Reydson Alcides de Lima-Souza1
Tayná Figueiredo Maciel2,3
Moisés Willian Aparecido Gonçalves2,3
Fernanda Cristina Poscai Ribeiro4
Rodrigo A. Maioral1
João Figueira Scarini1
Heloisa P Soraes5
Gary Chris Fillmore1
Erika Said Abu Egal1*- 1Biorepository and Molecular Pathology, Huntsman Cancer Institute, University of Utah (UU), Salt Lake City, UT, United States
- 2Department of Pathology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
- 3Department of Oral Diagnosis, Piracicaba Dental School, University of Campinas (UNICAMP), Piracicaba, São Paulo, Brazil
- 4Department of Internal Medicine, University of Western São Paulo (UNOESTE), Guarujá, São Paulo, Brazil
- 5Department of Oncology, Huntsman Cancer Institute, University of Utah (UU), Salt Lake City, UT, United States
Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are a heterogeneous group of tumors characterized by diverse biological behaviors and variable clinical outcomes. Recent advances have highlighted the important role of metabolic reprogramming in tumorigenesis, progression, and therapeutic resistance in GEP-NENs. In this review, we synthesize the current evidence on metabolic biomarkers and altered metabolic pathways—particularly those involving glucose, lipid, and amino acid metabolism. Key biomarkers such as GLUT-1, FASN, and enzymes involved in ferroptosis, cholesterol biosynthesis, and amino acid catabolism demonstrate strong associations with tumor aggressiveness, hypoxia, and mTOR signaling. Moreover, metabolomic profiling and functional studies suggest that metabolic markers may inform prognosis and predict response to targeted therapies such as Everolimus. Although promising, the clinical translation of these markers is still limited and requires further validation in large, subtype-specific cohorts. Our findings highlight the importance of integrating metabolic profiling into the diagnostic and therapeutic landscape of GEP-NENs. Future research should prioritize biomarker standardization, multi-omics integration, and the development of metabolism-based therapeutic strategies tailored to tumor subtype and differentiation grade.
1 Introduction
Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are a subset of neuroendocrine neoplasms (NENs) that arise in the stomach, small intestine, appendix, and pancreas (1). Over the past few decades, the global incidence of these tumors has increased significantly (2, 3). However, due to their typically mild and nonspecific symptoms, diagnosis is often delayed, with many cases only being detected at advanced stages (4). Thus, the tumor stage and the presence of metastases become crucial prognostic factors, significantly influencing patient survival (5).
Dysregulated metabolism is a hallmark of cancer, leading to the accumulation of aberrant metabolites that reflect both tumor activity and the underlying biological state (6). Recently, metabolites have gained increasing attention as promising biomarkers for early detection, prognostic assessment, and therapeutic monitoring. In GEP-NENs, several metabolic alterations have been identified that reflect tumor behavior and biology, offering valuable insights into potential targeted strategies (6–8).
Advances in analytical technologies have enabled comprehensive profiling of tumor-associated metabolites, thus enhancing our understanding of tumor metabolism and supporting the development of more precise, personalized therapeutic approaches (9). Despite this progress, the clinical translation of these findings remains a challenge, underscoring the need for continued research in this area (9).
This review synthesizes and critically evaluates current research to provide a deeper understanding of how metabolites profiling can bridge experimental discoveries and clinical practice in cancer diagnosis, management, and prognosis, with a particular focus on GEP-NENs.
2 NENs and pancreatic neuroendocrine neoplasms
NENs are a rare and heterogeneous group of malignant tumors that arise from cells of the neuroendocrine system and are mainly derived from two cell types: epithelial neuroendocrine cells and neuronal/para-neuronal cells (1). These cells are characterized by their ability to produce, store, and secrete hormones and other biologically active substances, giving NENs a wide range of clinical presentations and biological behaviors (10, 11).
Among the NENs, those of the GEP represent a significant proportion, predominantly affecting organs such as the stomach, small intestine, colon, rectum, and pancreas (12). GEP-NENs show considerable variability in their clinical and biological behavior, ranging from indolent, slow-growing forms to highly aggressive tumors with great potential for local invasion and distant metastasis (1, 10).
In recent decades, the understanding of these neoplasms has evolved significantly, driven by advances in molecular biology, diagnostic imaging, histopathologic techniques, and targeted therapies. These advances have contributed to better prognostic stratification and the development of more individualized therapeutic strategies, allowing a more precise and effective approach to the management of patients with GEP-NENs (10, 12).
2.1 Etiopathogenesis
The etiology of NENs is unknown. Hereditary genetic defects, including multiple endocrine neoplasia type 1, von Hippel-Lindau syndrome, and neurofibromatosis type 1, are associated with NETs of the thorax and upper digestive tract (1).
Known risk factors include a family history of cancer, advanced age, high body mass index, and site-specific risk factors common to non-neuroendocrine cancers, including smoking and alcohol consumption (13–15).
The pathogenesis is unknown, except for the enterochromaffin-like cell neuroendocrine tumors (NET) of the stomach, for which hypergastrinemia is the obligate promoting factor (1, 14, 15). Associated conditions include chronic atrophic gastritis (autoimmune or Helicobacter pylori infection-related), and multiple endocrine neoplasia type 1 (Zollinger-Ellison syndrome) may be involved (1, 13).
2.2 Classification
NEN is used as an umbrella term for all neoplasms that originate from cells of the neuroendocrine system (Table 1). NENs are classified based on their morphological differentiation: either well-differentiated neuroendocrine tumors (NETs) or poorly differentiated neuroendocrine carcinomas (NECs). These categories have distinct clinical behaviors and prognostic implications (1, 16). NETs are well-differentiated tumors with preserved cellular architecture and a relatively organized histologic pattern. Despite their homogeneous morphology, these tumors exhibit variable biological behavior, which is why they are stratified into three grades according to the rate of cell proliferation, using the Ki-67 index as the main parameter: NET grade 1 (G1), with Ki-67 <3%; NET grade 2 (G2), with Ki-67 between 3% and 20%; and NET grade 3 (G3), with Ki-67 >20% (1, 16).
