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PLoS One. 2013;8(1):e54644. doi: 10.1371/journal.pone.0054644. Epub 2013 Jan 25.

A novel proteomics-based clinical diagnostics technology identifies heterogeneity in activated signaling pathways in gastric cancers.

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Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center Sungkyunkwan University School of Medicine, Seoul, Korea.



The aim of this study was to utilize the proteomics-based Collaborative Enzyme Enhanced Reactive (CEER) immunoassay to investigate protein tyrosine phosphorylations as diagnostic markers in gastric cancers (GCs).


Protein lysates from fresh-frozen 434 advanced stage GCs were analyzed for phosphorylation of HER1, HER2, p95HER2, HER3, cMET, IGF1R and PI3K. The pathway activation patterns were segregated based on the tumor HER2 status. Hierarchical clustering was utilized to determine pathway coactivations in GCs. Prognostic value of pathway activation patterns was determined by correlating disease-free survival times of the various GC subgroups using Kaplan-Meier survival analysis. CEER was also used to determine the presence of tyrosine phosphorylated signaling cascades in circulating tumor cells (CTCs) and ascites tumor cells (ATCs).


Utilizing a novel diagnostics immunoassay, CEER, we demonstrate the presence of p95HER2 and concomitantly activated signaling pathways in GC tumor tissues, CTCs and ATCs isolated from GC patients for the first time. p95HER2 is expressed in ~77% of HER2(+) GCs. Approximately 54% of GCs have an activated HER1, HER2, HER3, cMET or IGF1R and demonstrate a poorer prognosis than those where these receptor tyrosine kinases (RTKs) are not activated. Hierarchical clustering of RTKs reveals co-clustering of phosphorylated HER1:cMET, HER2:HER3 and IGF1R-PI3K. Coactivation of HER1 with cMET renders GCs with a shorter disease-free survival as compared to only cMET activated GCs.


Our study highlights the utility of a novel companion diagnostics technology, CEER that has strong implications for drug development and therapeutic monitoring. CEER is used to provide an increased understanding of activated signaling pathways in advanced GCs that can significantly improve their clinical management through accurate patient selection for targeted therapeutics.

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