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Poster Display session 2

4778 - A correlation analysis between survival rate and the characteristic gene of gastric cancer based on bioinformatics analysis


29 Sep 2019


Poster Display session 2


Tumour Site

Gastric Cancer


Yi-wen Zhang


Annals of Oncology (2019) 30 (suppl_5): v253-v324. 10.1093/annonc/mdz247


Y. Zhang, Y. Liu

Author affiliations

  • Laboratory Of Clinical Pharmacy, Zhejiang cancer hospital, 310022 - Hangzhou/CN


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Abstract 4778


Gastric cancer is one of the most common fatal disease worldwide, but its mechanism and therapeutic targets are still unclear. In this study, we have analyzed the differences in gene modules and key pathways in gastric cancer patients, and elaborated the mechanism and effective treatment of gastric cancer with microarray data from the gene expression omnibus (GEO) database.


GEO2R tools was used to identify differential expression genes (DEGs) and String database was employed to construct protein-protein interaction (PPI) network. We firstly imported the PPI network into the Cytoscape software to find key nodes, and then employed the DAVID database to enrich and annotate the pathways and key modules.


63 characteristic genes of gastric cancer are involved in regulation of ECM-receptor interaction, focal adhesion and Protein digestion and absorption. SPARC, FN1, BGN and COL1A2 are four key nodes relating to tumour proliferation and metastasis, and their expression were strongly associated with poor survival (p < 0.05). 13 transcription factors including PRRX1 have remarkable changes in gastric cancer.


The crucial genes and pathways of gastric cancer were explored through different perspectives via multiple bioinformatics methods. Our study will not only contribute to elucidating the pathogenesis of gastric cancer, but also provide prognostic markers and potential therapeutic targets for gastric cancer.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.


National Natural Science Foundation of China (No. 81503165), Natural Science Foundation of Zhejiang Province (No. Q17H310010).


All authors have declared no conflicts of interest.

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