RNA-seq 数据的生物信息学分析揭示了结肠癌中的关键基因。
Bioinformatics analysis of RNA-seq data revealed critical genes in colon adenocarcinoma.
机构信息
Department of Gastroenterology, The Third People's Hospital of Chengdu, The Second Affiliated Chengdu Clinical College of Chongqing Medical University, Chengdu, Sichuan, China.
出版信息
Eur Rev Med Pharmacol Sci. 2017 Jul;21(13):3012-3020.
OBJECTIVE
RNA-seq data of colon adenocarcinoma (COAD) were analyzed with bioinformatics tools to discover critical genes in the disease. Relevant small molecule drugs, transcription factors (TFs) and microRNAs (miRNAs) were also investigated.
MATERIALS AND METHODS
RNA-seq data of COAD were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis was performed with package edgeR. False positive discovery (FDR) < 0.05 and |log2 (fold change)|>1 were set as the cut-offs to screen out differentially expressed genes (DEGs). Gene coexpression network was constructed with package Ebcoexpress. GO enrichment analysis was performed for the DEGs in the gene coexpression network with DAVID. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was also performed for the genes with KOBASS 2.0. Modules were identified with MCODE of Cytoscape. Relevant small molecules drugs were predicted by Connectivity map. Relevant miRNAs and TFs were searched by WebGestalt.
RESULTS
A total of 457 DEGs, including 255 up-regulated and 202 down-regulated genes, were identified from 437 COAD and 39 control samples. A gene coexpression network was constructed containing 40 DEGs and 101 edges. The genes were mainly associated with collagen fibril organization, extracellular matrix organization and translation. Two modules were identified from the gene coexpression network, which were implicated in muscle contraction and extracellular matrix organization, respectively. Several critical genes were disclosed, such as MYH11, COL5A2 and ribosomal proteins. Nine relevant small molecule drugs were identified, such as scriptaid and STOCK1N-35874. Accordingly, a total of 17 TFs and 10 miRNAs related to COAD were acquired, such as ETS2, NFAT, AP4, miR-124A, MiR-9, miR-96 and let-7.
CONCLUSIONS
Several critical genes and relevant drugs, TFs and miRNAs were revealed in COAD. These findings could advance the understanding of the disease and benefit therapy development.
目的
利用生物信息学工具分析结肠腺癌（COAD）的 RNA-seq 数据，以发现该疾病中的关键基因。还研究了相关的小分子药物、转录因子（TFs）和 microRNAs（miRNAs）。
材料与方法
从癌症基因组图谱（TCGA）下载 COAD 的 RNA-seq 数据。使用 package edgeR 进行差异分析。设置 FDR<0.05 和 |log2（fold change）|>1 作为截止值，以筛选出差异表达基因（DEGs）。使用 package Ebcoexpress 构建基因共表达网络。使用 DAVID 对基因共表达网络中的 DEGs 进行 GO 富集分析。使用 KOBASS 2.0 对具有 KOBASS 2.0 的基因进行京都基因与基因组百科全书（KEGG）通路富集分析。使用 Cytoscape 的 MCODE 识别模块。通过 Connectivity map 预测相关小分子药物。通过 WebGestalt 搜索相关的 miRNAs 和 TFs。
结果
从 437 个 COAD 和 39 个对照样本中鉴定出 457 个 DEGs，包括 255 个上调基因和 202 个下调基因。构建了一个包含 40 个 DEG 和 101 个边的基因共表达网络。这些基因主要与胶原纤维组织、细胞外基质组织和翻译有关。从基因共表达网络中鉴定出两个模块，分别与肌肉收缩和细胞外基质组织有关。发现了几个关键基因，如 MYH11、COL5A2 和核糖体蛋白。鉴定出 9 种相关的小分子药物，如 scriptaid 和 STOCK1N-35874。相应地，获得了 17 个与 COAD 相关的 TF 和 10 个 miRNAs，如 ETS2、NFAT、AP4、miR-124A、miR-9、miR-96 和 let-7。
结论
在 COAD 中发现了几个关键基因和相关的药物、TF 和 miRNAs。这些发现可以促进对该疾病的理解，并有助于治疗的发展。
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