A nuclear beacon of hope: an advanced, metastatic glucagonoma treated with [177Lu]Lu-DOTA-TATE.

Glucagonoma is a rare pancreatic neuroendocrine tumor (panNET) that can be characterized by increased secretion of glucagon and distinguishing symptoms - glucagonoma syndrome with a typical dermatosis, necrolytic migratory erythema, being its most common manifestation. While surgery and somatostatin analogs remain first-line therapeutic options in panNETs, radioligand therapy with [177Lu]Lu-DOTA-TATE is a recommended second-line palliative treatment in advanced, metastatic cases. However, its prospects and efficacy are still not vastly researched in less frequent neuroendocrine neoplasms. Here, we present an extraordinary case of a metastatic glucagonoma treated with [177Lu]Lu-DOTA-TATE used as a second-line treatment in progressive disease.

The value of a nomogram model based on CT imaging features in differentiating duodenal gastrointestinal stromal tumors from pancreatic head neuroendocrine tumors.

OBJECTIVE: To construct a nomogram model based on multi-slice spiral CT imaging features to predict and differentiate between duodenal gastrointestinal stromal tumors (GISTs) and pancreatic head neuroendocrine tumors (NENs), providing imaging evidence for clinical treatment decisions. METHODS: A retrospective collection of clinical information, pathological results, and imaging data was conducted on 115 cases of duodenal GISTs and 76 cases of pancreatic head NENs confirmed by surgical pathology at Zhongshan Hospital Fudan University from November 2013 to November 2022. Comparative analysis was performed on the tumor's maximum diameter, shortest diameter, long diameter/short diameter ratio, tumor morphology, tumor border, central position of the lesion, lesion long-axis direction, the relationship between tumor and common bile duct (CBD), duodenal side ulceration of the lesion, calcification, cystic and solid proportion within the tumor, thickened feeding arteries, tumor neovascularization, distant metastasis, and CT values during plain and enhanced scans in arterial and venous phases. Statistical analysis was conducted using t-tests, Mann-Whitney U tests, and χ2 tests. Univariate and multivariate logistic regression analyses were used to identify independent predictors for differentiating duodenal GISTs from pancreatic head NENs. Based on these independent predictors, a nomogram model was constructed, and the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of the model. The nomogram was validated using a calibration curve, and decision curve analysis was applied to assess the clinical application value of the nomogram. RESULTS: There were significant differences in the duodenal GISTs group and the pancreatic head NENs group in terms of longest diameter (P < 0.001), shortest diameter (P < 0.001), plain CT value (P < 0.001), arterial phase CT value (P < 0.001), venous phase CT value (P = 0.002), lesion long-axis direction (P < 0.001), central position of the lesion (P < 0.001), the relationship between tumor and CBD(< 0.001), border (P = 0.004), calcification (P = 0.017), and distant metastasis (P = 0.018). Multivariate logistic regression analysis identified uncertain location (OR 0.040, 95% CI 0.003-0.549), near the duodenum (OR 0, 95% CI 0-0.009), with the lesion long-axis direction along the pancreas as a reference, along the duodenum (OR 0.106, 95% CI 0.010-1.156) or no significant difference (OR 4.946, 95% CI 0.453-54.017), and the relationship between tumor and CBD (OR 0.013, 95% CI 0.001-0.180), shortest diameter (OR 0.705, 95% CI 0.546-0.909), and calcification (OR 18.638, 95% CI 1.316-263.878) as independent risk factors for differentiating between duodenal GISTs and pancreatic head NENs (all P values < 0.05). The combined diagnostic model's AUC values based on central position of the lesion, calcification, lesion long axis orientation, the relationship between tumor and CBD, shortest diameter, and the joint diagnostic model were 0.937 (0.902-0.972), 0.700(0.624-0.776), 0.717(0.631-0.802), 0.559 (0.473-0.644), 0.680 (0.603-0.758), and 0.991(0.982-0.999), respectively, with a sensitivity of 97.3% and a specificity of 93.0% for the joint diagnostic model. The nomogram model's AUC value was 0.985(0.973-0.996), with a sensitivity and specificity of 94.7% and 93.9%, respectively. The calibration curve indicated good agreement between predicted and actual risks. Decision curve analysis verified the clinical application value of the nomogram. CONCLUSION: The nomogram model based on CT imaging features effectively differentiates between duodenal GISTs and pancreatic head NENs, aiding in more precise clinical treatment decisions.

