BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

575 related articles for article (PubMed ID: 31974598)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 4. Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers.
    Liu Y; Teng L; Fu S; Wang G; Li Z; Ding C; Wang H; Bi L
    BMC Cancer; 2021 May; 21(1):644. PubMed ID: 34053447
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 7. 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]  

  • 8. 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]  

  • 9. Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer.
    Hu Y; Zou D
    PLoS One; 2021; 16(12):e0260811. PubMed ID: 34965257
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. 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]  

  • 12. Comprehensive analysis of novel three-long noncoding RNA signatures as a diagnostic and prognostic biomarkers of human triple-negative breast cancer.
    Fan CN; Ma L; Liu N
    J Cell Biochem; 2019 Mar; 120(3):3185-3196. PubMed ID: 30203490
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Identification of tRNA-derived small noncoding RNAs as potential biomarkers for prediction of recurrence in triple-negative breast cancer.
    Feng W; Li Y; Chu J; Li J; Zhang Y; Ding X; Fu Z; Li W; Huang X; Yin Y
    Cancer Med; 2018 Oct; 7(10):5130-5144. PubMed ID: 30239174
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. 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]  

  • 16. Identification of dysregulated miRNAs in triple negative breast cancer: A meta-analysis approach.
    Naorem LD; Muthaiyan M; Venkatesan A
    J Cell Physiol; 2019 Jul; 234(7):11768-11779. PubMed ID: 30488443
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identification of FOXM1 as a specific marker for triple‑negative breast cancer.
    Tan Y; Wang Q; Xie Y; Qiao X; Zhang S; Wang Y; Yang Y; Zhang B
    Int J Oncol; 2019 Jan; 54(1):87-97. PubMed ID: 30365046
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. A ten N6-methyladenosine-related long non-coding RNAs signature predicts prognosis of triple-negative breast cancer.
    Wu J; Cai Y; Zhao G; Li M
    J Clin Lab Anal; 2021 Jun; 35(6):e23779. PubMed ID: 33934391
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Identification of latent biomarkers in connection with progression and prognosis in oral cancer by comprehensive bioinformatics analysis.
    Reyimu A; Chen Y; Song X; Zhou W; Dai J; Jiang F
    World J Surg Oncol; 2021 Aug; 19(1):240. PubMed ID: 34384424
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 29.