Pancreatic Neuroendocrine Tumors Research Articles

An endoscopic ultrasound-based interpretable deep learning model and nomogram for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer

To retrospectively develop and validate an interpretable deep learning model and nomogram utilizing endoscopic ultrasound (EUS) images to predict pancreatic neuroendocrine tumors (PNETs). Following confirmation via pathological examination, a retrospective analysis was performed on a cohort of 266 patients, comprising 115 individuals diagnosed with PNETs and 151 with pancreatic cancer. These patients were randomly assigned to the training or test group in a 7:3 ratio. The least absolute shrinkage and selection operator algorithm was employed to reduce the dimensionality of deep learning (DL) features extracted from pre-standardized EUS images. The retained nonzero coefficient features were subsequently applied to develop predictive eight DL models based on distinct machine learning algorithms. The optimal DL model was identified and used to establish a clinical signature, which subsequently informed the construction and evaluation of a nomogram. Gradient-weighted Class Activation Mapping (Grad-CAM) and Shapley Additive Explanations (SHAP) were implemented to interpret and visualize the model outputs. A total of 2048 DL features were initially extracted, from which only 27 features with coefficients greater than zero were retained. The support vector machine (SVM) DL model demonstrated exceptional performance, achieving area under the curve (AUC) values of 0.948 and 0.795 in the training and test groups, respectively. Additionally, a nomogram was developed, incorporating both DL and clinical signatures, and was visually represented for practical application. Finally, the calibration curves, decision curve analysis (DCA) plots, and clinical impact curves (CIC) exhibited by the DL model and nomogram indicated high accuracy. The application of Grad-CAM and SHAP enhanced the interpretability of these models. These methodologies contributed substantial net benefits to clinical decision-making processes. A novel interpretable DL model and nomogram were developed and validated using EUS images, cooperating with machine learning algorithms. This approach demonstrates significant potential for enhancing the clinical applicability of EUS in predicting PNETs from pancreatic cancer, thereby offering valuable insights for future research and implementation.

First Single-Centre Experience with the Novel HIF-α Inhibitor Belzutifan in Switzerland

Belzutifan is a new HIF-α inhibitor mainly used in two different indications: von Hippel–Lindau syndrome-associated renal cell carcinoma, haemangioblastomas and pancreatic neuroendocrine tumours, as well as sporadic advanced pre-treated renal cell carcinoma. Although efficacy has been demonstrated in phase II and III studies, belzutifan is still not approved in many countries. In addition, von Hippel–Lindau syndrome is a rare disease. Therefore, there is virtually no real-world experience data of belzutifan efficacy available. We aim to determine the real-world efficacy and tolerability of belzutifan in patients with von Hippel–Lindau syndrome-associated tumours and in patients with sporadic advanced tyrosine kinase- and immune checkpoint inhibitors pre-treated for renal cell carcinoma. A retrospective analysis of five patients treated with belzutifan between 2023 and 2024 at a Swiss cancer centre was conducted. In this case series, all patients consistently benefitted from belzutifan with response to treatment. This case series provides real-world evidence that belzutifan is an effective and well-tolerated treatment option for patients with von Hippel–Lindau syndrome-associated renal cell carcinoma, haemangioblastomas and sporadic advanced pre-treated renal cell carcinoma.

Novel Surgical Initiatives in Gastroenteropancreatic Neuroendocrine Tumours.

Neuroendocrine tumours (NET) are rare entities arising from hormone producing cells in the gastroentero-pancreatic (GEP) tract. Surgery is the most common treatment of GEP-NETs. Improvements in surgical techniques allow for more locally advanced and metastasised GEP-NETs to be resected. Laparoscopic and robotically--assisted approaches are increasingly being utilised in the resection of selected GEP-NETs and are facilitated by novel intraoperative tumour localisation tools and parenchyma-sparing methods. At the same time, some authors suggest that indications for formal resections of small well differentiated non-functioning pancreatic NETs and appendiceal NETs should be more restrictive. Advancements in surgery allows for tissue-sparing resections of GEP-NETs. Indications for surgical resection and the extent of the procedure are highly dependent on GEP-NET size, localisation and grading. Robotically assisted surgeries with intraoperative ultrasound and visualisation methods as well as vessel-sparing radical retrograde lymphadenectomies for small intestinal NETs seem to be the future of GEP-NET surgery.

