held-out test sets. ERBB2 and MET variables ranked as top-performing features in 9 of 10 DT models and the full dataset model. These findings offer probabilistic guidance for FISH testing, emphasizing the prioritization of the ERBB2, SMAD4, and CDKN2A FISH probes in diagnosing NET primary sites.

Application of Machine Learning in Predicting Hepatic Metastasis or Primary Site in Gastroenteropancreatic Neuroendocrine Tumors

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) account for 80% of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). GEP-NETs are well-differentiated tumors, highly heterogeneous in biology and origin, and are often diagnosed at the metastatic stage. Diagnosis is commonly through clinical symptoms, histopathology, and PET-CT imaging, while molecular markers for metastasis and the primary site are unknown. Here, we report the identification of multi-gene signatures for hepatic metastasis and primary sites through analyses on RNA-SEQ datasets of pancreatic and small intestinal NETs tissue samples. Relevant gene features, identified from the normalized RNA-SEQ data using the mRMRe algorithm, were used to develop seven Machine Learning models (LDA, RF, CART, k-NN, SVM, XGBOOST, GBM). Two multi-gene random forest (RF) models classified primary and metastatic samples with 100% accuracy in training and test cohorts and >90% accuracy in an independent validation cohort. Similarly, three multi-gene RF models identified the pancreas or small intestine as the primary site with 100% accuracy in training and test cohorts, and >95% accuracy in an independent cohort. Multi-label models for concurrent prediction of hepatic metastasis and primary site returned >98.42% and >87.42% accuracies on training and test cohorts, respectively. A robust molecular signature to predict liver metastasis or the primary site for GEP-NETs is reported for the first time and could complement the clinical management of GEP-NETs.

The uprise of RNA biology in neuroendocrine neoplasms: altered splicing and RNA species unveil translational opportunities

Neuroendocrine neoplasms (NENs) comprise a highly heterogeneous group of tumors arising from the diffuse neuroendocrine system. NENs mainly originate in gastrointestinal, pancreatic, and pulmonary tissues, and despite being rare, show rising incidence. The molecular mechanisms underlying NEN development are still poorly understood, although recent studies are unveiling their genomic, epigenomic and transcriptomic landscapes. RNA was originally considered as an intermediary between DNA and protein. Today, compelling evidence underscores the regulatory relevance of RNA processing, while new RNA molecules emerge with key functional roles in core cell processes. Indeed, correct functioning of the interrelated complementary processes comprising RNA biology, its processing, transport, and surveillance, is essential to ensure adequate cell homeostasis, and its misfunction is related to cancer at multiple levels. This review is focused on the dysregulation of RNA biology in NENs. In particular, we survey alterations in the splicing process and available information implicating the main RNA species and processes in NENs pathology, including their role as biomarkers, and their functionality and targetability. Understanding how NENs precisely (mis)behave requires a profound knowledge at every layer of their heterogeneity, to help improve NEN management. RNA biology provides a wide spectrum of previously unexplored processes and molecules that open new avenues for NEN detection, classification and treatment. The current molecular biology era is rapidly evolving to facilitate a detailed comprehension of cancer biology and is enabling the arrival of personalized, predictive and precision medicine to rare tumors like NENs.

A Computational Approach to Identification of Candidate Biomarkers in High-Dimensional Molecular Data

Complex high-dimensional datasets that are challenging to analyze are frequently produced through ‘-omics’ profiling. Typically, these datasets contain more genomic features than samples, limiting the use of multivariable statistical and machine learning-based approaches to analysis. Therefore, effective alternative approaches are urgently needed to identify features-of-interest in ‘-omics’ data. In this study, we present the molecular feature selection tool, a novel, ensemble-based, feature selection application for identifying candidate biomarkers in ‘-omics’ data. As proof-of-principle, we applied the molecular feature selection tool to identify a small set of immune-related genes as potential biomarkers of three prostate adenocarcinoma subtypes. Furthermore, we tested the selected genes in a model to classify the three subtypes and compared the results to models built using all genes and all differentially expressed genes. Genes identified with the molecular feature selection tool performed better than the other models in this study in all comparison metrics: accuracy, precision, recall, and F1-score using a significantly smaller set of genes. In addition, we developed a simple graphical user interface for the molecular feature selection tool, which is available for free download. This user-friendly interface is a valuable tool for the identification of potential biomarkers in gene expression datasets and is an asset for biomarker discovery studies.

Identification of functional pathways and molecular signatures in neuroendocrine neoplasms by multi-omics analysis

BACKGROUND

Neuroendocrine neoplasms (NENs) represent a heterogeneous class of rare tumors with increasing incidence. They are characterized by the ability to secrete peptide hormones and biogenic amines but other reliable biomarkers are lacking, making diagnosis and identification of the primary site very challenging. While in some NENs, such as the pancreatic ones, next generation sequencing technologies allowed the identification of new molecular hallmarks, our knowledge of the molecular profile of NENs from other anatomical sites is still poor.

