Paraneoplastic β Cell Dedifferentiation in Nondiabetic Patients with Pancreatic Cancer

2019 ◽  
Vol 105 (4) ◽  
pp. e1489-e1503 ◽  
Author(s):  
Yichen Wang ◽  
Qicheng Ni ◽  
Jiajun Sun ◽  
Min Xu ◽  
Jing Xie ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Endocrine Cells ◽  
Fasting Blood Glucose ◽  
Ductal Adenocarcinoma ◽  
Benign Tumors ◽  
Β Cell ◽  
Cell Dedifferentiation ◽  
Glucose Transporter 2 ◽  
Onset Diabetes ◽  
New Onset

Abstract Context Beta-cell dedifferentiation was recently proposed as a mechanism of β-cell dysfunction, but whether it can be a trigger of β-cell failure preceding hyperglycemia in humans is uncertain. Pancreatic cancer can cause new-onset diabetes, yet the underlying mechanism is unknown. Objective To investigate whether β-cell dedifferentiation is present in nondiabetic pancreatic ductal adenocarcinoma (PDAC) patients, we examined pancreatic islets from 15 nondiabetic patients with benign tumors (control) and 15 nondiabetic PDAC patients. Design We calculated the number of hormone-negative endocrine cells and evaluated important markers of β-cell dedifferentiation and function in the paraneoplastic islets. We assessed tumor-related inflammatory changes under the pancreatic cancer microenvironment and their influence on β-cell identity. Results We found nearly 10% of nonhormone expressing endocrine cells in nondiabetic PDAC subjects. The PDAC islets were dysfunctional, evidenced by low expression of Glucose transporter 2 (GLUT2) and Urocortin3 (UCN3), and concomitant upregulation of Aldehyde Dehydrogenase 1 Family Member A3 (ALDH1A3) expression and proinsulin accumulation. Pancreatic cancer caused paraneoplastic inflammation with enhanced tissue fibrosis, monocytes/macrophages infiltration, and elevated inflammatory cytokines. Moreover, we detected β-cell dedifferentiation and defects in GSIS in islets exposed to PANC-1 (a cell line established from a pancreatic carcinoma of ductal origin from a 56-year-old Caucasian male)-conditioned medium. In a larger cohort, we showed high prevalence of new-onset diabetes in PDAC subjects, and fasting blood glucose (FBG) was found to be an additional useful parameter for early diagnosis of PDAC. Conclusions Our data provide a rationale for β-cell dedifferentiation in the pathogenesis of pancreatic cancer–associated diabetes. We propose that β-cell dedifferentiation can be a trigger for β-cell failure in humans, before hyperglycemia occurs.

scholarly journals Role of Pancreatic Stellate Cell-Derived Exosomes in Pancreatic Cancer-Related Diabetes: A Novel Hypothesis

Cancers ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 5224
Author(s):  
Chamini J. Perera ◽  
Marco Falasca ◽  
Suresh T. Chari ◽  
Jerry R. Greenfield ◽  
Zhihong Xu ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Pancreatic Cancer ◽  
Cancer Cells ◽  
Cell Function ◽  
Pancreatic Stellate Cells ◽  
Β Cell ◽  
Onset Diabetes ◽  
Β Cell Function ◽  
New Onset

Pancreatic ductal adenocarcinoma (PDAC) is a devastating condition characterised by vague symptomatology and delayed diagnosis. About 30% of PDAC patients report a history of new onset diabetes, usually diagnosed within 3 years prior to the diagnosis of cancer. Thus, new onset diabetes, which is also known as pancreatic cancer-related diabetes (PCRD), could be a harbinger of PDAC. Diabetes is driven by progressive β cell loss/dysfunction and insulin resistance, two key features that are also found in PCRD. Experimental studies suggest that PDAC cell-derived exosomes carry factors that are detrimental to β cell function and insulin sensitivity. However, the role of stromal cells, particularly pancreatic stellate cells (PSCs), in the pathogenesis of PCRD is not known. PSCs are present around the earliest neoplastic lesions and around islets. Given that PSCs interact closely with cancer cells to drive cancer progression, it is possible that exosomal cargo from both cancer cells and PSCs plays a role in modulating β cell function and peripheral insulin resistance. Identification of such mediators may help elucidate the mechanisms of PCRD and aid early detection of PDAC. This paper discusses the concept of a novel role of PSCs in the pathogenesis of PCRD.

scholarly journals New Onset of DiabetEs in aSsociation with pancreatic ductal adenocarcinoma (NODES Trial): protocol of a prospective, multicentre observational trial

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e037267
Author(s):  
Dóra Illés ◽  
Emese Ivány ◽  
Gábor Holzinger ◽  
Klára Kosár ◽  
M Gordian Adam ◽  
...  
Keyword(s):  
High Risk ◽  
Early Detection ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Clinical Symptoms ◽  
Risk Group ◽  
High Risk Group ◽  
Ductal Adenocarcinoma ◽  
Onset Diabetes ◽  
Dismal Prognosis ◽  
New Onset

IntroductionPancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis with an overall 5-year survival of approximately 8%. The success in reducing the mortality rate of PDAC is related to the discovery of new therapeutic agents, and to a significant extent to the development of early detection and prevention programmes. Patients with new-onset diabetes mellitus (DM) represent a high-risk group for PDAC as they have an eightfold higher risk of PDAC than the general population. The proposed screening programme may allow the detection of PDAC in the early, operable stage. Diagnosing more patients in the curable stage might decrease the morbidity and mortality rates of PDAC and additionally reduce the burden of the healthcare.Methods and analysisThis is a prospective, multicentre observational cohort study. Patients ≥60 years old diagnosed with new-onset (≤6 months) diabetes will be included. Exclusion criteria are (1) Continuous alcohol abuse; (2) Chronic pancreatitis; (3) Previous pancreas operation/pancreatectomy; (4) Pregnancy; (5) Present malignant disease and (6) Type 1 DM. Follow-up visits are scheduled every 6 months for up to 36 months. Data collection is based on questionnaires. Clinical symptoms, body weight and fasting blood will be collected at each, carbohydrate antigen 19–9 and blood to biobank at every second visit. The blood samples will be processed to plasma and analysed with mass spectrometry (MS)-based metabolomics. The metabolomic data will be used for biomarker validation for early detection of PDAC in the high-risk group patients with new-onset diabetes. Patients with worrisome features will undergo MRI or endoscopic ultrasound investigation, and surgical referral depending on the radiological findings. One of the secondary end points is the incidence of PDAC in patients with newly diagnosed DM.Ethics and disseminationThe study has been approved by the Scientific and Research Ethics Committee of the Hungarian Medical Research Council (41085-6/2019). We plan to disseminate the results to several members of the healthcare system includining medical doctors, dietitians, nurses, patients and so on. We plan to publish the results in a peer-reviewed high-quality journal for professionals. In addition, we also plan to publish it for lay readers in order to maximalise the dissemination and benefits of this trial.Trial registration numberClinicalTrials.gov NCT04164602

New‐onset Diabetes as a Harbinger of Pancreatic Cancer: is Early Diagnosis Possible?

2021 ◽  
pp. 409-417
Author(s):  
Dana K. Andersen ◽  
Suresh T. Chari ◽  
Eithne Costello ◽  
Tatjana Crnogorac‐Jurcevic ◽  
Phil A. Hart ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Early Diagnosis ◽  
Onset Diabetes ◽  
New Onset

scholarly journals The Screening and Early Detection of Pancreatic Cancer: Who, When, and How?

2020 ◽  
Vol 25 (2) ◽  
pp. 65-71
Author(s):  
Jae Hyuck Chang
Keyword(s):  
Pancreatic Cancer ◽  
Chronic Pancreatitis ◽  
General Population ◽  
Early Detection ◽  
Imaging Modality ◽  
Ductal Adenocarcinoma ◽  
Average Risk ◽  
Cystic Lesions ◽  
Low Prevalence ◽  
New Onset

More than 80% of patients with pancreatic ductal adenocarcinoma (PDA) present with symptomatic, surgically unresectable disease. If a “stage shift” from the current 20% resectable proportion to greater by early detection can be achieved, it will unequivocally lead to improved survival in this otherwise dismal disease. Although the goal of early detection of PDA is laudable, the relatively low prevalence PDA renders general population screening infeasible. To avoid the perils of overdiagnosis and to focus early detection efforts on individuals deemed to be at higher-than-average risk, we need to define those subsets of individuals, such as familial kindred and patients with precursor cystic lesions, chronic pancreatitis, and new-onset diabetes. The next step is to determine when and how often to conduct surveillance in the atrisk individuals and the modalities (biomarkers and imaging) that will be used in the surveillance and diagnostic settings, respectively. Nonetheless, vast challenges still remain in terms of validated blood-based biomarkers, imaging modality, and when and how often the surveillance.

scholarly journals Serum metabolomics differentiating pancreatic cancer from new-onset diabetes

Oncotarget ◽  
2017 ◽  
Vol 8 (17) ◽  
pp. 29116-29124 ◽  
Author(s):  
Xiangyi He ◽  
Jie Zhong ◽  
Shuwei Wang ◽  
Yufen Zhou ◽  
Lei Wang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Onset Diabetes ◽  
Serum Metabolomics ◽  
New Onset

scholarly journals New Onset Diabetes after Transplant – Risk Factors, Clinical Profile and Outcome

2018 ◽  
Vol 2 (1) ◽  
pp. 35-40
Author(s):  
Sakthirajan R ◽  
Dhanapriya J ◽  
Dineshkumar T ◽  
Balasubramaniyan T ◽  
Gopalakrishnan N ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Family History ◽  
Fasting Blood Glucose ◽  
Hcv Infection ◽  
Clinical Profile ◽  
Family History Of Diabetes ◽  
Onset Diabetes ◽  
History Of ◽  
New Onset