Table 1. Classification of neuroendocrine neoplasms.
It is worth remembering that the current classification recognizes that some well-differentiated tumors may exhibit a more aggressive clinical behavior while retaining the morphologic features that are typical of NET (1).
Alternately, NECs are high-grade, poorly differentiated tumors with highly aggressive behavior and rapid growth. They have a high proliferative rate, usually with a Ki-67 index greater than 20% and are divided into two main morphologic subtypes: small-cell neuroendocrine carcinoma and large-cell neuroendocrine carcinoma. Although the concept of progression from NET to NEC has not been fully elucidated, the distinction between these two subgroups is essential as it directly influences both prognosis and choice of therapeutic strategies (1, 17, 18).
In addition to morphological differentiation and proliferative index, another fundamental aspect in the characterization of NENs is their secretory potential. NENs, especially well-differentiated NETs, can produce, store, and secrete biologically active substances, such as peptide hormones, biogenic amines, and other mediators. Based on this functional profile, NEN are classified as functional and non-functional. Functioning tumors secrete hormones in sufficient quantities to cause specific clinical manifestations, whereas non-functioning tumors, on the other hand, do not secrete hormones at clinically significant levels and therefore are generally not associated with clinical hormonal syndromes (1, 12).
In this context, immunohistochemical evaluation plays a central role in the diagnosis of NENs, with chromogranin A and synaptophysin being the most widely used markers, as they reflect the presence of secretory structures typical of neuroendocrine cells (1, 19). Chromogranin A, which is present in dense secretory granules, is particularly useful in detecting well-differentiated NETs, while synaptophysin, which is associated with synaptic vesicles, has a higher sensitivity and is usually present in both NETs and NECs (1, 19). However, the expression of these markers may vary depending on the degree of tumor differentiation. Poorly differentiated tumors often show weak, focal, or even absent expression of chromogranin A expression due to the lack of secretory granules (1, 12, 19).
NENs are also classified as mixed NENs and non-NENs. These lesions are characterized as neoplasms whose cells express neuroendocrine and non-neuroendocrine features (1, 20). In the gastroenteropancreatic system, by arbitrary convention, each component should represent ≥ 30% of a neoplasm for the neoplasm to be included in the mixed NEN category; the presence of focal (< 30%) neuroendocrine differentiation may be mentioned in the diagnosis (especially when the component is poorly differentiated) but does not affect the diagnostic categorization (1). In these cases, other complementary markers such as CD56, NSE, and chromogranin B can be used to confirm the neuroendocrine nature of the neoplasm (20–22). Thus, although most NENs are positive for chromogranin A and synaptophysin: however, interpretation must always consider the degree of differentiation, histologic features, and biological behavior of the tumor (1).
2.2.1 Pancreatic neuroendocrine neoplasms
Like other NENs, pancreatic NENs (PanNENs) express synaptophysin and usually chromogranin A, and are classified into pancreatic neuroendocrine tumors (PanNETs), and poorly differentiated pancreatic NECs (PanNECs) (23, 24). For pancreatic mixed NEN cases, one neuroendocrine and the other non-neuroendocrine (usually ductal adenocarcinoma or acinar cell carcinoma), each component accounts for at least 30% of the tumor volume (24).
PanNENs are classified according to the degree of differentiation and are graded based on the mitotic rate and Ki-67 proliferation index, similarly to GEP-NENs (Table 2). Despite sharing neuroendocrine characteristics, PanNETs and PanNECs are biologically distinct and belong to different genetic categories (23, 24).
Table 2. Classification of pancreatic neuroendocrine neoplasms.
PanNETs are well-differentiated neoplasms of low, intermediate, or high-grade, composed of cells with minimal to moderate atypia, with organoid architectural patterns, often without necrosis (24). They express general markers of neuroendocrine differentiation (chromogranin A and synaptophysin, generally in a diffuse and intense form) and hormones (with generally intense expression, although not always diffuse), and may be orthotopic or ectopic concerning the pancreas (23, 24).
PanNECs, on the other hand, are poorly differentiated, high-grade neoplasms composed of highly atypical, small or medium to large cells expressing neuroendocrine markers (such as synaptophysin in a diffuse but weak form and chromogranin A in a focal or weak form), generally without hormone production (23, 24). It is important to note that PanNECs do not express acinar cell markers such as trypsin, chymotrypsin, or carboxyl ester hydrolase, which are typically detected by BCL10 (23, 24).
Finally, mixed NENs represent a conceptual category rather than a specific diagnostic entity (1). Generally, both components are high-grade (G3), but occasionally they may be G1 or G2. Therefore, each component should be graded separately, with special attention to the neuroendocrine component, as its proliferation index (Ki-67) appears to be the main prognostic determinant of mixed NENs (1, 22).
The phenomenon of grade progression in well-differentiated PanNETs has been increasingly recognized and is associated with a poorer prognosis (25). It has been hypothesized that PanNECs may eventually arise from the progression of a well-differentiated PanNET. However, this transformation has not been convincingly demonstrated (1).
2.3 Clinical and epidemiological features
The incidence of NENs is approximately seven new cases per 100,000 person-years and has increased steadily over the past two decades (2, 26–28). Both sexes are equally affected, although there is a slight male predominance in tumors of the digestive tract (27, 28). Most patients are between the sixth and eighth decades of life, but younger individuals may be affected, especially in the presence of hereditary syndromes or in ovarian neoplasms due to the association with mature teratomas. NENs are rare in childhood and the neonatal period (29, 30) (Tables 3–5).
Table 3. Clinicopathological features of gastroenteropancreatic neuroendocrine tumors.
