These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

387 related articles for article (PubMed ID: 32358373)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 4. 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]  

  • 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. 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]  

  • 7. 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]  

  • 8. Upregulated cyclins may be novel genes for triple-negative breast cancer based on bioinformatic analysis.
    Lu Y; Yang G; Xiao Y; Zhang T; Su F; Chang R; Ling X; Bai Y
    Breast Cancer; 2020 Sep; 27(5):903-911. PubMed ID: 32338339
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Identification of potential core genes in triple negative breast cancer using bioinformatics analysis.
    Li MX; Jin LT; Wang TJ; Feng YJ; Pan CP; Zhao DM; Shao J
    Onco Targets Ther; 2018; 11():4105-4112. PubMed ID: 30140156
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Bioinformatics Analysis of Candidate Genes and Pathways Related to Hepatocellular Carcinoma in China: A Study Based on Public Databases.
    Zhang P; Feng J; Wu X; Chu W; Zhang Y; Li P
    Pathol Oncol Res; 2021; 27():588532. PubMed ID: 34257537
    [No Abstract]   [Full Text] [Related]  

  • 11. Identification of differentially expressed genes regulated by molecular signature in breast cancer-associated fibroblasts by bioinformatics analysis.
    Vastrad B; Vastrad C; Tengli A; Iliger S
    Arch Gynecol Obstet; 2018 Jan; 297(1):161-183. PubMed ID: 29063236
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Analysis of genes associated with prognosis of lung adenocarcinoma based on GEO and TCGA databases.
    Yu Y; Tian X
    Medicine (Baltimore); 2020 May; 99(19):e20183. PubMed ID: 32384511
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Identification of CXCR4 and CXCL10 as Potential Predictive Biomarkers in Triple Negative Breast Cancer (TNBC).
    Chuan T; Li T; Yi C
    Med Sci Monit; 2020 Jan; 26():e918281. PubMed ID: 31924747
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Identification of core genes and potential molecular mechanisms in breast cancer using bioinformatics analysis.
    Liu F; Wu Y; Mi Y; Gu L; Sang M; Geng C
    Pathol Res Pract; 2019 Jul; 215(7):152436. PubMed ID: 31076281
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Bioinformatics analyses of gene expression profile identify key genes and functional pathways involved in cutaneous lupus erythematosus.
    Gao ZY; Su LC; Wu QC; Sheng JE; Wang YL; Dai YF; Chen AP; He SS; Huang X; Yan GQ
    Clin Rheumatol; 2022 Feb; 41(2):437-452. PubMed ID: 34553293
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Screening and identification of key genes and pathways in metastatic uveal melanoma based on gene expression using bioinformatic analysis.
    Xie J; Wu Z; Xu X; Liang G; Xu J
    Medicine (Baltimore); 2020 Oct; 99(43):e22974. PubMed ID: 33120861
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Common gene signatures and key pathways in hypopharyngeal and esophageal squamous cell carcinoma: Evidence from bioinformatic analysis.
    Zhou R; Liu D; Zhu J; Zhang T
    Medicine (Baltimore); 2020 Oct; 99(42):e22434. PubMed ID: 33080677
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Screening Hub Genes as Prognostic Biomarkers of Hepatocellular Carcinoma by Bioinformatics Analysis.
    Zhou Z; Li Y; Hao H; Wang Y; Zhou Z; Wang Z; Chu X
    Cell Transplant; 2019 Dec; 28(1_suppl):76S-86S. PubMed ID: 31822116
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Identification of Hub Genes and Pathways of Triple Negative Breast Cancer by Expression Profiles Analysis.
    Li L; Huang H; Zhu M; Wu J
    Cancer Manag Res; 2021; 13():2095-2104. PubMed ID: 33688252
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 20.