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pmid:29467930
Identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis.
Chunguang Li · Liangtao Luo · Sheng Wei · Xiongbiao Wang
Oncotarget · 2018 doi:10.18632/oncotarget.23239
Paper
complete
Experiment
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Data
partial
Analysis
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Execution
absent
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Complete file
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The gene expression profiles of GSE10780 which contained 42 histologically normal breast tissues and 143 IDC tissues were downloaded from the GEO database. Functional and pathway enrichment analysis of differentially expressed genes (DEGs) were performed and protein-protein interaction (PPI) network was analyzed using Cytoscape. In total, 999 DEGs were identified, including 667 up-regulated and 332 down-regulated DEGs. Gene ontology analysis demonstrated that most DEGs were significantly enriched in mitotic cell cycle, adhesion and protein binding process. Through PPI network analysis, a significant module was screened out, and the top 10 hub genes, CDK1, CCNB1, CENPE, CENPA, PLK1, CDC20, MAD2L1, HIST1H2BK, KIF2C and CCNA2 were identified from the PPI network. The expression levels of the 10 genes were validated in Oncomine database. KIF2C, MAD2L1 and PLK1 were associated with the overall survival. And we used cBioPortal to explore the genetic alterations of hub genes and potential drugs. In conclusion, the present study identified DEGs between normal and IDC samples, which could improve our understanding of the molecular mechanisms in the development of IDC, and these candidate genes might be used as therapeutic targets for IDC.", "claims": [{"id": "claim-method", "statement": "we used the Linear Models for Microarray Data (LIMMA, http://www.bioconductor.org/packages/release/bioc/html/limma.html) package in R to identify DEGs by comparing expression value between samples in IDC and normal group.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29467930", "locator": "sections[11] \"Identification of DEFs in IDC\" paragraph 2", "quote": "we used the Linear Models for Microarray Data (LIMMA, http://www.bioconductor.org/packages/release/bioc/html/limma.html) package in R to identify DEGs by comparing expression value between samples in IDC and normal group."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The gene expression profiles of GSE10780 were downloaded from the GEO database. 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