ATRX, DAXX or MEN1 mutant pancreatic neuroendocrine tumors are a distinct alpha-cell signature subgroup

Decoding the genetic puzzle: Mutations in key driver genes of pancreatic neuroendocrine tumors

Although pancreatic neuroendocrine tumors (PanNETs) are less common than other pancreatic tumors, they show significant differences in clinical behavior, genetics, and treatment responses. The understanding of the molecular pathways of PanNETs has gradually improved with advances in sequencing technology. Mutations in MEN1 (the most frequently varied gene) may result in the deletion of the tumor suppressor menin, affecting gene regulation, DNA repair, and chromatin modification. Changes in ATRX and DAXX involve chromatin remodeling, telomere stability and are associated with the alternative lengthening of telomeres (ALT) pathway and aggressive tumors. VHL mutations emphasize the roles of hypoxia and angiogenesis. Mutations in PTEN, TSC1/TSC2, and AKT1-3 often disrupt the mTOR pathway, complicating the genetic landscape of PanNETs. Understanding these genetic alterations and their impact on the PI3K/AKT/mTOR axis help to investigate new targeted therapies, which in turn can improve patient prognosis. This review aims to clarify PanNET pathogenesis through key mutations and their clinical relevance.

Pancreatic neuroendocrine neoplasms (pNENs): Genetic and environmental biomarkers for risk of occurrence and prognosis

Pancreatic neuroendocrine neoplasms (pNENs) are rare and heterogeneous tumors arising from neuroendocrine cells, representing approximately 10 % of all Gastro-Entero-Pancreatic neuroendocrine neoplasms. While most pNENs are sporadic, a subset is associated with genetic syndromes such as multiple endocrine neoplasia type 1 (MEN1) or von Hippel-Lindau disease (VHL). pNENs are further classified into functioning and non-functioning tumors, with distinct clinical behaviors, prognoses, and treatment approaches. This review explores genetic and environmental biomarkers that influence the risk, prognosis, and therapeutic responses in pNENs. The epidemiology of pNENs reveals an increasing incidence, primarily due to advancements in imaging techniques. Genetic factors play a pivotal role, with germline mutations in MEN1, VHL, and other genes contributing to familial pNENs. Somatic mutations, including alterations in the mTOR pathway and DNA maintenance genes such as DAXX and ATRX, are critical in sporadic pNENs. These mutations, along with epigenetic dysregulation and transcriptomic alterations, underpin the diverse clinical and molecular phenotypes of pNENs. Emerging evidence suggests that epigenetic changes, including DNA methylation profiles, can stratify pNEN subtypes and predict disease progression. Environmental and lifestyle factors, such as diabetes, smoking, and chronic pancreatitis, have been linked to an increased risk of sporadic pNENs. While the association between these factors and tumor progression is still under investigation, their potential role in influencing therapeutic outcomes warrants further study. Advances in systemic therapies, including somatostatin analogs, mTOR inhibitors, and tyrosine kinase inhibitors, have improved disease management. Biomarkers such as Ki-67, somatostatin receptor expression, and O6-methylguanine-DNA methyltransferase (MGMT) status are being evaluated for their predictive value. Novel approaches, including the use of circulating biomarkers (NETest, circulating tumor cells, and ctDNA) and polygenic risk scores, offer promising avenues for non-invasive diagnosis and monitoring. Despite these advancements, challenges remain, including the need for large, well-annotated datasets and validated biomarkers. Future research should integrate multi-omics approaches and leverage liquid biopsy technologies to refine diagnostic, prognostic, and therapeutic strategies. Interdisciplinary collaborations and global consortia are crucial for overcoming current limitations and translating research findings into clinical practice. These insights hold promise for improving prevention, early detection, and tailored treatments, ultimately enhancing patient outcomes.

Transcriptomic profiling of pancreatic neuroendocrine tumors: dysregulation of WNT, MAPK, PI3K, neddylation pathways and potential non-invasive biomarkers

The study aimed to identify altered signaling pathways and potential non-invasive biomarkers for pancreatic neuroendocrine tumors (PanNETs) through transcriptomic profiling of tumor tissues. The analysis encompassed samples from non-functional PanNETs (NF-PanNETs), insulinomas, and tumor-adjacent pancreatic tissues (TAPT). In the differential expression analysis comparing PanNETs and TAPTs, we identified 1,210 differentially expressed genes at a false discovery rate significance threshold of < 0.05 and with Log2FoldChange values of > 0.5 and <-0.5. Further pathway enrichment analysis revealed a multitude of overrepresented signaling pathways related to cell proliferation, survival, and tumorigenesis. Significant findings included the Beta-catenin-independent and TCF-dependent WNT signaling pathways, MAPK1/MAPK3 signaling, and terms associated with PI3K/AKT/mTOR signaling. Among the list of DEGs, we also identified 28 upregulated genes encoding cell surface proteins and 24 upregulated genes encoding cancer-associated secretome proteins. Since the proteins of these genes are found in the bloodstream, there is potential for further testing of these markers as biomarkers for liquid biopsy assays. Overall, these findings underscore the promise of transcriptomic landscape analysis in identifying PanNET-specific non-invasive biomarkers and uncovering potential therapeutic targets.

Alpha thalassemia/mental retardation X-linked (ATRX) protein expression in human pituitary neuroendocrine tumours and its reported correlation to prognosis and clinical outcomes: A systematic review

Mutations in Alpha thalassemia/mental retardation X-linked (ATRX) have been implicated in several cancers, including gliomas, sarcomas, neuroendocrine tumors, and other mesenchymal malignancies. ATRX loss contributes to oncogenesis, accelerates tumor growth, and reduces survival by disrupting epigenetic and telomere mechanisms. Additionally, ATRX loss can increase tumor sensitivity to treatment therapies. While research has explored ATRX expression in many cancers, data on its relationship to prognosis in pituitary neuroendocrine tumors (PitNETs) remain inconsistent. This systematic review aims to summarize all available studies on ATRX mutations and expression in PitNETs. A systematic search of PubMed, Scopus, and EMBASE databases was conducted to identify publications between 2014 and 2025 that investigated ATRX mutations or expression in PitNETs, following PRISMA 2020 guidelines. Of 32 identified studies, ten met the inclusion criteria, covering a total of 513 PitNETs. Only 20 tumors (3.9%) showed a loss of ATRX expression. Among these, 60% exhibited corticotrophic pathology, while 20% displayed lactotrophic pathology. A small subset of tumors (30%) was classified as pituitary carcinomas with aggressive and proliferative characteristics. Additionally, 10% demonstrated the alternative lengthening of telomeres (ALT) phenotype, 50% had concurrent TP53 mutations, and 25% had elevated Ki-67 indices, indicating a higher proliferative index. Although ATRX mutations are rare in PitNETs, tumors with ATRX loss tend to be more aggressive and exhibit proliferative and transformative properties. Due to the limited number of cases, further studies with larger, prospective cohorts are needed to better understand the role of ATRX loss in PitNET progression and aggressiveness.

From pathology to therapy: A comprehensive review of ATRX mutation related molecular functions and disorders

ATRX (alpha-thalassemia/mental retardation, X-linked), a chromatin remodeler, is one of the most commonly mutated genes in human cancer. The ATRX protein functions as a histone chaperone, facilitating the proper folding and assembly of histone proteins into nucleosome cores. Investigations into its molecular mechanisms have significantly advanced our understanding of its roles in diseases associated with chromosomal instability and defective DNA repair. In this comprehensive review, we delineate ATRX's critical function in maintaining heterochromatin integrity and genomic stability under physiological conditions. We further explore the pathogenesis of ATRX-deficient tumors and ATRX syndrome, systematically evaluate current therapeutic strategies for these conditions, and propose novel perspectives on potential targeted therapies for ATRX-mutated malignancies. This review provides useful resource for regarding the etiology and treatment of ATRX deficiency-related diseases.