Diffuse expression of p16 in pancreatic neuroendocrine tumors (PanNETs) and the association of morphology variants.

Distinguishing grade 3 pancreatic neuroendocrine tumors (PanNETs) from neuroendocrine carcinomas (PanNECs) is sometimes challenging. Recently, a diffuse p16-positive pattern was reported in PanNECs but not in grade 3 PanNETs, suggesting that p16 could help differentiate these entities. This study aimed to investigate p16 expression in PanNETs of various grades and its association with clinicopathologic features. A total of 114 PanNETs were selected, and their H&E resection slides were reviewed for pathologic features, with a focus on morphologic variants. Tissue microarrays were constructed, and p16 immunohistochemistry was performed. The results were categorized as diffuse positive, partial positive, or negative. Patient electronic health records were reviewed for follow-up data. Among the 114 PanNETs reviewed, 13 (11.4%) exhibited diffuse p16 expression, 40 (35.1%) were negative, and 61 (53.5%) had partial expression. Diffuse p16 expression occurred in 6 of 38 (15.8%) grade 1, 6 of 60 (10.0%) grade 2, and 1 of 16 (6.3%) grade 3 tumors. Expression did not differ substantially with patient demographics, tumor size, grading, staging, or survival, but diffuse p16 expression was more frequent in body/tail tumors (12/65 [18.5%], P = .019) and in stromal-rich tumors (10/23 [43.5%], P < .001). Diffuse p16 expression is not uncommon in PanNETs and may be associated with stroma-rich variants.

Predicting Factor for Occurrence of Postoperative Pancreatic Fistula in Patients with Pancreatic Neuroendocrine Tumors

Background: Neuroendocrine tumors are tumors that can develop in any organ but show a predilection for the pancreas. These can be secreting or non-secreting tumors, or they can be well differentiated or poorly differentiated, or neuroendocrine carcinomas. Surgical treatment is the only treatment with curative intent, but postoperatively, it shows an increased incidence of postoperative pancreatic fistulas. Methods: We carried out a retrospective study which included 26 patients with neuroendocrine tumors and neuroendocrine carcinomas, for whom we performed cephalic duodenopancreatectomies, distal pancreatic resections or enucleation. Results: In our study group, the incidence of pancreatic fistulas was 28%, and a series of risk factors such as the type of surgery (duodenopancreatectomy and enucleation were associated with the highest incidence of POPF), histological type (pancreatic neuroendocrine carcinomas were associated with lowest incidence of POPF), obesity (the incidence of POPF was double in the obese group), functioning tumors (with p = 0.032 and AUC = 746) and dynamic hemoglobin value (AUC = 705 shows a good predicting power, with a cutoff value = 1.8 drop hemoglobin) were indicated. Conclusions: Neuroendocrine tumors show a predisposition for the occurrence of postoperative complications, especially postoperative pancreatic fistulas. There are multiple risk factors that interact in the production of postoperative complications.

Deep Learning Enabled Scoring of Pancreatic Neuroendocrine Tumors Based on Cancer Infiltration Patterns

Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of neoplasms that include tumors with different histomorphologic characteristics that can be correlated to sub-categories with different prognoses. In addition to the WHO grading scheme based on tumor proliferative activity, a new parameter based on the scoring of infiltration patterns at the interface of tumor and non-neoplastic parenchyma (tumor-NNP interface) has recently been proposed for PanNET categorization. Despite the known correlations, these categorizations can still be problematic due to the need for human judgment, which may involve intra- and inter-observer variability. Although there is a great need for automated systems working on quantitative metrics to reduce observer variability, there are no such systems for PanNET categorization. Addressing this gap, this study presents a computational pipeline that uses deep learning models to automatically categorize PanNETs for the first time. This pipeline proposes to quantitatively characterize PanNETs by constructing entity-graphs on the cells, and to learn the PanNET categorization using a graph neural network (GNN) trained on these graphs. Different than the previous studies, the proposed model integrates pathology domain knowledge into the GNN construction and training for the purpose of a deeper utilization of the tumor microenvironment and its architectural changes for PanNET categorization. We tested our model on 105 HE stained whole slide images of PanNET tissues. The experiments revealed that this domain knowledge integrated pipeline led to a 76.70% test set F1-score, resulting in significant improvements over its counterparts.

