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Identification of key genes controlling cancer stem cell characteristics in gastric cancer

World Journal of Gastrointestinal Surgery 2020年第11期12卷 442-459页

作者： Chao Huang Ce-Gui Hu Zhi-Kun Ning Jun Huang Zheng-Ming Zhu Department of Gastrointestinal Surgery The Second Affiliated Hospital of Nanchang UniversityNanchang 330006Jiangxi ProvinceChina

BACKGROUND Self-renewal of gastric cancer stem cells(GCSCs)is considered to be the underlying cause of the metastasis,drug resistance,and recurrence of gastric cancer(GC).AIM To characterize the expression of stem cell-related genes in *** RNA sequencing results and clinical data for gastric adenoma and adenocarcinoma samples were obtained from The Cancer Genome Atlas database,and the results of the GC mRNA expression-based stemness index(mRNAsi)were *** gene coexpression network analysis was then used to find modules of interest and their key *** analysis of key genes was performed using the online tool Kaplan-Meier Plotter,and the online database Oncomine was used to assess the expression of key genes in *** mRNAsi was significantly upregulated in GC tissues compared to normal gastric tissues(Pgene coexpression network;the brown module was most positively correlated with *** key genes(BUB1,BUB1 B,NCAPH,KIF14,RACGAP1,RAD54 L,TPX2,KIF15,KIF18 B,CENPF,TTK,KIF4 A,SGOL2,PLK4,XRCC2,a n d C1 orf112)were identified in the brown *** functional and pathway enrichment analyses showed that the key genes were significantly enriched in the spindle cellular component,the sister chromatid segregation biological process,the motor activity molecular function,and the cell cycle and homologous recombination *** analysis and Oncomine analysis revealed that the prognosis of patients with GC and the expression of three genes(RAD54 L,TPX2,and XRCC2)were consistently *** Sixteen key genes are primarily associated with stem cell self-renewal and cell proliferation ***54 L,TPX2,and XRCC2 are the most likely therapeutic targets for inhibiting the stemness characteristics of GC cells.

关键词： Gastric cancer Cancer stem cell key gene The Cancer Genome Atlas database Weighted gene coexpression network analysis mRNA expression-based stemness index

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Bioinformatics analysis of key genes associated with the prognosis of breast cancer

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Journal of Nutritional Oncology 2023年第4期8卷 176-182页

作者： Kun Zhou Dao-Lai Huang Hui-Chao Ruan Xiang-Hua Wu Department of Gastrointestinal Gland Surgery The First Affiliated Hospital of Guangxi Medical UniversityNanning 530021GuangxiChina

Objective:We sought to identify potential therapeutic targets for breast cancer patients by employing a bioinformatics analysis to screen for genes linked with an unfavorable ***:The gene Expression Omnibus(GEO)database was utilized to obtain three gene expression profile datasets,namely GSE42568,GSE86374,and *** identify differentially expressed genes(DEGs),the GEO2R online tool was ***,a func-tional enrichment analysis was ***,a protein-protein interaction network was established using STRING,and DEGs were subjected to module analysis via Cytoscape software to identify pivotal ***,the selected pivotal genes underwent further ex-amination and validation utilizing three databases:GEPIA,UALCAN,and Kaplan-Meier ***:A total of 121 DEGs were detected,comprising 74 genes with increased expression and 47 genes with decreased *** key genes were identified:HMMR,RRM2,CDK1,TOP2A,AURKA,CCNB1,MAD2L1,KIF2C,BUB1B,*** in the GEPIA database revealed high expression levels for all key genes except CDK1.A survival analysis conducted using the Kaplan-Meier Plotter database revealed noteworthy associations between nine crucial genes and the overall survival(OS)of individuals diagnosed with breast ***,these nine key genes exhibited significantly increased expression across different molecular subtypes of breast cancer according to the UALCAN data ***:We identified nine crucial genes significantly linked to the onset,progression,and unfavorable prognosis of breast cancer,providing potential targets for novel treatment options and biomarkers to predict patient outcomes.

关键词： Breast cancer Bioinformatics Differentially expressed gene key gene Survival analysis Prognosis

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