Proteogenomic characterization of non-functional pancreatic neuroendocrine tumors unravels clinically relevant subgroups

The majority of neuroendocrine neoplasms in pancreas are non-functional pancreatic neuroendocrine tumors (NF-PanNETs), which exhibit a high occurrence of distant metastases with limited therapeutic options. Here, we perform a comprehensive molecular characterization of 108 NF-PanNETs through integrative analysis of genomic, transcriptomic, proteomic, and phosphoproteomic profiles. Proteogenomic analysis provides functional insights into the genomic driver alterations of NF-PanNETs, revealing a potential mediator of MEN1 alterations using Men1-conditional knockout mice. Machine-learning-based modeling uncovers a three-protein signature as an independent prognostic factor, which is validated by an independent external cohort. Proteomic and phosphoproteomic-based stratification identifies four subtypes with distinct molecular characteristics, immune microenvironments, and clinicopathological features. Drug screening using patient-derived tumor organoids identifies cyclin-dependent kinase (CDK) 5 and Calcium Voltage-Gated Channel Subunit Alpha1 D (CACNA1D) as ubiquitous and subtype-specific targets, respectively, with in vivo validation using xenograft models. Together, our proteogenomic analyses illustrate a comprehensive molecular landscape of NF-PanNETs, revealing biological insights and therapeutic vulnerabilities.

Prognostic Features in Surgically Resected Well-Differentiated Pancreatic Neuroendocrine Tumors: An Analysis of 904 Patients with 7882 Person-Years of Follow-Up

Importance

The clinical behavior of well-differentiated pancreatic neuroendocrine tumors (PanNETs) is difficult to predict.

Objective

To define more accurately prognosticators for patients with a surgically resected PanNET.

Design

The pathology and Ki-67 immunolabeling index of PanNETs resected from 904 patients was correlated with patient outcome.

Setting

Academic tertiary care hospital.

Participants

Consecutive patients who had a PanNET resected between 1985 and 2025.

Results

The mean patient age at surgery was 56.6 years (SD 14.0), 477 were male (52.8%), and 7882 person-years of follow-up were obtained (mean 8.8 years, SD 6.5). The 10-year survival was 81% (95% CI: 77,86%) for patients with G1 PanNETs (Ki-67 <3%), 68% (95% CI: 61,76%) for patients with G2a PanNETs (Ki-67 3- <10%), 44% (95% CI: 29,66%) for patients with G2b PanNETs (Ki-67 of 10%- ≤20%), and 23% (95% CI: 8,61%) for patients with G3 PanNETs. Metastases (HR 4.7, p <0.0001), vascular invasion (HR 3.0, p <0.0001), tumor size ≥ 2 cm (HR 2.88, p <0.0001), perineural invasion (HR 2.42, p<0.0001), and positive margins (HR 2.18, p <0.0001) were associated with worse overall survival. Insulinoma (HR 0.34, p=3e-04), sclerosing variant (HR 0.47, p=0.05), and cystic variant (HR 0.61, p=0.05) were associated with improved overall survival. T stage and N stage were all statistically significant classifiers of overall survival. Similar associations were found with respect to disease relapse. There was a significant (P<0.001) increase in the proportion of patients diagnosed with stage I vs stage IV disease over time.

Conclusions and relevance

This study supports the classification of PanNETs into four grades (G1, G2a, G2b, and G3) based on Ki-67 labeling, which allows a more accurate prognostic assessments of patients.

Discordant risk factors between pancreatic neuroendocrine neoplasms and pancreatic ductal adenocarcinoma

Pancreatic neuroendocrine neoplasm (panNEN) is a rare malignancy and the second most common type of pancreatic cancer after pancreatic ductal adenocarcinoma (PDAC), but its etiology is poorly understood. We investigated whether the risk factors of panNEN are concordant with those known for PDAC. We performed the largest case-control study to date on panNENs, comprising 927 sporadic nonfunctional panNEN cases and 1807 frequency-matched controls, using data from the Mayo Clinic Biospecimen Resource for Pancreas Research. We assessed associations for obesity, first-degree family history of pancreatic cancer, cigarette smoking, overall type II diabetes mellitus (T2DM), new-onset T2DM (<1 year before panNEN diagnosis), longstanding T2DM (≥5 years), alcohol intake and aspirin use. Multivariable logistic regression was used to calculate odds ratios and 95% confidence intervals (CIs). Our results show that overall T2DM (OR = 1.71, 95% CI: 1.37-2.14) and new-onset T2DM (OR = 2.65, 95% CI: 1.92-3.69) are associated with higher odds of panNEN, but not longstanding T2DM (OR = 1.29, 95% CI: 0.94-1.75). A non-significant elevated odds of panNEN was observed among participants with a positive family history of pancreatic cancer (OR = 1.44, 95% CI: 0.96-2.14). Alcohol use was inversely related to panNEN (OR = 0.52, 95% CI: 0.42-0.66, ever-vs-never). No association was observed for smoking, obesity or aspirin use. These findings indicate that overall T2DM and new-onset T2DM are associated with higher odds of panNEN. Unlike PDAC, alcohol use was inversely related to panNEN, and we found no associations for cigarette smoking, obesity or aspirin use. These results indicate differences in the risk factor profiles of panNEN and PDAC.

Molecular Classification and Characterization of Noninsulinoma: Ready for Prime Time in Clinical Practice?

Pancreatic neuroendocrine tumors are a heterogeneous group of rare clinical tumors, which can be classified into functional pancreatic neuroendocrine tumor (insulinoma is the most common) and noninsulinoma. Insulinoma and noninsulinoma have different mutation profiles. In noninsulinoma, ATRX/DAXX mutation is associated with alternative lengthening of telomeres-positive phenotype and positively correlated with poor prognosis. Copy number variation is also a prognostic marker for a high risk of recurrence. Scholars have used epigenetics as well as a multiomics approach (combining epigenetics, metabolomics, proteomics, etc) to molecularly type noninsulinoma, and there are huge differences in molecular expression and patient prognosis between different groups. In this manuscript, we summarize the published studies that utilized genome, epigenome, transcriptome, and proteome data to classify noninsulinoma.

Identification of metabolite biomarkers for pancreatic neuroendocrine tumours using a metabolomic approach

IMPORTANCE

Metabolic flexibility, a key hallmark of cancer, reflects aberrant tumour changes associated with metabolites. The metabolic plasticity of pancreatic neuroendocrine tumours (pNETs) remains largely unexplored. Notably, the heterogeneity of pNETs complicates their diagnosis, prognosis, and therapeutic management.

OBJECTIVE

Here, we compared the plasma metabolomic profiles of patients with pNET and non-cancerous individuals to understand metabolic dysregulation.

DESIGN, SETTING, PARTICIPANTS, INTERVENTION AND MEASURE

Plasma metabolic profiles of 76 patients with pNETs and 38 non-cancerous individuals were analyzed using LC-MS/MS and FIA-MS/MS (Biocrates AbsoluteIDQ p180 kit). Statistical analyses, including univariate and multivariate methods, were performed along with the generation of receiver operating characteristic (ROC) curves for metabolomic signature identification.

RESULTS

Compared with non-cancerous individuals, patients with pNET exhibited elevated levels of phosphoglyceride metabolites and reduced acylcarnitine levels, indicating an upregulation of fatty acid oxidation (FAO), which is crucial for the energy metabolism of pNET cells and one-carbon metabolism metabolites. Elevated glutamate levels and decreased lipid metabolite levels have been observed in patients with metastatic pNETs. Patients with the germline MEN1 mutations showed lower amino acid metabolites and FAO, with increased metabolites related to leucine catabolism and lipid metabolism, compared to non-MEN1 mutated patients. The highest area under the ROC curve was observed in patients with pNET harbouring MEN1 mutations.

CONCLUSION AND RELEVANCE

This study highlights the distinct plasma metabolic signatures of pNETs, including the critical role of FAO and elevated glutamate levels in metastasis, supporting the energy and biosynthetic needs of rapidly proliferating tumour cells. Mapping of these dysregulated metabolites may facilitate the identification of new therapeutic targets for pNETs management.

Prognosis of small pancreatic neuroendocrine neoplasms: Functionality matters

BACKGROUND

This study aimed to evaluate potential difference in clinicopathological characteristics, prognosis as well as the genetic bases between insulinomas and non-functional pancreatic neuroendocrine neoplasms (NF-PNENs).

METHOD

We analyzed data from 241 patients who underwent resection for PNENs measuring 1-2 ​cm at West China Hospital between 2002 and 2020.

RESULTS

NF-PNENs were more likely to show lymph node involvement (P ​< ​0.001), perineural invasion (P ​= ​0.025), and a more advanced tumor grade (P ​< ​0.001). In multivariate analysis, NF-PNENs, when combined with lymph node metastasis and WHO G2/G3 grading, independently decreased recurrence-free survival [hazard ratio (HR), 4.72; P ​= ​0.014]. Whole exome sequencing revealed that most of the top 20 somatic mutated genes (90 ​%, 36/40) between insulinomas and NF-PNENs are different. Besides, all copy number variant (CNV) patterns were present in NF-PNENs, whereas insulinomas were more likely to exhibit CNV amplification.

