10.3389/fgene.2018.00265.s004
Xinkui Liu
Xinkui
Liu
Jiarui Wu
Jiarui
Wu
Dan Zhang
Dan
Zhang
Zhitong Bing
Zhitong
Bing
Jinhui Tian
Jinhui
Tian
Mengwei Ni
Mengwei
Ni
Xiaomeng Zhang
Xiaomeng
Zhang
Ziqi Meng
Ziqi
Meng
Shuyu Liu
Shuyu
Liu
Table_2_Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis.XLSX
Frontiers
2018
gastric cancer
bioinformatics
differentially expressed genes
survival
biomarker
GEO
TCGA
2018-07-17 04:22:11
Dataset
https://frontiersin.figshare.com/articles/dataset/Table_2_Identification_of_Potential_Key_Genes_Associated_With_the_Pathogenesis_and_Prognosis_of_Gastric_Cancer_Based_on_Integrated_Bioinformatics_Analysis_XLSX/6824360
<p>Background and Objective: Despite striking advances in multimodality management, gastric cancer (GC) remains the third cause of cancer mortality globally and identifying novel diagnostic and prognostic biomarkers is urgently demanded. The study aimed to identify potential key genes associated with the pathogenesis and prognosis of GC.</p><p>Methods: Differentially expressed genes between GC and normal gastric tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Key genes related to the pathogenesis and prognosis of GC were identified by employing protein–protein interaction network and Cox proportional hazards model analyses.</p><p>Results: We identified nine hub genes (TOP2A, COL1A1, COL1A2, NDC80, COL3A1, CDKN3, CEP55, TPX2, and TIMP1) which might be tightly correlated with the pathogenesis of GC. A prognostic gene signature consisted of CST2, AADAC, SERPINE1, COL8A1, SMPD3, ASPN, ITGBL1, MAP7D2, and PLEKHS1 was constructed with a good performance in predicting overall survivals.</p><p>Conclusion: The findings of this study would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of GC.</p>