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Identification of Key Genes and Functions of Circulating Tumor Cells

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Identification of Key Genes and Functions of Circulating Tumor Cells Guan et al. BMC Medical Genomics (2020) 13:140 https://doi.org/10.1186/s12920-020-00795-w RESEARCH ARTICLE Open Access Identification of key genes and functions of circulating tumor cells in multiple cancers through bioinformatic analysis Yibing Guan1,2†, Fangshi Xu1,2†, Yiyuan Wang3†, Juanhua Tian1,2, Ziyan Wan1,2, Zhenlong Wang1 and Tie Chong1* 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. Keywords: Hub genes, Expression profiling data, Cancer, PSMC2, EMT Background of rarity and heterogeneity, which once restricted the re- Circulating tumor cells, as cells detached from solid tu- searches of CTCs [3]. Nowadays, with the development of mors and entering the circulating blood are a new type of technology, not only can CTCs be captured and enriched, tumor biomarker with real-time detection and minimally but also they can be identified at the molecular level, invasive characteristics [1]. At the same time, CTCs play which greatly improves the clinical application value of an important role in tumor progression, especially in the CTCs, and provides potential possible for the prognosis of formation of metastases [2]. CTCs have the characteristics tumor patients and personalized treatment [4]. In this art- icle, we analyze the differentially expressed genes (DEGs) * Correspondence: [email protected] between CTCs and primary tumors through the Gene Ex- † Yibing Guan, Fangshi Xu and Yiyuan Wang contributed equally to this work. pression Omnibus (GEO) database and use Gene Ontol- 1Department of Urology, the Second Affiliated Hospital, School of Medicine, Xi’an Jiaotong University, No 157 Xiwu Road, Xi’an 710004, Shaan Xi ogy (GO) / Kyoto Encyclopedia of Genes and Genomes Province, China (KEGG) enrichment tools, protein-protein interaction Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Guan et al. BMC Medical Genomics (2020) 13:140 Page 2 of 11 (PPI) analysis tools, and Kaplan–Meier plotter tools to protein score and obtain the top 10 hub genes with the analyze cell biological process, cellular component, mo- highest score [8]. lecular function, biological pathways, protein interactions, and clinical prognosis. Identify the differences between Patient CTCs analysis and hub gene survival analysis CTCs and primary tumors, and provide potential targets With the approval of the ethics review committee of the for tumor prognosis and treatment. Second Affiliated Hospital of Xi’an Jiaotong University, we obtained CTCs test data of renal cancer patients who Methods had undergone surgical treatment in our hospital from Data sources September 2015 to January 2019. The studies using clin- In this study, gene expression data were obtained from ical samples were approved by the institutional review the GEO database (https://www.ncbi.nlm.nih.gov/geo/). boards of the Second Affiliated Hospital of Xi’an Jiao- After careful screening, a total of GSE82198, GSE99394, tong University, and written-informed consents were ob- and GSE31023 were included in the analysis, GSE65505, tained from all participants. Peripheral blood samples (5 GSE67982, GSE76250, GSE50746 were also used as pri- ml, anticoagulated with EDTA) were drawn from all par- mary tumor controls. GSE31023 and GSE50746 are ticipants before each time point. Mononuclear cells based on the Agilent-026652 Whole Human Genome (MNC) were isolated by adding erythrocyte lysis buffer Microarray 4x44K v2 (Probe Name version) platform. (154 mM NH4Cl, 10 mM KHCO3 and 0.1 mM EDTA, GSE82198 is based on the [HG-U133_Plus_2] Affyme- Sigma, St. Louis, USA). After centrifugation (1500 rpm, trix Human Genome U133 Plus 2.0 Array platform. 5 min), the blood samples were resuspended in PBS buf- GSE99394, GSE65505, GSE67982, GSE76250 are based fer. CTCs were separated by using CanPatrol CTC en- on the [HTA-2_0] Affymetrix Human Transcriptome richment technique (SurExam, Guangzhou, China). Array 2.0 [transcript (gene) version] platform. Free ac- CTCs were divided into epithelial, mesenchymal and cess to all data. mixed phenotype based on the morphological and bio- logical biomarkers. Epithelial CTCs were detected with Acquisition of DEGs labeling epithelia markers, such as EpCAM, CK8, CK18 The NetworkAnalyst tool (https://www.networkanalyst.ca/) and CK19. Mesenchymal CTCs were tested by labeling was used to analyze the expression of CTCs and corre- mesenchymal markers, including Vimentin and Twist. sponding primary tumor genes in the above data set, and The expression levels of EpCAM, CK8, CK18, CK19, then genes with adjusted P < 0.05 and | logFC | > 1 were Vimentin and Twist were detected by RNA in situ marked as DEGs [5]. The NetworkAnalyst tool includes hybridization technique. The detailed procedures were stepssuchasdatafiltering,normalization, and difference described as following. White blood cells were loaded analysis. Through the above steps and the removal of the into 24 wells cell culture plates. All cells were treated batch effect function of the limma package in the difference with proteinase. Subsequently, targeted gene genomic analysis, it can reduce the influence of batch effect on ex- DNA sequences were detected with capture probes in- perimental results. After obtaining the DEGs of the three cluding preamplifier sequence, the amplifier sequence tumors, the DGEs co-expressed in different cancers were and the labeled probe17. Epithelial markers EpCAM, obtained through the Wayne Diagram tool (http://bioinfor- CK8, CK18 and CK19 were labeled with Alexa Fluor matics.psb.ugent.be/webtools/Venn/). 594. Mesenchymal markers Vimentin and Twist were la- beled with Alexa Fluor 488. White blood cells were GO / KEGG pathway analysis of DEGs stained by Alexa Fluor 750 conjugated anti-CD45. The metascape tool (https://metascape.org/gp/index. Meanwhile, the Kaplan–Meier plotter tool was used to html#/main/step1) was used to perform GO biological analyze the OS and RFS prognosis of hub genes in renal processes (BP), cell components (CC), molecular func- clear cell carcinoma. P < 0.05 was considered statistically tions (MF), and KEGG pathway enrichment analysis of significant. 589 DEGs [6]. Screening for enrichment information with statistical significance at P < 0.05. Expression of PSMC2 in kidney cancer cell lines and tissues PPI network construction and hub gene identification Access the RNAseq data of PSMC2 in common kidney The STRING tool (https://string-db.org/cgi/input.pl) cancer cell lines through the Cancer Cell Line was used to analyze the obtained 589 DEGs, set the con- Encyclopedia (CCLE) database (https://portals.broadin- fidence greater than 0.7 as the screening condition, and stitute.org/ccle/about)[9]. Statistics of expression data obtain the PPI network [7]. Use the Cytoscape tool through Prism software. Immunohistochemical pictures (https://cytoscape.org/) to visualize
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