Table 4. Clinicopathological features of gastroenteropancreatic neuroendocrine carcinomas.
Table 5. Clinicopathological features of gastroenteropancreatic mixed neuroendocrine and non-neuroendocrine neoplasms.
Most tumors are non-functional and therefore do not show signs or symptoms associated with active hormone secretion (1). Since they may remain asymptomatic for long periods, they are usually diagnosed at more advanced stages due to the absence of early clinical signs related to hormone secretion (31). In these cases, patients usually present with non-specific symptoms related to mass effect or incidental findings on examinations performed for other reasons (1).
In functional NENs, excessive production of their substances is associated with specific clinical presentations and the development of syndromic patterns (1). It is estimated that less than one-third of NENs are associated with hormonal syndromes, and they are categorized according to the predominant hormone secreted, such as carcinoid syndrome (due to serotonin secretion), Zollinger-Ellison syndrome (related to gastrinomas), recurrent hypoglycemia (in insulinomas), hyperglycemia and migratory necrolytic erythema (in glucagonomas), Verner-Morrison syndrome (in VIPomas), and manifestations such as diabetes, cholelithiasis, and steatorrhea (in somatostatinomas), among others (24, 32–34).
3 Metabolism in cancer
3.1 Carbohydrate metabolism
One of the most well-established hallmarks of cancer is metabolic reprogramming, particularly involving carbohydrate metabolism. The Warburg effect, first described by Otto Warburg, denotes the preferential use of aerobic glycolysis over oxidative phosphorylation, even under normoxic conditions. Although this pathway generates less ATP, it enables the continuous supply of intermediates necessary for rapid proliferation (35–37).
This metabolic shift is orchestrated by oncogenes such as myelocytomatosis oncogene (MYC), rat sarcoma virus oncogene (RAS), and protein kinase B (AKT), and transcriptional regulators like hypoxia-inducible factor 1 (HIF-1), while tumor protein p53 (TP53) downregulation further enhances glycolytic flux (35).
Consequently, tumor cells upregulate glucose transporters (GLUTs), particularly GLUT1, which is commonly overexpressed in several malignancies and represents a potential therapeutic target (38–40). Additionally, transporters such as SLC50A1 (SWEET1) have emerged as promising diagnostic biomarkers due to their strong association with tumor grade and prognosis (41).
Key glycolytic enzymes, including hexokinase 2 (HK2), pyruvate kinase M2 (PKM2), and lactate dehydrogenase A (LDHA), sustain the glycolytic phenotype. These enzymes promote lactate accumulation and acidification of the tumor microenvironment. This contributes to invasion and treatment resistance (42, 43). They are also regulated at the post-transcriptional level by microRNAs, such as miR-145, which modulate glycolysis and mTOR signaling (44–46).
Beyond glucose, tumor cells exhibit remarkable metabolic flexibility, utilizing other carbohydrates such as fructose, galactose, and mannose (47–49). The uptake of fructose via GLUT5 (SLC2A5) and the production of fructose endogenously through the polyol pathway (mediated by AKR1B1 and SORD) sustain glycolysis under hypoxic and acidic conditions. These processes have also been linked to epithelial-mesenchymal transition (EMT) and poor clinical outcomes (49–52). Similarly, alterations in galactose metabolism via the Leloir pathway affect glycosylation and cell signaling, thereby influencing tumor growth and therapeutic response (53–55). Conversely, mannose metabolism can have anti-tumor effects. Accumulation of mannose-6-phosphate inhibits glycolysis and enhances oxidative stress, making cancer cells more susceptible to chemotherapy (56–61).
3.2 Lipid metabolism
Although glucose and glutamine metabolism have been extensively studied, the crucial and multifaceted role of lipid metabolism in cancer progression has recently received significant attention (62, 63). Lipids, including fatty acids, cholesterol, and phospholipids, are essential for membrane structure, cellular signaling, energy storage, and the regulation of proliferation and survival. Alterations in lipid composition affect membrane dynamics and signaling, thereby influencing processes such as cell growth, apoptosis, motility, and metastasis (64, 65).
Enhanced lipid synthesis and fatty acid β-oxidation support tumor proliferation by supplying membrane components, generating energy, and producing lipid-derived signaling molecules. In particular, fatty acids and phospholipids contribute to tumor development, migration, and invasion, and their metabolic pathways represent potential therapeutic targets (66). A pivotal mediator of this enhanced lipogenesis is fatty acid synthase (FASN), an enzyme responsible for catalyzing the synthesis of long-chain fatty acids, whose overexpression has been associated with increased tumor proliferation and poor clinical outcomes (67).
Reprogramming cholesterol metabolism promotes aggressive tumor phenotypes, including therapy resistance and metastatic potential. This occurs largely through modulation of lipid rafts and oncogenic signaling (68–70). These processes are tightly controlled by oncogenic pathways, such as PI3K/Akt, Wnt/β-catenin, and STAT3, as well as by non-coding RNAs that regulate key enzymes, including SREBP, FASN, and PPARs (66). Overall, lipid metabolic reprogramming is a hallmark of oncogenesis, linking metabolism to tumor behavior and providing a framework for identifying metabolic biomarkers with diagnostic and prognostic potential in cancer.
3.3 Amino acid metabolism
Amino acids are key regulators of metabolic and signaling networks that sustain tumor growth and proliferation. Metabolic reprogramming is a hallmark of cancer that reflects tumor-intrinsic properties and microenvironmental influences. It encompasses alterations in transporter activity, biosynthesis, and catabolism (71).
Glutamine plays a central role among them as an anaplerotic substrate that fuels the TCA cycle through glutaminolysis. This process generates intermediates such as α-ketoglutarate (α-KG) and oxaloacetate (OAA), which are essential for mitochondrial ATP production (71, 72). Under hypoxic or glucose-limited conditions, glutamine metabolism adapts through reductive carboxylation to enable citrate production and sustain biosynthetic processes critical for tumor survival.
