Normal Pancreas Research Articles

Sitagliptin-induced Pancreatitis: A case report and plausible mechanism

Drugs are rare cause of acute pancreatitis (AP) with an estimate incidence of 0.1-2%. We present an 63-year-man 1 week history of severe and progressive epigastric pain that radiates to the back and is worse on lying down, who was found to have lipase of more than 813 IU/L. The patient denied current alcohol use. Abdominal ultrasound and abdominal computed tomography scan did not show gallstones or biliary duct abnormalities. For his type-2 diabetes mellitus, he was taking Gliclazide and Metformin for years and Sitagliptin was the only drug added 6 months ago. He was managed conservatively with intravenous fluids, pain medications, and control of diabetes with insulin. Within 3 days, he improved dramatically and was discharged on diabetic diet and Gliclazide 120 mg daily with Lantos 10 units at night. He was instructed to avoid oral hypoglycemia agents from the dipeptidyl-peptidase IV inhibitors (DPP-4i) group. Three weeks later, repeat computed tomography scan of the abdomen showed normal pancreas. On follow up; and up to 1 year, he did not have subsequent AP. The most plausible mechanism of such late-development of rare drug-induced AP is late-encounter with triggering factor/s for Sitagliptin in genetically-predisposed individuals. Keywords: CT scan, diabetes mellitus, DPP-4i, metformin, pancreatitis, Sitagliptin.

A case of acute calculous cholecystitis with contained gall bladder perforation with pericholecystic collections extending to liver parenchyma

Gall bladder perforation is a serious complication of acute cholecystitis and represents an advanced stage of the disease. Its clinical presentation is varied and can range from non-specific symptoms to acute generalized peritonitis. In many cases, GB perforation in diagnosis during exploratory laparotomy for peritonitis and with no definite source identified. The presentation of gall bladder perforation can be indistinguishable from uncomplicated acute cholecystitis. A 60 yrs. old male with no known comorbidities presented to a tertiary care hospital with diffuse pain abdomen associated with vomiting and constipation of 04 days’ duration. Clinical evaluation revealed icterus and tenderness in right hypochondrium and generalized peritonitis. Lab investigations revealed conjugated type hyperbilirubinemia and elevated serum Lipase levels and normal Amylase levels. Initial USG revealed Acute acalculous cholecystitis with normal IHBR and normal CBD. Later NCCT abdomen and MRCP were done which revealed calculous cholecystitis with sealed off GB perforation IHBR, CBD, and normal pancreas. The patient was managed non-operatively and responded well. The inflammatory reaction of the peritoneum in bile peritonitis increases the absorption of the spilled conjugated bile from the peritoneal cavity. The conjugated type hyperbilirubinemia without dilatation of the bile duct on imaging examination was the sign of bile leakage into the peritoneal cavity.

Hypoglycemia, Something Lost in Translation

Introduction: Insulinoma is a rare neuroendocrine tumor that may occur sporadically or as part of multiple neuroendocrine neoplasia type 1, with an incidence of 4 per million per year. Given the nonspecific symptoms of hypoglycemia, the diagnosis of insulinoma may be delayed by months, years or even decades. Case Presentation: A 50 year-old Hispanic, Spanish speaking male with a history of hypertension presented with progressive epigastric pain, nausea and bilious vomiting for 2 days. Physical exam was notable for abdominal distention and tenderness. Initial labs showed white blood cells of 19.4 k/uL (4-10.8), glucose of 85 mg/dl (65-140). CT abdomen showed findings consistent with moderate grade small bowel obstruction and normal pancreas. The patient was managed conservatively with nasogastric tube placement and nothing per oral (NPO). Within 8 hours started experience sweating, restlessness, fingerstick glucose was 40 mg/dl. Upon questioning, he reported episodes of lightheadedness, sweating and shakiness 8 years prior to this hospitalization, and he recalled being told that he was hypoglycemic during prior hospitalizations at another institution. He stated he was told to drink juice upon experiencing such symptoms and no work up or diagnostic investigation was recommended. We initiated a hypoglycemia investigation when he was NPO, when serum glucose level of 40 mg/dl. Labs showed insulin level 34 uIU/mL (3-19), free insulin 25 uIU/mL (3-19), C-peptide 3.32 ng/mL (0.81-3.85), beta hydroxybutyrate <0.02 mmol/L (0.02-0.27) and proinsulin of 36.6 pmol/L (3-50) and hemoglobin a1C of 5% (3.8-5.6). Serum screening for hypoglycemic agents was negative. When MRI abdomen was negative for a pancreatic mass. We proceeded with advanced diagnostic imaging with endoscopic ultrasound (EUS) which showed a 26 mm x 19 mm ovoid, hypoechoic mass at the junction of the pancreatic body and tail. Tissue specimen obtained with fine needle aspiration showed grade 1 neuroendocrine neoplasm. The patient underwent distal pancreatectomy and splenectomy with suture repair of the small bowel and left wedge liver biopsy. The pathology showed a well-differentiated neuroendocrine tumor of the pancreas, positive for synaptophysin, chromogranin and CD56 and Ki-67 with proliferation index <2% and no evidence of metastasis to the liver. The patient’s hypoglycemia resolved following surgery and rose to > 200 mg/dL requiring us to begin insulin therapy during the hospital stay before ultimately discharging the patient on metformin for type 2 diabetes. Conclusion: Insulinoma is a rare but treatable neuroendocrine tumor. Early diagnosis is important to avoid adverse clinical events related to hypoglycemia. It is important to maintain a strong clinical suspicion in order to identify and pursue the cause of unexplained hypoglycemia to improve the quality of life of patients with this rare condition.

