BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

334 related articles for article (PubMed ID: 30175120)

  • 1. Identification of Key Genes and Pathways in Triple-Negative Breast Cancer by Integrated Bioinformatics Analysis.
    Dong P; Yu B; Pan L; Tian X; Liu F
    Biomed Res Int; 2018; 2018():2760918. PubMed ID: 30175120
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Identification of key genes as potential biomarkers for triple‑negative breast cancer using integrating genomics analysis.
    Zhong G; Lou W; Shen Q; Yu K; Zheng Y
    Mol Med Rep; 2020 Feb; 21(2):557-566. PubMed ID: 31974598
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Identification of differentially expressed genes between triple and non-triple-negative breast cancer using bioinformatics analysis.
    Zhai Q; Li H; Sun L; Yuan Y; Wang X
    Breast Cancer; 2019 Nov; 26(6):784-791. PubMed ID: 31197620
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Overexpression of CCNE1 confers a poorer prognosis in triple-negative breast cancer identified by bioinformatic analysis.
    Yuan Q; Zheng L; Liao Y; Wu G
    World J Surg Oncol; 2021 Mar; 19(1):86. PubMed ID: 33757543
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Identification of a five genes prognosis signature for triple-negative breast cancer using multi-omics methods and bioinformatics analysis.
    Ma J; Chen C; Liu S; Ji J; Wu D; Huang P; Wei D; Fan Z; Ren L
    Cancer Gene Ther; 2022 Nov; 29(11):1578-1589. PubMed ID: 35474355
    [TBL] [Abstract][Full Text] [Related]  

  • 6. KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining.
    Chen J; Liu C; Cen J; Liang T; Xue J; Zeng H; Zhang Z; Xu G; Yu C; Lu Z; Wang Z; Jiang J; Zhan X; Zeng J
    Medicine (Baltimore); 2020 May; 99(18):e19986. PubMed ID: 32358373
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Integrated network analysis and machine learning approach for the identification of key genes of triple-negative breast cancer.
    Naorem LD; Muthaiyan M; Venkatesan A
    J Cell Biochem; 2019 Apr; 120(4):6154-6167. PubMed ID: 30302816
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Novel biomarkers identified in triple-negative breast cancer through RNA-sequencing.
    Chen YL; Wang K; Xie F; Zhuo ZL; Liu C; Yang Y; Wang S; Zhao XT
    Clin Chim Acta; 2022 Jun; 531():302-308. PubMed ID: 35504321
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Molecular Features of Triple Negative Breast Cancer: Microarray Evidence and Further Integrated Analysis.
    He J; Yang J; Chen W; Wu H; Yuan Z; Wang K; Li G; Sun J; Yu L
    PLoS One; 2015; 10(6):e0129842. PubMed ID: 26103053
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Identification of Key Prognostic Genes of Triple Negative Breast Cancer by LASSO-Based Machine Learning and Bioinformatics Analysis.
    Chen DL; Cai JH; Wang CCN
    Genes (Basel); 2022 May; 13(5):. PubMed ID: 35627287
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Integrated bioinformatics analysis for differentially expressed genes and signaling pathways identification in gastric cancer.
    Yang C; Gong A
    Int J Med Sci; 2021; 18(3):792-800. PubMed ID: 33437215
    [No Abstract]   [Full Text] [Related]  

  • 12. Integrated analysis of differentially expressed genes and pathways in triple‑negative breast cancer.
    Peng C; Ma W; Xia W; Zheng W
    Mol Med Rep; 2017 Mar; 15(3):1087-1094. PubMed ID: 28075450
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Hsa-mir-3163 and CCNB1 may be potential biomarkers and therapeutic targets for androgen receptor positive triple-negative breast cancer.
    Qiu P; Guo Q; Yao Q; Chen J; Lin J
    PLoS One; 2021; 16(11):e0254283. PubMed ID: 34797837
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Identification of Potential Key Genes Associated With the Pathogenesis, Metastasis, and Prognosis of Triple-Negative Breast Cancer on the Basis of Integrated Bioinformatics Analysis.
    Zhao B; Xu Y; Zhao Y; Shen S; Sun Q
    Front Oncol; 2020; 10():856. PubMed ID: 32596149
    [No Abstract]   [Full Text] [Related]  

  • 15. Immunity and Extracellular Matrix Characteristics of Breast Cancer Subtypes Based on Identification by T Helper Cells Profiling.
    Zhou Y; Tian Q; Gao H; Zhu L; Zhang Y; Zhang C; Yang J; Wang B
    Front Immunol; 2022; 13():859581. PubMed ID: 35795662
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Bioinformatics Analysis Identifies IL6ST as a Potential Tumor Suppressor Gene for Triple-Negative Breast Cancer.
    Jia R; Weng Y; Li Z; Liang W; Ji Y; Liang Y; Ning P
    Reprod Sci; 2021 Aug; 28(8):2331-2341. PubMed ID: 33650093
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Investigation of Candidate Genes and Pathways in Basal/TNBC Patients by Integrated Analysis.
    Liu Q; Song X; Liu Z; Yu Z
    Technol Cancer Res Treat; 2021; 20():15330338211019506. PubMed ID: 34184566
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Bioinformatics analysis of key genes in triple negative breast cancer and validation of oncogene PLK1.
    Ren Y; Deng R; Zhang Q; Li J; Han B; Ye P
    Ann Transl Med; 2020 Dec; 8(24):1637. PubMed ID: 33490149
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Identification of key differentially expressed genes between ER-positive/HER2-negative breast cancer and ER-negative/HER2-negative breast cancer using integrated bioinformatics analysis.
    Gan S; Dai H; Li R; Liu W; Ye R; Ha Y; Di X; Hu W; Zhang Z; Sun Y
    Gland Surg; 2020 Jun; 9(3):661-675. PubMed ID: 32775256
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Identification of
    Wang F; Cao X; Yin L; Wang Q; He Z
    DNA Cell Biol; 2020 Oct; 39(10):1813-1824. PubMed ID: 32816580
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 17.