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(1)H NMR Based Serum Metabolic Profiles Associated with Pathological Progression of Pancreatic Islet β Cell Tumor in Rip1-Tag2 Mice

Pancreatic islet β cell tumor is the most common islet cell tumor. A well-characterized tumor progression in Rip1-Tag2 mice undergoes five stages, involving normal, hyperplasia, angiogenic islets, tumorigenesis and invasive carcinoma. (1)H NMR based metabonomics was applied to identify potential bio...

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Detalles Bibliográficos
Autores principales: Yang, Yongxia, Liu, Ying, Zheng, Lingyun, Zhang, Qianqian, Gu, Quliang, Wang, Linlin, Wang, Lijing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4400390/
https://www.ncbi.nlm.nih.gov/pubmed/25892966
http://dx.doi.org/10.7150/ijbs.11058
Descripción
Sumario:Pancreatic islet β cell tumor is the most common islet cell tumor. A well-characterized tumor progression in Rip1-Tag2 mice undergoes five stages, involving normal, hyperplasia, angiogenic islets, tumorigenesis and invasive carcinoma. (1)H NMR based metabonomics was applied to identify potential biomarkers for monitoring pancreatic islet β cell tumor progression in Rip1-Tag2 mice. Multivariate analysis results showed the serum metabonome at hyperplasia stage shared the similar characteristics with the ones at normal stage as a result of slight proliferation of pancreatic islet β cells. At angiogenic islets stage, the up-regulated glycolysis, disturbed choline and phospholipid metabolism composed the metabolic signature. In addition to the changes mentioned above, several metabolites were identified as early biomarkers for tumorigenesis, including increased methionine, citrate and choline, and reduced acetate, taurine and glucose, which suggested the activated energy and amino acid metabolism. All the changes were aggravated at invasive carcinoma stage, coupled with notable changes in alanine, glutamate and glycine. Moreover, the distinct metabolic phenotype was found associated with the implanting of SV40 large T antigen in Rip1-Tag2 mice. The combined metabolic and multivariate statistics approach provides a robust method for screening the biomarkers of disease progression and examining the association between gene and metabolism.