Case report: Surgical treatment and literature review of a recurrent case of glucagonoma.

A 40-year-old male patient was admitted due to abdominal distension and discomfort in the upper abdomen persisting for three days. Enhanced CT of the upper abdomen revealed an irregularly dense soft tissue area in the body and tail of the pancreas, approximately 7.6 × 3.1 cm in size, with blurred boundaries, and indistinct separation from the splenic artery and vein. Multiple liver lesions of varying sizes and slightly lower densities were also observed. Liver tumor biopsy considering a neuroendocrine tumor G2, combined with the medical history, led to a diagnosis of pancreatic neuroendocrine tumor G2 with liver metastasis. Physical examination showed mild tenderness in the upper abdomen but no other significant positive signs. During treatment, the patient developed multiple red papular rashes around the mouth, on both lower limbs, and the perineum, accompanied by itching. The glucagon level was 1138.3 pg/L. The patient underwent resection of the pancreatic body and tail, splenectomy, partial liver tumor resection, and cholecystectomy. Within five days post-surgery, the skin lesions began to crust and flake off. On the 14th day post-surgery, the serum glucagon level was rechecked at 136.4 pg/L. As of April 2024, progression of liver lesions was noted, with no significant skin symptoms during the period.

Exploring the therapeutic potential of simvastatin in pancreatic neuroendocrine neoplasms: insights into cell cycle regulation and apoptosis.

Background: Pancreatic neuroendocrine neoplasm (pNEN) poses significant challenges in clinical management due to their heterogeneity and limited treatment options. In this study, we investigated the potential of simvastatin (SIM) as an anti-tumor agent in pNEN. Methods: We conducted cell culture experiments using QGP-1 and BON-1 cell lines and assessed cell viability, proliferation, migration, and invasion following SIM treatment. To further validate our findings, we performed in vivo experiments using a mouse xenograft model. Additionally, we investigated the underlying molecular mechanisms by analyzing changes in cell cycle progression, apoptosis, and signaling pathways. Results: SIM treatment suppresses pNEN growth both in vitro and in vivo, and led to G1 phase arrest in QGP-1 cells. In contrast, SIM affected both the G1-S and G2-M phase transitions in the BON-1 cell line and induced apoptosis, indicating diverse mechanisms of action. Furthermore, SIM treatment resulted in decreased expression of mutant p53 (mutp53) in BON-1 cells, suggesting a potential therapeutic strategy targeting mutp53. Modulation of the MAPK pathway was also implicated in QGP-1 cells. Conclusions: Our study highlights SIM as a promising candidate for pNEN treatment by inducing cell cycle arrest or apoptosis, potentially through the p53 and MAPK pathways. Further research is warranted to fully elucidate SIM's mechanisms of action and evaluate its therapeutic potential in clinical settings.

Oncogenic pathway signatures predict the risk of progression and recurrence in well-differentiated pancreatic neuroendocrine tumors.

BACKGROUND: Pancreatic neuroendocrine tumors (pNETs) are genomically diverse tumors. The management of newly diagnosed well-differentiated pNETs is limited by a lack of sensitivity of existing biomarkers for prognostication. Our goal was to investigate the potential utility of genetic markers as a predictor of progression-free survival (PFS) and recurrence-free survival (RFS). METHODS: Whole-exome sequencing of resected well-differentiated, low and intermediate-grade (G1 and G2) pNETs and normal adjacent tissue from patients who underwent resection from 2005 to 2015 was performed. Genetic alterations were classified using pan-genomic and oncogenic pathway classifications. Additional samples with genetic and clinicopathologic data available were obtained from the publicly available International Cancer Genome Consortium (ICGC) database and included in the analysis. The prognostic relevance of these genomic signatures on PFS and RFS was analyzed. RESULTS: Thirty-one patients who underwent resection for pNET were identified. Genomic analysis of mutational, copy number, cytogenetic, and complex phenomena revealed similar patterns to prior studies of pNETs with relatively few somatic gene mutations but numerous instances of copy number changes. Analysis of genomic and clinicopathologic outcomes using the combined data from our study as well as the ICGC pNET cohort (n = 124 patients) revealed that the recurrent pattern of whole chromosome loss (RPCL) and metastatic disease were independently associated with disease progression. When evaluating patients with local disease at the time of resection, RPCL and alterations in the TGFß oncogenic pathway were independently associated with the risk of recurrence. CONCLUSIONS: Well-differentiated pNETs are genomically diverse tumors. Pathway signatures may be prognostic for predicting disease progression and recurrence.