Glutamine uptake and utilization are highly heterogeneous across tumor types, modulated by factors such as oncogenic signaling and hypoxia (73, 74). Although glutaminase (GLS) is a pivotal enzyme in glutamine catabolism, its inhibition alone is often insufficient due to metabolic plasticity and compensatory pathways involving other amino acids (75–77). Broader targeting strategies that disrupt both anaplerotic and nitrogen metabolism have demonstrated improved antitumor efficacy (78, 79).
Furthermore, perturbations in glutamine availability can reshape the tumor immune microenvironment by reducing PD-L1 expression, reprogramming macrophage polarization, and enhancing immunotherapy response (80, 81). Glutamine deprivation also increases tumor reliance on other amino acids, such as aspartate, asparagine, and branched-chain amino acids (BCAAs: leucine, isoleucine, and valine), which support biosynthesis and redox balance (82, 83). Together, these adaptive mechanisms demonstrate the importance of amino acid metabolism in cancer biology. Understanding how tumors rewire these pathways provides a foundation for identifying metabolic biomarkers with diagnostic and prognostic potential and for designing therapies that exploit metabolic vulnerabilities.
3.4 Nucleotide metabolism
Nucleotide metabolism is fundamental to nucleic acid synthesis, energy homeostasis, and intracellular signaling (84). The balance between synthesis and recycling is maintained through two main pathways: the de novo pathway, which produces nucleotides from metabolic precursors such as glucose and glutamine, and the salvage pathway, which recycles nitrogenous bases and nucleosides (84, 85).
In normal cells, nucleotide biosynthesis is tightly coupled to proliferation signals. Transcription factors such as MYC and Rb/E2F regulate key enzymes during the cell cycle. However, in cancer, these pathways are extensively reprogrammed to sustain uncontrolled proliferation and genomic instability. Different tumor subtypes have specific dependencies, such as a preference for de novo synthesis or the salvage pathway, reflecting metabolic plasticity and adaptive survival strategies (85, 86).
This metabolic flexibility supports not only DNA and RNA synthesis, but also redox regulation and signaling. Consequently, enzymes within nucleotide biosynthetic pathways have become important therapeutic targets. Classic antimetabolites and newer, subtype-specific inhibitors demonstrate how disrupting nucleotide metabolism can hinder tumor growth and expose metabolic vulnerabilities (86, 87).
Together, these insights reinforce the concept that metabolic reprogramming, spanning carbohydrate, lipid, amino acid, and nucleotide metabolism, is integral to tumor progression. This framework provides a foundation for understanding how metabolic biomarkers can inform diagnosis, prognosis, and treatment response, particularly in NENs.
4 Methods
This review was conducted as a narrative synthesis of the current literature on the role of metabolism in GEP-NENs. Although not designed as a systematic review, the selection and evaluation of the literature followed a structured and transparent approach to ensure comprehensiveness and relevance.
A targeted search was performed in the PubMed/MEDLINE database from its inception to May 2025 using combinations of controlled vocabulary (MeSH terms) and free-text keywords related to metabolism and GEP-NENs. The main search strategy included terms such as “metabolism”, “metabolic”, “neuroendocrine tumor”, and “neuroendocrine neoplasm”. Additional relevant studies were identified through manual screening of reference lists from retrieved articles and key reviews. No language restrictions were applied.
Studies were considered for inclusion if they provided original data on metabolic alterations associated with the diagnosis, prognostic stratification, or therapeutic response of GEP-NENs. Both clinical and preclinical investigations were included when they offered mechanistic insights into metabolic alterations underlying tumor behavior.
All titles and abstracts were screened for relevance, followed by a full-text evaluation of eligible papers. Given the heterogeneity of study designs and analytical platforms, a qualitative synthesis was prioritized over a quantitative meta-analysis. The findings are therefore presented descriptively, emphasizing emerging patterns, recurrent metabolic pathways, and clinical implications.
5 Neuroendocrine neoplasms and metabolic markers
5.1 Esophagus
No studies specifically addressing metabolic biomarkers in esophageal neuroendocrine tumors NETs were identified. The available literature primarily focuses on immunohistochemical, genetic, and prognostic aspects of these tumors, with no direct emphasis on pathways or proteins related to cellular metabolism. For instance, one study article evaluated the expression of p16 and RB proteins in esophageal NEC, demonstrating frequent alterations in the p16–RB pathway with prognostic implications, but without relevance to cellular metabolism (88).
5.2 Stomach
The ALDH enzyme family plays a critical role in oxidizing both endogenous and exogenous aldehydes. Among its members, ALDH1A1 is primarily responsible for metabolizing acetaldehyde and has been linked to alcohol sensitivity, dependence, and osteosarcoma. In the context of NEMs, immunohistochemical analysis of gastric tumors revealed that 52.2% exhibited positive cytoplasmic staining for ALDH1A1, with 20.9% demonstrating strong positivity. Notably, strong ALDH1A1 expression was significantly associated with adverse clinicopathological features, including lymph node involvement, lymphovascular invasion, and a higher Ki-67 index, and correlated with poorer overall survival. Furthermore, multivariate analysis confirmed that high ALDH1A1 expression, along with lymph node metastasis and lymphovascular invasion, served as independent predictors of decreased overall survival (89).
Complementing these findings, the role of ubiquitin-specific peptidase 10 (USP10), a member of the ubiquitin-specific protease family involved in stress responses, tumor growth, and cellular metabolism, has been investigated in gastric cancer (GC). Expression studies demonstrated that USP10 levels were significantly lower in GC tissues and cell lines compared to non-cancerous gastric mucosa and an immortalized gastric epithelial cell line. Moreover, reduced USP10 expression was inversely correlated with deeper gastric wall invasion, nodal metastasis, and advanced TNM stage, while showing a positive association with E-cadherin expression. Kaplan-Meier analysis indicated that negative USP10 expression was linked to poorer prognosis, and multivariate analysis identified USP10 as an independent prognostic factor for overall survival in GC patients (90) (Figures 1, 2).