Normative CT perfusion parameters of pancreas in relation to the age and gender

Purpose: A variety of inflammatory and neoplastic lesions of pancreas can be characterized and prognosticated by perfusion CT (Computed Tomography). Knowing the normal perfusion values is essential before such values could be interpreted as abnormal. The aim of this study was to obtain a normative data of the perfusion parameters of normal pancreatic parenchyma with respect to the age and gender.Materials and Methods: Total 33 subjects underwent perfusion CT of pancreas. The perfusion parameters like BF (Blood-Flow), PEI (Peak Enhancement Index), TTP (Time to Peak) and BV (Blood-Volume) were obtained by placing an ROI (Region of Interest) on normal pancreas. Descriptive statistics of the perfusion values was tabulated and relationship of perfusion characteristics with age and sex of the subjects were calculated applying Pearson’s correlation coefficient.Results: 18 subjects were males and 15 were females. 4 subjects belonged to 20-40 age group, 18 belonged to 40-60 age group and 11 belonged to 60-80 age group. BF fell within a range of 11.0 to 161.2 ml100gm-1min-1 (Mean ± SD=69.12 ± 36.96), PEI ranged from 23.70 to 165.0HU (Mean ± SD=51.82 ± 26.51), BV ranged from 7.8 to 321.5 ml100gm-1 (Mean ± SD=52.31 ± 54.97) and TTP ranged from 8.0 to 58.30s (Mean ± SD=20.16 ± 9.08). BF showed a negative correlation with the patient's age (r = -.252) on applying the Pearson’s correlation coefficient, indicating parenchymal perfusion of the normal pancreas declining with age (p>0.05). The PEI showed a negative correlation with patient’s age (P>0.05) and BV and TTP showed appositive correlation with the patient’s age (P>0.05). No statistically significant differences were observed in perfusion values of normal pancreatic parenchyma between men and women.Conclusion: Though not statistically significant, a tendency of BF and PEI to reduce with age, BV and TTP to increase with age was observed which require studies with large sample size to determine the true significance.

An Overview of Artificial Intelligence Applications in Liver and Pancreatic Imaging.

Simple SummaryArtificial intelligence (AI) is gaining more and more attention in radiology. The efficiency of AI-based algorithms to solve specific problems is, in some cases, far superior compared to human-driven approaches. This is particularly evident in some repetitive tasks, such as segmentation, where AI usually outperforms manual approaches. AI may be also used in quantification where it can provide, for example, fast and efficient longitudinal follow up in liver tumour burden. AI, thanks to the association with radiomic and big data, may also suggest a diagnosis. Finally, AI algorithms can also reduce scan time, increase image quality and, in the case of computed tomography, reduce patient dose.Artificial intelligence (AI) is one of the most promising fields of research in medical imaging so far. By means of specific algorithms, it can be used to help radiologists in their routine workflow. There are several papers that describe AI approaches to solve different problems in liver and pancreatic imaging. These problems may be summarized in four different categories: segmentation, quantification, characterization and image quality improvement. Segmentation is usually the first step of successive elaborations. If done manually, it is a time-consuming process. Therefore, the semi-automatic and automatic creation of a liver or a pancreatic mask may save time for other evaluations, such as quantification of various parameters, from organs volume to their textural features. The alterations of normal liver and pancreas structure may give a clue to the presence of a diffuse or focal pathology. AI can be trained to recognize these alterations and propose a diagnosis, which may then be confirmed or not by radiologists. Finally, AI may be applied in medical image reconstruction in order to increase image quality, decrease dose administration (referring to computed tomography) and reduce scan times. In this article, we report the state of the art of AI applications in these four main categories.

