Literature DB >> 28058586

Key Genes in Stomach Adenocarcinoma Identified via Network Analysis of RNA-Seq Data.

Li Shen1, Lizhi Zhao1, Jiquan Tang1, Zhiwei Wang1, Weisong Bai1, Feng Zhang1, Shouli Wang1, Weihua Li2.   

Abstract

RNA-seq data of stomach adenocarcinoma (STAD) were analyzed to identify critical genes in STAD. Meanwhile, relevant small molecule drugs, transcription factors (TFs) and microRNAs (miRNAs) were also investigated. Gene expression data of STAD were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis was performed with package edgeR. Relationships with correlation coefficient > 0.6 were retained in the gene co-expression network. Functional enrichment analysis was performed for the genes in the network with DAVID and KOBASS 2.0. Modules were identified using Cytoscape. Relevant small molecules drugs, transcription factors (TFs) and microRNAs (miRNAs) were revealed by using CMAP and WebGestalt databases. A total of 520 DEGs were identified between 285 STAD samples and 33 normal controls, including 244 up-regulated and 276 down-regulated genes. A gene co-expression network containing 53 DEGs and 338 edges was constructed, the genes of which were significantly enriched in focal adhesion, ECM-receptor interaction and vascular smooth muscle contraction pathways. Three modules were identified from the gene co-expression network and they were associated with skeletal system development, inflammatory response and positive regulation of cellular process, respectively. A total of 20 drugs, 9 TFs and 6 miRNAs were acquired that may regulate the DEGs. NFAT-COL1A1/ANXA1, HSF2-FOS, SREBP-IL1RN and miR-26-COL5A2 regulation axes may be important mechanisms for STAD.

Entities:  

Keywords:  Differentially expressed genes; Functional enrichment analysis; Gene co-expression network; Gene expression data; Stomach adenocarcinoma

Mesh:

Substances:

Year:  2017        PMID: 28058586     DOI: 10.1007/s12253-016-0178-y

Source DB:  PubMed          Journal:  Pathol Oncol Res        ISSN: 1219-4956            Impact factor:   3.201


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