Figure 1. Metabolic reprogramming during progression of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). Initial phases of tumor progression are characterized by reduced activation of mTOR/PI3K/AKT and EZH2 signaling, with increased expression of CBR4, USP10, and SDHB. As tumors progress, a shift from basal neuroendocrine metabolism to intensified metabolic reprogramming occurs, marked by elevated levels of choline, phosphocholine, lactate, taurine, acetate, and succinate, along with suppression of aspartate, glucose/alanine, and ethanolamine/valine. Metastatic lesions show upregulation of GLUT-1, HIF-1α, CA9, miR-210, FASN, FTO, and EZH2, along with enhanced BCAA and tryptophan metabolism and increased LAT-1/4F2hc expression. These changes collectively support the metabolic plasticity required for tumor dissemination and adaptation to the metastatic niche.
Figure 2. Site-specific molecular and metabolic alterations in gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). In the liver, metastatic lesions frequently harbor TP53, APC, and PIK3CA mutations, with elevated miR-210 and miR-21 expression and increased levels of 5-HIAA, choline, phosphocholine, lactate, and aspartate. In the pancreas, MEN1 mutations are associated with downregulation of CBR4 and upregulation of FTO, FASN, LAT-1/4F2hc, GLUT-1, HIF-1α, CA9, and SQSTM1/p62, along with altered BCAA and tryptophan metabolism and activation of mTOR signaling. Gallbladder NENs show CD117 (KIT) positivity and dysregulation of SESN1, IL-6, and AKT pathways. Stomach NENs show increased ALDH1A1 expression and decreased USP10 expression. In the colon, SATB2, INSL5, and RXFP4 are expressed with upregulation of SCGN and GRP78. Small intestinal tumors are associated with CDKN1B mutations, increased EZH2, GIPR, and SDHB expression.
5.3 Small intestine and ampulla
Growing evidence indicates that epigenetic and metabolic changes in cancer cells are closely linked. EZH2, a key epigenetic regulator, suppresses gene transcription through H3K27me3 trimethylation and exhibits high enzymatic activity in cancer cells. It promotes glucose metabolism and aerobic glycolysis, thereby supporting tumor progression through the Warburg effect (91). Small bowel NETs, although genetically stable, display significant epigenetic dysregulation. Unlike normal enterochromaffin cells, small bowel NETs and their metastases exhibit high EZH2 expression. Silencing EZH2 in CNDT2.5 cells reduced proliferation and induced apoptosis, while EZH2 knockout in a xenograft model inhibited tumor growth. Furthermore, EZH2 inhibitors such as CPI-1205 and GSK126 reduced viability, migration, and proliferation in small intestine NET (SI-NET) cell lines. Metformin has also been shown to suppress EZH2 expression and inhibit proliferation in CNDT2.5 and GOT1 cells (92).
GIPR, a key regulator of postprandial metabolism, is involved in glucose metabolism and insulin sensitivity. Gene expression analysis in gastric and duodenal NETs, as well as in small bowel NETs and PanNETs, revealed significant overexpression of multiple receptors; however, GIPR exhibited the greatest overexpression relative to normal tissue. This suggests that GIPR may offer an improved signal-to-noise ratio for imaging and represents a novel therapeutic target (93).
Cyclin-dependent kinases (CDKs) regulate cell cycle progression, and their deregulation has been associated with various diseases, including cancer. In SI-NETs, 8.5% of patients exhibited pathogenic CDKN1B mutations, including insertions, deletions, nonsense variants, and stop-loss variants. These mutations displayed inter- and intratumor heterogeneity but did not correlate with p27 protein expression or clinical characteristics. CDKN1B is considered a potential haploinsufficient tumor suppressor gene in SI-NETs (94).
Finally, SDHB, a mitochondrial complex II subunit, was detected in all ileal tumor cells. Expression levels were significantly higher in primary specimens compared to metastatic ones. Notably, loss of SDHB expression in metastatic tumors correlated with longer overall survival, suggesting that SDHB, combined with Ki-67%, may serve as a prognostic marker in metastatic SI-NETs (95).
5.4 Colorectum and appendix
SATB2, a nuclear matrix-associated protein that regulates gene expression, is normally expressed in the lower gastrointestinal tract. The immunohistochemical analysis identified SATB2 as a sensitive and specific marker for rectal and appendiceal well-differentiated NETs, showing strong expression in 100% of rectal and appendiceal tumors. These findings suggest that SATB2 may serve as a potential diagnostic tool for differentiating primary sites of gastrointestinal NETs (96).
In the context of NEC metabolic biomarkers, INSL5 and its receptor RXFP4 have been identified in colorectal tissues and may play a role in rectal NETs. All examined rectal NETs co-expressed INSL5 and RXFP4, suggesting that INSL5-RXFP4 signaling could be involved in the biology of colorectal NETs (97).
Glucose-regulated proteins (GRPs), cellular proteins responsive to glucose deprivation, play essential roles in protein folding, assembly, and homeostasis. Proteomic analysis of colorectal carcinoma revealed significant alterations in protein expression, with secretagogin (SCGN) downregulated and GRP78 upregulated in tumor tissues. Although GRP78 exhibited increased protein levels, mRNA expression did not differ significantly between tumor samples and normal mucosa. Immunohistochemical analysis demonstrated strong SCGN expression in 98% of neuroendocrine tumors, highlighting its potential as a diagnostic marker (98).
