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生物信息学对胰腺癌细胞外基质有关基因的研究
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Abstract:
通过生物信息学方法挖掘胰腺癌组织中差异基因，明确差异基因的功能与信号通路，筛选出与细胞外基质有关的信号通路，确定细胞外基质通路研究与胰腺癌之间的关系，找寻胰腺癌中外基质的潜在生物标志物。从Gene Expression Omnibus (GEO)数据库中下载胰腺癌样本数据，基于GSE91035芯片数据，运用R语言筛选数据中的差异表达基因(differentially expressed genes, DGEs)，对胰腺癌DGEs进行基因本体功能注释(GO)和京都基因与基因组百科全书通路分析(KEGG)。利用GSEA数据库构建细胞外基质通路可视化，并确定关键基因，用GEPIA2数据库验证关键基因的表达与预后的关系。结果确定有3023个差异基因，上调1803个，下调1220个。其中和细胞外基质相关的基因为COL1A1，LAMB3，COMP，FN1，THBS2，LAMC2，ITGA11，ITGB6，COL4A5，HMMR并对其进行验证确定LAMB3，ITGB6，HMMR三个基因与胰腺癌的发生发展相关。该数据集的差异基因主要通过参与抗原加工和呈递，ECM受体相互作用，细胞粘附分子，细胞黏附等生物学过程从而影响胰腺癌的发生发展，并确定细胞外基质有关基因对胰腺癌至关重要。本研究通过对胰腺癌差异基因的分析，确定细胞外基质有关基因可以作为关键影响靶点。
This paper aims to identify differentially expressed genes (DGEs) in pancreatic cancer tissues using bioinformatics methods, elucidate the functions and signaling pathways of these DGEs, screen out signaling pathways related to the extracellular matrix (ECM), determine the relationship between ECM pathway research and pancreatic cancer, and identify potential biomarkers of the ECM in pancreatic cancer. Sample data of pancreatic cancer were downloaded from the Gene Expression Omnibus (GEO) database. Based on the chip data from GSE91035, R language was used to screen DGEs in the data. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the DGEs related to pancreatic cancer. The GSEA database was utilized to visualize the ECM pathway and identify key genes. The GEPIA2 database was employed to verify the relationship between the expression of these key genes and prognosis. A total of 3023 DGEs were identified, with 1803 upregulated and 1220 downregulated genes. Among them, genes related to the ECM included COL1A1, LAMB3, COMP, FN1, THBS2, LAMC2, ITGA11, ITGB6, COL4A5, and HMMR. Verification was conducted to confirm that LAMB3, ITGB6, and HMMR are associated with the occurrence and development of pancreatic cancer. The DGEs in this dataset primarily affect the occurrence and development of pancreatic cancer by participating in biological processes such as antigen processing and presentation, ECM receptor interaction, cell adhesion molecules, and cell adhesion. It was determined that genes related to the ECM are crucial in pancreatic cancer. Through the analysis of DGEs in pancreatic cancer, this study identified genes related to the ECM as key targets of influence.
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