Comprehensive Plasma Metabolomic Profile of Patients with Advanced Neuroendocrine Tumors (NETs). Diagnostic and Biological Relevance

Metabolomics for searching validated biomarkers in cancer studies: a decade in review

INTRODUCTION

In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways.

AREAS COVERED

This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types.

EXPERT OPINION

Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

FOXA2-initiated transcriptional activation of INHBA induced by methylmalonic acid promotes pancreatic neuroendocrine neoplasm progression

Pancreatic neuroendocrine neoplasms (PanNENs) are a group of highly heterogeneous neoplasms originating from the endocrine islet cells of the pancreas with characteristic neuroendocrine differentiation, more than 60% of which represent metastases when diagnosis, causing major tumor-related death. Metabolic alterations have been recognized as one of the hallmarks of tumor metastasis, providing attractive therapeutic targets. However, little is known about the molecular mechanism of metabolic changes regulating PanNEN progression. In this study, we first identified methylmalonic acid (MMA) as an oncometabolite for PanNEN progression, based on serum metabolomics of metastatic PanNEN compared with non-metastatic PanNEN patients. One of the key findings was the potentially novel mechanism of epithelial-mesenchymal transition (EMT) triggered by MMA. Inhibin βA (INHBA) was characterized as a key regulator of MMA-induced PanNEN progression according to transcriptomic analysis, which has been validated in vitro and in vivo. Mechanistically, INHBA was activated by FOXA2, a neuroendocrine (NE) specific transcription factor, which was initiated during MMA-induced progression. In addition, MMA-induced INHBA upregulation activated downstream MITF to regulate EMT-related genes in PanNEN cells. Collectively, these data suggest that activation of INHBA via FOXA2 promotes MITF-mediated EMT during MMA inducing PanNEN progression, which puts forward a novel therapeutic target for PanNENs.

Metabolomic profile of neuroendocrine tumors identifies methionine, porphyrin, and tryptophan metabolisms as key dysregulated pathways associated with patient survival

OBJECTIVE

Metabolic profiling is a valuable tool to characterize tumor biology but remains largely unexplored in neuroendocrine tumors (NETs). Our aim was to comprehensively assess the metabolomic profile of NETs and identify novel prognostic biomarkers and dysregulated molecular pathways.

DESIGN AND METHODS

Multiplatform untargeted metabolomic profiling (GC-MS, CE-MS, and LC-MS) was performed in plasma from 77 patients with G1-2 extra-pancreatic NETs enrolled in the AXINET trial (NCT01744249) (study cohort) and from 68 non-cancer individuals (control). The prognostic value of each differential metabolite (n = 155) in NET patients (P < .05) was analyzed by univariate and multivariate analyses adjusted for multiple testing and other confounding factors. Related pathways were explored by Metabolite Set Enrichment Analysis (MSEA) and Metabolite Pathway Analysis (MPA).

RESULTS

Thirty-four metabolites were significantly associated with progression-free survival (PFS) (n = 16) and/or overall survival (OS) (n = 27). Thirteen metabolites remained significant independent prognostic factors in multivariate analysis, 3 of them with a significant impact on both PFS and OS. Unsupervised clustering of these 3 metabolites stratified patients in 3 distinct prognostic groups (1-year PFS of 71.1%, 47.7%, and 15.4% (P = .012); 5-year OS of 69.7%, 32.5%, and 27.7% (P = .003), respectively). The MSEA and MPA of the 13-metablolite signature identified methionine, porphyrin, and tryptophan metabolisms as the 3 most relevant dysregulated pathways associated with the prognosis of NETs.

CONCLUSIONS

We identified a metabolomic signature that improves prognostic stratification of NET patients beyond classical prognostic factors for clinical decisions. The enriched metabolic pathways identified reveal novel tumor vulnerabilities that may foster the development of new therapeutic strategies for these patients.

Metabolism of pancreatic neuroendocrine tumors: what can omics tell us?

Introduction

Reprogramming of cellular metabolism is now a hallmark of tumorigenesis. In recent years, research on pancreatic neuroendocrine tumors (pNETs) has focused on genetic and epigenetic modifications and related signaling pathways, but few studies have been devoted to characterizing the metabolic profile of these tumors. In this review, we thoroughly investigate the metabolic pathways in pNETs by analyzing the transcriptomic and metabolomic data available in the literature.