5.5 Pancreas
Several studies have highlighted the role of glucose transporters, particularly GLUT-1, as metabolic biomarkers in PanNETs. One study (99) demonstrated significantly increased expression of GLUT-1 and hypoxia-inducible factor 1-alpha (HIF-1α) in grade 2 PanNETs, NECs, and mixed tumors. These markers were correlated with vascular invasion, lymph node metastasis, high Ki-67 index, and shorter disease-free survival. Furthermore, the association between GLUT-1 and HIF-1α (P = 0.025) suggests HIF-1α-driven GLUT-1 upregulation under hypoxic conditions, facilitating glucose uptake and metabolic reprogramming. By contrast, GLUT-2 showed no prognostic relevance in pancreatic tumors, further supporting the specificity of GLUT-1 as a biomarker in PanNETs.
A comprehensive study of GEP-NETs, including PanNETs, demonstrated that GLUT-1 is overexpressed in aggressive tumors and correlates with metastatic disease and reduced VHL (von Hippel–Lindau) expression, reinforcing the activation of HIF-related pathways under hypoxic conditions (100). These findings highlight the potential of GLUT-1 not only as a diagnostic marker but also as a therapeutic target, particularly in high-grade tumors. In addition to glucose metabolism, amino acid metabolism plays a critical role in supporting PanNET growth. The L-type amino acid transporter 1 (LAT-1) and 4F2hc amino acid transporters exhibit distinct expression patterns linked to tumor aggressiveness (100). Specifically, LAT-1 overexpression was associated with metastatic behavior, low pVHL levels, and high GLUT-1 expression, suggesting coordinated metabolic adaptation to hypoxia. Meanwhile, 4F2hc was more frequently expressed in NET-G2/G3 tumors with vascular invasion and elevated Ki-67, serving as both a diagnostic and prognostic marker. Notably, only 4F2hc was proposed as a potential predictor of mTOR inhibitor response, despite showing no significant impact on overall survival (101).
Additionally, GLUT-1 expression is relevant in functional imaging, such as FDG-PET, which is more frequently positive in aggressive PanNETs. A complementary dual-imaging phenotype has been described in PanNETs, reflecting distinct metabolic and molecular profiles. SSTR-PET (e.g., 68Ga-DOTATATE) positivity is characteristic of well-differentiated tumors with preserved neuroendocrine features and predominant somatostatin receptor expression. In contrast, FDG-PET positivity correlates with higher proliferative activity, dedifferentiation, and activation of glycolytic pathways (102, 103). The upregulation of glycolytic mediators, such as GLUT-1, in PanNETs has repeatedly been correlated with malignant potential and is often linked to increased HIF-1α expression in hypoxic tumor areas (99, 102). Mechanistically, mTOR signaling can induce HIF activity and thereby promote glycolytic gene expression in pancreatic cells, providing a biological link between growth-promoting pathways and metabolic reprogramming (104). Taken together, these observations suggest that the shift from an SSTR-dominant to an FDG-dominant phenotype reflects metabolic reprogramming during PanNET progression. This integration of imaging, molecular, and metabolic features provides a continuum of tumor aggressiveness.
In addition to glucose metabolism, FASN also emerges as a central metabolic biomarker, commonly overexpressed in PanNETs and associated with metastasis, advanced stages, and poor overall survival (105). FASN inhibition with orlistat-induced ferroptosis, evidenced by decreased xCT and GPX4 expression. Moreover, recent studies demonstrated that FABP5 and the FTO demethylase stabilize FASN, enhancing lipid accumulation and activating key oncogenic pathways such as WNT/β-catenin and PI3K/AKT/mTOR inhibition of FABP5 or FTO decreased tumor cell proliferation and migration, and the combination of orlistat with everolimus enhanced antitumor effects. These findings highlight FASN as both a prognostic marker and a potential therapeutic target (106, 107).
The MEN1 gene, frequently mutated in PanNETs, also modulates lipid metabolism. It inhibits the mTOR–SCD1 axis, promoting ferroptosis via polyunsaturated fatty acid (PUFA) peroxidation (108). MEN1 overexpression reduces SCD1 levels, sensitizing cells to ferroptosis. The effect is partially reversed by oleic acid, a product of SCD1. Combined treatment with Everolimus and ferroptosis inducers (e.g., RSL3) demonstrated enhanced efficacy in pNET cells with high MEN1 expression.
Additionally, beyond its effect on FASN, FTO also regulates APOE expression in PanNETs, promoting the accumulation of lipids, cholesterol, and triglycerides (107). Inhibition of FTO with FB23 significantly reduced tumor progression, particularly when combined with Everolimus. Additionally, the oxysterol 24S-hydroxycholesterol (24S-HC), synthesized by Cyp46a1, was linked to HIF-1α-mediated angiogenesis. Although this mechanism has been described beyond pancreatic neuroendocrine tumors, inhibition of Cyp46a1 with zaragozic acid or overexpression of SULT2B1b reduced angiogenesis, indicating a potential role of cholesterol metabolism in PanNETs and other GEP-NENs (109).
Carbonyl reductase 4 (CBR4), which negatively regulates FASN, is frequently downregulated in PanNETs as a result of hypoxia-induced promoter methylation. Its low expression was associated with poor prognosis and resistance to Everolimus (110). Overexpression of CBR4 led to FASN degradation, mTOR inhibition, and increased Everolimus sensitivity, supporting its role as a predictive biomarker.
A metabolomic study specifically focusing on metastatic PanNETs (111) identified an enrichment of branched-chain amino acid (BCAA) degradation pathways (involving BCKDHA and BCKDHB) and tryptophan metabolism (via TDO2, DAO, DPYS). The metabolic reprogramming appeared to support energy production through the TCA cycle, contributing to tumor growth and dissemination in PanNETs.
Hypoxia is a critical feature of the PanNET tumor microenvironment, influencing the expression of markers such as carbonic anhydrase 9 (CA9), which is induced by HIF-1α. CA9, a pH-regulating enzyme induced by hypoxia, was expressed in large PanNETs and those associated with von Hippel-Lindau (VHL) syndrome, while absent in microadenomas or small tumors (112). Its presence was associated with aggressive behavior and an unfavorable prognosis.
