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>