METHODS

Starting from the concept that NENs from different organs may be clinically and genetically correlated, we applied a multi-omics approach by combining multigene panel testing, CGH-array, transcriptome and miRNome profiling and computational analyses, with the aim to highlight common molecular and functional signatures of gastroenteropancreatic (GEP)-NENs and medullary thyroid carcinomas (MTCs) that could aid diagnosis, prognosis and therapy.

RESULTS

By comparing genomic and transcriptional profiles, ATM-dependent signaling emerged among the most significant pathways at multiple levels, involving gene variations and miRNA-mediated regulation, thus representing a novel putative druggable pathway in these cancer types. Moreover, a set of circulating miRNAs was also selected as possible diagnostic/prognostic biomarkers useful for clinical management of NENs.

CONCLUSIONS

These findings depict a complex molecular and functional landscape of NENs, shedding light on novel therapeutic targets and disease biomarkers to be exploited.

Novel MicroRNA-Regulated Transcript Networks Are Associated with Chemotherapy Response in Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is a highly lethal gynecologic cancer, in part due to resistance to platinum-based chemotherapy reported among 20% of patients. This study aims to generate novel hypotheses of the biological mechanisms underlying chemotherapy resistance, which remain poorly understood. Differential expression analyses of mRNA- and microRNA-sequencing data from HGSOC patients of The Cancer Genome Atlas identified 21 microRNAs associated with angiogenesis and 196 mRNAs enriched for adaptive immunity and translation. Coexpression network analysis identified three microRNA networks associated with chemotherapy response enriched for lipoprotein transport and oncogenic pathways, as well as two mRNA networks enriched for ubiquitination and lipid metabolism. These network modules were replicated in two independent ovarian cancer cohorts. Moreover, integrative analyses of the mRNA/microRNA sequencing and single-nucleotide polymorphisms (SNPs) revealed potential regulation of significant mRNA transcripts by microRNAs and SNPs (expression quantitative trait loci). Thus, we report novel transcriptional networks and biological pathways associated with resistance to platinum-based chemotherapy in HGSOC patients. These results expand our understanding of the effector networks and regulators of chemotherapy response, which will help to improve the management of ovarian cancer.

Artificial Intelligence and Machine Learning in the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms—A Scoping Review

Neuroendocrine neoplasms (NENs) and tumors (NETs) are rare neoplasms that may affect any part of the gastrointestinal system. In this scoping review, we attempt to map existing evidence on the role of artificial intelligence, machine learning and deep learning in the diagnosis and management of NENs of the gastrointestinal system. After implementation of inclusion and exclusion criteria, we retrieved 44 studies with 53 outcome analyses. We then classified the papers according to the type of studied NET (26 Pan-NETs, 59.1%; 3 metastatic liver NETs (6.8%), 2 small intestinal NETs, 4.5%; colorectal, rectal, non-specified gastroenteropancreatic and non-specified gastrointestinal NETs had from 1 study each, 2.3%). The most frequently used AI algorithms were Supporting Vector Classification/Machine (14 analyses, 29.8%), Convolutional Neural Network and Random Forest (10 analyses each, 21.3%), Random Forest (9 analyses, 19.1%), Logistic Regression (8 analyses, 17.0%), and Decision Tree (6 analyses, 12.8%). There was high heterogeneity on the description of the prediction model, structure of datasets, and performance metrics, whereas the majority of studies did not report any external validation set. Future studies should aim at incorporating a uniform structure in accordance with existing guidelines for purposes of reproducibility and research quality, which are prerequisites for integration into clinical practice.

An update on the diagnosis of gastroenteropancreatic neuroendocrine neoplasms

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) arise from neuroendocrine cells found throughout the gastrointestinal tract and islet cells of the pancreas. The incidence and prevalence of GEP-NENs have been increasing each year due to higher awareness, improved diagnostic modalities, and increased incidental detection on cross-sectional imaging and endoscopy for cancer screening and other conditions and symptoms. GEP-NENs are a heterogeneous group of tumors and have a wide range in clinical presentation, histopathologic features, and molecular biology. Clinical presentation most commonly depends on whether the GEP-NEN secretes an active hormone. The World Health Organization recently updated the classification of GEP-NENs to introduce a distinction between high-grade neuroendocrine tumors and neuroendocrine carcinomas, which can be identified using histology and molecular studies and are more aggressive with a worse prognosis compared to high-grade neuroendocrine tumors. As our understanding of the biology of GEP-NENs has grown, new and improved diagnostic modalities can be developed and optimized. Here, we discuss clinical features and updates in diagnosis, including histopathological analysis, biomarkers, molecular techniques, and radiology of GEP-NENs. We review established diagnostic tests and discuss promising novel diagnostic tests that are currently in development or require further investigation and validation prior to broad utilization in patient care.