Comparison among different preclinical models derived from the same patient with a non-functional pancreatic neuroendocrine tumor.

Pancreatic neuroendocrine tumors are the second most common tumors of the pancreas, and approximately half of patients are diagnosed with liver metastases. Currently, the improvement in the efficacy of relevant treatment methods is still limited. Therefore, there is an urgent need for in-depth research on the molecular biological mechanism of pancreatic neuroendocrine tumors. However, due to their relatively inert biology, preclinical models are extremely scarce. Here, the patient-derived organoid, and patient-derived xenograft were successfully constructed. These two models and the previously constructed cell line named SPNE1 all derived from the same patient with a grade 3 non-functional pancreatic neuroendocrine tumor, providing new tumor modeling platforms, and characterized using immunohistochemistry, whole-exome sequencing, and single-cell transcriptome sequencing. Combined with a tumor formation experiment in immunodeficient mice, we selected the model that most closely recapitulated the parental tumor. Overall, the patient-derived xenograft model most closely resembled human tumor tissue.

Subgrading of G2 Pancreatic Neuroendocrine Tumors as 2A (Ki67 3% to < 10%) Versus 2B (10% to ≤ 20%) Identifies Behaviorally Distinct Subsets in Keeping with the Evolving Management Protocols.

BACKGROUND: Grade 1/2 PanNETs are mostly managed similarly, typically without any adjunct treatment with the belief that their overall metastasis rate is low. In oncology literature, Ki67-index of 10% is increasingly being used as the cutoff in stratifying patients to different protocols, although there are no systematic pathology-based studies supporting this approach. METHODS: Ki67-index was correlated with clinicopathologic parameters in 190 resected PanNETs. A validation cohort (n = 145) was separately analyzed. RESULTS: In initial cohort, maximally selected rank statistics method revealed 12% to be the discriminatory cutoff (close to 10% rule of thumb). G2b cases had liver/distant metastasis rate of almost threefold higher than that of G2a and showed significantly higher frequency of all histopathologic signs of aggressiveness (tumor size, perineural/vascular invasion, infiltrative growth pattern, lymph node metastasis). In validation cohort, these figures were as striking. When all cases were analyzed together, compared with G1, the G2b category had nine times higher liver/distant metastasis rate (6.1 vs. 58.5%; p < 0.001) and three times higher lymph node metastasis rate (20.5 vs. 65.1%; p < 0.001). CONCLUSIONS: G2b PanNETs act very similar to G3, supporting management protocols that regard them as potential therapy candidates. Concerning local management, metastatic behavior in G2b cases indicate they may not be as amenable for conservative approaches, such as watchful waiting or enucleation. This substaging should be considered into diagnostic guidelines, and clinical trials need to be devised to determine the more appropriate management protocols for G2b (10% to ≤ 20%) group, which shows liver/distant metastasis in more than half of the cases, which at minimum warrants closer follow-up.

miRNA Expression Profiling in G1 and G2 Pancreatic Neuroendocrine Tumors.

