Integration of graph neural networks and transcriptomics analysis identify key pathways and gene signature for immunotherapy response and prognosis of skin melanoma.

Journal: BMC cancer
PMID: 40205338

Abstract

OBJECTIVE: The assessment of immunotherapy plays a pivotal role in the clinical management of skin melanoma. Graph neural networks (GNNs), alongside other deep learning algorithms and bioinformatics approaches, have demonstrated substantial promise in advancing cancer diagnosis and treatment strategies.

Authors

  • Maodong Ye
    Medical Cosmetic Center, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, People's Republic of China. 624683069@qq.com.
  • Shuai Ren
    Department of Orthopedics, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150001 Heilongjiang, China.
  • Huanjuan Luo
    Shantou University Medical College, Shantou, Guangdong, 515041, P.R. China.
  • Xiumin Wu
    Shantou University Medical College, Shantou, Guangdong, 515041, P.R. China.
  • Hongwei Lian
    Shantou University Medical College, Shantou, Guangdong, 515041, P.R. China.
  • Xiangna Cai
    Medical Cosmetic Center, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, People's Republic of China.
  • Yingchang Ji
    Medical Cosmetic Center, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, P.R. China. jiyingchang@126.com.

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