Literature DB >> 28849078

Screening and identification of potential biomarkers in triple-negative breast cancer by integrated analysis.

Jilong Guo1, Guohua Gong1, Bin Zhang1.   

Abstract

Triple-negative breast cancer (TNBC) has attracted great attention due to its unique biology, poor prognosis, and aggressiveness. TNBC patients are more likely to suffer from metastasis. We screened and identified the TNBC-specific genes as potential biomarkers. A total of 167 breast cancer samples (45 TNBC and 122 non-TNBC) were used in the integrated analysis. Gene expression microarrays were used to screen the differentially expressed genes. We identified 65 core DEGs. According to the GO and KEGG analysis, the gene function enrichment in TNBC was revealed, such as basal cell carcinoma, prostate cancer, oocyte meiosis and choline metabolism in cancer pathways. Moreover, the PPI network reconstruction would benefit the screening of hubs. A RFS analysis of TNBC-specific genes was also conducted. RT-PCR was used to validate the expression pattern of hubs in TNBC. Finally, nine genes were identified and all of them were novel, specific and higher dysregulation expressed genes in TNBC. Such that, these genes will serve as potential biomarkers in TNBC and benefit further research in TNBC.

Entities:  

Mesh:

Substances:

Year:  2017        PMID: 28849078     DOI: 10.3892/or.2017.5911

Source DB:  PubMed          Journal:  Oncol Rep        ISSN: 1021-335X            Impact factor:   3.906


  3 in total

1.  Harnessing the Digital Exhaust: Incorporating wellness into the pharma model.

Authors:  Justin M Wright; Graham B Jones
Journal:  Digit Biomark       Date:  2018-04-11

2.  KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining.

Authors:  Jiarui Chen; Chong Liu; Jiemei Cen; Tuo Liang; Jiang Xue; Haopeng Zeng; Zide Zhang; Guoyong Xu; Chaojie Yu; Zhaojun Lu; Zequn Wang; Jie Jiang; Xinli Zhan; Jian Zeng
Journal:  Medicine (Baltimore)       Date:  2020-05       Impact factor: 1.817

3.  Constructing cancer patient-specific and group-specific gene networks with multi-omics data.

Authors:  Wook Lee; De-Shuang Huang; Kyungsook Han
Journal:  BMC Med Genomics       Date:  2020-08-27       Impact factor: 3.063

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.