BMC Medical Genomics (Sep 2020)

Identification of key genes and functions of circulating tumor cells in multiple cancers through bioinformatic analysis

  • Yibing Guan,
  • Fangshi Xu,
  • Yiyuan Wang,
  • Juanhua Tian,
  • Ziyan Wan,
  • Zhenlong Wang,
  • Tie Chong

DOI
https://doi.org/10.1186/s12920-020-00795-w
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 11

Abstract

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Abstract Background Circulating tumor cells (CTCs) play a key role in cancer progression, especially metastasis, due to the rarity and heterogeneity of CTCs, fewer researches have been conducted on them at the molecular level. However, through the Gene Expression Omnibus (GEO) database, this kind of minority researches can be well integrated, the gene expression differences between CTCs and primary tumors can be identified, and molecular targets for CTCs can be found. Methods We analyzed 7 sets of gene chips (GSE82198, GSE99394, GSE31023, GSE65505, GSE67982, GSE76250, GSE50746) obtained by GEO. Analysis of differentially expressed genes (DEGs) between CTCs and corresponding primary tumors by NetworkAnalyst. Metascape tool for Gene Ontology (GO) / Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differential genes and visual display. Cytoscape performs protein-protein interaction (PPI) analysis and obtains the hub genes. Renal cancer patients’ clinical specimens to verify the correctness of enrichment results. Prognostic analysis of hub genes in kidney cancer patients using the Kaplan–Meier plotter survival analysis tool. Results We obtained a total of 589 DEGs. The GO / KEGG enrichment results indicate that the DEGs are mainly concentrated in cell adhesion, epithelial-mesenchymal transition (EMT), and apoptosis. Renal cancer clinical specimens suggest that CTCs have epithelial and mesenchymal types. At the same time, PSMC2 can be used as a poor prognostic indicator for renal cancer patients. Conclusions In summary, our study suggests that compared with primary tumors, CTCs mainly change cell adhesion, EMT, and apoptosis. PSMC2 can be used as a poor prognostic factor.

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