Surgical Management of Gastroenteropancreatic Neuroendocrine Tumors

Background/Objectives: Neuroendocrine tumors (NETs) are heterogeneous malignancies arising from enterochromaffin cells that can arise from the gastrointestinal (GI) tract and pancreas. Surgical management is the cornerstone of treatment, with the optimal approach tailored by tumor grade, size, location, and presence of metastasis. This review discusses the current strategies for the surgical management of NETs of the gastroenteropancreatic tract. Methods: A review of the available literature was conducted to evaluate surgical approaches to NETs. Consensus guidelines were incorporated to synthesize evidence-based recommendations. Results: For gastric NETs, surgical approach depends on Rindi Classification, WHO grade, and tumor size, with endoscopic approaches favored for smaller and low-grade lesions. Small bowel NETs can be multifocal and thus often require a surgical approach with careful evaluation of the entire intestine. Pancreatic NETs are categorized as functional or non-functional, with enucleation or formal resection strategies based on size, location, functional status, and risk of malignancy. Colorectal NETs are primarily treated with transanal localized or formal surgical resection, depending on lesion size and depth of invasion or presence of lymph node involvement. Appendiceal NETs are either treated with appendectomy or right hemicolectomy, depending on the size, location, and invasiveness of the lesions. For metastatic NETs, cytoreduction, liver transplantation, and targeted therapies offer symptom relief and possible survival benefits. Conclusions: Surgical resection provides curative potential for localized NETs and symptom control in metastatic cases. Future research is essential to refine guidelines for intermediate-risk lesions and multifocal tumors, ensuring optimal outcomes for patients with gastroenteropancreatic NETs.

Differentiation of intrapancreatic accessory spleen from pancreatic neuroendocrine tumor using MRI R2.

To evaluate the performance of R2* in distinguishing intrapancreatic accessory spleens (IPASs) from pancreatic neuroendocrine tumors (PNETs). Two radiologists (R1 and R2) retrospectively reviewed the MRIs of 20 IPAS and 20 PNET patients. IPASs were diagnosed with uptake on 99mTc labeled heat-damaged red blood cell scintigraphy or characteristic findings on CT/MRI and ≥ 12 month-long-stability. PNETs were histopathologically diagnosed with resection. Using McNemar test, sensitivities and specificities of the diagnostic criterion based on R2* mass-to-spleen ratio (MSR) were compared with those of the other criteria using contrast-enhanced (CE) MRI and apparent diffusion coefficient (ADC) MSR. The study included 40 patients (median age, 54; interquartile range, 43-65; 24 men, 16 women). IPASs exhibited spleen-isointensity on T2WI, late arterial and portal phases, and diffusion-weighted images more frequently than PNETs (p <.05). ADC MSRs were lower (p <.001) and R2* MSRs were higher (p <.001) in IPASs compared to PNETs. For R1, sensitivity and specificity were 45.0% and 100.0% for criterion 1 (spleen-isointensity on CE-MRI); 45.0% and 85.0% for criterion 2 (ADC MSR ≤ 1.08); 90.0% and 95.0% for criterion 3 (0.9 ≤ R2* MSR ≤ 1.7). For R2, 75.0% and 100.0%; 45.0% and 90.0%; 90.0% and 100.0%. Criterion 3 showed higher sensitivity than criterion 1 for R1 (p =.004), and criterion 2 for R1 and R2 (p =.012). There was no difference in specificity. For differentiating IPAS from PNET, R2* showed higher sensitivity than, and similar specificity to CE-MRI and ADC.

A nomogram to preoperatively predict the aggressiveness of pancreatic neuroendocrine tumors based on CT features and 3D CT radiomic features.

Combining Computed Tomography (CT) intuitive anatomical features with Three-Dimensional (3D) CT multimodal radiomic imaging features to construct a model for assessing the aggressiveness of pancreatic neuroendocrine tumors (pNETs) prior to surgery. This study involved 242 patients, randomly assigned to training (170) and validation (72) cohorts. Preoperative CT and 3D CT radiomic features were used to develop a model predicting pNETs aggressiveness. The aggressiveness of pNETs was characterized by a combination of factors including G3 grade, nodal involvement (N + status), presence of distant metastases, and/or recurrence of the disease. Three distinct predictive models were constructed to evaluate the aggressiveness of pNETs using CT features, 3D CT radiomic features, and their combination. The combined model demonstrated the greatest predictive accuracy and clinical applicability in both the training and validation sets (AUCs (95% CIs) = 0.93 (0.90-0.97) and 0.89 (0.79-0.98), respectively). Subsequently, a nomogram was developed using the features from the combined model, displaying strong alignment between actual observations and predictions as indicated by the calibration curves. Using a nomogram score of 86.06, patients were classified into high- and low-aggressiveness groups, with the high-aggressiveness group demonstrating poorer overall survival and shorter disease-free survival. This study presents a combined model incorporating CT and 3D CT radiomic features, which accurately predicts the aggressiveness of PNETs preoperatively.

Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors

ObjectivesThe objective is to develop and validate intratumoral and peritumoral ultrasomics models utilizing endoscopic ultrasonography (EUS) to predict pathological grading in pancreatic neuroendocrine tumors (PNETs).MethodsEighty-one patients, including 51 with grade 1 PNETs and 30 with grade 2/3 PNETs, were included in this retrospective study after confirmation through pathological examination. The patients were randomly allocated to the training or test group in a 6:4 ratio. Univariate and multivariate logistic regression were used for screening clinical and ultrasonic characteristics. Ultrasomics is ultrasound-based radiomics. Ultrasomics features were extracted from both the intratumoral and peritumoral regions of conventional EUS images. Subsequently, the dimensionality of these radiomics features was reduced using the least absolute shrinkage and selection operator (LASSO) algorithm. A machine learning algorithm, namely multilayer perception (MLP), was employed to construct prediction models using only the nonzero coefficient features and retained clinical features, respectively.ResultsOne hundred seven ultrasomics features based on EUS were extracted, and only features with nonzero coefficients were ultimately retained. Among all the models, the combined ultrasomics model achieved the greatest performance, with an AUC of 0.858 (95% CI, 0.7512 - 0.9642) in the training group and 0.842 (95% CI, 0.7061 - 0.9785) in the test group. A calibration curve and a decision curve analysis (DCA) also demonstrated its accuracy and utility.ConclusionsThe integrated model using EUS ultrasomics features from intratumoral and peritumoral tumors accurately predicts PNETs' pathological grades pre-surgery, aiding personalized treatment planning.Trial registrationChiCTR2400091906.

Loss of O6-Methylguanine-DNA Methyltransferase Protein Expression by Immunohistochemistry Is Associated With Response to Capecitabine and Temozolomide in Neuroendocrine Neoplasms.

A recent prospective phase II study (ECOG-ACRIN E2211) demonstrated that MGMT deficiency was associated with a significant response to capecitabine and temozolomide (CAPTEM) in pancreatic neuroendocrine neoplasms (NENs); however, routine MGMT analysis in NENs was not recommended. Our study sought to demonstrate whether loss of MGMT protein expression is associated with improved overall survival (OS) in patients receiving CAPTEM for NENs from various tumor sites. Paraffin-embedded tumor samples were evaluated by immunohistochemistry (IHC) using an MGMT monoclonal antibody. Intact MGMT protein expression (i.e., IHC positivity) was defined as any staining intensity (>1+) in ≥36% of neoplastic cells according to an internal validation study. IHC and pyrosequencing for MGMT promotor methylation was performed in an independent cohort of 58 NENs. Real-world OS was extrapolated from insurance claims data with Kaplan-Meier estimates from the date of first CAPTEM administration to the last date of contact. The study cohort included 80 patients (42 men and 38 women) with a median age of 57years (range: 19-89). They had various NENs (33 pancreatic, 17 intestinal, 7 pulmonary, 8 other, and 15 of unknown origin) treated with CAPTEM. The median OS for the 48 patients with MGMT negative tumors was 31months compared to 17.5months for the 32 patients whose tumors were MGMT positive by IHC (HR: 1.75 [95% CI: 1.066-2.87] and p=0.025). IHC results from the independent cohort of 58 NENs showed only 57% concordance with pyrosequencing results. MGMT promotor status by IHC may be a clinically useful indicator that predicts improved OS for NENs treated with CAPTEM, but IHC does not reliably correlate with the findings of MGMT promoter methylation by pyrosequencing.

Can CT Image Reconstruction Parameters Impact the Predictive Value of Radiomics Features in Grading Pancreatic Neuroendocrine Neoplasms?

