Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas.

Journal: Cancer research and treatment
PMID:

Abstract

PURPOSE: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).

Authors

  • Yaolin Song
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Guangqi Li
    Division of Biotherapy, Cancer Center, West China Hospital and State Key Laboratory of Biotherapy, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China.
  • Zhenqi Zhang
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Yinbo Liu
    School of Sciences, Anhui Agricultural University, Hefei, 230036, Anhui, China.
  • Huiqing Jia
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Chao Zhang
    School of Information Engineering, Suqian University, Suqian, Jiangsu, China.
  • Jigang Wang
    Haihe Hospital, Tianjin University, Tianjin Institute of Respiratory Diseases, Tianjin, China.
  • Yanjiao Hu
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Fengyun Hao
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Xianglan Liu
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Yunxia Xie
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Ding Ma
    Department of Obstetrics and Gynaecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
  • Ganghua Li
    Geneplus-Shenzhen, Shenzhen, China.
  • Zaixian Tai
    Geneplus-Shenzhen, Shenzhen, China.
  • Xiaoming Xing
    Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China.