Pancreatic Neuroendocrine Neoplasms: Updates on Genomic Changes in Inherited Tumour Syndromes and Sporadic Tumours Based on WHO Classification

Pancreatic neuroendocrine neoplasms (PanNENs) are the neuroendocrine neoplasms with greatest rate of increase in incidence. Approximately 10% of PanNENs arise as inherited tumour syndromes which include multiple endocrine neoplasia type 1, multiple endocrine neoplasia type 4, von Hippel-Lindau syndrome, neurofibromatosis type1, tuberous sclerosis complex 1/2, Cowden syndrome, and Glucagon cell hyperplasia and neoplasia as well as familial insulinomatosis. In sporadic PanNENs, driver mutations in MEN1, DAXX/ATRX and mTOR pathway genes are associated with development and progression in pancreatic neuroendocrine tumours. The other changes are in VEGF pathway, Notch pathway, germline mutations in MUTYH, CHEK2, BRCA2, PHLDA3 as well as other genetic alterations. On the other hand, pancreatic neuroendocrine carcinomas share similar genetic alterations with ductal adenocarcinomas, e.g., TP53, RB1 or KRAS. In addition, microRNA and changes in immune microenvironment were noted in PanNENs. Updates on these genetic knowledges contribute to the development of management strategies for patients with PanNENs.

Current and New Challenges in the Management of Pancreatic Neuroendocrine Tumors: The Role of miRNA-Based Approaches as New Reliable Biomarkers

Pancreatic neuroendocrine tumors (PanNETs) are rare tumors; however, their incidence greatly increases with age, and they occur more frequently among the elderly. They represent 5% of all pancreatic tumors, and despite the fact that low-grade tumors often have an indolent evolution, they portend a poor prognosis in an advanced stages and undifferentiated tumors. Additionally, functional pancreatic neuroendocrine tumors greatly impact quality of life due to the various clinical syndromes that result from abnormal hormonal secretion. With limited therapeutic and diagnostic options, patient stratification and selection of optimal therapeutic strategies should be the main focus. Modest improvements in the management of pancreatic neuroendocrine tumors have been achieved in the last years. Therefore, it is imperative to find new biomarkers and therapeutic strategies to improve patient survival and quality of life, limiting the disease burden. MicroRNAs (miRNAs) are small endogenous molecules that modulate the expression of thousands of genes and control numerous critical processes involved in tumor development and progression. New data also suggest the implication of miRNAs in treatment resistance and their potential as prognostic or diagnostic biomarkers and therapeutic targets. In this review, we discusses the current and new challenges in the management of PanNETs, including genetic and epigenetic approaches. Furthermore, we summarize the available data on miRNAs as potential prognostic, predictive, or diagnostic biomarkers and discuss their function as future therapeutic targets.

Application and prospect of artificial intelligence in digestive endoscopy

INTRODUCTION

With the progress of science and technology, artificial intelligence represented by deep learning has gradually begun to be applied in the medical field. Artificial intelligence has been applied to benign gastrointestinal lesions, tumors, early cancer, inflammatory bowel disease, gallbladder, pancreas, and other diseases. This review summarizes the latest research results on artificial intelligence in digestive endoscopy and discusses the prospect of artificial intelligence in digestive system diseases.

AREAS COVERED

We retrieved relevant documents on artificial intelligence in digestive tract diseases from PubMed and Medline. This review elaborates on the knowledge of computer-aided diagnosis in digestive endoscopy.

EXPERT OPINION

Artificial intelligence significantly improves diagnostic accuracy, reduces physicians' workload, and provides a shred of evidence for clinical diagnosis and treatment. Shortly, artificial intelligence will have high application value in the field of medicine.

Perspectives on the diagnostic, predictive and prognostic markers of neuroendocrine neoplasms (Review)

Neuroendocrine neoplasms (NENs) are a heterogeneous group of rare tumors with different types of physiology and prognosis. Therefore, prognostic information, including morphological differentiation, grade, tumor stage and primary location, are invaluable and contribute to the formulation of treatment decisions. Biomarkers that are currently used, including chromogranin A (CgA), serotonin and neuron-specific enolase, are singular parameters that cannot be used to accurately predict variables associated with tumor growth, including proliferation, metabolic rate and metastatic potential. In addition, site-specific biomarkers, such as insulin and gastrin, cannot be applied to all types of NENs. The clinical application of broad-spectrum markers, as it is the case for CgA, remains controversial despite being widely used. Due to limitations of the currently available mono-analyte biomarkers, recent studies were conducted to explore novel parameters for NEN diagnosis, prognosis, therapy stratification and evaluation of treatment response. Identification of prognostic factors for predicting NEN outcome is a critical requirement for the planning of adequate clinical management. Advances in ‘liquid’ biopsies and genomic analysis techniques, including microRNA, circulating tumor DNA or circulating tumor cells and sophisticated biomathematical analysis techniques, such as NETest or molecular image-based biomarkers, are currently under investigation as potentially novel tools for the management of NENs in the future. Despite these recent findings yielding promising observations, further research is necessary. The present review therefore summarizes the existing knowledge and recent advancements in the exploration of biochemical markers for NENs, with focus on gastroenteropancreatic-neuroendocrine tumors.