Pancreatic neuroendocrine neoplasms pose a growing clinical challenge due to their rising incidence and variable prognosis. The current study aims to investigate microRNAs (miRNA; miR) as potential biomarkers for distinguishing between grade 1 (G1) and grade 2 (G2) pancreatic neuroendocrine tumors (PanNET). A total of 33 formalin-fixed, paraffin-embedded samples were analyzed, comprising 17 G1 and 16 G2 tumors. Initially, literature-based miRNAs were validated via real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR), confirming significant downregulation of miR-130b-3p and miR-106b in G2 samples. Through next-generation sequencing, we have identified and selected the top six miRNAs showing the highest difference between G1 and G2 tumors, which were further validated. RT-qPCR validation confirmed the downregulation of miR-30d-5p in G2 tumors. miRNA combinations were created to distinguish between the two PanNET grades. The highest diagnostic performance in distinguishing between G1 and G2 PanNETs by a machine learning algorithm was achieved when using the combination miR-106b + miR-130b-3p + miR-127-3p + miR-129-5p + miR-30d-5p. The ROC analysis resulted in a sensitivity of 83.33% and a specificity of 87.5%. The findings underscore the potential use of miRNAs as biomarkers for stratifying PanNET grades, though further research is warranted to enhance diagnostic accuracy and clinical utility.

Occult Pancreatic Neuroendocrine Tumor Presenting as Carcinoid Syndrome.

We present a case of a 50-year-old male who initially presented to the clinic with complaints of palpitations, shortness of breath, dizziness, night sweats, headaches with associated intermittent episodes of diarrhea, episodes of flushing, and rash on the upper body. Laboratory testing revealed elevated chromogranin A levels. Initial imaging with computed tomography (CT) of the abdomen and pelvis with contrast was negative for any lesions. However, due to his clinical presentation and high suspicion of a neuroendocrine tumor (NET), a positron emission tomography-CT (PET-CT) scan with Gallium 68-DOTATATE was obtained, confirming and localizing his NET in the neck of the pancreas and the liver. Following confirmation and localization of his tumor, he was referred for surgical evaluation and treatment. Pancreatic neuroendocrine tumors are rare and difficult to diagnose, highlighted by unsuccessful initial efforts to localize and confirm the tumor. This case underscores the importance of clinical suspicion and acumen in diagnosing neuroendocrine tumors. Upcoming imaging modalities of PET-CT scans provide promising avenues to uncover neuroendocrine tumors.

Sweet Saboteur: Insulinoma Presenting As Recurrent Hypoglycemic Seizures.

Insulinoma, a rare neuroendocrine tumor of the pancreas, often presents diagnostic challenges due to its diverse clinical manifestations. We present the case of a 25-year-old female with recurrent hypoglycemic seizures and neuroglycopenic symptoms, ultimately diagnosed with insulinoma. Despite an initial asymptomatic period, the patient experienced progressively worsening symptoms over three years, culminating in eight episodes of generalized tonic-clonic seizures per week. Biochemical investigations during hypoglycemic episodes revealed elevated C-peptide and insulin levels, consistent with endogenous hyperinsulinemia. Imaging studies, including contrast-enhanced computed tomography (CECT) and Ga-DOTATATE scan, confirmed a hyper-enhancing lesion in the distal body of the pancreas, indicative of insulinoma. Histopathological examination (HPE) further corroborated the diagnosis. Prompt recognition and surgical excision led to the complete resolution of symptoms and improved long-term prognosis. This case underscores the importance of considering insulinoma in young individuals presenting with recurrent hypoglycemic episodes and highlights the significance of early diagnosis and intervention in preventing morbidity and mortality associated with this condition.

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-Tag2 (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 2-D 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.

Grade 3 Pancreatic Neuroendocrine Tumor Refractory to Chemotherapy Successfully Treated with Peptide Receptor Radionuclide Therapy Leading to Conversion Surgery.

A 59-year-old woman was diagnosed with a pancreatic neuroendocrine tumor (P-NET; Grade 3, Ki67: 25%) with multiple liver and lymph node metastases and started chemotherapy with streptozosin (500 mg/m2/day) in combination with lanreotide acetate (120 mg). After six courses of (daily) streptozosin, the patient had progressive disease, as assessed by computed tomography (CT), and peptide receptor radionuclide therapy (PRRT) was started as second-line treatment. As PRRT was remarkably successful and the tumor shrank, surgery was performed to resect the primary pancreatic tumor, liver metastases, and lymph node metastases. CT evaluation performed six months after the surgery showed a complete response.

Disease-free survival after pancreatectomy for pancreatic neuroendocrine tumors: A 17-year single-center experience of 223 patients.

