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 *

177 related articles for article (PubMed ID: 37739440)

  • 1. Machine learning-based integration develops a metabolism-derived consensus model for improving immunotherapy in pancreatic cancer.
    Guo Y; Wang R; Shi J; Yang C; Ma P; Min J; Zhao T; Hua L; Song Y; Li J; Su H
    J Immunother Cancer; 2023 Sep; 11(9):. PubMed ID: 37739440
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Machine learning-based identification of tumor-infiltrating immune cell-associated model with appealing implications in improving prognosis and immunotherapy response in bladder cancer patients.
    Chen H; Yang W; Ji Z
    Front Immunol; 2023; 14():1171420. PubMed ID: 37063886
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Immune Infiltrating Cells-Derived Risk Signature Based on Large-scale Analysis Defines Immune Landscape and Predicts Immunotherapy Responses in Glioma Tumor Microenvironment.
    Zhang N; Zhang H; Wang Z; Dai Z; Zhang X; Cheng Q; Liu Z
    Front Immunol; 2021; 12():691811. PubMed ID: 34489938
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Stemness Refines the Classification of Colorectal Cancer With Stratified Prognosis, Multi-Omics Landscape, Potential Mechanisms, and Treatment Options.
    Liu Z; Xu H; Weng S; Ren Y; Han X
    Front Immunol; 2022; 13():828330. PubMed ID: 35154148
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A cellular senescence-related classifier based on a tumorigenesis- and immune infiltration-guided strategy can predict prognosis, immunotherapy response, and candidate drugs in hepatocellular carcinoma.
    Luo Y; Liu H; Fu H; Ding GS; Teng F
    Front Immunol; 2022; 13():974377. PubMed ID: 36458010
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A 4-gene-based hypoxia signature is associated with tumor immune microenvironment and predicts the prognosis of pancreatic cancer patients.
    Ding J; He X; Cheng X; Cao G; Chen B; Chen S; Xiong M
    World J Surg Oncol; 2021 Apr; 19(1):123. PubMed ID: 33865399
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Pan-cancer analysis implicates novel insights of lactate metabolism into immunotherapy response prediction and survival prognostication.
    Chen D; Liu P; Lu X; Li J; Qi D; Zang L; Lin J; Liu Y; Zhai S; Fu D; Weng Y; Li H; Shen B
    J Exp Clin Cancer Res; 2024 Apr; 43(1):125. PubMed ID: 38664705
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Integrated machine learning identifies epithelial cell marker genes for improving outcomes and immunotherapy in prostate cancer.
    Zhu W; Zeng H; Huang J; Wu J; Wang Y; Wang Z; Wang H; Luo Y; Lai W
    J Transl Med; 2023 Nov; 21(1):782. PubMed ID: 37925432
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Characterization of stem cell landscape and identification of stemness-relevant prognostic gene signature to aid immunotherapy in colorectal cancer.
    Zheng H; Liu H; Li H; Dou W; Wang J; Zhang J; Liu T; Wu Y; Liu Y; Wang X
    Stem Cell Res Ther; 2022 Jun; 13(1):244. PubMed ID: 35681225
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Comprehensive Analysis of m6A RNA Methylation Regulators and the Immune Microenvironment to Aid Immunotherapy in Pancreatic Cancer.
    Guo Y; Wang R; Li J; Song Y; Min J; Zhao T; Hua L; Shi J; Zhang C; Ma P; Yang C; Zhu L; Gan D; Li S; Liu X; Su H
    Front Immunol; 2021; 12():769425. PubMed ID: 34804059
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Pan-cancer landscape of T-cell exhaustion heterogeneity within the tumor microenvironment revealed a progressive roadmap of hierarchical dysfunction associated with prognosis and therapeutic efficacy.
    Zhang Z; Chen L; Chen H; Zhao J; Li K; Sun J; Zhou M
    EBioMedicine; 2022 Sep; 83():104207. PubMed ID: 35961204
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comprehensive analysis of nicotinamide metabolism-related signature for predicting prognosis and immunotherapy response in breast cancer.
    Cui H; Ren X; Dai L; Chang L; Liu D; Zhai Z; Kang H; Ma X
    Front Immunol; 2023; 14():1145552. PubMed ID: 36969219
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Identification of the immune cell infiltration landscape in pancreatic cancer to assist immunotherapy.
    Wang Z; Zou W; Wang F; Zhang G; Chen K; Hu M; Liu R
    Future Oncol; 2021 Nov; 17(31):4131-4143. PubMed ID: 34346253
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Machine learning-derived identification of prognostic signature for improving prognosis and drug response in patients with ovarian cancer.
    Huan Q; Cheng S; Ma HF; Zhao M; Chen Y; Yuan X
    J Cell Mol Med; 2024 Jan; 28(1):e18021. PubMed ID: 37994489
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Leveraging Tumor Microenvironment Infiltration in Pancreatic Cancer to Identify Gene Signatures Related to Prognosis and Immunotherapy Response.
    Yang J; Zeng L; Chen R; Huang L; Wu Z; Yu M; Zhou Y; Chen R
    Cancers (Basel); 2023 Feb; 15(5):. PubMed ID: 36900234
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Novel Molecular Signature of Cancer-Associated Fibroblasts Predicts Prognosis and Immunotherapy Response in Pancreatic Cancer.
    Ge W; Yue M; Wang Y; Wang Y; Xue S; Shentu D; Mao T; Zhang X; Xu H; Li S; Ma J; Wang L; Cui J
    Int J Mol Sci; 2022 Dec; 24(1):. PubMed ID: 36613599
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Oncogenic signaling pathway-related long non-coding RNAs for predicting prognosis and immunotherapy response in breast cancer.
    Li H; Liu H; Hao Q; Liu X; Yao Y; Cao M
    Front Immunol; 2022; 13():891175. PubMed ID: 35990668
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients.
    Wang Z; Wang Y; Yang T; Xing H; Wang Y; Gao L; Guo X; Xing B; Wang Y; Ma W
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33839757
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Integrated analysis of single-cell and bulk RNA sequencing data reveals a pan-cancer stemness signature predicting immunotherapy response.
    Zhang Z; Wang ZX; Chen YX; Wu HX; Yin L; Zhao Q; Luo HY; Zeng ZL; Qiu MZ; Xu RH
    Genome Med; 2022 Apr; 14(1):45. PubMed ID: 35488273
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.