Background: New onset diabetes after transplant (NODAT) remains one among the significant threats to both renal allograft and patient survival. The aim of this study was to analyse the clinical profile and risk factors for NODAT.Methods: This prospective observational study involved patients who underwent renal transplantation in our centre between 2010 and 2015.Results: During the mean follow up period of 18 ± 6 months, incidence of NODAT was 26.6% and the cumulativeincidence was highest in the first year after transplant. Recipient age, pre transplant impaired fasting glucose, Hepatitis C virus (HCV) infection, family history of diabetes, tacrolimus, post transplant hypertriglyceridemia and metabolic syndrome were found to be statistically significant risk factors for NODAT. In Cox multivariate regression analysis, age and family history of diabetes were found to be independent risk factors for NODAT. Fasting C-peptide level underlines insulin resistance as predominant mechanism for NODAT in two third of patients. There were higher incidence of urinary tract infection in the NODAT patients. NODAT was found to be an independent risk factor for fungal infection and 10 year cardiovascular risk in the renal recipients. There was no significant impact of NODAT on short term graft and patient survival.Conclusion: Age, pre-transplant fasting blood glucose, family history of diabetes, HCV infection and tacrolimus were found to be the important risk factors, with insulin resistance as the predominant mechanism for NODAT.

Prospective assessment for prediabetes and new-onset diabetes in high-risk individuals undergoing pancreatic cancer screening

2021 ◽  
Author(s):  
Ishani Shah ◽  
Vaibhav Wadhwa ◽  
Mohammad Bilal ◽  
Katharine A. Germansky ◽  
Mandeep S. Sawhney ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Screening ◽  
High Risk ◽  
Onset Diabetes ◽  
Pancreatic Cancer Screening ◽  
Prospective Assessment ◽  
New Onset

Pancreatic cancer detection using EpiDetect signatures in plasma-derived cell free DNA in high-risk patients with new onset diabetes.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16265-e16265
Author(s):  
Gulfem Guler ◽  
Anna Bergamaschi ◽  
David Haan ◽  
Michael Kesling ◽  
Yuhong Ning ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Early Stage ◽  
Model Performance ◽  
Training Data ◽  
Diabetes Diagnosis ◽  
Whole Genome ◽  
Data Set ◽  
Independent Validation ◽  
Onset Diabetes ◽  
New Onset

e16265 Background: Pancreatic cancer (PaCa) is the third leading cause of cancer death in the United States despite its low incidence rate, owing to a 5-year survival rate of 10%. It is often asymptomatic in early stage, resulting in the majority of diagnoses occurring when cancer has already metastasized to distant organs. Late diagnosis deprives patients of potentially curative treatments such as surgery and impacts survival rates. Diabetes can be an early symptom of PaCa. Indeed, 25% of PaCa patients had a preceding diabetes diagnosis. Among all people with new onset diabetes (NOD), 0.85% will be diagnosed with PaCa within 3 years, which represents 6-8 fold increased risk for PaCa compared to the general population. Surveillance of the NOD population for PaCa presents an opportunity to shift PaCa diagnosis to earlier stage by finding it sooner. Methods: Whole blood was obtained from a cohort of 117 PaCa patients as well as 800 non-cancer controls with and without NOD. Plasma was processed to isolate cfDNA and 5hmC and low pass whole genome libraries were generated and sequenced. The EpiDetect assay combines 5hmC and whole genome sequencing data and were generated using Bluestar Genomics’s technology platform. Results: To investigate whether PaCa can be detected in plasma, we interrogated plasma-derived cfDNA epigenomic and genomic signal from PaCa patients and non-cancer controls. We first trained stacked ensemble models on PaCa and non-cancer samples utilizing 5hmC, fragmentation and CNV-based biomarkers from cfDNA. These models performed stably with a median of 72.8% sensitivity and 90.1% specificity measured across 25 outer fold iterations using the training data set, which was composed of 50% early stage (Stages I & II) disease. The final binomial ensemble model was trained using all of the training data, yielding an area under the receiver operating characteristic curve (auROC) of 0.9, with 75% sensitivity and 89% specificity. This model was then tested on an independent validation data set from 33 PaCa patients (24 with diabetes, 15 of which was NOD) and 202 non-cancer control patients (76 with diabetes, 51 of which was NOD) and yielded a classification performance auROC of 0.9 with 67% sensitivity at 92% specificity. Lastly, model performance in the subset of patient cohort with NOD only had an auROC of 0.87 with 60% sensitivity at 88% specificity. Conclusions: Our results indicate that 5hmC profiles along with CNV and fragmentation patterns from cfDNA can be used to detect PaCa in plasma-derived cfDNA. Overall, model performance was stable and consistent between the training and independent validation datasets. A larger clinical study is under development to investigate the utility of the model described in this pilot study in identifying occult PaCa within the NOD population, with the aim of shifting diagnosis to early stage and potentially improving patient outcomes.

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