CONCLUSION

Insulinomas and small NF-PNENs exhibit distinct tumor biology, prognosis, and genetic backgrounds, which may inform changes in surgical management and postoperative follow-up strategies for these patients.

Locking the gates of immortality: targeting alternative lengthening of telomeres (ALT) pathways

Telomere maintenance is essential for the unlimited proliferation of cancer cells. While most cancers reactivate telomerase to preserve telomeres, approximately 10-15% utilize the alternative lengthening of telomeres (ALT), a telomerase-independent mechanism driven by homologous recombination. ALT is primarily observed in sarcomas and neuroepithelial tumors and it is characterized by hallmarks such as heterogeneous telomere lengths, the presence of ALT-associated PML bodies (APBs), extrachromosomal telomeric repeats (ECTRs), and elevated replication stress. This review has a threefold aim: (1) to examine the mechanisms of ALT activation, (2) to highlight existing therapeutic interventions targeting ALT components and telosomic complexes, and, (3) to pinpoint potential molecular targets for novel anticancer treatments. Therapeutic strategies focus on disrupting APBs, stabilizing G-quadruplex structures, and inhibiting replication stress proteins such as FANCM and SMARCAL1. Emerging evidence highlights the role of shelterin proteins like TRF1 and TRF2, chromatin remodeling factors such as ATRX and DAXX, and the dysregulated cGAS-STING pathway in facilitating ALT activity. Moreover, the inhibitory role of RAP1-SUN1 protein interactions in telomere recombination provides a novel therapeutic avenue. Recent advances have elucidated the intricate balance of replication stress, DNA damage response, and recombination in ALT regulation. These insights can help overcome challenges posed by ALT + cancers, including their ability to transition from telomerase-dependent states. Targeting ALT-specific vulnerabilities offers a promising direction for developing innovative therapies that exploit the unique biology of ALT-driven tumors.

Clinical Relevance of ATRX/DAXX Gene Mutations and ALT in Functioning Pancreatic Neuroendocrine Tumors

Functioning pancreatic neuroendocrine tumors (PanNETs) represent a subset of PanNETs that cause symptoms due to hormonal activity. Insulinoma is the most common functioning PanNET type. Mutations in the alpha thalassemia/mental retardation X-linked (ATRX) and death domain-associated protein (DAXX) genes result in genomic instability. ATRX/DAXX mutations and associated alternative lengthening of telomeres (ALT) are common in non-functioning PanNETs and associated with aggressive tumor behavior. Recent reports have shown that ATRX/DAXX mutations and ALT are also present in functioning PanNETs. In this review, we summarize the literature addressing ATRX/DAXX mutations and ALT in functioning PanNETs and discuss the clinical relevance with regard to distinguishing aggressive and indolent functioning tumors. ATRX/DAXX gene mutations and/or ALT have been reported in insulinoma, glucagonoma, gastrinoma, VIPoma and calcitoninoma. In insulinoma, the presence of ATRX/DAXX mutations and ALT are associated with aggressive behavior and could therefore be used as prognostic biomarkers. Although ATRX/DAXX mutation and ALT assessment may currently not be the standard of care in routine diagnostic pathology practice, the use of DAXX/ATRX immunohistochemistry at least can be encouraged not only for non-functioning but also for functioning PanNETs.

Mechanisms of Alternative Lengthening of Telomeres

In recent years, significant advances have been made in understanding the intricate details of the mechanisms underlying alternative lengthening of telomeres (ALT). Studies of a specialized DNA strand break repair mechanism, known as break-induced replication, and the advent of telomere-specific DNA damaging strategies and proteomic methodologies to profile the ribonucleoprotein composition of telomeres enabled the discovery of networks of proteins that coordinate the stepwise homology-directed DNA repair and DNA synthesis processes of ALT. These networks couple mediators of homologous recombination, DNA template-switching, long-range template-directed DNA synthesis, and DNA strand resolution with SUMO-dependent liquid condensate formation to create discrete nuclear bodies where telomere extension occurs. This review will discuss the recent findings of how these networks may cooperate to mediate telomere extension by the ALT mechanism and their impact on telomere function and integrity in ALT cancer cells.

Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor

CONTEXT

Pancreatic neuroendocrine tumors (PNETs) exhibit a wide range of behavior from localized disease to aggressive metastasis. A comprehensive transcriptomic profile capable of differentiating between these phenotypes remains elusive.

OBJECTIVE

Use machine learning to develop predictive models of PNET metastatic potential dependent upon transcriptomic signature.

METHODS

RNA-sequencing data were analyzed from 95 surgically resected primary PNETs in an international cohort. Two cohorts were generated with equally balanced metastatic PNET composition. Machine learning was used to create predictive models distinguishing between localized and metastatic tumors. Models were validated on an independent cohort of 29 formalin-fixed, paraffin-embedded samples using NanoString nCounter®, a clinically available mRNA quantification platform.

RESULTS

Gene expression analysis identified concordant differentially expressed genes between the 2 cohorts. Gene set enrichment analysis identified additional genes that contributed to enriched biologic pathways in metastatic PNETs. Expression values for these genes were combined with an additional 7 genes known to contribute to PNET oncogenesis and prognosis, including ARX and PDX1. Eight specific genes (AURKA, CDCA8, CPB2, MYT1L, NDC80, PAPPA2, SFMBT1, ZPLD1) were identified as sufficient to classify the metastatic status with high sensitivity (87.5-93.8%) and specificity (78.1-96.9%). These models remained predictive of the metastatic phenotype using NanoString nCounter® on the independent validation cohort, achieving a median area under the receiving operating characteristic curve of 0.886.

CONCLUSION

We identified and validated an 8-gene panel predictive of the metastatic phenotype in PNETs, which can be detected using the clinically available NanoString nCounter® system. This panel should be studied prospectively to determine its utility in guiding operative vs nonoperative management.

Characterization and functional evaluation of goat PDX1 regulatory modules through comparative analysis of conserved interspecies homologs

PDX1 is a crucial transcription factor in pancreas development and mature β-cell function. However, the regulation of PDX1 expression in larger animals mirroring human pancreas morphogenesis and endocrine maturation remains poorly understood. Therefore, we conducted a comparative analysis to characterize regulatory regions of goat PDX1 gene and assessed their transcriptional activity by transient transfection of several transgenic EGFP constructs in β- and non-β cell lines. We recognized several highly conserved regions encompassing the promoter and cis-regulatory elements (Area I-IV) at 5' flanking sequence of the genes. Within the promoter, we identified that a key E-box and nearby CAAT element synergistically drive transcription, constituting the basal promoter of goat PDX1 gene. Furthermore, each recognized regulatory area separately enhances this basal promoter activity in β-cells compared to non-β cells; however, cooperatively, they exhibit a bifunctional regulatory effect on transcription. Additionally, the intact ~ 3 kb upstream region (Area I-III) functions as the most efficient reporter transgene in vitro and shows islet-specific expression in native rat pancreas. Together, our findings suggest that the regulation of goat PDX1 gene is governed by conserved regions similar to other mammals, while both structurally and functionally, these regions exhibit a closer resemblance to those found in humans.

Subtyping of pancreatic neuroendocrine tumors by transcription factors, hormones, histology, and patient outcome

BACKGROUND

Pancreatic neuroendocrine tumors (PanNETs) show pronounced heterogeneity in terms of hormone and transcription factor (TF) expression. TFs such as ARX and PDX1 are related to alpha- and beta-cell-type features, respectively, and partly associate with patient outcome. However, detailed studies correlating hormone expression, histology, and clinical data are lacking.

OBJECTIVE

The aim of this study was to identify subtypes of PanNETs that associate with histological, hormonal, and prognostic findings.

METHODS

A total of 185 resected PanNETs were divided into five subtypes (types A1, A2, B, C, and D) by cluster analysis based on expression of four TFs (ARX, PDX1, ISL1, and CDX2) and correlated to the expression of hormones and DAXX/ATRX as well as ALT activation status, histology, and progression-free survival.