The WHO grading of pancreatic neuroendocrine neoplasms (PanNENs) is essential in patient management and an independent prognostic factor for patient survival. Radiomics features from CE-CT images hold promise for the outcome and tumor grade prediction. However, variations in reconstruction parameters can impact the predictive value of radiomics. 127 patients with histopathologically confirmed PanNENs underwent CT scans with filtered back projection (B20f) and iterative (I26f) reconstruction kernels. 3190 radiomic features were extracted from tumors and pancreatic volumes. Wilcoxon paired tests assessed the impact of reconstruction kernels and ComBat harmonization efficiency. SVM models were employed to predict tumor grade using the entire set of radiomics features or only those identified as harmonizable. The models' performance was assessed on an independent dataset of 36 patients. Significant differences, after correction for multiple testing, were observed in 69% of features in the pancreatic volume and 51% in the tumor volume with B20f and I26f kernels. SVM models demonstrated accuracy ranging from 0.67 (95%CI: 0.50-0.81) to 0.83 (95%CI: 0.69-0.94) in distinguishing grade 1 cases from higher grades. Reconstruction kernels alter radiomics features and iterative kernel models trended towards higher performance. ComBat harmonization mitigates kernel impacts but addressing this effect is crucial in studies involving data from different kernels.

Single-docking robot-assisted radical antegrade modular pancreatosplenectomy with partial left nephrectomy in a patient with synchronous pancreatic neuroendocrine neoplasm and clear cell renal cell carcinoma.

The synchronous occurrence of pancreatic neuroendocrine neoplasm (PNEN) and clear cell renal cell carcinoma (ccRCC) in one patient is extremely rare. Synchronous resection of both tumours is preferred over a two-stage procedure if possible. The robotic da Vinci Xi platform allows for multi-quadrant surgery with oncological outcomes comparable to those of laparoscopic or open surgery. We present the case report of an 80-year-old male who underwent synchronous resection of a PNEN in the tail of the pancreas and ccRCC in the left kidney. To the best of our knowledge, this is the first case report on this topic.

Endoscopic-Ultrasound-Guided Radiofrequency Ablation for Pancreatic Tumors.

Endoscopic ultrasound (EUS)-guided radiofrequency ablation (RFA) is a promising minimally invasive technique for the treatment of pancreatic lesions. This review first focuses on the technical aspects in EUS-RFA: the procedure typically employs EUS probes with integrated radiofrequency electrodes, enabling accurate targeting and ablation of pancreatic lesions. Different types of RFA devices, monopolar and bipolar energy delivery systems, are discussed, along with considerations for optimal ablation, including energy settings, procedure time, and pre- and post-procedural management. This paper presents a comprehensive literature review of EUS-RFA applied to both solid and cystic pancreatic lesions, including functioning and non-functioning pancreatic neuroendocrine tumors (pNETs), pancreatic cystic lesions (PCLs), pancreatic ductal adenocarcinoma (PDAC), and pancreatic metastases (PMs), discussing current evidence on safety, efficacy, clinical outcomes, and adverse events (AEs). EUS-RFA is an emerging technique with expanding potential for the treatment of both benign and malignant conditions; however, further studies are needed to better define patient selection criteria, assess long-term benefits, and establish definitive indications for its use.

MiR-223 and Chromogranin A Affect Inflammatory Immune Cell Activation in Liver Metastasis of Neuroendocrine Neoplasms.

Neuroendocrine neoplasms (NENs) are a diverse group originating from endocrine cells/their precursors in pancreas, small intestine, or lung. The key serum marker is chromogranin A (CgA). While commonly elevated in patients with NEN, its prognostic value is still under discussion. Secretion/posttranslational proteolytic cleavage of CgA results in multiple bioactive fragments, which are essential regulators of the cardiovascular and immune system. miR-223, regulator of Nrlp3 inflammasome and neutrophil activation, was recently found to have decreased in patients with NEN. We performed flow cytometry of circulating neutrophils in a patient cohort (n = 10) with NEN, microdissection and histology of tumor tissue. Subsequently, in vitro transfections using the well-established human pancreatic NEN cell line (BON), and co-culture experiments with primary macrophages and neutrophils were performed. Serum miR-223 in patients correlated with the expression of the neutrophil activation marker CD15 in circulating cells. Neutrophilic CD62L/CD63 showed good discrimination compared to healthy controls. Immune cell-derived miR-155, miR-193 and miR-223 colocalize with neutrophil in the extra-tumoral tissue alongside Nlrp3-associated caspase-1 activation. miR-223 knockdown in BON decreased the CgA intracellularly, increased in cellular granularity and caspase-1 activation. Plasmin inhibitor a2-aP reverted those effects. Western Blot showed fragmented CgA following miR-223 knockdown, which altered the inflammatory potential of neutrophils. Our data hence provide initial insights into an immunoregulatory mechanism via miR-223 and CgA in NEN cells, as regulation of miR-223 in NEN may affect tumor-associated inflammation.