Pancreatic Neuroendocrine Tumors: Molecular Mechanisms and Therapeutic Targets

Pancreatic neuroendocrine tumors (pNETs) are unique, slow-growing malignancies whose molecular pathogenesis is incompletely understood. With rising incidence of pNETs over the last four decades, larger and more comprehensive 'omic' analyses of patient tumors have led to a clearer picture of the pNET genomic landscape and transcriptional profiles for both primary and metastatic lesions. In pNET patients with advanced disease, those insights have guided the use of targeted therapies that inhibit activated mTOR and receptor tyrosine kinase (RTK) pathways or stimulate somatostatin receptor signaling. Such treatments have significantly benefited patients, but intrinsic or acquired drug resistance in the tumors remains a major problem that leaves few to no effective treatment options for advanced cases. This demands a better understanding of essential molecular and biological events underlying pNET growth, metastasis, and drug resistance. This review examines the known molecular alterations associated with pNET pathogenesis, identifying which changes may be drivers of the disease and, as such, relevant therapeutic targets. We also highlight areas that warrant further investigation at the biological level and discuss available model systems for pNET research. The paucity of pNET models has hampered research efforts over the years, although recently developed cell line, animal, patient-derived xenograft, and patient-derived organoid models have significantly expanded the available platforms for pNET investigations. Advancements in pNET research and understanding are expected to guide improved patient treatments.

Artificial intelligence in small intestinal diseases: Application and prospects

The small intestine is located in the middle of the gastrointestinal tract, so small intestinal diseases are more difficult to diagnose than other gastrointestinal diseases. However, with the extensive application of artificial intelligence in the field of small intestinal diseases, with its efficient learning capacities and computational power, artificial intelligence plays an important role in the auxiliary diagnosis and prognosis prediction based on the capsule endoscopy and other examination methods, which improves the accuracy of diagnosis and prediction and reduces the workload of doctors. In this review, a comprehensive retrieval was performed on articles published up to October 2020 from PubMed and other databases. Thereby the application status of artificial intelligence in small intestinal diseases was systematically introduced, and the challenges and prospects in this field were also analyzed.

Circulating MicroRNAs in Small-bowel Neuroendocrine Tumors: A Potential Tool for Diagnosis and Assessment of Effectiveness of Surgical Resection

OBJECTIVE

To discover serum-based microRNA (miRNA) biomarkers for small-bowel neuroendocrine tumors (SBNET) to help guide clinical decisions.

BACKGROUND

MiRNAs are small noncoding RNA molecules implicated in the initiation and progression of many cancers. MiRNAs are remarkably stable in bodily fluids, and can potentially be translated into clinically useful biomarkers. Novel biomarkers are needed in SBNET to determine disease aggressiveness, select patients for treatment, detect early recurrence, and monitor response.

METHODS

This study was performed in 3 stages (discovery, validation, and a prospective, longitudinal assessment). Discovery comprised of global profiling of 376 miRNA in sera from SBNET patients (n = 11) versus healthy controls (HCs; n = 3). Up-regulated miRNAs were subsequently validated in additional SBNET (n = 33) and HC sera (n = 14); and then longitudinally after SBNET resection (n = 12), with serial serum sampling (preoperatively day 0; postoperatively at 1 week, 1 month, and 12 months).

RESULTS

Four serum miRNAs (miR-125b-5p, -362-5p, -425-5p and -500a-5p) were significantly up-regulated in SBNET (P < 0.05; fold-change >2) based on multiple normalization strategies, and were validated by RT-qPCR. This combination was able to differentiate SBNET from HC with an area under the curve of 0.951. Longitudinal assessment revealed that miR-125b-5p returned towards HC levels at 1 month postoperatively in patients without disease, whereas remaining up-regulated in those with residual disease (RSD). This was also true at 12 months postoperatively. In addition, miR-362-5p appeared up-regulated at 12 months in RSD and recurrent disease (RCD).

CONCLUSIONS

Our study represents the largest global profiling of serum miRNAs in SBNET patients, and the first to evaluate ongoing serum miRNA expression changes after surgical resection. Serum miR-125b-5p and miR-362-5p have potential to be used to detect RSD/RCD.