RESULTS

Subgroup A1 (ISL1+/ARX+/PDX-/CDX2-) was most frequent (46%), followed by type B (18%; ISL1+/ARX-/PDX+/CDX2-), A2 (15%; ISL1+/ARX+/PDX+/CDX2-), C (15%; ISL1-/ARX-/PDX-/CDX2-), and D (5%; ISL1-/ARX-/PDX+/CDX2+). Subgroups A1 and A2 showed a strong association with a trabecular growth pattern and glucagon and pancreatic polypeptide (PP) expression (p < 0.001), while A2 was in addition associated with gastrin expression. Subgroup B was associated with insulin production (p < 0.001) and included all 17 insulinomas. Subgroup C was associated with solid morphology and expression of serotonin, calcitonin, and adrenocorticotropic hormone (ACTH). Subgroup D showed solid morphology, expression of ACTH, somatostatin, or serotonin and had the shortest disease-free survival (p < 0.01). ALT positivity was associated with poorer outcome in types A1 and A2 but not in other types.

CONCLUSION

PanNETs can be categorized into five subgroups based on different TF signatures, which associate strongly with histology, hormone production, functionality, and patient outcome.

ARX, PDX1, ISL1, and CDX2 Expression Distinguishes 5 Subgroups of Pancreatic Neuroendocrine Tumors With Correlations to Histology, Hormone Expression, and Outcome

Many pancreatic neuroendocrine tumors (PanNETs) fall into 2 major prognostic subtypes based on DAXX/ATRX-induced alternative lengthening of telomerase phenotype and alpha- and beta-cell-like epigenomic profiles. However, these PanNETs are still flanked by other PanNETs that do not fit into either subtype. Furthermore, despite advanced genotyping, PanNETs are generally not well-characterized in terms of their histologic and hormonal phenotypes. We aimed to identify new subgroups of PanNETs by extending the currently used transcription factor signatures and investigating their correlation with histologic, hormonal, molecular, and prognostic findings. One hundred eighty-five PanNETs (nonfunctioning 165 and functioning 20), resected between 1996 and 2023, were classified into 5 subgroups (A1, A2, B, C, and D) by cluster analysis based on ARX, PDX1, islet-1 (ISL1), and CDX2 expressions and correlated with trabecular vs solid histology, expression of insulin, glucagon, polypeptide (PP), somatostatin, serotonin, gastrin, calcitonin, adrenocorticotropic hormone (ACTH), DAXX/ATRX, MEN1, and alternative lengthening of telomerase status by fluorescence in situ hybridization, and disease-free survival. A1 (46%, ARX+/ISL1+/PDX1-/CDX2-) and A2 (15%, ARX+/ISL1+/PDX1+/CDX2-) showed trabecular histology and glucagon/PP expression, with A2 also showing gastrin expression. B (18%, PDX1+/ISL1+/ARX-/CDX2-) showed solid histology, insulin, and somatostatin expression (P < .001). It included all insulinomas and had the best outcome (P < .01). C (15%, ARX-/PDX1-/ISL1-/CDX2-) showed solid histology and frequent expression of serotonin, calcitonin, and ACTH. D (5%, PDX1+/CDX2+/ISL1-/ARX-) showed solid histology, expressed ACTH/serotonin, and was an independent poor prognosticator (P < .01). Differential expressions of ARX, PDX1, ISL1, and CDX2 stratified PanNETs into 5 subgroups with different histologies, hormone expressions, and outcomes. Subgroups A1 and A2 resembled the alpha-cell-like type, and subgroup B, the beta-cell-like type. Subgroup C with almost no transcription factor signature was unclear in cell lineage, whereas the PDX+/CDX2+ signature of subgroup D suggested a pancreatic/intestinal cell lineage. Assigning PanNETs to the subgroups may help establish the diagnosis, predict the outcome, and guide the treatment.

Mutant ATRX: pathogenesis of ATRX syndrome and cancer

The transcriptional regulator ATRX, a genetic factor, is associated with a range of disabilities, including intellectual, hematopoietic, skeletal, facial, and urogenital disabilities. ATRX mutations substantially contribute to the pathogenesis of ATRX syndrome and are frequently detected in gliomas and many other cancers. These mutations disrupt the organization, subcellular localization, and transcriptional activity of ATRX, leading to chromosomal instability and affecting interactions with key regulatory proteins such as DAXX, EZH2, and TERRA. ATRX also functions as a transcriptional regulator involved in the pathogenesis of neuronal disorders and various diseases. In conclusion, ATRX is a central protein whose abnormalities lead to multiple diseases.

Molecular Basis of Pancreatic Neuroendocrine Tumors

Pancreatic neuroendocrine tumors (NETs) are rare well-differentiated neoplasms with limited therapeutic options and unknown cells of origin. The current classification of pancreatic neuroendocrine tumors is based on proliferative grading, and guides therapeutic strategies, however, tumors within grades exhibit profound heterogeneity in clinical manifestation and outcome. Manifold studies have highlighted intra-patient differences in tumors at the genetic and transcriptomic levels. Molecular classification might become an alternative or complementary basis for treatment decisions and reflect tumor biology, actionable cellular processes. Here, we provide a comprehensive review of genomic, transcriptomic, proteomic and epigenomic studies of pancreatic NETs to elucidate patterns shared between proposed subtypes that could form a foundation for new classification. We denote four NET subtypes with distinct molecular features, which were consistently reproduced using various omics technologies.

Gastroenteropancreatic neuroendocrine neoplasms: epidemiology, genetics, and treatment

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

Genomic Landscape of Pancreatic Neuroendocrine Tumors and Implications for Clinical Practice

Pancreatic neuroendocrine tumors (pNETs) are the second most prevalent neoplasms of the pancreas with variable prognosis and clinical course. Our knowledge of the genetic alterations in patients with pNETs has expanded in the past decade with the availability of whole-genome sequencing and germline testing. This review will focus on potential clinical applications of the genetic testing in patients with pNETs. For somatic testing, we discuss the commonly prevalent somatic mutations and their impact on prognosis and treatment of patients with pNET. We also highlight the relevant genomic biomarkers that predict response to specific treatments. Previously, germline testing was only recommended for high-risk patients with syndromic features (MEN1, VHL, TSC, and NF1), we review the evolving paradigm of germline testing in pNETs as recent studies have now shown that sporadic-appearing pNETs can also harbor germline variants.

Neoplastic Progression in Neuroendocrine Neoplasms of the Pancreas

CONTEXT.—

Pancreatic neuroendocrine neoplasms (PanNENs) represent a heterogeneous group of epithelial tumors of the pancreas showing neuroendocrine differentiation. These neoplasms are classified into well-differentiated pancreatic neuroendocrine tumors (PanNETs), which include G1, G2, and G3 tumors, and poorly differentiated pancreatic neuroendocrine carcinomas (PanNECs), which are G3 by definition. This classification mirrors clinical, histologic, and behavioral differences and is also supported by robust molecular evidence.

OBJECTIVE.—

To summarize and discuss the state of the art regarding neoplastic progression of PanNENs. A better comprehension of the mechanisms underpinning neoplastic evolution and progression of these neoplasms may open new horizons for expanding biologic knowledge and ultimately for addressing new therapeutic strategies for patients with PanNENs.

DATA SOURCES.—

Literature review of published studies and the authors' own work.

CONCLUSIONS.—

PanNETs can be seen as a unique category, where G1-G2 tumors may progress to G3 tumors mainly driven by DAXX/ATRX mutations and alternative lengthening of telomeres. Conversely, PanNECs display totally different histomolecular features more closely related to pancreatic ductal adenocarcinoma, including TP53 and Rb alterations. They seem to derive from a nonneuroendocrine cell of origin. Even the study of PanNEN precursor lesions corroborates the rationale of considering PanNETs and PanNECs as separate and distinct entities. Improving the knowledge regarding this dichotomous distinction, which guides tumor evolution and progression, will represent a critical basis for PanNEN precision oncology.

Proteogenomic characterization of pancreatic neuroendocrine tumors uncovers hypoxia and immune signatures in clinically aggressive subtypes

Pancreatic neuroendocrine tumors (PanNETs) represent well-differentiated endocrine neoplasms with variable clinical outcomes. Predicting patient outcomes using the current tumor grading system is challenging. In addition, traditional systemic treatment options for PanNETs, such as somatostatin analogs or cytotoxic chemotherapies, are very limited. To address these issues, we characterized PanNETs using integrated proteogenomics and identified four subtypes. Two proteomic subtypes showed high recurrence rates, suggesting clinical aggressiveness that was missed by current classification. Hypoxia and inflammatory pathways were significantly enriched in the clinically aggressive subtypes. Detailed analyses revealed metabolic adaptation via glycolysis upregulation and oxidative phosphorylation downregulation under hypoxic conditions. Inflammatory signature analysis revealed that immunosuppressive molecules were enriched in immune hot tumors and might be immunotherapy targets. In this study, we characterized clinically aggressive proteomic subtypes of well-differentiated PanNETs and identified candidate therapeutic targets.