Expression and Prognostic Value of Cripto-1 in Pancreatic Cancer

Objective To investigate the expression of Cripto-1 in pancreatic cancer and to analyze its clinical significance. Methods Cripto-1 expression in normal pancreas,pancreatic cancer and adjacent non-tumor tissues,chronic pancreatitis tissues and other related tissues was evaluated using immunohistochemistry.The association of Cripto-1 expression with the clinicopathological characteristics and the prognostic value of Cripto-1 in patients with pancreatic cancer were analyzed. Results The expression of Cripto-1 was higher in chronic pancreatitis tissues,pancreatic cancer and its metastases than in normal pancreas(P=0.019,P=0.025,and P=0.018,respectively).Cripto-1 overexpression was correlated with poorly differentiated pancreatic cancer.The patients with Cripto-1 upregulation had shorter median survival time(8 months vs.16 months,χ 2=4.787,P=0.029).However,multivariate analysis failed to demonstrate overexpression of Cripto-1 an independent prognostic indicator in patients with pancreatic cancer(HR=1.341,95% CI=0.800-2.248,P=0.266).Conclusions Cripto-1 may play an important role in the development and progression of pancreatic cancer.It can be a potential prognostic biomarker for patients with pancreatic cancer.

Abstract No. 86 Treatment of pancreatic cancer by intra-arterial injection of an emulsion of lipiodol and bumetanide (an anti-glycolytic drug) in a transgenic mutated pig model (Oncopig)

The most important adaptive metabolic mechanism exhibited by cancer cells is the Warburg effect, whereby most energy is produced by aerobic glycolysis. Bumetanide (BU), a loop diuretic, blocks glycolysis. Intra-arterial lipiodol is retained in pancreatic cancer and forms an emulsion with BU. The aim of this study was to evaluate the safety and efficacy of intra-arterial injection of a lipiodol/BU emulsion to treat pancreatic cancer in a pig model. 13 pancreatic tumors were induced in 10, 3-12 months old female Oncopigs (transgenic pigs with inducible p53 and Kras mutations). Six of the pancreatic tail tumors were treated by intra-arterial injection of a lipiodol/BU emulsion into the dorsal pancreatic artery. The other 7 tumors were left untreated as a negative control. Laboratory evaluation (including lipase and liver function tests) and multi-phase contrast-enhanced CT were obtained before and after treatment, and histopathological examination of the pancreas was performed on necropsy. Average tumor size was 2.5 cm (one week after inoculation). Untreated tumors (n = 7) grew by an average of 54% (two weeks after inoculation). Embolized pancreatic tumors (n = 6) decreased in size by an average of 11% (P = 0.002). In 2 of 6 pigs (33%), there was preferential lipiodol retention in tumor versus normal pancreas (2200 versus 90 HU). In 4 of 6 pigs (67%), there was slightly preferential lipiodol retention in pancreas versus tumor (210 versus 150 HU). Prior to pancreatic inoculation, average lipase was 4 ± 2 U/L. In pigs with untreated pancreatic tumors, lipase increased to 27 ± 46 U/L. In pigs treated with dorsal pancreatic artery embolization, lipase increased to 16 ± 12 U/L (P = 0.68 for treated versus untreated pigs). There was no pancreatitis or other complications, based on clinical, biochemical, and imaging evaluation. This initial animal study demonstrates that intra-arterial injection of a lipiodol/BU emulsion is feasible and can safely and effectively treat pancreatic cancer in this porcine model.

Expressional and Prognostic Value of S100A16 in Pancreatic Cancer Via Integrated Bioinformatics Analyses.

Studies have shown that the calcium-binding protein family S100 may play a role in the development of pancreatic cancer (PC), but the role of S100A16 in PC is still unknown. In this study, Oncomine was first used to detect the expression level and prognosis of S100A16 in PC and other tumors. The results showed that S100A16 was highly expressed in PC tissues compared with a normal pancreas, and the increased expression level may be related to poor prognosis in PC patients. The TCGA and ICGC RNA-seq data of PC patients were downloaded, and the S100A16-related differentially expressed genome (DEGs) was defined by taking the intersection of two gene sets. The GO and KEGG pathways were then analyzed. For clinical analysis, boxplots were depicted for the correlation between clinical characteristics and S100A16 expression. Then Cox regression was applied for exploring the prognostic value of S100A16 for PDAC patients. Based on the Cox regression model, we further estabished a S100A16-related risk score system to strengthen the ability to predict patients' prognosis. After integrating the risk score model and multiple clinicopathological factors, we finally established a nomogram that could predict the survival time of patients. Moreover, Gene set enrichment the effect of S100A16 expression differences on downstream biological processes. At last, using TIMER, ImmuneCellAI and GSEA we analyzed the correlation between S100A16 and pancreatic cancer immune infiltration and predicted the response of patients to checkpoint Blocker (ICB). In summary, S100A16 is involved in the occurrence and development of PC, affecting the prognosis of patients, and may have potential reference values for the immunotherapy of PC.

