Non-invasively predicting differentiation of pancreatic cancer through comparative serum metabonomic profiling

BMC Cancer
Shi WenHeguang Huang

Abstract

The differentiation of pancreatic ductal adenocarcinoma (PDAC) could be associated with prognosis and may influence the choices of clinical management. No applicable methods could reliably predict the tumor differentiation preoperatively. Thus, the aim of this study was to compare the metabonomic profiling of pancreatic ductal adenocarcinoma with different differentiations and assess the feasibility of predicting tumor differentiations through metabonomic strategy based on nuclear magnetic resonance spectroscopy. By implanting pancreatic cancer cell strains Panc-1, Bxpc-3 and SW1990 in nude mice in situ, we successfully established the orthotopic xenograft models of PDAC with different differentiations. The metabonomic profiling of serum from different PDAC was achieved and analyzed by using 1H nuclear magnetic resonance (NMR) spectroscopy combined with the multivariate statistical analysis. Then, the differential metabolites acquired were used for enrichment analysis of metabolic pathways to get a deep insight. An obvious metabonomic difference was demonstrated between all groups and the pattern recognition models were established successfully. The higher concentrations of amino acids, glycolytic and glutaminolytic participato...Continue Reading

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Citations

Feb 7, 2018·Cancers·Yasutsugu AsaiMakoto Sunamura
Sep 1, 2018·Clinical Chemistry and Laboratory Medicine : CCLM·Zikuan SongWei Jiang
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Methods Mentioned

BETA
NMR
PCA
metabonomic profiling

Software Mentioned

SIMCA
OPLS
- P
MATLAB
DA
MestReNova
MBROLE
PLS
Mestrelab

Related Concepts

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