Protein signatures for classification and prognosis of gastric cancer: A signaling pathway-based approach

Daguang Wang, Fei Ye, Yabin Sun, Wei Li, Hongyi Liu, Jing Jiang, Yang Zhang, Chengkui Liu, Weihua Tong, Ling Gao, Yezhou Sun, Weijia Zhang, Terry Seetoe, Peng Lee, Jian Suo, David Y. Zhang

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

Current methods have limited accuracy in predicting survival and stratifying patients with gastric cancer for appropriate treatment. We sought to identify protein signatures of gastric cancer for classification and prognostication. The Protein Pathway Array (initial study) and Western blot (confirmation) were used to assess the protein expression in a total of 199 fresh frozen gastric samples. There were 56 paired samples divided into a training set (n = 37) and a validation set (n = 19) for the identification of differentially expressed proteins between tumor and normal tissues. There were 56 tumor samples used to identify proteins correlating with tumor and nodal staging. All 93 tumor samples were used to identify candidate proteins for predicting survival. We confirmed the survival prediction of the candidate proteins by using an additional cohort of gastric cancer samples (n = 50). There were 22 proteins differentially expressed between normal and tumor tissues. Nine proteins were selected to build the predictor to classify normal and tumor samples. Ten proteins were differentially expressed among different T stages and four of these were associated with invasive behavior. An additional four proteins were associated with lymph node metastasis. Two proteins were identified as independent risk factors for overall survival. This study indicated that some dysregulated signaling proteins could be selected as useful biomarkers for tumor classification and predicting outcome in gastric cancer patients.

Original languageEnglish
Pages (from-to)1657-1666
Number of pages10
JournalAmerican Journal of Pathology
Volume179
Issue number4
DOIs
StatePublished - Oct 2011
Externally publishedYes

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