Methodology

We retrieved and downloaded gene expression profiles from all publicly available gene set enrichments (GSE43797, GSE73338, and GSE117851) to compare the differences in expressed genes based on both the stage and MEN1 mutational status. In addition, we conducted a systematic review of metabolomic data in NETs.

Results

By combining transcriptomic and metabolomic approaches, we have identified a distinctive metabolism in pNETs compared with controls without pNETs. Our analysis showed dysregulations in the one-carbon, glutathione, and polyamine metabolisms, fatty acid biosynthesis, and branched-chain amino acid catabolism, which supply the tricarboxylic acid cycle. These targets are implicated in pNET cell proliferation and metastasis and could also have a prognostic impact. When analyzing the profiles of patients with or without metastasis, or with or without MEN1 mutation, we observed only a few differences due to the scarcity of published clinical data in the existing research. Consequently, further studies are now necessary to validate our data and investigate these potential targets as biomarkers or therapeutic solutions, with a specific focus on pNETs.

Inhibition of serotonin biosynthesis in neuroendocrine neoplasm suppresses tumor growth in vivo

Small bowel neuroendocrine tumors (SBNETs) originate from enterochromaffin cells in the intestine which synthesize and secrete serotonin. SBNETs express high levels of tryptophan hydroxylase 1 (Tph1), a key enzyme in serotonin biosynthesis. Patients with high serotonin level may develop carcinoid syndrome, which can be treated with somatostatin analogues and the Tph1 inhibitor telotristat ethyl in severe cases. Although the active drug telotristat can efficiently reduce serotonin levels, its effect on tumor growth is unclear. This study determined the effect of serotonin inhibition on tumor cell growth in vitro and in vivo . The levels of Tph1 in various neuroendocrine neoplasms (NENs) were determined and the biological effects of Tph1 inhibition in vitro and in vivo using genetic and pharmacologic approaches was tested. Gene and protein expression analyses were performed on patient tumors and cancer cell lines. shRNAs targeting TPH1 were used to create stable knockdown in BON cells. Control and knockdown lines were assessed for their growth rates in vitro and in vivo , angiogenesis potential, serotonin levels, endothelial cell tube formation, tumor weight, and tumor vascularity. TPH1 is highly expressed in SBNETs and many cancer types. TPH1 knockdown cells and telotristat treated cells showed similar growth rates as control cells in vitro . However, TPH1 knockdown cells formed smaller tumors in vivo and tumors were less vascularized. Although Tph1 inhibition with telotristat showed no effect on tumor cell growth in vitro , Tph1 inhibition reduced tumor formation in vivo . Serotonin inhibition in combination with other therapies is a promising new avenue for targeting metabolic vulnerabilities in NENs.

Inflammatory Cytokines Associated with Diagnosis, Tumor Grade and Prognosis in Patients with Neuroendocrine Tumors

Background and aims: Inflammatory cytokines represent diagnostic and prognostic biomarkers in manifold cancers. Recent data suggest a pivotal role of these cytokines in different biological processes involved in the development of neuroendocrine tumors (NETs). However, their role as biomarkers in NETs is only poorly understood. Methods: We analyzed serum concentrations of 13 inflammation-related cytokines at different time points in 43 patients with well-differentiated gastroenteropancreatic NETs (G1/G2) treated at Charité Berlin and compared them to 40 healthy controls. The results were correlated with clinical records. Results: Serum concentrations (Median (Interquartile Range (IQR)) in pg/mL) of IL-1β (124 (82) vs. 68 (61) pg/mL; p = 0.0003), IL-6 (111(122) vs. 88 (32) pg/mL; p = 0.0086), IL-8 (1058 (768) vs. 210 (90) pg/mL; p < 0.0001), IL-18 (2936 (1723) vs. 1590 (704) pg/mL; p < 0.0001), and TNF (271 (260) vs. 42 (25) pg/mL; p < 0.0001) were significantly elevated in NET patients, whereas IL-10 (43 (44) vs. 105 (48) pg/mL; p < 0.0001) showed lower concentrations in NETs when compared to controls. Cytokine levels significantly correlated with tumor grade (IL-6; p = 0.0070), prevalence of distant metastasis (IL-18; p = 0.0313), and disease progression over time (IL-10; p = 0.0033) but not tumor location. Chromogranin A (CgA) and the NETest are currently used to monitor treatment response. A more accurate prediction could possibly be achieved by employing a subset of cytokines. Our data clearly warrants further functional investigation into the role of the immune response and cytokine release in NETs. Conclusion: A biologically plausible panel of cytokines might be added to the diagnostic and prognostic tools currently employed in patients with NETs. Combining different markers into a score would elevate diagnostic accuracy compared to single markers.

