BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

191 related articles for article (PubMed ID: 38345575)

  • 1. Machine learning constructs a T cell-related signature for predicting prognosis and drug sensitivity in ovarian cancer.
    Zhang Y; Pei L
    Aging (Albany NY); 2024 Feb; 16(4):3332-3349. PubMed ID: 38345575
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning.
    Zhao B; Pei L
    BMC Med Genomics; 2023 Oct; 16(1):230. PubMed ID: 37784081
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine learning developed a CD8
    Chen R; Zheng Y; Fei C; Ye J; Fei H
    Sci Rep; 2024 Mar; 14(1):5794. PubMed ID: 38461331
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Machine learning developed a PI3K/Akt pathway-related signature for predicting prognosis and drug sensitivity in ovarian cancer.
    Han X; Yang L; Tian H; Ji Y
    Aging (Albany NY); 2023 Oct; 15(20):11162-11183. PubMed ID: 37851341
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Machine learning developed a fibroblast-related signature for predicting clinical outcome and drug sensitivity in ovarian cancer.
    Fu W; Feng Q; Tao R
    Medicine (Baltimore); 2024 Apr; 103(16):e37783. PubMed ID: 38640321
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine Learning Developed a Programmed Cell Death Signature for Predicting Prognosis, Ecosystem, and Drug Sensitivity in Ovarian Cancer.
    Wang L; Chen X; Song L; Zou H
    Anal Cell Pathol (Amst); 2023; 2023():7365503. PubMed ID: 37868825
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Machine Learning-Based Integration Develops a Macrophage-Related Index for Predicting Prognosis and Immunotherapy Response in Lung Adenocarcinoma.
    Li Z; Guo M; Lin W; Huang P
    Arch Med Res; 2023 Nov; 54(7):102897. PubMed ID: 37865004
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Identification of an Autophagy-Related Signature for Prognosis and Immunotherapy Response Prediction in Ovarian Cancer.
    Ding J; Wang C; Sun Y; Guo J; Liu S; Cheng Z
    Biomolecules; 2023 Feb; 13(2):. PubMed ID: 36830707
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Single-Cell Transcriptomic Analysis Reveals a Tumor-Reactive T Cell Signature Associated With Clinical Outcome and Immunotherapy Response In Melanoma.
    Yan M; Hu J; Ping Y; Xu L; Liao G; Jiang Z; Pang B; Sun S; Zhang Y; Xiao Y; Li X
    Front Immunol; 2021; 12():758288. PubMed ID: 34804045
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine learning-based on cytotoxic T lymphocyte evasion gene develops a novel signature to predict prognosis and immunotherapy responses for kidney renal clear cell carcinoma patients.
    Chen M; Nie Z; Huang D; Gao Y; Cao H; Zheng L; Zhang S
    Front Immunol; 2023; 14():1192428. PubMed ID: 37600786
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Suppressive stroma-immune prognostic signature impedes immunotherapy in ovarian cancer and can be reversed by PDGFRB inhibitors.
    Yang D; Duan MH; Yuan QE; Li ZL; Luo CH; Cui LY; Li LC; Xiao Y; Zhu XY; Zhang HL; Feng GK; Liu GC; Deng R; Li JD; Zhu XF
    J Transl Med; 2023 Sep; 21(1):586. PubMed ID: 37658364
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine learning-based integration develops an immune-related risk model for predicting prognosis of high-grade serous ovarian cancer and providing therapeutic strategies.
    Wu Q; Tian R; He X; Liu J; Ou C; Li Y; Fu X
    Front Immunol; 2023; 14():1164408. PubMed ID: 37090728
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Assessing of programmed cell death gene signature for predicting ovarian cancer prognosis and treatment response.
    Lian X; Liu B; Wang C; Wang S; Zhuang Y; Li X
    Front Endocrinol (Lausanne); 2023; 14():1182776. PubMed ID: 37342266
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Identifying the Role of Oxidative Stress-Related Genes as Prognostic Biomarkers and Predicting the Response of Immunotherapy and Chemotherapy in Ovarian Cancer.
    Liu Q; Yang X; Yin Y; Zhang H; Yin F; Guo P; Zhang X; Sun C; Li S; Han Y; Yang Z
    Oxid Med Cell Longev; 2022; 2022():6575534. PubMed ID: 36561981
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A T-cell-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma based on transcriptomics and single-cell sequencing.
    Chen X; Peng C; Chen Y; Ding B; Liu S; Song Y; Li Y; Sun B; Yang R
    BMC Bioinformatics; 2023 May; 24(1):216. PubMed ID: 37231356
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Developing four cuproptosis-related lncRNAs signature to predict prognosis and immune activity in ovarian cancer.
    Liu L; Wang Q; Zhou JY; Zhang B
    J Ovarian Res; 2023 Apr; 16(1):88. PubMed ID: 37122030
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A novel hypoxia- and lactate metabolism-related signature to predict prognosis and immunotherapy responses for breast cancer by integrating machine learning and bioinformatic analyses.
    Li J; Qiao H; Wu F; Sun S; Feng C; Li C; Yan W; Lv W; Wu H; Liu M; Chen X; Liu X; Wang W; Cai Y; Zhang Y; Zhou Z; Zhang Y; Zhang S
    Front Immunol; 2022; 13():998140. PubMed ID: 36275774
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Construction of ovarian metastasis-related immune signature predicting prognosis of gastric cancer patients.
    Gao J; Huo S; Zhang Y; Zhao Z; Pan H; Liu X
    Cancer Med; 2023 Jan; 12(1):913-929. PubMed ID: 35621244
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Integrated analysis of single-cell RNA-seq and bulk RNA-seq unveils heterogeneity and establishes a novel signature for prognosis and tumor immune microenvironment in ovarian cancer.
    Wang Z; Zhang J; Dai F; Li B; Cheng Y
    J Ovarian Res; 2023 Jan; 16(1):12. PubMed ID: 36642706
    [TBL] [Abstract][Full Text] [Related]  

  • 20. T-cell exhaustion signatures characterize the immune landscape and predict HCC prognosis
    Chi H; Zhao S; Yang J; Gao X; Peng G; Zhang J; Xie X; Song G; Xu K; Xia Z; Chen S; Zhao J
    Front Immunol; 2023; 14():1137025. PubMed ID: 37006257
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.