Literature DB >> 35474355

Identification of a five genes prognosis signature for triple-negative breast cancer using multi-omics methods and bioinformatics analysis.

Jiulong Ma1, Chen Chen2, Shan Liu1, Jiahua Ji1, Di Wu1, Peng Huang1, Dexian Wei1, Zhimin Fan3, Liqun Ren4.   

Abstract

Triple-negative breast cancer (TNBC) has a high degree of malignancy, lack of effective diagnosis and treatment, and poor prognosis. Bioinformatics methods are used to screen the hub genes and signal pathways involved in the progress of TNBC to provide reliable biomarkers for the diagnosis and treatment of TNBC. Download the raw data of four TNBC-related datasets from the Gene Expression Omnibus (GEO) database and use them for bioinformatics analysis. GEO2R tool was used to analyze and identify differentially expressed (DE) mRNAs. DAVID database was used to carry out gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genome Pathways (KEGG) signal pathway enrichment analysis for DE mRNAs. STRING database and Cytoscape were used to build DE mRNAs protein-protein interaction (PPI) network diagram and visualize PPI network, respectively. Through cytoHubba, cBioPortal database, Kaplan-Meier mapper database, Gene Expression Profiling Interactive Analysis (GEPIA) Database, UALCAN Database, The Cancer Genome Atlas (TCGA) database, Tumor Immunity Estimation Resource identify hub genes. Perform qRT-PCR, Human Protein Atlas analysis, mutation analysis, survival analysis, clinical-pathological characteristics, and infiltrating immune cell analysis. 22 DE mRNAs were identified from the four datasets, including 16 upregulated DE mRNAs and six downregulated DE mRNAs. Enrichment analysis of the KEGG showed that DE mRNAs were principally enriched in pathways in cancer, mismatch repair, cell cycle, platinum drug resistance, breast cancer. Six hub genes were screened based on the PPI network diagram of DE mRNAs. Survival analysis found that TOP2A, CCNA2, PCNA, MSH2, CDK6 are related to the prognosis of TNBC. In addition, mutations, clinical indicators, and immune infiltration analysis show that these five hub genes play an important role in the progress of TNBC and immune monitoring. Compared with MCF-10A, MCF-7, and SKBR-3 cells, TOP2A, PCNA, MSH2, and CDK6 were significantly upregulated in MDA-MB-321 cells. Compared with normal, luminal, and Her-2 positive tissues, CCNA2, MSH2, and CDK6 were significantly upregulated in TNBC. Through comparative analysis of GEO datasets related to colorectal cancer and lung adenocarcinoma, it was determined that these five hub genes were unique differentially expressed genes of TNBC. At last, the hub genes related to the progression, prognosis, and immunity of TNBC have been successfully screened. They are indeed specific to TNBC as prognostic features. They can be used as potential markers for the prognosis of TNBC and provide potential therapeutic targets.
© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.

Entities:  

Year:  2022        PMID: 35474355     DOI: 10.1038/s41417-022-00473-2

Source DB:  PubMed          Journal:  Cancer Gene Ther        ISSN: 0929-1903            Impact factor:   5.987


  3 in total

1.  Resistance to cytotoxic drugs in DNA mismatch repair-deficient cells.

Authors:  S Aebi; D Fink; R Gordon; H K Kim; H Zheng; J L Fink; S B Howell
Journal:  Clin Cancer Res       Date:  1997-10       Impact factor: 12.531

2.  Identification of Key Genes and Pathways in Triple-Negative Breast Cancer by Integrated Bioinformatics Analysis.

Authors:  Pengzhi Dong; Bing Yu; Lanlan Pan; Xiaoxuan Tian; Fangfang Liu
Journal:  Biomed Res Int       Date:  2018-08-02       Impact factor: 3.411

3.  Identification of key genes as potential biomarkers for triple‑negative breast cancer using integrating genomics analysis.

Authors:  Guansheng Zhong; Weiyang Lou; Qinyan Shen; Kun Yu; Yajuan Zheng
Journal:  Mol Med Rep       Date:  2019-12-06       Impact factor: 2.952

  3 in total
  2 in total

1.  Identification and validation of a 17-gene signature to improve the survival prediction of gliomas.

Authors:  Shiao Tong; Minqi Xia; Yang Xu; Qian Sun; Liguo Ye; Jiayang Cai; Zhang Ye; Daofeng Tian
Journal:  Front Immunol       Date:  2022-09-29       Impact factor: 8.786

2.  High expression of hypoxia-inducible factor 1-alpha predicts poor prognosis in pancreatic ductal adenocarcinoma: a meta-analysis and database validation protocol.

Authors:  Alexis Zoa; Yingjie Yang; Wenjin Huang; Jing Yang; Jiangping Wang; Haibo Wang; Minghua Dong; Yuantong Tian
Journal:  Transl Cancer Res       Date:  2022-09       Impact factor: 0.496

  2 in total

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