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 *

213 related articles for article (PubMed ID: 38615305)

  • 1. Exploring a specialized programmed-cell death patterns to predict the prognosis and sensitivity of immunotherapy in cutaneous melanoma via machine learning.
    Xiao L; He R; Hu K; Song G; Han S; Lin J; Chen Y; Zhang D; Wang W; Peng Y; Zhang J; Yu P
    Apoptosis; 2024 Aug; 29(7-8):1070-1089. PubMed ID: 38615305
    [TBL] [Abstract][Full Text] [Related]  

  • 2. RNA M6A modification shaping cutaneous melanoma tumor microenvironment and predicting immunotherapy response.
    Wu Y; He H; Zheng K; Qin Z; Cai N; Zuo S; Zhu X
    Pigment Cell Melanoma Res; 2024 Jul; 37(4):496-509. PubMed ID: 38624045
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Characteristics and significance of programmed cell death-related gene expression signature in skin cutaneous melanoma.
    Wu X; Chen S; Ji Q; Chen H; Chen X
    Skin Res Technol; 2024 May; 30(5):e13739. PubMed ID: 38766879
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Based on scRNA-seq and bulk RNA-seq to establish tumor immune microenvironment-associated signature of skin melanoma and predict immunotherapy response.
    Li S; Zhao J; Wang G; Yao Q; Leng Z; Liu Q; Jiang J; Wang W
    Arch Dermatol Res; 2024 May; 316(6):262. PubMed ID: 38795156
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma.
    Deng Z; Liu J; Yu YV; Jin YN
    Front Immunol; 2024; 15():1451103. PubMed ID: 39355255
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Development of a biomarker signature associated with anoikis to predict prognosis and immunotherapy response in melanoma.
    Wu Z; Zhang R; Bao J; Yin M; Wang X
    Arch Dermatol Res; 2024 May; 316(6):219. PubMed ID: 38787413
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in skin cutaneous melanoma.
    Zhang W; Wang S
    Melanoma Res; 2024 Jun; 34(3):215-224. PubMed ID: 38364052
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Identification of novel disulfidptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of skin cutaneous melanoma patients.
    Cheng S; Wang X; Yang S; Liang J; Song C; Zhu Q; Chen W; Ren Z; Zhu F
    Skin Res Technol; 2024 Jul; 30(7):e13814. PubMed ID: 38924611
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Experimentally validated oxidative stress -associated prognostic signatures describe the immune landscape and predict the drug response and prognosis of SKCM.
    Rong D; Su Y; Jia D; Zeng Z; Yang Y; Wei D; Lu H; Cao Y
    Front Immunol; 2024; 15():1387316. PubMed ID: 38660305
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Development and validation of an immune gene set-based prognostic signature in cutaneous melanoma.
    Tian Q; Gao H; Zhao W; Zhou Y; Yang J
    Future Oncol; 2021 Nov; 17(31):4115-4129. PubMed ID: 34291650
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Programmed Cell Death-Related Gene Signature Associated with Prognosis and Immune Infiltration and the Roles of HMOX1 in the Proliferation and Apoptosis were Investigated in Uveal Melanoma.
    Zhao Y; Wang L; Li X; Jiang J; Ma Y; Guo S; Zhou J; Li Y
    Genes Genomics; 2024 Jul; 46(7):785-801. PubMed ID: 38767825
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Characterization of prognostic signature related with twelve types of programmed cell death in lung squamous cell carcinoma.
    Li S; Ding B; Weng D
    J Cardiothorac Surg; 2024 Oct; 19(1):569. PubMed ID: 39354528
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Leveraging single-cell sequencing analysis and bulk-RNA sequencing analysis to forecast necroptosis in cutaneous melanoma prognosis.
    Xie J; Zhang P; Tang Q; Ma C; Li M; Qi M
    Exp Dermatol; 2024 Jul; 33(7):e15148. PubMed ID: 39051739
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Integrative lactylation and tumor microenvironment signature as prognostic and therapeutic biomarkers in skin cutaneous melanoma.
    Zhu Y; Song B; Yang Z; Peng Y; Cui Z; Chen L; Song B
    J Cancer Res Clin Oncol; 2023 Dec; 149(20):17897-17919. PubMed ID: 37955686
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Development of an IFNγ response-related signature for predicting the survival of cutaneous melanoma.
    Hu B; Wei Q; Li X; Ju M; Wang L; Zhou C; Chen L; Li Z; Wei M; He M; Zhao L
    Cancer Med; 2020 Nov; 9(21):8186-8201. PubMed ID: 32902917
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Leveraging a disulfidptosis-related signature to predict the prognosis and immunotherapy effectiveness of cutaneous melanoma based on machine learning.
    Zhao Y; Wei Y; Fan L; Nie Y; Li J; Zeng R; Li J; Zhan X; Lei L; Kang Z; Li J; Zhang W; Yang Z
    Mol Med; 2023 Oct; 29(1):145. PubMed ID: 37884883
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Machine learning-derived immunosenescence index for predicting outcome and drug sensitivity in patients with skin cutaneous melanoma.
    Zhu L; Zhang L; Qi J; Ye Z; Nie G; Leng S
    Genes Immun; 2024 Jun; 25(3):219-231. PubMed ID: 38811681
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comprehensive analysis of single cell and bulk RNA sequencing reveals the heterogeneity of melanoma tumor microenvironment and predicts the response of immunotherapy.
    Zhang Y; Zhang C; He J; Lai G; Li W; Zeng H; Zhong X; Xie B
    Inflamm Res; 2024 Aug; 73(8):1393-1409. PubMed ID: 38896289
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Multi
    Wu M; Li K; Liao Y; Li L; Xiao X; Chen Y; Guo J; Hu F; Qu J; Wang Z; Feng H
    Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2024 Feb; 49(2):159-174. PubMed ID: 38755712
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Unravelling tumour cell diversity and prognostic signatures in cutaneous melanoma through machine learning analysis.
    Cheng W; Ni P; Wu H; Miao X; Zhao X; Yan D
    J Cell Mol Med; 2024 Jul; 28(14):e18570. PubMed ID: 39054572
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.