2013
DOI: 10.1016/j.jprot.2013.03.031
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Identification of proteins implicated in the development of pancreatic cancer-associated diabetes mellitus by iTRAQ-based quantitative proteomics

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Cited by 23 publications
(11 citation statements)
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“…Numerous genes were found to be differentially expressed on bioinformatic analysis of the gene expression profiles, consistent with former reports [16,17]. We then extracted secretory genes and did GO analysis.…”
Section: Discussionsupporting
confidence: 86%
“…Numerous genes were found to be differentially expressed on bioinformatic analysis of the gene expression profiles, consistent with former reports [16,17]. We then extracted secretory genes and did GO analysis.…”
Section: Discussionsupporting
confidence: 86%
“…111 Another proteomic study found upregulation of S100-A9 in pancreatic ductal adenocarcinoma tissues with diabetes compared with those without diabetes. 112 S100A8/A9 is highly abundant in neutrophils and activated monocytes or macrophages, and these findings might reflect the myeloid cell infiltration observed even at early stages of pancreatic ductal adenocarcinoma development. 113,114 A study using peripheral blood mononuclear cell gene profiling for pancreatic ductal adenocarcinoma proposed vanin-1 and matrix metalloproteinase-9 (MMP9) as biomarkers to discriminate diabetes secondary to pancreatic cancer from type 2 diabetes.…”
Section: Diabetes Secondary To Pancreatic Cancermentioning
confidence: 93%
“…Source: extracted from Suppl. Tables S3 and S4 of Wang et al (2013a), including proteins with >3/2 or <2/3 fold change in at least 3 of 4 iTRAQ experiments for different pooled samples. LCM of CD24 + cells from PDAC vs CD24 − cells from adjacent normal tissue (ANT).…”
Section: Data Sourcesmentioning
confidence: 99%
“…1B show that up-expressed proteins in pancreatic cancer often have significantly higher Z C [ ]. A dataset obtained for pancreatic cancer associated with diabetes mellitus (Wang et al, 2013a) [ ] has both significantly higher Z C and n H 2 O . Only one dataset, from a study that targeted accessible proteins (Turtoi et al, 2011) (Chen et al, 2007), accessible proteins (Turtoi et al, 2011), and low-grade tumors (Wang et al, 2013b).…”
Section: /24mentioning
confidence: 99%