Loss of ATRX and DAXX in pancreatic neuroendocrine tumors: Association with recurrence risk, cellular phenotype, and heterogeneity

Pancreatic neuroendocrine tumors (PanNETs) comprise a heterogeneous group of neoplasms in terms of biological behavior. This study aims to develop a practical algorithm based on emerging biomarkers, including chromatin-remodeling molecules DAXX/ATRX/H3K36me3, in conjunction with established prognostic factors, such as WHO grade and size. In immunohistochemical analyses, 18 of the 111 (16.2%) primary PanNETs showed DAXX or ATRX loss in a mutually exclusive manner. DAXX/ATRX loss was significantly correlated with higher recurrence risk and better predicted postoperative recurrence than WHO grade. We proposed a novel algorithm for stratifying patients with resectable PanNET into three groups according to recurrence risk: (A) WHO Grade 1 and ≤2 cm (very low-risk); for the others, (B) retained DAXX/ATRX (low-risk) and (C) DAXX/ATRX complete/heterogeneous loss (high-risk). Furthermore, we elucidated the intratumoral heterogeneities of PanNETs. Among cases with DAXX or ATRX loss, nine cases demonstrated heterogeneous loss of expression of DAXX/ATRX/H3K36me3. The majority of cases with DAXX/ATRX loss, either homogeneous or heterogeneous loss, showed uniform α-cell-like phenotype (ARX1+/PDX1-). In cases of metastatic or recurrent tumors, the expression pattern was identical to that observed in at least part of the primary tumor. In some instances, the expression pattern differed among different metastatic or recurrent tumors of the same patient. In summary, we propose a clinically useful and practical algorithm for postoperative recurrence risk stratification in PanNETs, by combining DAXX/ATRX status with WHO grade and size. Moreover, our findings highlighted the frequent spatiotemporal heterogeneity of chromatin-remodeling molecule expression in PanNETs with an α-cell phenotype, offering insights into tumorigenesis.

A cross-species transcriptomic analysis reveals a novel 2-dimensional classification system explaining the invasiveness heterogeneity of pancreatic neuroendocrine tumor

Pancreatic neuroendocrine tumors (PanNETs), the second most common type of primary pancreatic tumors, display notable heterogeneity in invasiveness. Current knowledge regarding genomic alterations, including DAXX/ATRX, MEN1 mutations, and copy number variations (CNVs), provides some insights into tumor invasiveness. However, the underlying reasons for the significant variation in invasiveness between insulinoma and other types of PanNETs remain unclear. To construct a comprehensive model for the stratification of prognosis, we employed analysis of both the well-established Rip1-Tag 2 (RT2) mouse model of PanNETs and human PanNETs with various functional types. Firstly, by applying single-cell and bulk RNA sequencing in PanNETs from different ages and strains of RT2 mice and human PanNETs, we introduced a 2-dimensional (2D) classification system. Based on the 2D classification system, human PanNETs were mainly classified as benign insulinomas or non-insulinomas subclusters. Non-insulinomas subtypes mainly included gastrinomas, glucagonomas, VIPomas, and NF-PanNETs, which all exhibited potential invasiveness. In addition, we discovered an enrichment of specific CNV patterns and mutations in corresponding human PanNET subclusters. Then we denoted somatic DAXX/ATRX as the 'second hit' and confounding factors for invasiveness. Finally, by combining the 2D system, DAXX/ATRX mutation status, and tumor diameter, a group of indolent PanNETs with minimal recurrence risk was identified. In conclusion, our current work constructed a comprehensive model to elucidate the heterogeneity of invasiveness in PanNETs and improve prognostic stratification.

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

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

DNA Methylation Profiling Enables Accurate Classification of Nonductal Primary Pancreatic Neoplasms

BACKGROUND & AIMS

Cytologic and histopathologic diagnosis of non-ductal pancreatic neoplasms can be challenging in daily clinical practice, whereas it is crucial for therapy and prognosis. The cancer methylome is successfully used as a diagnostic tool in other cancer entities. Here, we investigate if methylation profiling can improve the diagnostic work-up of pancreatic neoplasms.

METHODS

DNA methylation data were obtained for 301 primary tumors spanning 6 primary pancreatic neoplasms and 20 normal pancreas controls. Neural Network, Random Forest, and extreme gradient boosting machine learning models were trained to distinguish between tumor types. Methylation data of 29 nonpancreatic neoplasms (n = 3708) were used to develop an algorithm capable of detecting neoplasms of non-pancreatic origin.

RESULTS

After benchmarking 3 state-of-the-art machine learning models, the random forest model emerged as the best classifier with 96.9% accuracy. All classifications received a probability score reflecting the confidence of the prediction. Increasing the score threshold improved the random forest classifier performance up to 100% with 87% of samples with scores surpassing the cutoff. Using a logistic regression model, detection of nonpancreatic neoplasms achieved an area under the curve of >0.99. Analysis of biopsy specimens showed concordant classification with their paired resection sample.

CONCLUSIONS

Pancreatic neoplasms can be classified with high accuracy based on DNA methylation signatures. Additionally, non-pancreatic neoplasms are identified with near perfect precision. In summary, methylation profiling can serve as a valuable adjunct in the diagnosis of pancreatic neoplasms with minimal risk for misdiagnosis, even in the pre-operative setting.

Well-differentiated G1 and G2 pancreatic neuroendocrine tumors: a meta-analysis of published expanded DNA sequencing data

Introduction

Well-differentiated pancreatic neuroendocrine tumors (PNETs) can be non-functional or functional, e.g. insulinoma and glucagonoma. The majority of PNETs are sporadic, but PNETs also occur in hereditary syndromes, primarily multiple endocrine neoplasia type 1 (MEN1). The Knudson hypothesis stated a second, somatic hit in MEN1 as the cause of PNETs of MEN1 syndrome. In the recent years, reports on genetic somatic events in both sporadic and hereditary PNETs have emerged, providing a basis for a more detailed molecular understanding of the pathophysiology. In this systematic review and meta-analysis, we made a collation and statistical analysis of aggregated frequent genetic alterations and potential driver events in human grade G1/G2 PNETs.

Methods

A systematic search was performed in concordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) reporting guidelines of 2020. A search in Pubmed for published studies using whole exome, whole genome, or targeted gene panel (+400 genes) sequencing of human G1/G2 PNETs was conducted at the 25th of September 2023. Fourteen datasets from published studies were included with data on 221 patients and 225 G1/G2 PNETs, which were divided into sporadic tumors, and hereditary tumors with pre-disposing germline variants, and tumors with unknown germline status. Further, non-functioning and functioning PNETs were distinguished into two groups for pathway evaluation. The collated genetical analyses were conducted using the 'maftools' R-package.

Results

Sporadic PNETs accounted 72.0% (162/225), hereditary PNETs 13.3% (30/225), unknown germline status 14.7% (33/225). The most frequently altered gene was MEN1, with somatic variants and copy number variations in overall 42% (95/225); hereditary PNETs (germline variations in MEN1, VHL, CHEK2, BRCA2, PTEN, CDKN1B, and/or MUTYH) 57% (16/30); sporadic PNETs 36% (58/162); unknown germline status 64% (21/33). The MEN1 point mutations/indels were distributed throughout MEN1. Overall, DAXX (16%, 37/225) and ATRX-variants (12%, 27/225) were also abundant with missense mutations clustered in mutational hotspots associated with histone binding, and translocase activity, respectively. DAXX mutations occurred more frequently in PNETs with MEN1 mutations, p<0.05. While functioning PNETs shared few variated genes, non-functioning PNETs had more recurrent variations in genes associated with the Phosphoinositide 3-kinase, Wnt, NOTCH, and Receptor Tyrosine Kinase-Ras signaling onco-pathways.