MiRNA Expression in Neuroendocrine Neoplasms of Frequent Localizations

Neuroendocrine neoplasms (NEN) are infrequent malignant tumors of a neuroendocrine nature that arise in various organs. They occur most frequently in the lungs, intestines, stomach and pancreas. Molecular diagnostics and prognosis of NEN development are highly relevant. The role of clinical biomarkers can be played by microRNAs (miRNAs). This work is devoted to the analysis of data on miRNA expression in NENs. For the first time, a search for specificity or a community of their functional characteristics in different types of NEN was carried out. Their properties as biomarkers were also analyzed. To date, more than 100 miRNAs have been characterized as differentially expressed and significant for the development of NEN tumors. Only about 10% of the studied miRNAs are expressed in several types of NEN; differential expression of the remaining 90% was found only in tumors of specific localizations. A significant number of miRNAs have been identified as potential biomarkers. However, only a few miRNAs have values that characterized their quality as markers. The analysis demonstrates the predominant specific expression of miRNA in each studied type of NEN. This indicates that miRNA’s functional features are predominantly influenced by the tissue in which they are formed.

A miR-375/YAP axis regulates neuroendocrine differentiation and tumorigenesis in lung carcinoid cells

Lung carcinoids are variably aggressive and mechanistically understudied neuroendocrine neoplasms (NENs). Here, we identified and elucidated the function of a miR-375/yes-associated protein (YAP) axis in lung carcinoid (H727) cells. miR-375 and YAP are respectively high and low expressed in wild-type H727 cells. Following lentiviral CRISPR/Cas9-mediated miR-375 depletion, we identified distinct transcriptomic changes including dramatic YAP upregulation. We also observed a significant decrease in neuroendocrine differentiation and substantial reductions in cell proliferation, transformation, and tumor growth in cell culture and xenograft mouse disease models. Similarly, YAP overexpression resulted in distinct and partially overlapping transcriptomic changes, phenocopying the effects of miR-375 depletion in the same models as above. Transient YAP knockdown in miR-375-depleted cells reversed the effects of miR-375 on neuroendocrine differentiation and cell proliferation. Pathways analysis and confirmatory real-time PCR studies of shared dysregulated target genes indicate that this axis controls neuroendocrine related functions such as neural differentiation, exocytosis, and secretion. Taken together, we provide compelling evidence that a miR-375/YAP axis is a critical mediator of neuroendocrine differentiation and tumorigenesis in lung carcinoid cells.

Application of multiomics sequencing and advances in the molecular mechanisms of pancreatic neuroendocrine neoplasms

The incidence of pancreatic neuroendocrine neoplasms (PanNENs) has gradually increased. PanNENs comprise two subtypes with different clinical manifestations and molecular mechanisms: functional PanNENs and nonfunctional PanNENs. Excessive hormones and tumor progression severely affect the quality of life of patients or are even life threatening. However, the molecular mechanisms of hormone secretion and tumor progression in PanNENs have not yet been fully elucidated. At present, advancements in sequencing technologies have led to the exploration of new biological markers and an advanced understanding of molecular mechanisms in PanNENs. Multiomics sequencing could reveal differences and similarities in molecular features in different fields. However, sequencing studies of PanNENs are booming and should be summarized to integrate the current findings. In this review, we summarize the current status of multiomics sequencing in PanNENs to further guide its application. We explore mainly advancements in the genome, transcriptome, and DNA methylation fields. In addition, the cell origin of PanNENs, which has been a hot issue in sequencing research, is described in multiple fields.

Blood extracellular vesicles from healthy individuals regulate hematopoietic stem cells as humans age

Hematopoietic stem cells (HSCs) maintain balanced blood cell production in a process called hematopoiesis. As humans age, their HSCs acquire mutations that allow some HSCs to disproportionately contribute to normal blood production. This process, known as age‐related clonal hematopoiesis, predisposes certain individuals to cancer, cardiovascular and pulmonary pathologies. There is a growing body of evidence suggesting that factors outside cells, such as extracellular vesicles (EVs), contribute to the disruption of stem cell homeostasis during aging. We have characterized blood EVs from humans and determined that they are remarkably consistent with respect to size, concentration, and total protein content, across healthy subjects aged 20–85 years. When analyzing EV protein composition from mass spectroscopy data, our machine‐learning‐based algorithms are able to distinguish EV proteins based on age and suggest that different cell types dominantly produce EVs released into the blood, which change over time. Importantly, our data show blood EVs from middle and older age groups (>40 years) significantly stimulate HSCs in contrast to untreated and EVs sourced from young subjects. Our study establishes for the first time that although EV particle size, concentration, and total protein content remain relatively consistent over an adult lifespan in humans, EV content evolves during aging and potentially influences HSC regulation.

