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综合分析鉴定胰腺癌基因表达谱中的关键基因和通路。

Identification of Key Genes and Pathways in Pancreatic Cancer Gene Expression Profile by Integrative Analysis.

机构信息

Department of Biomedical Engineering, College of Electronic and Information Engineering, Xi'an Technological University, Xi'an 710021, China.

出版信息

Genes (Basel). 2019 Aug 13;10(8):612. doi: 10.3390/genes10080612.

DOI:10.3390/genes10080612
PMID:31412643
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6722756/
Abstract

BACKGROUND

Pancreatic cancer is one of the malignant tumors that threaten human health.

METHODS

The gene expression profiles of GSE15471, GSE19650, GSE32676 and GSE71989 were downloaded from the gene expression omnibus database including pancreatic cancer and normal samples. The differentially expressed genes between the two types of samples were identified with the Limma package using R language. The gene ontology functional and pathway enrichment analyses of differentially-expressed genes were performed by the DAVID software followed by the construction of a protein-protein interaction network. Hub gene identification was performed by the plug-in cytoHubba in cytoscape software, and the reliability and survival analysis of hub genes was carried out in The Cancer Genome Atlas gene expression data.

RESULTS

The 138 differentially expressed genes were significantly enriched in biological processes including cell migration, cell adhesion and several pathways, mainly associated with extracellular matrix-receptor interaction and focal adhesion pathway in pancreatic cancer. The top hub genes, namely , , , and were identified from the protein-protein interaction network. The expression levels of hub genes were consistent with data obtained in The Cancer Genome Atlas. , , and were significantly linked with poor survival in pancreatic adenocarcinoma.

CONCLUSIONS

These hub genes may be used as potential targets for pancreatic cancer diagnosis and treatment.

摘要

背景

胰腺癌是威胁人类健康的恶性肿瘤之一。

方法

从基因表达综合数据库中下载 GSE15471、GSE19650、GSE32676 和 GSE71989 这 4 个基因芯片数据集，包含胰腺癌和正常样本。使用 R 语言中的 Limma 包识别两种样本之间的差异表达基因。通过 DAVID 软件对差异表达基因进行基因本体论功能和通路富集分析，然后构建蛋白质-蛋白质相互作用网络。在 cytoscape 软件的插件 cytoHubba 中识别枢纽基因，并在癌症基因组图谱基因表达数据中对枢纽基因进行可靠性和生存分析。

结果

138 个差异表达基因在细胞迁移、细胞黏附和几个通路等生物学过程中显著富集，主要与胰腺癌中的细胞外基质-受体相互作用和黏着斑通路有关。从蛋白质-蛋白质相互作用网络中鉴定出了前 5 个枢纽基因，即 、 、 、 、 。枢纽基因的表达水平与癌症基因组图谱中的数据一致。 、 、 、 与胰腺腺癌的不良预后显著相关。

结论

这些枢纽基因可能可作为胰腺癌诊断和治疗的潜在靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/e9bab897a64a/genes-10-00612-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/d1d4cd2eee6e/genes-10-00612-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/4f15eac21ec6/genes-10-00612-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/a15b9930fc78/genes-10-00612-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/de2b09e87ee5/genes-10-00612-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/e9bab897a64a/genes-10-00612-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/d1d4cd2eee6e/genes-10-00612-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/4f15eac21ec6/genes-10-00612-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/a15b9930fc78/genes-10-00612-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/de2b09e87ee5/genes-10-00612-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dbd/6722756/e9bab897a64a/genes-10-00612-g005.jpg

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