Background: Diabetes is a risk factor associated with pancreatic ductal adenocarcinoma (PDAC), and new adult-onset diabetes can be an early sign of pancreatic malignancy. Development of blood-based biomarkers to identify diabetic patients who warrant imaging tests for cancer detection may represent a realistic approach to facilitate earlier diagnosis of PDAC in a risk population. Methods: A spectral library-based proteomic platform was applied to interrogate biomarker candidates in plasma samples from clinically well-defined diabetic cohorts with and without PDAC. Random forest algorithm was used for prediction model building and receiver operating characteristic (ROC) curve analysis was applied to evaluate the prediction probability of potential biomarker panels. Results: Several biomarker panels were cross-validated in the context of detection of PDAC within a diabetic background. In combination with carbohydrate antigen 19-9 (CA19-9), the panel, which consisted of apolipoprotein A-IV (APOA4), monocyte differentiation antigen CD14 (CD14), tetranectin (CLEC3B), gelsolin (GSN), histidine-rich glycoprotein (HRG), inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3), plasma kallikrein (KLKB1), leucine-rich alpha-2-glycoprotein (LRG1), pigment epithelium-derived factor (SERPINF1), plasma protease C1 inhibitor (SERPING1), and metalloproteinase inhibitor 1 (TIMP1), demonstrated an area under curve (AUC) of 0.85 and a two-fold increase in detection accuracy compared to CA19-9 alone. The study further evaluated the correlations of protein candidates and their influences on the performance of biomarker panels. Conclusions: Proteomics-based multiplex biomarker panels improved the detection accuracy for diagnosis of early stage PDAC in diabetic patients.

Proteins are the essential functional biomolecules profoundly implicated in all aspects of pancreatic tumorigenesis and its progression. While common genomic factors, such as KRAS, TP53, SMAD4, and CDKN2A have been well recognized in association of pancreatic ductal adenocarcinoma (PDAC), our understanding of functional changes at the proteome level merits further investigation. Malignance associated proteome alterations can be attributed to the convoluted outcomes from genetic, epigenetic and environmental factors in initiating and progressing PDAC, and may reflect on changes in protein expressional level, structure, localization, as well as post-translational modifications (PTMs) status. The study of localized or systemic proteome alterations in PDAC, as well as its precursor lesions, such as pancreatic intraepithelial neoplasia (PanIN) and mucinous pancreatic cystic neoplasm, would provide unique perspectives in elucidating functional molecular events underlying PDAC. While efforts have been made, challenges still exist to comprehensively integrate much of the proteomic discovery to the perspectives gained from genomic studies in the context of biomarker discovery. Novel approaches and data from well-defined longitudinal clinical studies and experimental models are needed to facilitate the study of PDAC and precursor lesions for early detection and intervention.

Although the gut microbiome has been associated with dietary patterns linked to health, microbial metabolism is not well characterized. This ancillary study was a proof of principle analysis for a novel application of metaproteomics to study microbial protein expression in a controlled dietary intervention. We measured the response of the microbiome to diet in a randomized crossover dietary intervention of a whole-grain, low glycemic load diet (WG) and a refined-grain, high glycemic load diet (RG). Total proteins in stools from 9 participants at the end of each diet period (n = 18) were analyzed by LC MS/MS and proteins were identified using the Human Microbiome Project (HMP) human gut microbiome database and UniProt human protein databases. T-tests, controlling for false discovery rate (FDR) <10%, were used to compare the Gene Ontology (GO) biological processes and bacterial enzymes between the two interventions. Using shotgun proteomics, more than 53,000 unique peptides were identified including microbial (89%) and human peptides (11%). Forty-eight bacterial enzymes were statistically different between the diets, including those implicated in SCFA production and degradation of fatty acids. Enzymes associated with degradation of human mucin were significantly enriched in the RG diet. These results illustrate that the metaproteomic approach is a valuable tool to study the microbial metabolism of diets that may influence host health.

Glyceraldehyde-derived advanced glycation end products (AGEs) play an important role in the pathogenesis of many diseases including cancer. Accumulation of intracellular AGEs could stimulate cancer induction and facilitate cancer progression. We evaluated the toxic effect of glyceraldehyde-derived intracellular AGEs on normal and malignant pancreatic ductal cells by assessing the cell viability, toxicity, and oxidative stress, followed by proteomic analysis. Our functional studies showed that pancreatic cancer cells (PANC-1 and MIA PaCa-2) were more resistant to glyceraldehyde treatment compared to normal pancreatic ductal epithelial cells (HPDE), while cytotoxicity effects were observed in all cell types. Furthermore, using ¹³C isotopic labeled glyceraldehyde, the proteomic data revealed a dose-dependent increment of the number of glycation adducts in both these cell types. HPDE cells showed a higher number of intracellular AGEs compared to cancer cells. At a molecular level, the glycations in the lysine residues of proteins showed a concurrent increase with the concentration of the glyceraldehyde treatment, while the arginine glycations appeared to be less affected by the glyceraldehyde doses. Further pathway analysis of these glycated proteins suggested that the glycated proteins participate in important biological processes that are major hallmarks of cancer initiation and progression, including metabolic processes, immune response, oxidative stress, apoptosis, and S100 protein binding.