Screening of hub genes and prognosis-related genes in colorectal cancer based on bioinformatics

doi:10.3877/cma.j.issn.2095-3224.2021.05.009

Abstract

Abstract:

Objective

To screen differentially expressed genes (DEGs) between colorectal cancer and normal colorectal mucosa tissues by bioinformatics and analyze their relationship with prognosis.

Methods

Colorectal cancer gene microarrays datasets GSE110224, GSE41328 and GSE22598 were downloaded from Gene Expression Omnibus (GEO) database. DEGs between colorectal cancer samples and normal tissue samples from those three datasets were screened by R software 4.0.3, and then GO and KEGG pathway analysis were carried out. The protein interaction network was constructed by STRING database, Cytoscape software v3.7.2 was used to screen the hub genes in the protein-protein interaction (PPI) network. Finally, the selected hub genes were validated and analyzed for the relationship with prognosis by the GEPIA database.

Results

A total of 366 DEGs were screened, of which 128 were up-regulated and 238 were down-regulated. GO function enrichment showed hub genes were mainly involved in proteolysis, positive regulation of proliferation and other biological processes, and cellular component mainly enriched in extracellular space, extracellular region, mediating zinc ion binding, calcium ion binding and other molecular functions. KEGG analysis showed that the enriched pathways are mainly related to cytokine-cytokine receptor interaction, chemokine signaling pathway and other signal transduction pathway. Ten hub genes were selected from the PPI network, including nine up-regulated genes, which were CXCL8, CXCL1, SPP1, COL1A1, SOX9, MMP3, COL1A2, CD44, CXCL5, and one down-regulated gene CXCL12. Those ten genes were verified by using GEPIA showing that eight of them existed significant difference and all of them were consistent with the above analysis. Survival analysis results showed that genes CXCL8, SPP1 and COL1A2 were significantly associated with the survival rate of colorectal tumor patients.

Conclusion

CXCL8 and SPP1 may be prognosis key genes of colorectal tumor patients and may serve as a potential biomarker providing basis on molecular level for screening and diagnosis of colorectal tumor.

Key words: Colorectal neoplasms, Gene expression omnibus (GEO) database, Bioinformatics, Prognosis

Fei Li, Qiangqiang Qin, Zhanfeng Gu, Tianxiang Zhang, Si Shen, Li Zhou, Lesha Zhang. Screening of hub genes and prognosis-related genes in colorectal cancer based on bioinformatics[J]. Chinese Journal of Colorectal Diseases(Electronic Edition), 2021, 10(05): 497-504.

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References 22

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差异表达基因	基因名称	连通度	中文名称
上调基因	C-X-C motif chemokine ligand 8，CXCL8	30	白细胞介素8
	C-X-C motif chemokine ligand 1，CXCL1	28	白细胞介素1
	CD44	28	CD44分子
	Secreted phosphoprotein 1，SPP1	27	分泌磷蛋白1
	Collagen type Ⅰ alpha 1 chain，COL1A1	26	Ⅰ型胶原α1
	Collagen type Ⅰ alpha 2 chain，COL1A2	26	Ⅰ型胶原α2
	SOX9	22	SRY-box 9
	Matrix Metalloproteinase 3，MMP3	22	基质金属蛋白酶3
	C-X-C motif chemokine ligand 5，CXCL5	20	白细胞介素5
下调基因	C-X-C motif chemokine ligand 1，CXCL12	26	白细胞介素12

差异表达基因	基因名称	连通度	中文名称
上调基因	C-X-C motif chemokine ligand 8，CXCL8	30	白细胞介素8
	C-X-C motif chemokine ligand 1，CXCL1	28	白细胞介素1
	CD44	28	CD44分子
	Secreted phosphoprotein 1，SPP1	27	分泌磷蛋白1
	Collagen type Ⅰ alpha 1 chain，COL1A1	26	Ⅰ型胶原α1
	Collagen type Ⅰ alpha 2 chain，COL1A2	26	Ⅰ型胶原α2
	SOX9	22	SRY-box 9
	Matrix Metalloproteinase 3，MMP3	22	基质金属蛋白酶3
	C-X-C motif chemokine ligand 5，CXCL5	20	白细胞介素5
下调基因	C-X-C motif chemokine ligand 1，CXCL12	26	白细胞介素12

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