BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

193 related articles for article (PubMed ID: 37686013)

  • 1. A Risk Model for Prognosis and Treatment Response Prediction in Colon Adenocarcinoma Based on Genes Associated with the Characteristics of the Epithelial-Mesenchymal Transition.
    Huang H; Li T; Meng Z; Zhang X; Jiang S; Suo M; Li N
    Int J Mol Sci; 2023 Aug; 24(17):. PubMed ID: 37686013
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Glucose metabolism-based signature predicts prognosis and immunotherapy strategies for colon adenocarcinoma.
    Bai Z; Yan C; Nie Y; Zeng Q; Xu L; Wang S; Chang D
    J Gene Med; 2024 Jan; 26(1):e3620. PubMed ID: 37973153
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Identification of 9 Gene Signatures by WGCNA to Predict Prognosis for Colon Adenocarcinoma.
    Yang M; He H; Peng T; Lu Y; Yu J
    Comput Intell Neurosci; 2022; 2022():8598046. PubMed ID: 35392038
    [TBL] [Abstract][Full Text] [Related]  

  • 4. An epithelial-mesenchymal transition-related mRNA signature associated with the prognosis, immune infiltration and therapeutic response of colon adenocarcinoma.
    Zhang Y; Li Y; Zuo Z; Li T; An Y; Zhang W
    Pathol Oncol Res; 2023; 29():1611016. PubMed ID: 36910014
    [No Abstract]   [Full Text] [Related]  

  • 5. Transcriptomic correlates of cell cycle checkpoints with distinct prognosis, molecular characteristics, immunological regulation, and therapeutic response in colorectal adenocarcinoma.
    Wang H; Wang W; Wang Z; Li X
    Front Immunol; 2023; 14():1291859. PubMed ID: 38143740
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients.
    Zhang Z; Zheng S; Lin Y; Sun J; Ding N; Chen J; Zhong J; Shi L; Xue M
    BMC Cancer; 2020 Nov; 20(1):1135. PubMed ID: 33228590
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Identification of sixteen metabolic genes as potential biomarkers for colon adenocarcinoma.
    Zhao F; Liu Y; Gu X; Zhang B; Song C; Cui B
    J BUON; 2021; 26(4):1252-1259. PubMed ID: 34564978
    [TBL] [Abstract][Full Text] [Related]  

  • 8. In silico development and clinical validation of novel 8 gene signature based on lipid metabolism related genes in colon adenocarcinoma.
    Jiang C; Liu Y; Wen S; Xu C; Gu L
    Pharmacol Res; 2021 Jul; 169():105644. PubMed ID: 33940186
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Development of a prognostic model for personalized prediction of colon adenocarcinoma (COAD) patient outcomes using methylation-driven genes.
    Chen D; Zhang B; Kang K; Li L; Liao Y; Qing S; Di Y
    J Appl Genet; 2023 Dec; 64(4):713-721. PubMed ID: 37589877
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Developing a RiskS-core Model based on Angiogenesis-related lncRNAs for Colon Adenocarcinoma Prognostic Prediction.
    Li X; Lei J; Shi Y; Peng Z; Gong M; Shu X
    Curr Med Chem; 2023 Nov; ():. PubMed ID: 37961859
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Construction of a prognostic model based on genes associated with mitochondrial energy metabolic pathway in colon adenocarcinoma and its clinical significance.
    Zhang X; Liang C; Zhou B; Pang L
    J Mol Recognit; 2023 Aug; 36(8):e3044. PubMed ID: 37322568
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Identification of necroptosis-related genes for predicting prognosis and exploring immune infiltration landscape in colon adenocarcinoma.
    Wang Y; Lin MG; Meng L; Chen ZM; Wei ZJ; Ying SC; Xu A
    Front Oncol; 2022; 12():941156. PubMed ID: 36505813
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comprehensive analysis of the prognosis, tumor microenvironment, and immunotherapy response of SDHs in colon adenocarcinoma.
    Nan H; Guo P; Fan J; Zeng W; Hu C; Zheng C; Pan B; Cao Y; Ge Y; Xue X; Li W; Lin K
    Front Immunol; 2023; 14():1093974. PubMed ID: 36949947
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A novel enterocyte-related 4-gene signature for predicting prognosis in colon adenocarcinoma.
    Cheng X; Wei Y; Fu Y; Li J; Han L
    Front Immunol; 2022; 13():1052182. PubMed ID: 36532007
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Identification of the six-hormone secretion-related gene signature as a prognostic biomarker for colon adenocarcinoma.
    Jia X; Zhang T; Lv X; Du H; Sun Y; Guan Y
    Cancer Biomark; 2023; 38(4):523-535. PubMed ID: 38143338
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Construction and validation of a prognostic model for colon adenocarcinoma based on bile acid metabolism-related genes.
    Luo Q; Zhou P; Chang S; Huang Z; Zeng X
    Sci Rep; 2023 Aug; 13(1):12728. PubMed ID: 37543674
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identification of a Four-Gene Metabolic Signature to Evaluate the Prognosis of Colon Adenocarcinoma Patients.
    Zheng Y; Wu R; Wang X; Yin C
    Front Public Health; 2022; 10():860381. PubMed ID: 35462848
    [TBL] [Abstract][Full Text] [Related]  

  • 18. AEBP1 Is One of the Epithelial-Mesenchymal Transition Regulatory Genes in Colon Adenocarcinoma.
    Li D; Liu Z; Ding X; Qin Z
    Biomed Res Int; 2021; 2021():3108933. PubMed ID: 34938806
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A Prognostic Model for Colon Adenocarcinoma Patients Based on Ten Amino Acid Metabolism Related Genes.
    Ren Y; He S; Feng S; Yang W
    Front Public Health; 2022; 10():916364. PubMed ID: 35712285
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comprehensive
    Xu T; Xu W; Zheng Y; Li X; Cai H; Xu Z; Zou Q; Yu B
    Front Immunol; 2022; 13():931906. PubMed ID: 35958598
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.