Literature DB >> 30989379

Glucose metabolism during tumorigenesis in the genetic mouse model of pancreatic cancer.

Valentina Pasquale1, Erica Dugnani1, Daniela Liberati2, Paolo Marra3, Antonio Citro1, Tamara Canu3, Martina Policardi1, Libera Valla1, Antonio Esposito3,4, Lorenzo Piemonti5,6.   

Abstract

AIM: More than 40% of pancreatic ductal adenocarcinoma (PDAC) patients have glucose intolerance or diabetes. The association has led to two hypotheses: PDAC causes diabetes or diabetes shares risk factors for the development of PDAC. In order to elucidate the relationship between diabetes and PDAC, we investigated the glucose metabolism during tumorigenesis in the LSL-KrasG12D/+; LSL-Trp53R172H/+; and Pdx-1-Cre (KPC) mouse, a genetically engineered model of PDAC.
METHODS: Male and female KPCs have been fed with standard diet (SD) or high-fat diet (HFD). The imaging-based 4-class tumor staging was used to follow pancreatic cancer development. Not fasting glycemia, 4-h fasting glycemia, insulin, C-peptide, glucose tolerance after OGTT and abdominal fat volume were measured during tumorigenesis.
RESULTS: PDAC development did not lead to an overt diabetic phenotype or to any alterations in glucose tolerance in KPC fed with SD. Consumption of HFD induced higher body weight/abdominal fat volume and worsened glucose homeostasis both in control CRE mice and only in early tumorigenesis stages of the KPC mice, excluding that the cancer development itself acts as a trigger for the onset of dysmetabolic features.
CONCLUSION: Our data demonstrate that carcinogenesis in KPC mice is not associated with paraneoplastic diabetes.

Entities:  

Keywords:  Diabetes; High-fat diet; KPC; Pancreatic cancer; Staging

Mesh:

Substances:

Year:  2019        PMID: 30989379     DOI: 10.1007/s00592-019-01335-4

Source DB:  PubMed          Journal:  Acta Diabetol        ISSN: 0940-5429            Impact factor:   4.280


  5 in total

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5.  Exploring and validating the clinical risk factors for pancreatic cancer in chronic pancreatitis patients using electronic medical records datasets: three cohorts comprising 2,960 patients.

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  5 in total

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