Antidiabetic and antihyperlipidemic activities of a novel polyherbal formulation in streptozotocin - nicotinamide induced diabetic wistar rats

Objective: To investigate the antidiabetic and antihyperlipidemic activities of polyherbal formulation (PHF) containing seven plants namely Cassia auriculata, Cassia fistula, Syzygium cumini, Cyperus rotundus, Saussurea lappa, Terminalia arjuna and Salacia reticulate in streptozotocin (STZ) - nicotinamide (NC) induced diabetic rats by administering oral doses (200 and 400 mg/kg body weight).&#x0D; Materials and Methods: Animals were divided into diabetic and nondiabetic groups. Rats were fed with normal laboratory diet and induced with a single intraperitoneal injection of 60mg/kg of STZ, and thereafter 120 mg/kg NC was injected after 15min. Diabetic rats were treated with formulation (200 and 400 mg/kg) and glibenclamide 5 mg/kg. Blood glucose levels were measured using blood glucose test strips with ACCU CHEK glucometer. Glycosylated haemoglobin, total haemoglobin, lipid profiles, lipoproteins, hepatic marker enzymes activity were determined in normal and STZ- NC induced diabetic rats after oral administration of the PHF for 28 days. Histopathological changes in normal and diabetic rat pancreas organs were also observed after PHF treatment.The statistical analysis of results was carried out using one-way analysis (ANOVA) followed by post hoc multiple comparison tests.&#x0D; Results: Treatment of diabetic rats with PHF (200 and 400 mg/kg) and glibenclamide (5 mg/kg) indicate significant decreased blood glucose level and significant improvement in body weight. PHF treated rats showed significant (P &lt; 0.01) decrease in the level of HbA1C, TC, TG, LDL, VLDL, AST, ALT and ALP while a significant increment in the level of Hb, HDL cholesterol was observed. Furthermore, the PHF treated rats has a favourable effect on the histopathological changes of the pancreas in STZ-NC induced diabetes.&#x0D; Conclusion: These findings suggested the antihyperglycemic and antihyperlipidemic properties of the PHF and thus help in preventing future complications of diabetes.

Multiparameter Analysis Using 18F-FDG PET/CT in the Differential Diagnosis of Pancreatic Cystic Neoplasms.

Purpose To evaluate multiparametric analysis in differential diagnosis between pancreatic serous cystic neoplasms (SCNs) and mucinous cystic neoplasms (MCNs) as well as the differentiation of the benign and malignant MCNs with 18F-FDG (18-fluorodeoxyglucose) PET/CT (positron emission tomography). Methods Forty patients with total of 41 lesions (SCNs: 27/41; MCNs: 14/41), who were preoperatively examined with 18F-FDG PET/CT, were retrospectively analyzed. Multiple quantitative parameters using conventional and texture features were included. The combined model was established with complementary PET/MR parameters. The differential diagnostic efficacy of each independent parameter and the combined model were evaluated with receiver operating characteristic (ROC) analysis. Integrated discriminatory improvement (IDI) and net reclassification improvement (NRI) were used to evaluate improvement of diagnostic efficacy by using combination of multiple parameters. Results Among all independent parameters, the percentile 5th (0.88 ± 0.38 vs 0.47 ± 0.23, P < 0.001) showed the highest discriminative diagnostic value. The combination of multiple parameters can improve the differential diagnostic efficacy of SCNs and MCNs (sensitivity = 71.4%, specificity = 77.8%, and AUC = 0.788), and the addition of texture parameters to the conventional parameters allowed a significant reclassification with IDI = 0.236 (95% CI: 0.095–0.377) and categorical NRI = 0.434 (95% CI: 0.030–0.838). SURmax (tumor to normal pancreas ratio, T/P) and SURmax (tumor to aorta ratio, T/A) both showed the highest discriminative diagnostic value (sensitivity = 100.0%, specificity = 70.0%, AUC = 0.900, and Youden index = 0.700) in the differential diagnosis of benign and malignant MCNs, with the cutoff values of 0.84 and 0.90, respectively. ConclusionCombination of multiple parameters using 18F-FDG PET/CT could further improve differentiation between pancreatic SCNs and MCNs. SURmax (T/P) and SURmax (T/A) could improve differential diagnosis of benign and malignant MCNs.