BACKGROUND: Metastasis or recurrence of pancreatic neuroendocrine tumors (pNETs) after pancreatectomy is an important source of postsurgical morbidity. This study aimed to define disease-free survival (DFS) in this population. METHODS: Patients who underwent pancreatectomy for pNETs between January 2005 and January 2022 were included. Clinicopathologic and survival data were collected, and the primary endpoint was DFS. Kaplan-Meier survival analysis and Cox proportional hazards regression modeling were performed. RESULTS: Of the 223 patients, 144 (65%) distal/subtotal/partial pancreatectomies, 71 (32%) pancreaticoduodenectomies, 6 (3%) total pancreatectomies, and 2 (1%) enucleations were performed. Of the 223 patients, 45 (20%) experienced disease recurrence or metastasis after index pancreatectomy during the 17 years of the study. Nonfunctional pNETs (162 [73%]) were more common than hormonally functional subtypes. The 2- and 5-year DFSs were 82% and 76%, respectively. Kaplan-Meier analysis demonstrated that N1 node positive disease, size of ≥ 4 cm, lymphovascular invasion, perineural invasion, Ki-67 of ≥ 20%, and nonfunctional pNETs are significantly associated with a lower DFS (P < .05). Univariate Cox analysis identified the following predictors to be significantly associated with poorer DFS: larger tumor size (hazard ratio [HR], 1.16; 95% CI, 1.04-1.28), Ki-67 index of ≥ 20% (HR, 4.93; 95% CI, 2.00-11.44), perineural invasion (HR, 3.23; 95% CI, 1.40-7.89), open surgery (HR, 3.34; 95% CI, 1.03-1.33), node-positive disease (HR, 5.27; 95% CI, 2.28-13.26), and increased body mass index (HR, 1.10; 95% CI, 1.03-1.17) (P < .05). CONCLUSION: Of note, 1 in 5 patients who underwent resection developed recurrence or metastasis after pancreatectomy. Prognostic predictors of DFS in pNETs could help optimize treatment and enhance follow-up protocols to improve quality and reduce morbidity.

The association between non-HDL cholesterol and high-grade pancreatic neuroendocrine neoplasms.

PURPOSE: High-density lipoprotein cholesterol (HDL-c) plays an important role in tumorigenesis in several endocrine-related cancers. Few studies have shown the effect of non-HDL-c in malignant tumors. The present study aimed to identify the association between non-HDL-c and high-grade pancreatic neuroendocrine neoplasms (PNENs). METHODS: A total of 197 PNEN patients who underwent surgery were analyzed retrospectively. Clinical and histopathological features, such as patients' age and sex, tumor location and size, tumor grade, the level of serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c) and fasting plasma-glucose levels were obtained. Non-HDL-c was calculated as total cholesterol - HDL-c. The relationships between those features and high-grade PNENs were identified using logistic regression analysis. RESULTS: Among the 197 patients with PNENs, a lower HDL-c level was more common seen in patients with poorly differentiated PNENs than in those with well-differentiated PNENs (P < 0.05). The non-HDL-c/HDL-c ratio was greater in patients with poorly differentiated PNENs than in those with well-differentiated PNENs (P < 0.01). Similarly, a greater proportion of patients with a non-HDL-c/HDL-c ratio larger than 5 was found in patients with poorly differentiated PNENs than in those with well-differentiation PNENs (P < 0.01). Multivariate logistic analysis showed that the non-HDL-c/HDL-c ratio was positively associated with poorly differentiated PNENs (odds ratio (OR) = 1.45, 95% conference interval (CI):1.13-1.87). Similarly, the risk of poorly differentiated PNENs increased significantly in patients with a non-HDL-c/HDL-c greater than 5 (OR = 14.13, 95%CI: 2.98-66.89). The risk of high-grade PNENs increased in patients with a high non-HDL-c/HDL-c ratio (OR = 1.27, 95% CI: 1.04-1.55), and the risk also increased markedly when the ratio was greater than 5 (OR = 5.00, 95%CI: 1.28-19.49). CONCLUSIONS: A high ratio of non-HDL-c/HDL-c was associated with high-grade PNENs or poorly differentiated PNENs.