In parallel, the mTOR signaling pathway is a central metabolic regulator that is frequently activated in PanNETs (113). Markers such as p-mTOR and p-p70S6K have been associated with better response to Everolimus, while p-4EBP1 expression correlated with poor survival. In addition, SQSTM1/p62, involved in autophagy and mTOR signaling, was overexpressed in PanNETs and associated with recurrence and worse outcomes (114). Its inhibition reduced mTOR phosphorylation and tumor proliferation.
Although not a classical metabolic biomarker, insulin-like growth factor 1 (IGF-1) modulates the PI3K/AKT/mTOR pathway and chromogranin A secretion via R-type Ca²+ channels (CaV2.3). This mechanism has been observed in neuroendocrine cell lines, but further validation in human PanNETs is needed (115).
5.6 Liver
Primary hepatic NENs are rare entities, and their molecular landscape remains poorly understood. TP53 mutations have been identified in both NETs and NECs, reflecting genomic instability and contributing to tumor metabolic plasticity (116). TP53 dysfunction promotes a shift toward aerobic glycolysis (Warburg effect), enhances lipid biosynthesis, and suppresses oxidative phosphorylation, thereby supporting cellular proliferation under hypoxic conditions (117–119).
In addition to TP53 alterations in NECs, mutations in genes such as APC, MLL2 (also known as KMT2D), and SF3B1 have also been reported (116). Although these mutations are not currently actionable, they may cooperatively modulate cellular metabolism. For example, APC mutations can activate the Wnt/β-catenin signaling pathway, which increases glucose uptake and stimulates anabolic metabolic programs (120, 121). Mutations in MLL2, an epigenetic regulator, and SF3B1, a key component of the RNA splicing machinery, have the potential to alter the expression of metabolic enzymes and transporters through epigenomic remodeling or splicing modulation (6, 122, 123).
In another case of a well-differentiated grade 3 NET, the molecular analysis identified additional alterations in PIK3CA, BCL2, and SETD2 in addition to TP53 mutations (116). In particular, the activating mutation in PIK3CA leads to constitutive activation of the PI3K/AKT/mTOR pathway (124), a key regulator of glucose uptake, aerobic glycolysis, nucleotide biosynthesis, and protein synthesis - critical processes for maintaining tumor cell survival and proliferation under metabolic stress (120, 121, 124). In addition, SETD2, a histone methyltransferase, plays a role in regulating gene expression associated with oxidative phosphorylation and the DNA damage response, potentially contributing to a more adaptive cellular phenotype (6, 121, 122). Alterations in BCL2, a key regulator of apoptosis and mitochondrial metabolism, may further impair mitochondrial integrity and promote a glycolytic metabolic shift (125, 126).
In secondary hepatic NENs, elevated levels of urinary 5-hydroxyindoleacetic acid (u5HIAA) - reflecting the secretory activity of functioning tumors - have been associated with increased tumor aggressiveness, disease progression, and the presence of liver metastases (127, 128).
Metabolomic profiling of liver metastases from small intestinal NETs (SI-NETs) has revealed elevated levels of malignancy-associated metabolites - including choline, phosphocholine, taurine, and lactate - compared to normal liver tissue (129). Additional metabolites such as acetate, succinate, and aspartate also contribute to the metabolic signature of metastatic lesions. Acetate is a marker of fatty acid synthesis via acetyl-CoA, while aspartate is considered a limiting metabolite for cell proliferation in cancers with mitochondrial dysfunction. Notably, NET cells appear to be particularly vulnerable to aspartate depletion due to their inherently low asparaginase activity and limited permeability to exogenous aspartate (130).
Furthermore, metabolites such as glucose, alanine, and ethanolamine have been identified as discriminative markers in liver metastases compared to primary SI-NETs (129). Interestingly, these metabolites-along with valine-were found in higher concentrations in normal liver tissue compared to metastatic lesions, highlighting the role of the hepatic microenvironment in shaping the metabolic phenotype of metastatic NETs. These data support the concept of metastatic site-specific metabolic reprogramming and suggest that liver colonization drives a distinct biochemical profile shaped by tumor-host interactions (131).
Accumulating evidence supports the role of epigenetic alterations in the development and progression of NENs. Karpathakis et al. (2017) demonstrated that global DNA hypomethylation is enhanced in liver metastases and is associated with the upregulation of key signaling components including PI3K, EGFR, PDGFRβ, and mTOR (132). Notably, dysregulation of these same pathways has also been reported in primary NENs (133), highlighting shared molecular mechanisms between primary and metastatic disease.
In the broader context of NENs, microRNA-210 (miR-210) has emerged as a critical biomarker linked to tumor progression, metabolic reprogramming, and liver metastasis. Elevated expression of miR-210 and miR-21 correlate with higher Ki-67 proliferation index and the presence of liver metastases in NEs (134) and adenocarcinomas (135), supporting their potential use as prognostic markers. miR-210 is particularly responsive to hypoxic conditions and promotes metabolic adaptation by shifting energy production toward anaerobic glycolysis, one of the hallmarks of malignancy. Its overexpression suppresses tricarboxylic acid (TCA) cycle activity while promoting lactate production, contributing to the Warburg effect (136, 137).
Beyond its role in NETs, miR-210 regulates key targets such as vascular endothelial growth factor (VEGF), a major driver of angiogenesis, further highlighting its potential as a therapeutic target, particularly in tumors where neovascularization and metabolic flexibility are essential for progression (138). The consistent association of miR-210 with metabolic remodeling, cellular stress responses, and tumor aggressiveness positions it as a central molecular integrator of hypoxia-driven tumor adaptation (136, 139, 140).