Multiple Endocrine Neoplasia Type 1: The Potential Role of microRNAs in the Management of the Syndrome

Multiple endocrine neoplasia type 1 (MEN1) is a rare inherited tumor syndrome, characterized by the development of multiple neuroendocrine tumors (NETs) in a single patient. Major manifestations include primary hyperparathyroidism, gastro-entero-pancreatic neuroendocrine tumors, and pituitary adenomas. In addition to these main NETs, various combinations of more than 20 endocrine and non-endocrine tumors have been described in MEN1 patients. Despite advances in diagnostic techniques and treatment options, which are generally similar to those of sporadic tumors, patients with MEN1 have a poor life expectancy, and the need for targeted therapies is strongly felt. MEN1 is caused by germline heterozygous inactivating mutations of the MEN1 gene, which encodes menin, a tumor suppressor protein. The lack of a direct genotype–phenotype correlation does not permit the determination of the exact clinical course of the syndrome. One of the possible causes of this lack of association could be ascribed to epigenetic factors, including microRNAs (miRNAs), single-stranded non-coding small RNAs that negatively regulate post-transcriptional gene expression. Some miRNAs, and their deregulation, have been associated with MEN1 tumorigenesis. Recently, an extracellular class of miRNAs has also been identified (c-miRNAs); variations in their levels showed association with various human diseases, including tumors. The aim of this review is to provide a general overview on the involvement of miRNAs in MEN1 tumor development, to be used as possible targets for novel molecular therapies. The potential role of c-miRNAs as future non-invasive diagnostic and prognostic biomarkers of MEN1 will be discussed as well.

Classifying Lung Neuroendocrine Neoplasms through MicroRNA Sequence Data Mining

Lung neuroendocrine neoplasms (NENs) can be challenging to classify due to subtle histologic differences between pathological types. MicroRNAs (miRNAs) are small RNA molecules that are valuable markers in many neoplastic diseases. To evaluate miRNAs as classificatory markers for lung NENs, we generated comprehensive miRNA expression profiles from 14 typical carcinoid (TC), 15 atypical carcinoid (AC), 11 small cell lung carcinoma (SCLC), and 15 large cell neuroendocrine carcinoma (LCNEC) samples, through barcoded small RNA sequencing. Following sequence annotation and data preprocessing, we randomly assigned these profiles to discovery and validation sets. Through high expression analyses, we found that miR-21 and -375 are abundant in all lung NENs, and that miR-21/miR-375 expression ratios are significantly lower in carcinoids (TC and AC) than in neuroendocrine carcinomas (NECs; SCLC and LCNEC). Subsequently, we ranked and selected miRNAs for use in miRNA-based classification, to discriminate carcinoids from NECs. Using miR-18a and -155 expression, our classifier discriminated these groups in discovery and validation sets, with 93% and 100% accuracy. We also identified miR-17, -103, and -127, and miR-301a, -106b, and -25, as candidate markers for discriminating TC from AC, and SCLC from LCNEC, respectively. However, these promising findings require external validation due to sample size.

Randomised phase II trial of CAPTEM or FOLFIRI as SEcond-line therapy in NEuroendocrine CArcinomas and exploratory analysis of predictive role of PET/CT imaging and biological markers (SENECA trial): a study protocol

INTRODUCTION

Patients with metastatic or locally advanced, non-resectable, grade 3 poorly differentiated gastroenteropancreatic (GEP) and lung neuroendocrine carcinomas (NECs) are usually treated with in first-line platinum compounds. There is no standard second-line treatment on progression. Accurate biomarkers are needed to facilitate diagnosis and prognostic assessment of patients with NEC.

METHODS AND ANALYSIS

The SEcond-line therapy in NEuroendocrine CArcinomas (SENECA) study is a randomised, non-comparative, multicentre phase II trial designed to evaluate the efficacy and safety of folinic acid, 5-fluorouracil and irinotecan (FOLFIRI) or capecitabine plus temozolomide (CAPTEM) regimens after failure of first-line chemotherapy in patients with lung NEC and GEP-NEC. Secondary aims are to correlate the serum miRNA profile and primary mutational status of MEN1, DAXX, ATRX and RB-1 with prognosis and outcome and to investigate the prognostic and predictive role of the Ki-67 score and 18-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) or ⁶⁸Ga-PET/CT. The main eligibility criteria are age ≥18 years; metastatic or locally advanced, non-resectable, grade 3 lung or GEP-NECs; progression to first-line platinum-based chemotherapy. A Bryant and Day design taking into account treatment activity and toxicity was used to estimate the sample size. All analyses will be performed separately for each treatment group in the intention-to-treat population. A total of 112 patients (56/arm) will be randomly assigned (1:1) to receive FOLFIRI every 14 days or CAPTEM every 28 days until disease progression or unacceptable toxicity or for a maximum of 6 months. Patients undergo testing for specific biomarkers in primary tumour tissue and for miRNA in blood samples. MiRNA profiling will be performed in the first 20 patients who agree to participate in the biological substudy.

