Impact of Pancreatic Cancer and Subsequent Resection on Glycemic Control in Diabetic and Nondiabetic Patients

2011 ◽  
Vol 77 (8) ◽  
pp. 1032-1037 ◽  
Author(s):  
Michael A. White ◽  
Steven C. Agle ◽  
Hannah M. Fuhr ◽  
James H. Mehaffey ◽  
Brett H. Waibel ◽  
...  

The incidence of new onset or worsening diabetes is surprisingly low in patients after partial pancreatectomy for cancer, leading us to question what factors predict diminished glycemic control in those undergoing resection. All patients undergoing pancreatectomy for cancer at a large, rural university teaching hospital between 1996 and 2010 were identified. The incidence of new onset, or worsening, existing diabetes was determined based on pre and postoperative medication requirement. Univariate analysis was undertaken to identify factors that predict worsened glycemic control. One hundred and one (1 total, 79 Whipple, 21 distal) patients were identified, 41 per cent of which had preexisting diabetes. Nearly half of existing diabetics manifested an increased medication requirement prior to their cancer diagnosis. New onset diabetes occurred in 20 per cent of postoperative patients. Of established diabetics, 34 per cent had either improved glycemic control (9/41) or were cured (5/41) despite the reduction of islet cell mass that occurred with surgery. On univariate analysis, only prolonged hospitalization was associated with worsened glycemic control. Diminished glycemic control is a frequent presenting symptom of pancreatic cancer. Worsened or new onset diabetes is associated with length of stay, which can be influenced by a number of factors including complications and comorbidities.

2015 ◽  
Vol 6 (10) ◽  
pp. e118-e118 ◽  
Author(s):  
Satish Munigala ◽  
Ajaypal Singh ◽  
Andres Gelrud ◽  
Banke Agarwal

Author(s):  
Dana K. Andersen ◽  
Suresh T. Chari ◽  
Eithne Costello ◽  
Tatjana Crnogorac‐Jurcevic ◽  
Phil A. Hart ◽  
...  

2018 ◽  
Vol 7 ◽  
pp. 1-7 ◽  
Author(s):  
Constantine E Kosmas ◽  
Delia Silverio ◽  
Andreas Sourlas ◽  
Frank Garcia ◽  
Peter D Montan ◽  
...  

Oncotarget ◽  
2017 ◽  
Vol 8 (17) ◽  
pp. 29116-29124 ◽  
Author(s):  
Xiangyi He ◽  
Jie Zhong ◽  
Shuwei Wang ◽  
Yufen Zhou ◽  
Lei Wang ◽  
...  

Author(s):  
Ishani Shah ◽  
Vaibhav Wadhwa ◽  
Mohammad Bilal ◽  
Katharine A. Germansky ◽  
Mandeep S. Sawhney ◽  
...  

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16265-e16265
Author(s):  
Gulfem Guler ◽  
Anna Bergamaschi ◽  
David Haan ◽  
Michael Kesling ◽  
Yuhong Ning ◽  
...  

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.


2019 ◽  
Vol 105 (4) ◽  
pp. e1489-e1503 ◽  
Author(s):  
Yichen Wang ◽  
Qicheng Ni ◽  
Jiajun Sun ◽  
Min Xu ◽  
Jing Xie ◽  
...  

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.


2020 ◽  
Vol 18 (8) ◽  
pp. 1812-1821.e7 ◽  
Author(s):  
Brian Z. Huang ◽  
Stephen J. Pandol ◽  
Christie Y. Jeon ◽  
Suresh T. Chari ◽  
Catherine A. Sugar ◽  
...  

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