Discussion

The somatic genetic alterations in G1/G2 PNETs are diverse, but with distinct differences between sporadic vs. hereditary, and functional vs. non-functional PNETs. Increased understanding of the genetic alterations may lead to identification of more drivers and driver hotspots in the tumorigenesis in well-differentiated PNETs, potentially giving a basis for the identification of new drug targets. (Funded by Novo Nordisk Foundation, grant number NNF19OC0057915).

Context-specific functions of chromatin remodellers in development and disease

Chromatin remodellers were once thought to be highly redundant and nonspecific in their actions. However, recent human genetic studies demonstrate remarkable biological specificity and dosage sensitivity of the thirty-two adenosine triphosphate (ATP)-dependent chromatin remodellers encoded in the human genome. Mutations in remodellers produce many human developmental disorders and cancers, motivating efforts to investigate their distinct functions in biologically relevant settings. Exquisitely specific biological functions seem to be an emergent property in mammals, and in many cases are based on the combinatorial assembly of subunits and the generation of stable, composite surfaces. Critical interactions between remodelling complex subunits, the nucleosome and other transcriptional regulators are now being defined from structural and biochemical studies. In addition, in vivo analyses of remodellers at relevant genetic loci have provided minute-by-minute insights into their dynamics. These studies are proposing new models for the determinants of remodeller localization and function on chromatin.

The stromal microenvironment endows pancreatic neuroendocrine tumors with spatially specific invasive and metastatic phenotypes

Cancer-associated fibroblasts (CAFs) play an important role in a variety of cancers. However, the role of tumor stroma in nonfunctional pancreatic neuroendocrine tumors (NF-PanNETs) is often neglected. Profiling the heterogeneity of CAFs can reveal the causes of malignant phenotypes in NF-PanNETs. Here, we found that patients with high stromal proportion had poor prognosis, especially for that with infiltrating stroma (stroma and tumor cells that presented an infiltrative growth pattern and no regular boundary). In addition, myofibroblastic CAFs (myCAFs), characterized by FAP+ and α-SMAhigh, were spatially closer to tumor cells and promoted the EMT and tumor growth. Intriguingly, only tumor cells which were spatially closer to myCAFs underwent EMT. We further elucidated that myCAFs stimulate TGF-β expression in nearby tumor cells. Then, TGF-β promoted the EMT in adjacent tumor cells and promoted the expression of myCAFs marker genes in tumor cells, resulting in distant metastasis. Our results indicate that myCAFs cause spatial heterogeneity of EMT, which accounts for liver metastasis of NF-PanNETs. The findings of this study might provide possible targets for the prevention of liver metastasis.

Molecular Pathology of Pancreatic Cystic Lesions with a Focus on Malignant Progression

The malignant progression of pancreatic cystic lesions (PCLs) remains understudied with a knowledge gap, yet its exploration is pivotal for effectively stratifying patient risk and detecting cancer at its earliest stages. Within this review, we delve into the latest discoveries on the molecular level, revealing insights into the IPMN molecular landscape and revised progression model, associated histologic subtypes, and the role of inflammation in the pathogenesis and malignant progression of IPMN. Low-grade PCLs, particularly IPMNs, can develop into high-grade lesions or invasive carcinoma, underscoring the need for long-term surveillance of these lesions if they are not resected. Although KRAS and GNAS remain the primary oncogenic drivers of neoplastic development in IPMNs, additional genes that are important in tumorigenesis have been recently identified by whole exome sequencing. A more complete understanding of the genes involved in the molecular progression of IPMN is critical for effective monitoring to minimize the risk of malignant progression. Complicating these strategies, IPMNs are also frequently multifocal and multiclonal, as demonstrated by comparative molecular analysis. Algorithms for preoperative cyst sampling and improved radiomic techniques are emerging to model this spatial and temporal genetic heterogeneity better. Here, we review the molecular pathology of PCLs, focusing on changes associated with malignant progression. Developing models of molecular risk stratification in PCLs which can complement radiologic and clinical features, facilitate the early detection of pancreatic cancer, and enable the development of more personalized surveillance and management strategies are summarized.

Altered CELF4 splicing factor enhances pancreatic neuroendocrine tumors aggressiveness influencing mTOR and everolimus response

Pancreatic neuroendocrine tumors (PanNETs) comprise a heterogeneous group of tumors with growing incidence. Recent molecular analyses provided a precise picture of their genomic and epigenomic landscape. Splicing dysregulation is increasingly regarded as a novel cancer hallmark influencing key tumor features. We have previously demonstrated that splicing machinery is markedly dysregulated in PanNETs. Here, we aimed to elucidate the molecular and functional implications of CUGBP ELAV-like family member 4 (CELF4), one of the most altered splicing factors in PanNETs. CELF4 expression was determined in 20 PanNETs, comparing tumor and non-tumoral adjacent tissue. An RNA sequencing (RNA-seq) dataset was analyzed to explore CELF4-linked interrelations among clinical features, gene expression, and splicing events. Two PanNET cell lines were employed to assess CELF4 function in vitro and in vivo. PanNETs display markedly upregulated CELF4 expression, which is closely associated with malignancy features, altered expression of key tumor players, and distinct splicing event profiles. Modulation of CELF4 influenced proliferation in vitro and reduced in vivo xenograft tumor growth. Interestingly, functional assays and RNA-seq analysis revealed that CELF4 silencing altered mTOR signaling pathway, enhancing the effect of everolimus. We demonstrate that CELF4 is dysregulated in PanNETs, where it influences tumor development and aggressiveness, likely by modulating the mTOR pathway, suggesting its potential as therapeutic target.

Premalignant Lesions in the Kidney Transplant Candidate

End-stage kidney disease patients who are referred for transplant undergo an extensive evaluation process to ensure their health prior to transplant due in part to the shortage of available organs. Although management and surveillance guidelines exist for malignancies identified in the transplant and waitlist populations, less is written about the management of premalignant lesions in this population. This review covers the less common premalignant lesions (intraductal papillary mucinous neoplasm, gastrointestinal stromal tumor, thymoma, and pancreatic neuroendocrine tumor) that can be found in the transplant candidate population. High-level evidence for the management of these rarer premalignant lesions in the transplant population is lacking, and this review extrapolates evidence from the general population and should not be a substitute for a multidisciplinary discussion with medical and surgical oncologists.

Genetic and epigenetic prognosticators of neuroendocrine tumours of the GI tract, liver, biliary tract and pancreas: A systematic review and meta-analysis

Multiple recurrent genetic and epigenetic aberrations have been associated with worse prognosis in multiple studies of neuroendocrine tumours (NETs), but these have been mainly small cohorts and univariate analysis. This review and meta-analysis will focus upon the literature available on NETs of the gastrointestinal (GI) tract, liver, biliary tract and pancreas. PubMed and Embase were searched for publications that investigated the prognostic value of (epi)genetic changes of neuroendocrine tumours. A meta-analysis was performed assessing the association of the (epi)genetic alterations with overall survival (OS), disease-free survival (DFS) or locoregional control (LRC). In the pancreas DAXX/ATRX [hazard ratio (HR) = 3.29; 95% confidence interval (CI) = 2.28-4.74] and alternative lengthening telomeres (ALT) activation (HR = 8.20; 95% CI = 1.40-48.07) showed a pooled worse survival. In the small bowel NETs gains on chromosome 14 were associated with worse survival (HR  2.85; 95% CI = 1.40-5.81). NETs from different anatomical locations must be regarded as different biological entities with diverging molecular prognosticators, and epigenetic changes being important to the pathogenesis of these tumours. This review underpins the prognostic drivers of pancreatic NET which lie in mutations of DAXX/ATRX and ALT pathways. However, there is reaffirmation that prognostic molecular biomarkers of small bowel NETs should be sought in copy number variations (CNVs) rather than in single nucleotide variations (SNVs). This review also reveals how little is known about the prognostic significance of epigenetics in NETs.

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.

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.

Predicting recurrence in pancreatic neuroendocrine tumours: role of ARX and alternative lengthening of telomeres (ALT)

BACKGROUND

While many pancreatic neuroendocrine tumours (PanNET) show indolent behaviour, predicting the biological behaviour of small nonfunctional PanNETs remains a challenge. Nonfunctional PanNETs with an epigenome and transcriptome that resemble islet alpha cells (ARX-positive) are more aggressive than neoplasms that resemble islet beta cells (PDX1-positive). In this study, we explore the ability of immunohistochemistry for ARX and PDX1 and telomere-specific fluorescence in situ hybridisation (FISH) for alternative lengthening of telomeres (ALT) to predict recurrence.

