Conclusions and clinical relevance
Integrating labeling and label-free approaches improve the confidence in quantitative profiling of pancreatic tissue proteome, which furthers the understanding of the dysregulated pathways and functional subnetworks associated with T1D pathogenesis and may aid to develop diagnostic and therapeutic strategies for T1D.
Purpose
Type 1 diabetes (T1D) is characterized by autoimmune mediated self-destruction of the pancreatic islet beta cells and the resultant insulin deficiency. However, little is known about the underlying molecular pathogenesis at the pancreatic tissue level given the limited availability of clinical specimens. Experimental design: Quantitative proteomic studies is performed on age-matched T1D and healthy cadaveric pancreatic tissues (n = 18 each) using TMT 10plex-based isobaric labeling and BoxCar-based label-free LC-MS/MS approaches. ELISA is used to validate the differentially expressed proteins (DEPs).
Results
Overall, the two quantitative proteomics approaches identified 8824 proteins, of which 261 are DEPs. KEGG pathway and functional network analyses of the DEPs reveal dysregulations to pancreatic exocrine function, complement coagulation cascades, and extracellular matrix receptor interaction pathways in T1D. A selected list of the DEPs associated with pathways, subnetworks, and plasma proteome of T1D are validated using ELISA. Conclusions and clinical relevance: Integrating labeling and label-free approaches improve the confidence in quantitative profiling of pancreatic tissue proteome, which furthers the understanding of the dysregulated pathways and functional subnetworks associated with T1D pathogenesis and may aid to develop diagnostic and therapeutic strategies for T1D.