Pancreatic Well-Differentiated Neuroendocrine Tumors are Frequently Undergraded on Endoscopic Ultrasound-Guided Fine Needle Biopsy Sampling: A Single Institutional Experience.

Objectives. To determine the accuracy of grading pancreatic well-differentiated neuroendocrine tumors (PanNETs) on endoscopic ultrasound-guided fine needle biopsy (EUS-FNB). Methods. Fifty-three (53) PanNETs from 52 patients with EUS-FNB and subsequent resection were included, including 1 patient with 2 synchronous tumors biopsied separately. Grade (G) was assigned as per the 2019 World Health Organization criteria. The concordance of grade between EUS-FNB and resection was measured using kappa statistic. Clinicopathologic features were compared between specimens with concordant or discordant grading. Results. Two-thirds of patients were male, and the median age was 62 years (range 27-85). Four received neoadjuvant therapy. 89% were nonfunctional, whereas 11% were functional. Concordance of grade between EUS-FNB and resection was moderate (kappa = 0.45). Precisely 25% (13 out of 51) of G1 or G2 specimens were discordant. G2 tumors were frequently undergraded on EUS-FNB (11 out of 18; 61%), whereas G1 tumors were only rarely overgraded (2 out of 33; 6%). Two G3 tumors were concordant. There was no correlation between concordance and other clinicopathologic features, except for perineural invasion. Conclusions. The concordance of PanNET grading between EUS-FNB and resection was moderate, and G2 tumors were frequently undergraded on EUS-FNB. Knowledge of this is important to recognize and acknowledge, as this could potentially impact treatment decisions in some patients.

Successful Surgery of a Pancreatic Insulinoma Misdiagnosed as a Neuropsychiatric Disorder for 9 Years: A Case Report

Insulinoma is a rare functional pancreatic neuroendocrine tumour that is usually sporadic and solitary. It can have a varied presentation. Neuroglycopenic manifestations of hypoglycemia due to insuline hypersecretion can mimic neurological or psychiatric disorders, thus often a diagnosis and treatment delay. Insulinoma is a potentially curable condition, but it can be fatal if left unrecognized. We report a case of A 45-year-old woman who had a 9-year delay before diagnosing insulinoma after being initially assessed with anxiety–depressive disorder. The case report below provides a detailed review of the diagnosis, tumour localization, and the successful surgical intervention implemented for the patient.

Venous Thromboembolism in Patients with Neuroendocrine Neoplasms: A Systematic Review of Incidence, Types, and Clinical Outcomes.

Background: Neuroendocrine neoplasms (NENs) are a heterogeneous group of tumors with unique biological characteristics and complications, including thromboembolism. This systematic review evaluates the incidence, types, and clinical outcomes of venous thromboembolic events (VTEs) in NEN patients. Methods: A systematic search of PubMed, Scopus, and Embase was conducted to identify studies on TEs in NENs. Eligible studies included case reports, case series, and retrospective cohort studies reporting VTEs, including deep vein thrombosis (DVT), pulmonary embolism (PE), and visceral vein thrombosis (VVT). Data were extracted on tumor site, functionality, differentiation grade, and VTE type. Results: In total, 33 studies were included, comprising 26 case reports, 2 case series, and 5 retrospective cohort studies. VTE prevalence ranged from 7.5% to 33% across studies. The most common VTEs were DVT, PE, and portal vein thrombosis (PVT). A meta-analysis revealed a pooled VTE prevalence of 11.1% (95% CI: 9.07-13.53%). Pancreatic NENs exhibited the highest thrombotic burden, particularly in poorly differentiated and advanced-stage tumors. Functioning tumors, including glucagonomas and ACTH-secreting NENs, were strongly associated with VTEs, potentially related to their systemic effects on coagulation and inflammation. Conclusions: Venous thromboembolism is a significant complication in NEN patients, especially in advanced or poorly differentiated tumors. Early detection and targeted management are critical for improving outcomes. Further investigations are required to clarify the mechanisms underlying thromboembolism in NENs and to develop optimized prophylactic and therapeutic strategies tailored to this patient population.