ETHICS AND DISSEMINATION

The SENECA trial, supported by Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST), was authorised by the locals Ethics Committee and the Italian Medicines Agency (AIFA). Results will be widely disseminated via peer-reviewed manuscripts, conference presentations and reports to relevant authorities.The study is currently open in Italy.

TRAIL REGISTRATION NUMBER

NCT03387592; Pre-results. EudraCT-2016-000767-17.

PROTOCOL VERSION

Clinical Study Protocol Version 1, 7 November 2016.

Altered miRNAs Expression Correlates With Gastroenteropancreatic Neuroendocrine Tumors Grades

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.

Characterizing and classifying neuroendocrine neoplasms through microRNA sequencing and data mining

Neuroendocrine neoplasms (NENs) are clinically diverse and incompletely characterized cancers that are challenging to classify. MicroRNAs (miRNAs) are small regulatory RNAs that can be used to classify cancers. Recently, a morphology-based classification framework for evaluating NENs from different anatomical sites was proposed by experts, with the requirement of improved molecular data integration. Here, we compiled 378 miRNA expression profiles to examine NEN classification through comprehensive miRNA profiling and data mining. Following data preprocessing, our final study cohort included 221 NEN and 114 non-NEN samples, representing 15 NEN pathological types and 5 site-matched non-NEN control groups. Unsupervised hierarchical clustering of miRNA expression profiles clearly separated NENs from non-NENs. Comparative analyses showed that miR-375 and miR-7 expression is substantially higher in NEN cases than non-NEN controls. Correlation analyses showed that NENs from diverse anatomical sites have convergent miRNA expression programs, likely reflecting morphological and functional similarities. Using machine learning approaches, we identified 17 miRNAs to discriminate 15 NEN pathological types and subsequently constructed a multilayer classifier, correctly identifying 217 (98%) of 221 samples and overturning one histological diagnosis. Through our research, we have identified common and type-specific miRNA tissue markers and constructed an accurate miRNA-based classifier, advancing our understanding of NEN diversity.

Distinguishing Tumor and Stromal Sources of MicroRNAs Linked to Metastasis in Cutaneous Melanoma

MicroRNA (miRNA) dysregulation in cancer causes changes in gene expression programs regulating tumor progression and metastasis. Candidate metastasis suppressor miRNA are often identified by differential expression in primary tumors compared to metastases. Here, we performed comprehensive analysis of miRNA expression in The Cancer Genome Atlas (TCGA) skin cutaneous melanoma (SKCM) tumors (97 primary, 350 metastatic), and identified candidate metastasis-suppressor miRNAs. Differential expression analysis revealed miRNA significantly downregulated in metastatic tumors, including miR-205, miR-203, miR-200a-c, and miR-141. Furthermore, sequential feature selection and classification analysis identified miR-205 and miR-203 as the miRNA best able to discriminate between primary and metastatic tumors. However, cell-type enrichment analysis revealed that gene expression signatures for epithelial cells, including keratinocytes and sebocytes, were present in primary tumors and significantly correlated with expression of the candidate metastasis-suppressor miRNA. Examination of miRNA expression in cell lines revealed that candidate metastasis-suppressor miRNA identified in the SKCM tumors, were largely absent in melanoma cells or melanocytes, and highly restricted to keratinocytes and other epithelial cell types. Indeed, the differences in stromal cell composition between primary and metastatic tumor tissues is the main basis for identification of differential miRNA that were previously classified as metastasis-suppressor miRNAs. We conclude that future studies must consider tumor-intrinsic and stromal sources of miRNA in their workflow to identify bone fide metastasis-suppressor miRNA in cutaneous melanoma and other cancers.

Neuroendocrine Neoplasms of the Small Bowel and Pancreas

The traditionally promulgated perspectives of neuroendocrine neoplasms (NEN) as rare, indolent tumours are blunt and have been outdated for the last 2 decades. Clear increments in their incidence over the past decades render them increasingly clinically relevant, and at initial diagnosis many present with nodal and/or distant metastases (notably hepatic). The molecular pathogenesis of these tumours is increasingly yet incompletely understood. Those arising from the small bowel (SB) or pancreas typically occur sporadically; the latter may occur within the context of hereditary tumour predisposition syndromes. NENs can also be associated with endocrinopathy of hormonal hypersecretion. Tangible advances in the development of novel biomarkers, functional imaging modalities and therapy are especially applicable to this sub-set of tumours. The management of SB and pancreatic neuroendocrine tumours (NET) may be challenging, and often comprises a multidisciplinary approach wherein surgical, medical, interventional radiological and radiotherapeutic modalities are implemented. This review provides a comprehensive overview of the epidemiology, pathophysiology, diagnosis and treatment of SB and pancreatic NETs. Moreover, we provide an outlook of the future in these tumour types which will include the development of precision oncology frameworks for individualised therapy, multi-analyte predictive biomarkers, artificial intelligence-derived clinical decision support tools and elucidation of the role of the microbiome in NEN development and clinical behaviour.