5.7 Gallbladder and bile ducts
To our knowledge, no studies have investigated the role of classical metabolic markers in NENs of this anatomical location. However, emerging evidence points to molecular players that may influence metabolic reprogramming, providing new insights into the gallbladder and bile ducts NENs (12).
Metabolic reprogramming in neoplasia has been increasingly implicated in the activation of oncogenic signaling pathways, adaptation to the tumor microenvironment, and epigenetic regulation. Recent evidence indicates that microRNA-200c (miR-200c) plays a central role in maintaining cholangiocyte homeostasis by suppressing proliferation and neuroendocrine differentiation through inhibition of SESN1 and the IL-6/AKT axis (141). This signaling axis, known for its involvement in the reprogramming of glucose metabolism (i.e., the Warburg effect), also regulates amino acid and nucleotide metabolism via mTORC1 activation (142–145). Dysregulation of SESN1 - a key cellular stress sensor - may further promote adaptive responses such as autophagy and survival under hypoxic conditions, contributing to a more aggressive and metabolically active tumor phenotype, a hallmark of NENs (146, 147).
In the same context, CD117 (c-Kit) expression, although traditionally associated with proliferation in gastrointestinal stromal tumors (GISTs), may also have indirect effects on tumor metabolism. c-Kit is capable of activating the PI3K/AKT/mTOR pathway (133, 148, 149), which has previously been implicated in NEN pathogenesis (133). This activation can enhance glucose uptake, stimulate aerobic glycolysis through the regulation of glucose transporters such as GLUT1, and promote nucleotide and protein biosynthesis - processes essential for rapid cell proliferation (150, 151).
Interestingly, immunohistochemical positivity for CD117 has been reported in a case of MiNEN (large cell neuroendocrine carcinoma and adenocarcinoma) of the gallbladder (152). Although CD117 is not a direct metabolic marker, its expression may reflect the activation of key metabolic pathways, particularly those involved in glucose and nucleotide biosynthesis, thus serving as an indirect indicator of metabolic reprogramming in these rare tumors.
5 Conclusion and future directions
Metabolic reprogramming is increasingly recognized as a key feature in the pathogenesis of GEP-NENs. Markers such as GLUT-1, HIF-1α, FASN, LAT-1, and CA9 have been associated with tumor aggressiveness, metastasis, and poor prognosis, particularly in PanNENs. Additionally, epigenetic modulators and hypoxia-induced pathways further contribute to metabolic adaptation and therapeutic resistance.
Despite these insights, metabolic biomarkers have not yet been fully integrated into clinical decision-making. A key limitation of the current literature is the lack of studies directly comparing the metabolic profiles of the various clinical and biological subtypes of GEP-NENs. Tumor functionality, grade, differentiation status, primary site, and hereditary background likely drive distinct metabolic phenotypes; however, available studies do not provide stratified data according to these variables. Consequently, it remains challenging to delineate specific metabolic signatures for these subgroups. Most studies are based on small cohorts and lack external validation, and knowledge regarding nucleotide metabolism, mitochondrial regulation, and amino acid pathways in specific NEN subtypes remains limited. Furthermore, near-term research priorities include: (1) multicenter validation of GLUT-1, FASN, and CA9 cut-offs using standardized IHC; (2) prospective studies linking dual-tracer PET imaging to tissue metabolism and outcomes; (3) development of plasma and urine metabolomics panels benchmarked against CgA and u-5HIAA; (4) trials evaluating metabolic co-targeting strategies, such as mTOR inhibition combined with lipogenesis or ferroptosis modulation; (5) investigations designed to explore metabolic heterogeneity in NENs. These approaches aim to translate metabolic insights into clinically actionable tools and address the heterogeneity of GEP-NENs.
Author contributions
RALS: Writing – review & editing, Writing – original draft, Data curation, Methodology, Conceptualization. TFM: Conceptualization, Writing – review & editing, Methodology, Data curation, Writing – original draft. MWAG: Writing – original draft, Data curation, Writing – review & editing. FCPR: Writing – original draft, Writing – review & editing, Data curation. RAM: Writing – original draft, Software, Writing – review & editing. JFS: Writing – review & editing, Writing – original draft, Data curation. HPS: Writing – review & editing, Funding acquisition, Writing – original draft, Project administration. GCF: Supervision, Writing – review & editing, Funding acquisition, Writing – original draft, Resources. ESAG: Resources, Visualization, Funding acquisition, Conceptualization, Supervision, Writing – review & editing, Writing – original draft, Methodology, Project administration.
Funding
The author(s) declared that financial support was received for this work and/or its publication. The authors were supported by the National Cancer Institute of Health under Award Number P30CA042014 (CCSG Award), and by the Gastrointestinal Center at the Huntsman Cancer Institute, Award Number 01-02052-6000-39006.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Keywords: neuroendocrine neoplasms, gastroenteropancreatic neoplasms, metabolic reprogramming, metabolic biomarkers, diagnosis
Citation: de Lima-Souza RA, Maciel TF, Gonçalves MWA, Ribeiro FCP, Maioral RA, Scarini JF, Soraes HP, Fillmore GC and Egal ESA (2025) Metabolic signatures in gastroenteropancreatic neuroendocrine neoplasms: unraveling diagnostic and prognostic insights. Front. Endocrinol. 16:1676021. doi: 10.3389/fendo.2025.1676021
Received: 02 August 2025; Accepted: 17 November 2025; Revised: 03 November 2025;
Published: 11 December 2025.
Edited by:
Francesco Panzuto, Sapienza University of Rome, ItalyReviewed by:
Maria Rinzivillo, Sapienza University of Rome, ItalyAna Paula Santos, Portuguese Oncology Institute, Portugal
Copyright © 2025 de Lima-Souza, Maciel, Gonçalves, Ribeiro, Maioral, Scarini, Soraes, Fillmore and Egal. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Erika Said Abu Egal, ZXJpa2EuZWdhbEBoY2kudXRhaC5lZHU=