The diagnostic potential of targeted imaging of the fetal pancreas

To report our experience with targeted scans of the fetal pancreas. Targeted scans were performed in 16 cases referred for anatomical or genetic conditions associated with structural pancreatic malformations. Four fetuses were evaluated for nephromegaly and macroglossia. In three of them, the pancreas circumference was >90th percentile. Genetic testing revealed Beckwith-Wiedemann syndrome. In the fourth case, the pancreas circumference was normal; exome sequencing revealed two heterozygous ETFDH gene mutations consistent with glutaric acidemia type II. In a case referred for non-visualization of the gallbladder, the fetal pancreas was not visualized and genetic analysis revealed a mutation in the ONECUT1 gene encoding for HNF6. Targeted scan for heterotaxia revealed three cases with variable degrees of agenesis of the pancreas, one case with a normally structured right sided pancreas and one case with a normal pancreas. Cases referred following a genetic diagnosis included a case of maternal nesidioblastosis with an extremely large fetal pancreas; and five fetuses diagnosed with a TCF2 deletion all with a normal pancreas. Prenatal assessment of the fetal pancreas may be a significant factor in prenatal diagnosis and counselling in cases presenting with anatomical and genetic conditions reported post-natally to be associated with pancreatic structural and functional abnormalities.

Quality gaps in public pancreas imaging datasets: Implications & challenges for AI applications

ObjectiveQuality gaps in medical imaging datasets lead to profound errors in experiments. Our objective was to characterize such quality gaps in public pancreas imaging datasets (PPIDs), to evaluate their impact on previously published studies, and to provide post-hoc labels and segmentations as a value-add for these PPIDs. MethodsWe scored the available PPIDs on the medical imaging data readiness (MIDaR) scale, and evaluated for associated metadata, image quality, acquisition phase, etiology of pancreas lesion, sources of confounders, and biases. Studies utilizing these PPIDs were evaluated for awareness of and any impact of quality gaps on their results. Volumetric pancreatic adenocarcinoma (PDA) segmentations were performed for non-annotated CTs by a junior radiologist (R1) and reviewed by a senior radiologist (R3). ResultsWe found three PPIDs with 560 CTs and six MRIs. NIH dataset of normal pancreas CTs (PCT) (n = 80 CTs) had optimal image quality and met MIDaR A criteria but parts of pancreas have been excluded in the provided segmentations. TCIA-PDA (n = 60 CTs; 6 MRIs) and MSD(n = 420 CTs) datasets categorized to MIDaR B due to incomplete annotations, limited metadata, and insufficient documentation. Substantial proportion of CTs from TCIA-PDA and MSD datasets were found unsuitable for AI due to biliary stents [TCIA-PDA:10 (17%); MSD:112 (27%)] or other factors (non-portal venous phase, suboptimal image quality, non-PDA etiology, or post-treatment status) [TCIA-PDA:5 (8.5%); MSD:156 (37.1%)]. These quality gaps were not accounted for in any of the 25 studies that have used these PPIDs (NIH-PCT:20; MSD:1; both: 4). PDA segmentations were done by R1 in 91 eligible CTs (TCIA-PDA:42; MSD:49). Of these, corrections were made by R3 in 16 CTs (18%) (TCIA-PDA:4; MSD:12) [mean (standard deviation) Dice: 0.72(0.21) and 0.63(0.23) respectively]. ConclusionSubstantial quality gaps, sources of bias, and high proportion of CTs unsuitable for AI characterize the available limited PPIDs. Published studies on these PPIDs do not account for these quality gaps. We complement these PPIDs through post-hoc labels and segmentations for public release on the TCIA portal. Collaborative efforts leading to large, well-curated PPIDs supported by adequate documentation are critically needed to translate the promise of AI to clinical practice.

Three Immune-Related Prognostic mRNAs as Therapeutic Targets for Pancreatic Cancer.

Objective: Pancreatic cancer is a highly lethal malignancy globally. This study aimed to probe and validate immune-related prognostic mRNAs as therapeutic targets for pancreatic cancer.Methods: Gene transcriptome data of pancreatic cancer and normal pancreas were retrieved from TCGA-GTEx projects. Two thousand four hundred and ninety-eight immune-related genes were obtained from the IMMUPORT database. Abnormally expressed immune-related genes were then identified. Under univariate and multivariate cox models, a gene signature was constructed. Its predictive efficacy was assessed via ROCs. The interactions between the 21 genes were analyzed by Spearson analysis and PPI network. Using the GEPIA and The Human Protein Atlas databases, their expression and prognostic value were evaluated. The TIMER database was utilized to determine the relationships between MET, OAS1, and OASL mRNAs and immune infiltrates. Finally, their mRNA expression was externally verified in the GSE15471 and GSE62452 datasets.Results: An immune-related 21-gene signature was developed for predicting patients' prognosis. Following verification, this signature exhibited the well predictive performance. There were physical and functional interactions between them. MET, OAS1, and OASL mRNAs were all up-regulated in pancreatic cancer and associated with unfavorable prognosis. They showed strong correlations with tumor progression. Furthermore, the three mRNAs were distinctly associated with immune infiltrates. Their up-regulation was confirmed in the two external datasets.Conclusion: These findings identified three immune-related prognostic mRNAs MET, OAS1, and OASL, which may assist clinicians to choose targets for immunotherapy and make personalized treatment strategy for pancreatic cancer patients.

