Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors and is difficult to diagnose in the early phase. This study was aimed at obtaining the metabolic profiles and characteristic metabolites of pancreatic intraepithelial neoplasia (PanIN) and PDAC tissues from Sprague–Dawley (SD) rats to establish metabonomic methods used in the early diagnosis of PDAC. In the present study, the animal models were established by embedding 7,12‐dimethylbenzanthracene (DMBA) in the pancreas of SD rats to obtain PanIN and PDAC tissues. After the preprocessing of tissues, 1H nuclear magnetic resonance (NMR) spectroscopy combined with multivariate and univariate statistical analysis was applied to identify the potential metabolic signatures and the corresponding metabolic pathways. Pattern recognition models were successfully established and differential metabolites, including glucose, amino acids, carboxylic acids and coenzymes, were screened out. Compared with the control, the trends in the variation of several metabolites were similar in both PanIN and PDAC. Kynurenate and methionine levels were elevated in PanIN but decreased in PDAC, thus, could served as biomarkers to distinguish PanIN from PDAC. Our results suggest that NMR‐based techniques combined with multivariate statistical analysis can distinguish the metabolic differences among PanIN, PDAC and normal tissues, and, therefore, present a promising approach for physiopathologic metabolism investigations and early diagnoses of PDAC.

Metabonomics has been applied in many bio-related scientific fields. Nevertheless, some animal research works are shown to fail when they are extended to humans. Therefore, it is essential to figure out suitable animal modeling to mimic human metabolism so that animal findings can serve humans. In this study, two kinds of commonly selected body fluids, serum and urine, from humans and various experimental animals were characterized by integration of nuclear magnetic resonance (NMR) spectroscopy with multivariate statistical analysis to identify the interspecies metabolic differences and similarities at a baseline physiological status. Our results highlight that the dairy cow and pig may be an optimal choice for transportation and biodistribution studies of drugs and that the Kunming (KM) mouse model may be the most effective for excretion studies of drugs, whereas the Sprague-Dawley (SD) rat could be the most suitable candidate for animal modeling under overall considerations. The biochemical pathways analyses further provide an interconnection between genetic evolution and metabolic variations, where species evolution most strongly affects microbial biodiversity and, consequently, has effects on the species-specific biological substances of biosynthesis and corresponding biological activities. Knowledge of the metabolic effects from species difference will enable the construction of better models for disease diagnosis, drug metabolism, and toxicology research.

Pancreatic cancer is a highly malignant disease with a poor prognosis and it is essential to diagnose and treat the disease at an early stage. The aim of this study was to understand the underlying biochemical mechanisms of pancreatic intraepithelial neoplasia (PanIN) and pancreatic ductal adenocarcinoma (PDAC) and to identify potential serum biomarkers for early detection of pancreatic cancer. 7,12-Dimethylbenz(a)anthracene (DMBA)-induced PanIN and PDAC rat models were established and the serum samples were collected. The serum samples were measured using (1)H nuclear magnetic resonance (NMR) spectroscopy and analyzed by chemometric methods including principal component analysis (PCA) and (orthogonal) partial least squares discriminant analysis ((O)PLS-DA). The related biochemical pathways were derived from KEGG analysis of the significantly different metabolites. As results, some serum metabolites demonstrated alarming metabolic changes in the precursor lesion of pancreatic cancer (PanIN-2 in this study). These changes involved elevated levels of ketone compounds including 3-hydroxybutyrate, acetoacetate, and acetone, some amino acids including asparagine, glutamate, threonine, and phenylalanine, glycoproteins and lipoproteins including N-acetylglycoprotein, LDL and VLDL, and some metabolites that have been shown to contribute to mutagenicity and cancer promotion such as deoxyguanosine and cytidine. More metabolites were shown to be significantly different between PanIN and PDAC, suggesting that a more complex set of changes occurs from noninvasive precursor lesion to invasive cancer. The serum metabonomic changes of rats with PanIN and PDAC may extend our understanding of pancreatic molecular pathogenesis, and the metabolic variations from PanIN to PDAC will be helpful to understand evolution processes of the pancreatic disease. NMR-based metabonomic analysis of animal models will be beneficial for the human study and will be helpful for the early detection of pancreatic cancer.

a b s t r a c tIn this study, NMR-based metabolomics in combination with multivariate pattern recognition technologies were employed to evaluate the physiological variations in the Wistar rats' plasma that are induced by pregnancy on the gestational days (GDs) 11, 14, 17 and 20. Untargeted metabolomics analysis revealed some possible mechanism of physiological effects for healthy pregnancies and showed a metabolic trajectory during pregnancy process. The levels of 24 metabolites were found to change significantly throughout pregnancy in maternal plasma. These metabolite changes involved in varied kinds of metabolic pathways including synthesis of biological substances, microbial metabolism in diverse environments, protein digestion and absorption, carbohydrate metabolism, digestion and absorption, mineral absorption, and ATP (Adenosine Triphosphate)-binding cassette transporters (ABC transporters). The substantial cores of all the metabolic pathways are promoting fetal growth and development and regulating maternal physiological state. This work showed relevant metabolic pathways perturbation in the maternal plasma due to normal pregnancy and provided the physical basis of time-dependent metabolic trajectory against which disease-related maternal physiological responses may be better understood in future studies.

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