METHODS

Two hundred fifty-six patients with PanNETs were identified, and immunohistochemistry for ARX and PDX1 was performed. Positive staining was defined as strong nuclear staining in >5% of tumour cells. FISH for ALT was performed in a subset of cases.

RESULTS

ARX reactivity correlated with worse disease-free survival (DFS) (P = 0.011), while there was no correlation between PDX1 reactivity and DFS (P = 0.52). ALT-positive tumours (n = 63, 31.8%) showed a significantly lower DFS (P < 0.0001) than ALT-negative tumours (n = 135, 68.2%). ARX reactivity correlated with ALT positivity (P < 0.0001). Among nonfunctional tumours, recurrence was noted in 18.5% (30/162) of ARX-positive tumours and 7.5% (5/67) of ARX-negative tumours. Among WHO grade 1 and 2 PanNETs with ≤2 cm tumour size, 14% (6/43) of ARX-positive tumours recurred compared to 0 of 33 ARX-negative tumours and 33.3% (3/9) ALT-positive tumours showed recurrence versus 4.4% (2/45) ALT-negative tumours.

CONCLUSION

Immunohistochemistry for ARX and ALT FISH status may aid in distinguishing biologically indolent cases from aggressive small low-grade PanNETs, and help to identify patients who may preferentially benefit from surgical intervention.

Intertumoral lineage diversity and immunosuppressive transcriptional programs in well-differentiated gastroenteropancreatic neuroendocrine tumors

Neuroendocrine tumors (NETs) are rare cancers that most often arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic (GEP)-NET growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we investigated the single-cell transcriptomes of tumor and immune cells from patients with gastroenteropancreatic NETs. Malignant GEP-NET cells expressed genes and regulons associated with normal, gastrointestinal endocrine cell differentiation, and fate determination stages. Tumor and lymphoid compartments sparsely expressed immunosuppressive targets commonly investigated in clinical trials, such as the programmed cell death protein-1/programmed death ligand-1 axis. However, infiltrating myeloid cell types within both primary and metastatic GEP-NETs were enriched for genes encoding other immune checkpoints, including VSIR (VISTA), HAVCR2 (TIM3), LGALS9 (Gal-9), and SIGLEC10. Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

Upregulation of Somatostatin Receptor Type 2 Improves 177Lu-DOTATATE Therapy in Receptor-Deficient Pancreatic Neuroendocrine Tumor Model

Pancreatic neuroendocrine tumors (PNET) express high levels of somatostatin receptor type 2 (SSTR2), a unique target for both tumor imaging and therapy. This surface expression is lost in metastatic high-grade PNETs, making patients ineligible for SSTR2-targeted 177 Lutetium (Lu)-DOTATATE peptide receptor radionuclide therapy (PRRT), and represents an unmet clinical need. Here, we aimed to restore SSTR2 expression through the reversal of inhibitory epigenetic gene silencing to improve tumor responsiveness to PRRT. We first assessed human SSTR2 promoter methylation and expression levels in 96 patient samples. We then used three NET cell lines (QGP-1, BON-1, GOT-1) with variable SSTR2 expression profiles for functional in vitro studies using histone deacetylase inhibitors (HDACi). Finally, the QGP-1 xenograft mouse model, with low basal SSTR2 expression, was used to assess the therapeutic efficacy of combined HDACi and 177Lu-DOTATATE therapies. We confirm that SSTR expression is decreased and correlates with SSTR2 promoter methylation in patients with high-grade NETs. When exposed to HDACis, SSTR2 surface expression is increased in three NET cell lines in vitro. In an in vivo PNET xenograft model with low basal SSTR2 expression, our studies demonstrate significantly higher tumor uptake of SSTR2-targeted 177Lu-DOTATATE in animals pretreated with HDACis compared with controls. For the first time, we show that this higher tumor uptake results in significant antitumor response when compared with standard PRRT alone. These preclinical results provide a rationale for utilizing HDACi pretreatment to improve targeted radionuclide therapy in patients with SSTR2-negative, metastatic PNETs.

Pan-Cancer Analysis of Copy-Number Features Identifies Recurrent Signatures and a Homologous Recombination Deficiency Biomarker to Predict Poly (ADP-Ribose) Polymerase Inhibitor Response

PURPOSE

Copy-number (CN) features reveal the molecular state of cancers and may have predictive and prognostic value in the treatment of cancer. We sought to apply published CN analysis methods to a large pan-cancer data set and characterize ubiquitous CN signatures across tumor types, including potential utility for treatment selection.

METHODS

We analyzed the landscape of CN features in 260,333 pan-cancer samples. We examined the association of 10 signatures with genomic alterations and clinical characteristics and trained a machine learning classifier using CN and insertion and deletion features to detect homologous recombination deficiency signature (HRDsig) positivity. Clinical outcomes were assessed using a real-world clinicogenomic database (CGDB) of comprehensive genomic profiling linked to deidentified, electronic health record-derived clinical data.

RESULTS

CN signatures were prevalent across cancer types and associated with diverse processes including focal tandem duplications, seismic amplifications, genome-wide loss of heterozygosity (gLOH), and HRD. Our novel HRDsig outperformed gLOH in predicting BRCAness and effectively distinguished biallelic BRCA and homologous recombination-repair wild-type (HRRwt) samples pan-tumor, demonstrating high sensitivity to detect biallelic BRCA in ovarian (93%) and other HRD-associated cancers (80%-87%). Pan-tumor prevalence of HRDsig was 6.4%. HRRwt cases represented a significant fraction of the HRDsig-positive cohort, likely reflecting a population with nongenomic mechanisms of HRD. In ovarian and prostate CGDBs, HRDsig identified more patients than gLOH and had predictive value for poly (ADP-ribose) polymerase inhibitor (PARPi) benefit.

CONCLUSION

Tumor CN profiles are informative, revealing diverse processes active in cancer. We describe the landscape of 10 CN signatures in a large pan-cancer cohort, including two associated with HRD. We trained a machine learning-based HRDsig that robustly identified BRCAness and associated with biallelic BRCA pan-tumor, and was predictive of PARPi benefit in real-world ovarian and prostate data sets.

Models in Pancreatic Neuroendocrine Neoplasms: Current Perspectives and Future Directions

Pancreatic neuroendocrine neoplasms (pNENs) are a heterogeneous group of tumors derived from multiple neuroendocrine origin cell subtypes. Incidence rates for pNENs have steadily risen over the last decade, and outcomes continue to vary widely due to inability to properly screen. These tumors encompass a wide range of functional and non-functional subtypes, with their rarity and slow growth making therapeutic development difficult as most clinically used therapeutics are derived from retrospective analyses. Improved molecular understanding of these cancers has increased our knowledge of the tumor biology for pNENs. Despite these advances in our understanding of pNENs, there remains a dearth of models for further investigation. In this review, we will cover the current field of pNEN models, which include established cell lines, animal models such as mice and zebrafish, and three-dimensional (3D) cell models, and compare their uses in modeling various disease aspects. While no study model is a complete representation of pNEN biology, each has advantages which allow for new scientific understanding of these rare tumors. Future efforts and advancements in technology will continue to create new options in modeling these cancers.

A systems biology approach to define mechanisms, phenotypes, and drivers in PanNETs with a personalized perspective

Pancreatic neuroendocrine tumors (PanNETs) are a rare tumor entity with largely unpredictable progression and increasing incidence in developed countries. Molecular pathways involved in PanNETs development are still not elucidated, and specific biomarkers are missing. Moreover, the heterogeneity of PanNETs makes their treatment challenging and most approved targeted therapeutic options for PanNETs lack objective responses. Here, we applied a systems biology approach integrating dynamic modeling strategies, foreign classifier tailored approaches, and patient expression profiles to predict PanNETs progression as well as resistance mechanisms to clinically approved treatments such as the mammalian target of rapamycin complex 1 (mTORC1) inhibitors. We set up a model able to represent frequently reported PanNETs drivers in patient cohorts, such as Menin-1 (MEN1), Death domain associated protein (DAXX), Tuberous Sclerosis (TSC), as well as wild-type tumors. Model-based simulations suggested drivers of cancer progression as both first and second hits after MEN1 loss. In addition, we could predict the benefit of mTORC1 inhibitors on differentially mutated cohorts and hypothesize resistance mechanisms. Our approach sheds light on a more personalized prediction and treatment of PanNET mutant phenotypes.