Pancreatic cancer is marked by complement-high blood monocytes and tumor-associated macrophages.

Pancreatic ductal adenocarcinoma (PDA) is accompanied by reprogramming of the local microenvironment, but changes at distal sites are poorly understood. We implanted biomaterial scaffolds, which act as an artificial premetastatic niche, into immunocompetent tumor-bearing and control mice, and identified a unique tumor-specific gene expression signature that includes high expression of C1qa, C1qb, Trem2, and Chil3 Single-cell RNA sequencing mapped these genes to two distinct macrophage populations in the scaffolds, one marked by elevated C1qa, C1qb, and Trem2, the other with high Chil3, Ly6c2 and Plac8 In mice, expression of these genes in the corresponding populations was elevated in tumor-associated macrophages compared with macrophages in the normal pancreas. We then analyzed single-cell RNA sequencing from patient samples, and determined expression of C1QA, C1QB, and TREM2 is elevated in human macrophages in primary tumors and liver metastases. Single-cell sequencing analysis of patient blood revealed a substantial enrichment of the same gene signature in monocytes. Taken together, our study identifies two distinct tumor-associated macrophage and monocyte populations that reflects systemic immune changes in pancreatic ductal adenocarcinoma patients.

High expression of MMP28 indicates unfavorable prognosis in pancreatic cancer.

To investigate the expression pattern and diagnostic performance of matrix metalloproteinase 28 (MMP28) in pancreatic cancer (PC).The RNA-seq data of PC and normal pancreas tissue were acquired from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression. Clinical information of PC that included prognostic data was obtained from TCGA. Later, Fisher exact test was applied for comparison of different clinicopathological features between high and low expression of MMP28 in PC. Afterwards, Kaplan-Meier survival analysis and Cox analysis (univariate and multivariate analysis) were used to explore the prognostic performance of MMP28 in PC cohort. Finally, gene set enrichment analysis (GSEA) revealed the potential signaling pathways related to high expression of MMP28 in PC.Upregulation of MMP28 was identified in PC tissue compared to normal pancreas tissue (P < .001). Overexpression of MMP28 was related to histological grade (P < .001), M classification (P = .014), and survival status (P = .028). Kaplan-Meier survival analysis revealed that high level of MMP28 implied unfavorable prognosis in PC (P = .002). Multivariate analysis confirmed that MMP28 was an independent risk factor in PC (hazard rate = 1.308, P = .018). Our GSEA analysis found that signaling pathways including glycolysis, p53 pathway, notch signaling, estrogen response late, cholesterol homeostasis, estrogen response early, mitotic spindle, and transforming growth factor beta signaling were enriched in the group with higher MMP28 expression.High expression of MMP28 could be identified in PC, which also served as an independent risk element for PC.

Marked clinical heterogeneity in congenital hyperinsulinism due to a novel homozygous ABCC8 mutation.

The most severe forms of congenital hyperinsulinism (CHI) are caused by inactivating mutations of two KATP channel genes, KCNJ11 and ABCC8. Unresponsiveness to diazoxide and need for subtotal pancreatectomy can usually be predicted by genetic form, particularly biallelic mutations in KATP channel genes. A few reports indicated marked clinical heterogeneity in siblings with identical biallelic mutations in ABCC8. The clinical heterogeneity in biallelic KATP CHI was speculated to be caused by epigenetic and environmental factors or related to differences in splicing factor machinery. To elucidate the clinical pathophysiology, especially heterogeneity, among three cases with CHI caused by a homogenous novel mutation. We report a case series that includes two siblings and one unrelated individual with CHI caused by a homogenous 1-bp deletion around the splice acceptor site at the exon 35 mutation of ABCC8, which exhibited markedly distinct phenotypes. To assess the effect of the mutation on splicing, we performed digital droplet polymerase chain reaction (ddPCR) on normal pancreas tissue and a patient's lymphocytes. ddPCR of ABCC8 cDNA revealed that expression of exon 35 and its upstream and downstream regions did not differ. These data suggested that clinical heterogeneity may not be caused by differences in splicing factor machinery. The phenotypic variation in homozygotes could not be explained by splicing abnormalities. Though early genetic diagnosis of KATP CHI could contribute to selecting appropriate therapeutic options, more deliberate selection of therapeutic options in diffuse CHI due to biallelic ABCC8 mutations may be required.