Insulinoma Unmasked Post Sleeve Gastrectomy With Incidental Renal Cell Carcinoma: A Rare Case.

Insulinoma is a functional pancreatic neuroendocrine tumor (pNET). Usually benign and solitary, these tumors present with recurrent episodes of hypoglycemia due to insulin hypersecretion. It's a rare cause of post bariatric surgery hypoglycemia and hence poses a diagnostic challenge. Here, we report the first case of a 53-year-old male with insulinoma unmasked post sleeve gastrectomy with incidental renal cell carcinoma (RCC). He presented with symptoms of Whipple's triad after two months of sleeve gastrectomy done for morbid obesity. On further inquiry, the patient gave a history of an asymptomatic peripancreatic neuroendocrine tumor (NET) for the past 11 years. With a suspicion of insulinoma, biochemical workup followed by non-invasive imaging like GA-68 DOTA and CT triphasic abdomen scan was done to guide the diagnosis of an insulinoma which also detected a second primary tumor in the right kidney, likely to be a malignant RCC. Following pancreatic mass excision with radical nephrectomy for right renal mass, histopathology (HPE) and immunohistochemistry (IHC) confirmed the diagnosis of an insulinoma and a right renal clear cell carcinoma. The patient was discharged with no further episodes of hypoglycemia. Hence, persistent hypoglycemia post bariatric surgery could be an indication of a hidden insulinoma and this possibility of synchronous tumors should be kept in mind when dealing with rare tumors like insulinoma.

Synchronous neuroendocine liver metastases in comparison to primary pancreatic neuroendocrine tumors on MRI and SSR-PET/CT.

Background: The study aimed to compare and correlate morphological and functional parameters in pancreatic neuroendocrine tumors (pNET) and their synchronous liver metastases (NELM), while also assessing prognostic imaging parameters. Methods: Patients with G1/G2 pNET and synchronous NELM underwent pretherapeutic abdominal MRI with DWI and 68Ga-DOTATATE/TOC PET/CT were included. ADC (mean, min), SNR_art and SNT_T2 (SNR on arterial phase and on T2) and SUV (max, mean) for three target NELM and pNET, as well as tumor-free liver and spleen (only in PET/CT) were measured. Morphological parameters including size, location, arterial enhancement, cystic components, T2-hyperintensity, ductal dilatation, pancreatic atrophy, and vessel involvement were noted. Response evaluation used progression-free survival (PFS) with responders (R;PFS>24 months) and non-responders (NR;PFS ≤ 24 months). Results: 33 patients with 33 pNETs and 95 target NELM were included. There were no significant differences in ADC and SUV values between NELM and pNET. 70% of NELM were categorized as hyperenhancing lesions, whereas the pNETs exhibited significantly lower rate (51%) of hyperenhancement (p<0.01) and significant lower SNR_art. NELM were qualitatively and quantitatively (SNR_T2) significantly more hyperintense on T2 compared to pNET (p=0.01 and p<0.001). NELM of R displayed significantly lower ADCmean value in comparison to the ADC mean value of pNET (0.898 versus 1.037x10-3mm²/s,p=0.036). In NR, T2-hyperintensity was notably higher in NELM compared to pNET (p=0.017). The hepatic tumor burden was significantly lower in the R compared to the NR (10% versus 30%). Conclusions: Arterial hyperenhancement and T2-hyperintensity differ between synchronous NELM and pNET. These findings emphasize the importance of a multifaceted approach to imaging and treatment planning in patients with these tumors as well as in predicting treatment responses.

Diagnostics and Imaging for Pancreatic Neuroendocrine Tumors.

Pancreatic neuroendocrine tumors originate from hormone-producing islet cells and have a propensity to metastasize to the liver once they reach 2 cm in size. Their diagnosis relies upon a combination of computed tomography, MRI, DOTATATE PET, and endoscopic ultrasound with or without tissue biopsy. Biochemical work-up is driven by patient symptoms of hormone excess.

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.

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 two 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 AUROC of 0.886. CONCLUSIONS: We identified and validated an eight-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 versus non-operative management.