Neutrophil recruitment and function in endometriosis patients and a syngeneic murine model

Endometriosis is a chronic inflammatory, gynecological disease characterized by the presence of endometrial-like tissue lesions outside of the uterus. Neutrophils are elevated in the systemic circulation and peritoneal fluid of endometriosis patients; however, whether and how neutrophils contribute to endometriosis pathophysiology remain poorly understood. With emerging roles for neutrophils in chronic and sterile inflammatory conditions, we sought to provide in-depth characterization of neutrophil involvement in endometriosis. We demonstrate that neutrophils reside within patient endometriotic lesions and that patient lesions possess a microenvironment that may influence neutrophil recruitment and function. We also provide the first evidence that systemic circulating neutrophils from endometriosis patients display distinct transcriptomic differences compared neutrophils from healthy control subjects. Time course characterization of our syngeneic, immunocompetent mouse model of endometriosis revealed that neutrophils are rapidly recruited to the peritoneal environment early after endometriotic lesion establishment and remain present in murine lesions long term. In vivo neutrophil depletion altered the systemic and peritoneal immune microenvironment of mice with endometriosis as demonstrated by changes in pro-inflammatory and angiogenic mediators. Taken together, these findings highlight a novel role for neutrophils in early events such as angiogenesis and modulation of the local inflammatory environment associated with endometriosis pathogenesis.

Insights into the biology and treatment strategies of pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumors (PNETs) are the second most common primary pancreatic neoplasms after pancreatic ductal adenocarcinoma. PNETs present with widely various clinical manifestation and unfavorable survival rate. The recent advances in next generation sequencing have significantly increased our understanding of the molecular landscape of PNETs and help guide the development of targeted therapies. This review intends to outline a holistic picture of the tumors by discussing current understanding of clinical presentations, up-to-date treatment strategies, novel mouse models, and molecular biology of PNETs. Furthermore, we will provide insight into the future development of more effective targeted therapies that are necessary to manage PNETs.

Treatment with somatostatin analogs induces differentially expressed let-7c-5p and mir-3137 in small intestine neuroendocrine tumors

BACKGROUND

Distant metastases frequently occur in gastroenteropancreatic neuroendocrine tumors. If hepatic surgery is not feasible, patients are treated with somatostatin analogs. However, the underlying mechanisms of action of this treatment remain to be defined. The aim of the present study was to analyze the micro-RNA expression profile inter-individually before and after the treatment with somatostatin analogs.

MATERIAL AND METHODS

Tumor specimens of all included patients (n = 8) before and after the onset of a therapy with somatostatin analogs were analyzed and a micro-RNA expression profile (754 micro-RNAs) of each probe was generated. This analysis in an intra-individual setting was selected to avoid bias from inter-individual differences. The micro-RNA expression profiles were validated by qPCR. Patients with any other systemic treatment were excluded from the present study.

RESULTS

Eight patients were included in the present study of which all had neuroendocrine tumors of the small intestine with diffuse hepatic metastases. Grouped analyses revealed that 15 micro-RNAs were differentially expressed (3 up- and 12 downregulated) after the exposure to somatostatin analogs. Additionally, let-7c-5p and mir-3137 are concordantly regulated in the inter-individually analysis.

CONCLUSIONS

This is the first study analyzing the individual micro-RNA expression profile before and after a therapy with somatostatin analogs. Data from this study reveal that somatostatin analogs may in part exert their beneficial effects through an alteration in the micro-RNA expression profile.

Neuroendocrine neoplasms: current and potential diagnostic, predictive and prognostic markers

Some biomarkers for functioning and non-functioning neuroendocrine neoplasms (NENs) are currently available. Despite their application in clinical practice, results should be interpreted cautiously. Considering the variable sensitivity and specificity of these parameters, there is an unmet need for novel biomarkers to improve diagnosis and predict patient outcome. Nowadays, several new biomarkers are being evaluated and may become future tools for the management of NENs. These biomarkers include (1) peptides and growth factors; (2) DNA and RNA markers based on genomics analysis, for example, the so-called NET test, which has been developed for analyzing gene transcripts in circulating blood; (3) circulating tumor/endothelial/progenitor cells or cell-free tumor DNA, which represent minimally invasive methods that would provide additional information for monitoring treatment response and (4) improved imaging techniques with novel radiolabeled somatostatin analogs or peptides. Below we summarize some future directions in the development of novel diagnostic and predictive/prognostic biomarkers in NENs. This review is focused on circulating and selected tissue markers.