Not Your Typical Ascites, Pancreatic Ascites: A Case Report and Systematic Review of the Literature

Background: Pancreatic ascites is a rare entity resulting from pancreatic duct leakage into peritoneum. The most common etiology is chronic pancreatitis or abdominal trauma. Case Presentation: A 23-year-old female with history of chronic pancreatitis secondary to alcohol abuse presented with acute on chronic epigastric pain with unintentional weight loss. Physical exam revealed epigastric and right upper quadrant tenderness without rebound or guarding. Labs were significant for low serum albumin and elevated lipase level. CT of abdomen without contrast demonstrated large volume ascites with normal looking pancreas. MRI of abdomen with intravenous contrast revealed two dilated tubules within the pancreatic neck communicating with the pancreatic duct, representing pancreatic fluid leakage into the peritoneal cavity. Paracentesis was performed yielding large volume of ascitic fluid with high amylase level, characteristic of pancreatic ascites. Patient was managed conservatively with bowel rest and octreotide. Conclusion: Pancreatic ascites is uncommon among the differential diagnosis of ascites. Diagnosis is suspected in a patient with chronic alcoholism or pancreatitis presenting with high amylase exudative ascites and/or pleural effusion. Though limited evidence, interventional therapy especially endoscopic procedure is recommended as initial treatment.

Eicosapentaenoic Acid Inhibits KRAS Mutant Pancreatic Cancer Cell Growth by Suppressing Hepassocin Expression and STAT3 Phosphorylation.

Background: The oncogenic Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation was reported to be the signature genetic event in most cases of pancreatic ductal adenocarcinoma (PDAC). Hepassocin (HPS/FGL1) is involved in regulating lipid metabolism and the progression of several cancer types; however, the underlying mechanism of HPS/FGL1 in the KRAS mutant PDAC cells undergoing eicosapentaenoic acid (EPA) treatment remains unclear. Methods: We measured HPS/FGL1 protein expressions in a human pancreatic ductal epithelial (HPNE) normal pancreas cell line, a KRAS-wild-type PDAC cell line (BxPC-3), and KRAS-mutant PDAC cell lines (PANC-1, MIA PaCa-2, and SUIT-2) by Western blot methods. HEK293T cells were transiently transfected with corresponding KRAS-expressing plasmids to examine the level of HPS expression with KRAS activation. We knocked-down HPS/FGL1 using lentiviral vectors in SUIT-2 cells and measured the cell viability by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and clonogenicity assays. Furthermore, a lipidomic analysis was performed to profile changes in lipid metabolism after HPS/FGL1 knockdown. Results: We found that the HPS/FGL1 level was significantly upregulated in KRAS-mutated PDAC cells and was involved in KRAS/phosphorylated (p)-signal transduction and activator of transcription 3 (STAT3) signaling, and the knockdown of HPS/FGL1 in SUIT-2 cells decreased cell proliferation through increasing G2/M cell cycle arrest and cyclin B1 expression. In addition, the knockdown of HPS/FGL1 in SUIT-2 cells significantly increased omega-3 polyunsaturated fatty acids (PUFAs) and EPA production but not docosahexaenoic acid (DHA). Moreover, EPA treatment in SUIT-2 cells reduced the expression of de novo lipogenic protein, acetyl coenzyme A carboxylase (ACC)-1, and decreased p-STAT3 and HPS/FGL1 expressions, resulting in the suppression of cell viability. Conclusions: Results of this study indicate that HPS is highly expressed by KRAS-mutated PDAC cells, and HPS/FGL1 plays a crucial role in altering lipid metabolism and increasing cell growth in pancreatic cancer. EPA supplements could potentially inhibit or reduce ACC-1-involved lipogenesis and HPS/FGL1-mediated cell survival in KRAS-mutated pancreatic cancer cells.