Circulating Neuroendocrine Tumor Biomarkers: Past, Present and Future

Neuroendocrine tumors are a heterogeneous group of neoplasms originating from the diffuse endocrine system. Depending on primary location and hormonal status, they range in terms of clinical presentation, prognosis and treatment. Functional tumors often develop symptoms indicating an excess of hormones produced by the neoplasm (exempli gratia insulinoma, glucagonoma and VIPoma) and can be diagnosed using monoanalytes. For non-functional tumors (inactive or producing insignificant amounts of hormones), universal biomarkers have not been established. The matter remains an important unmet need in the field of neuroendocrine tumors. Substances researched over the years, such as chromogranin A and neuron-specific enolase, lack the desired sensitivity and specificity. In recent years, the potential use of Circulating Tumor Cells or multianalytes such as a circulating microRNA and NETest have been widely discussed. They offer superior diagnostic parameters in comparison to traditional biomarkers and depict disease status in a more comprehensive way. Despite a lot of promise, no international standards have yet been developed regarding their routine use and clinical application. In this literature review, we describe the analytes used over the years and cover novel biomarkers that could find a use in the future. We discuss their pros and cons while showcasing recent advances in the field of neuroendocrine tumor biomarkers.

Contribution of allergy in the acquisition of uncontrolled severe asthma

Asthma is a multifactorial, heterogeneous disease that has a challenging management. It can be divided in non-allergic and allergic (usually associated with house dust mites (HDM) sensitization). There are several treatments options for asthma (corticosteroids, bronchodilators, antileukotrienes, anticholinergics,…); however, there is a subset of patients that do not respond to any of the treatments, who can display either a T2 or a non-T2 phenotype. A deeper understanding of the differential mechanisms underlying each phenotype will help to decipher the contribution of allergy to the acquisition of this uncontrolled severe phenotype. Here, we aim to elucidate the biological pathways associated to allergy in the uncontrolled severe asthmatic phenotype. To do so, twenty-three severe uncontrolled asthmatic patients both with and without HDM-allergy were recruited from Hospital Universitario de Gran Canaria Dr. Negrin. A metabolomic fingerprint was obtained through liquid chromatography coupled to mass spectrometry, and identified metabolites were associated with their pathways. 9/23 patients had uncontrolled HDM-allergic asthma (UCA), whereas 14 had uncontrolled, non-allergic asthma (UCNA). 7/14 (50%) of the UCNA patients had Aspirin Exacerbated Respiratory Disease. There were no significant differences regarding gender or body mass index; but there were significant differences in age and onset age, which were higher in UCNA patients; and in total IgE, which was higher in UCA. The metabolic fingerprint revealed that 103 features were significantly different between UCNA and UCA (p < 0.05), with 97 being increased in UCA and 6 being decreased. We identified lysophosphocholines (LPC) 18:2, 18:3 and 20:4 (increased in UCA patients); and deoxycholic acid and palmitoleoylcarnitine (decreased in UCA). These metabolites were related with a higher activation of phospholipase A2 (PLA2) and other phospholipid metabolism pathways. Our results show that allergy induces the activation of specific inflammatory pathways, such as the PLA2 pathway, which supports its role in the development of an uncontrolled asthma phenotype. There are also clinical differences, such as higher levels of IgE and earlier onset ages for the allergic asthmatic group, as expected. These results provide evidences to better understand the contribution of allergy to the establishment of a severe uncontrolled phenotype.

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.