Clinicopathological Characteristics and Long-Term Outcomes of Cystic vs. Solid Pancreatic Neuroendocrine Tumors: A Multi-Institutional Experience with 1727 Patients.

To investigate the clinicopathological features and long-term outcomes of cystic and solid pancreatic neuroendocrine tumors (PanNETs). PanNETs uncommonly present as cystic lesions. Whether cystic PanNETs represent a distinct clinical entity compared to solid PanNETs is controversial. Clinicopathologic data of patients with resected PanNETs were collected from 4 high-volume centers between 2000-2019. Clinicopathological characteristics and outcomes of patients with cystic and solid PanNETs were compared based on a 3cm tumor size cut-off using the Chi-squared test and Mann-Whitney U test. Survival estimates were calculated with the Kaplan-Meier method and log-rank test and multivariable analysis using a Cox proportional hazard model. Of the 1727 patients undergoing pancreatectomy for PanNET, the median age was 58.1 years (IQR, 18.4), and 53.3% were male. Of these, 177 (10.3%) were cystic and 1550 (89.7%) solid. Cystic PanNETs were more prevalent in patients with hereditary syndromes, less frequently functional, and more often located in the body/tail of the pancreas. After the exclusion of patients with functional tumors, WHO G3 tumors, hereditary syndromes, neoadjuvant treatment, and metastatic stage, 145 cystic PanNETs were compared to 1059 solid PanNETs, and the median follow-up period of the cohort was 64 months. Cystic PanNETs demonstrated significantly fewer high-risk histopathological features, lymph node metastases (5.5% vs. 24.0%, P<0.001), and distant recurrence (4.1% vs. 14.4%; P<0.001). Among tumors ≤3cm, cystic PanNETs had a low rate of lymph node metastases (3.9% vs. 17.8%; P<0.001), recurrence (3.1% vs. 8.4%; P=0.041), and low propensity to recur distantly. Cystic PanNETs had favorable long-term survival regardless of tumor size. Cystic PanNETs have a more benign course than their solid counterparts and conservative management can be considered for EUS-FNA-proven cystic PanNETs ≤3cm. Parenchyma and lymph-node sparing resections are warranted in patients with cystic PanNETs>3cm. Patients with poor baseline performance status may forego cystic PanNET resection and not affect their overall survival.

Temporal increase in Ki-67 index in patients with pancreatic neuroendocrine tumours.

Pancreatic neuroendocrine tumours (PanNETs) have intra-tumour heterogeneity, notably regarding the Ki-67 index, which is a major prognostic factor. The temporal evolution of PanNET biology is poorly known. We aimed to study the prognostic impact of the temporal evolution of Ki-67 and other molecular markers (MEN1, ATRX/DAXX, PDX1/ARX) in PanNETs. We retrospectively studied 109 patients with sporadic PanNETs and serial tumour samples (n=286), on which we measured the Ki-67 index and the expression of the other markers. Variables associated with shorter overall survival [OS] and Ki-67 increase over time were explored using multivariable analyses. The median time between the initial and last samples was 49.4 months, with a median variation in Ki-67 of +4% (interquartile range [IQR], -1 to +15%; p<0.001) and +0.5%/year (IQR -0.2 to +3.3%). Tumour grade increased in 36% of cases. At multivariable analysis, increase of Ki-67 ≥ 2%/year was associated with shorter OS (HR 1.96, 95% CI [1.02-3.73], p=0.041). This variation was more common in patients who received alkylating agents (OR 4.47, 95%CI [1.48-15.38, p=0.011) and was less common in those who achieved tumour control with somatostatin analogues (OR 0.27, 95%CI [0.08-0.82], p=0.027). MEN1 and ATRX/DAXX expressions were stable over time while the proportion of alpha-like signature (PDX1-/ARX+) decreased (p=0.016); none was associated with Ki-67 nor influenced prognosis. Overall, an increase of PanNET grade and Ki-67 index is frequent over time, indicates poorer prognosis, and is promoted by alkylating agents. Rebiopsy during PanNET evolution seems relevant to adjust prognosis evaluation and therapeutic strategy.