Abstract PO-084: Automated detection of pancreatic ductal adenocarcinoma (PDAC) on CT scans using artificial intelligence (AI): Impact of inclusion of automated pancreas segmentation on the accuracy of 3D-convolutional neural network (CNN)

Abstract Purpose: Around 30% of PDAC less than 2-cm tend to go undetected on CT due to their subtle imaging signatures. Automated detection of PDAC using AI represents an opportunity to augment physician expertise and to improve outcomes through early detection of PDAC. Our purpose was to develop a 3D-CNN for fully automated detection of PDAC and to further evaluate the impact of inclusion of pancreas segmentation on the accuracy of this 3D-CNN. Methods: A Medical Imaging Data Readiness Scale (MIDaR) level A dataset (portal venous phase CTs, slice thickness ≤ 3.75 mm) of 466 treatment-naïve biopsy-proven PDAC and 1994 subjects with normal pancreas was created after exclusion of CTs with suboptimal image quality or biliary stents. Volumetric pancreas and tumor segmentations on CTs were done by two radiologists using 3D Slicer. A total of 370 CTs with PDAC and 370 CTs with normal pancreas were randomly selected for separate training and validation sets, and 396 CTs (96 CTs with PDAC and 300 CTs with normal pancreas) were utilized for testing. Two separate 3D-CNNs were trained. A three-stage bounding-box-only model (A): stage 1 was based on a UNET-like architecture and localized the pancreas on CT with a bounding box; stage 2 utilized an Inception ResNet architecture and classified each slice through the pancreas into PDAC vs. normal; and stage 3 utilized the output of stage 2 to generate final classification for a given CT. Conversely, a four-stage pancreas segmentation-based model (B) included stage 1 of model A followed by an additional stage of automated pancreas and tumor segmentation (stage 2), classification of each slice through the pancreas into PDAC vs. normal (stage 3) and, finally, generation of final classification score (stage 4) for a given CT. Area under the receiver operating characteristic curve (AUROC) of the two models were compared on the test set. Results: Mean (SD) PDAC diameter in the test set was 1.1 (0.43) cm. Model A (three-stage bounding-box-only) correctly classified 305 (77%) out of 396 CTs from the test set into PDAC vs. normal. It incorrectly classified 12/96 (12.5%) CTs with PDAC as normal and 79/300 (26%) normal CTs as PDAC. AUROC for model A was 0.85. Model B (four-stage pancreas segmentation-based) correctly classified 351 (88%) out of 396 CTs. It incorrectly classified 13/96 (13.5%) CTs with PDAC as normal and 32/300 (10.7%) normal CTs as PDAC. AUROC for model B was 0.94. AUROC for model B was significantly higher than model A (p&amp;lt;0.005). Conclusion: A 3D-CNN can detect small PDAC with high accuracy using automated localization of pancreas with a bounding box without relying on separate pancreas segmentation. Inclusion of an additional automated pancreas segmentation step reduced false positives with consequent incremental gain in the model’s accuracy. Prospective validation and subsequent integration of such models into clinical workflows has the potential to reduce inadvertent errors in detection of subtle or small PDAC on standard-of-care CT scans. Citation Format: Anurima Patra, Korfiatis Panagiotis, Garima Suman, Ananya Panda, Sushil Kumar Garg, Ajit Goenka. Automated detection of pancreatic ductal adenocarcinoma (PDAC) on CT scans using artificial intelligence (AI): Impact of inclusion of automated pancreas segmentation on the accuracy of 3D-convolutional neural network (CNN) [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-084.

Aggressive PDACs Show Hypomethylation of Repetitive Elements and the Execution of an Intrinsic IFN Program Linked to a Ductal Cell of Origin.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by extensive desmoplasia, which challenges the molecular analyses of bulk tumor samples. Here we FACS-purified epithelial cells from human PDAC and normal pancreas and derived their genome-wide transcriptome and DNA methylome landscapes. Clustering based on DNA methylation revealed two distinct PDAC groups displaying different methylation patterns at regions encoding repeat elements. Methylationlow tumors are characterized by higher expression of endogenous retroviral transcripts and double-stranded RNA sensors, which lead to a cell-intrinsic activation of an interferon signature (IFNsign). This results in a protumorigenic microenvironment and poor patient outcome. Methylationlow/IFNsignhigh and Methylationhigh/IFNsignlow PDAC cells preserve lineage traits, respective of normal ductal or acinar pancreatic cells. Moreover, ductal-derived Kras G12D/Trp53 -/- mouse PDACs show higher expression of IFNsign compared with acinar-derived counterparts. Collectively, our data point to two different origins and etiologies of human PDACs, with the aggressive Methylationlow/IFNsignhigh subtype potentially targetable by agents blocking intrinsic IFN signaling. SIGNIFICANCE: The mutational landscapes of PDAC alone cannot explain the observed interpatient heterogeneity. We identified two PDAC subtypes characterized by differential DNA methylation, preserving traits from normal ductal/acinar cells associated with IFN signaling. Our work suggests that epigenetic traits and the cell of origin contribute to PDAC heterogeneity.This article is highlighted in the In This Issue feature, p. 521.