Molecular and Functional Heterogeneity of Primary Pancreatic Neuroendocrine Tumors and Metastases

INTRODUCTION

Treatment response to the standard therapy is low for metastatic pancreatic neuroendocrine tumors (PanNETs) mainly due to the tumor heterogeneity. We investigated the heterogeneity between primary PanNETs and metastases to improve the precise treatment.

METHODS

The genomic and transcriptomic data of PanNETs were retrieved from the Genomics, Evidence, Neoplasia, Information, Exchange (GENIE), and Gene Expression Omnibus (GEO) database, respectively. Potential prognostic effects of gene mutations enriched in metastases were investigated. Gene set enrichment analysis was performed to investigate the functional difference. Oncology Knowledge Base was interrogated for identifying the targetable gene alterations.

RESULTS

Twenty-one genes had significantly higher mutation rates in metastases which included TP53 (10.3% vs. 16.9%, p = 0.035) and KRAS (3.7% vs. 9.1%, p = 0.016). Signaling pathways related to cell proliferation and metabolism were enriched in metastases, whereas epithelial-mesenchymal transition (EMT) and TGF-β signaling were enriched in primaries. Gene mutations were highly enriched in metastases that had significant unfavorable prognostic effects included mutation of TP53 (p < 0.001), KRAS (p = 0.001), ATM (p = 0.032), KMT2D (p = 0.001), RB1 (p < 0.001), and FAT1 (p < 0.001). Targetable alterations enriched in metastases included mutation of TSC2 (15.5%), ARID1A (9.7%), KRAS (9.1%), PTEN (8.7%), ATM (6.4%), amplification of EGFR (6.0%), MET (5.5%), CDK4 (5.5%), MDM2 (5.0%), and deletion of SMARCB1 (5.0%).

CONCLUSION

Metastases exhibited a certain extent of genomic and transcriptomic diversity from primary PanNETs. TP53 and KRAS mutation in primary samples might associate with metastasis and contribute to a poorer prognosis. A high fraction of novel targetable alterations enriched in metastases deserves to be validated in advanced PanNETs.

Indications for genetic study in gastro-entero-pancreatic and thoracic neuroendocrine tumors

Gastro-entero-pancreatic (GEP-NET) and thoracic neuroendocrine tumours (NETs) are one of the most heritable groups of neoplasms in the body, being multiple endocrine neoplasia syndrome type 1 (MEN1), the genetic syndrome most frequently associated with this type of tumours. Moreover, Von Hippel Lindau syndrome, tuberous sclerosis, type 4 multiple neoplasia syndrome, and type 1 neurofibromatosis are associated with an increased risk of developing GEP-NETs. Another important aspect in GEP-NETs and thoracic NETs is the knowledge of the molecular background since the molecular profile of these tumours may have implications in the prognosis and in the response to specific treatments. This review summarizes the main indications for performing a genetic study in patients with GEP-NETs and thoracic NETs, and the methods used to carry it out. Moreover, it offers a description of the main hereditary syndromes associated with these NETs and their molecular background, as well as the clinical implications of the molecular profile.

All Together Now: Standardization of Nomenclature for Neuroendocrine Neoplasms across Multiple Organs

Neuroendocrine neoplasms (NENs) span virtually all organ systems and exhibit a broad spectrum of behavior, from indolent to highly aggressive. Historically, nomenclature and grading practices have varied widely across, and even within, organ systems. However, certain core features are recapitulated across anatomic sites, including characteristic morphology and the crucial role of proliferative activity in prognostication. A recent emphasis on unifying themes has driven an increasingly standardized approach to NEN classification, as delineated in the World Health Organization's Classification of Tumours series. Here, we review recent developments in NEN classification, with a focus on NENs of the pancreas and lungs.

The Expression of Autophagy-Associated Genes Represents a Valid Footprint for Aggressive Pancreatic Neuroendocrine Neoplasms

Pancreatic neuroendocrine neoplasms (pNEN) are rare and heterogeneous tumors. Previous investigations have shown that autophagy can be a target for cancer therapy. This study aimed to determine the association between the expression of autophagy-associated gene transcripts and clinical parameters in pNEN. In total, 54 pNEN specimens were obtained from our human biobank. The patient characteristics were retrieved from the medical record. RT-qPCR was performed to assess the expression of the autophagic transcripts BECN1, MAP1LC3B, SQSTM1, UVRAG, TFEB, PRKAA1, and PRKAA2 in the pNEN specimens. A Mann-Whitney U test was used to detect differences in the expression of autophagic gene transcripts between different tumor characteristics. This study showed that G1 sporadic pNEN have a higher expression of autophagic genes compared to G2. Lymphatic and distant metastasis occurred significantly more often in pNEN with a decreased expression of the autophagic genes. Within sporadic pNEN, the insulinomas express higher levels of autophagic transcripts than gastrinomas and non-functional pNEN. MEN1-associated pNEN show a higher expression of autophagic genes than sporadic pNEN. In summary, a decreased expression of autophagic transcripts distinguishes metastatic from non-metastatic sporadic pNEN. The significance of autophagy as a molecular marker for prognosis and therapy decisions needs to be further investigated.

Transcriptomic Deconvolution of Neuroendocrine Neoplasms Predicts Clinically Relevant Characteristics

Pancreatic neuroendocrine neoplasms (panNENs) are a rare yet diverse type of neoplasia whose precise clinical-pathological classification is frequently challenging. Since incorrect classifications can affect treatment decisions, additional tools which support the diagnosis, such as machine learning (ML) techniques, are critically needed but generally unavailable due to the scarcity of suitable ML training data for rare panNENs. Here, we demonstrate that a multi-step ML framework predicts clinically relevant panNEN characteristics while being exclusively trained on widely available data of a healthy origin. The approach classifies panNENs by deconvolving their transcriptomes into cell type proportions based on shared gene expression profiles with healthy pancreatic cell types. The deconvolution results were found to provide a prognostic value with respect to the prediction of the overall patient survival time, neoplastic grading, and carcinoma versus tumor subclassification. The performance with which a proliferation rate agnostic deconvolution ML model could predict the clinical characteristics was found to be comparable to that of a comparative baseline model trained on the proliferation rate-informed MKI67 levels. The approach is novel in that it complements established proliferation rate-oriented classification schemes whose results can be reproduced and further refined by differentiating between identically graded subgroups. By including non-endocrine cell types, the deconvolution approach furthermore provides an in silico quantification of panNEN dedifferentiation, optimizing it for challenging clinical classification tasks in more aggressive panNEN subtypes.

Combined Infiltrative Macroscopic Growth Pattern and Infiltrative Microscopic Tumor Border Status Is a Novel Surrogate Marker of Poor Prognosis in Patients With Pancreatic Neuroendocrine Tumor

CONTEXT.—

Pancreatic neuroendocrine tumors (PanNETs) are heterogeneous tumors with a wide range of malignant potential. Therefore, identification of prognostic factors is essential.

OBJECTIVE.—

To systematically assess the significance of tumor border, a well-known prognostic indicator in other cancers, in PanNETs.

DESIGN.—

We evaluated the macroscopic growth pattern (expansile [Exp] versus infiltrative [Inf]) and the microscopic tumor border (pushing [Pus] versus Inf) of 203 surgically resected PanNETs and compared them with other clinicopathologic factors.

RESULTS.—

Based on macroscopic growth pattern, 83 cases had Exp patterns whereas 84 had Inf patterns. According to microscopic tumor border, 122 PanNETs had Pus borders whereas 81 had Inf borders. Combining macroscopic growth pattern and microscopic tumor border, 65 PanNETs had Exp/Pus, 34 had Inf/Pus, 18 had Exp/Inf, and 50 had Inf/Inf status. PanNETs with Inf/Inf status were associated with higher tumor grade, pT classification, and American Joint Committee on Cancer stage grouping; lymph node metastasis; and lymphovascular and perineural invasions (all P < .001). Patients with PanNET having Inf/Inf status had significantly shorter overall survival (OS) and recurrence-free survival (RFS; all P < .001). Further, using multivariate analysis, Inf/Inf status was identified as an independent poor prognostic factor of OS (P = .02) and RFS (P = .03).

CONCLUSIONS.—

In summary, combined Inf/Inf status was observed in approximately 25% of PanNETs and was associated with aggressive biological behavior and short OS and RFS. Therefore, assessing combined macroscopic growth pattern and microscopic tumor border can provide additional information regarding survival and recurrence in PanNET patients.