Integrating machine learning models with multi-omics analysis to decipher the prognostic significance of mitotic catastrophe heterogeneity in bladder cancer.

Journal: Biology direct
PMID:

Abstract

BACKGROUND: Mitotic catastrophe is well-known as a major pathway of endogenous tumor death, but the prognostic significance of its heterogeneity regarding bladder cancer (BLCA) remains unclear.

Authors

  • Haojie Dai
    Liyang Branch of the First Affiliated Hospital of Nanjing Medical University, The Affliated Liyang People's Hospital of Kangda College of Nanjing Medical University, Changzhou, Jiangsu, China.
  • Zijie Yu
    Liyang Branch of the First Affiliated Hospital of Nanjing Medical University, The Affliated Liyang People's Hospital of Kangda College of Nanjing Medical University, Changzhou, Jiangsu, China.
  • You Zhao
    National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology (Chongqing), College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China; Key laboratory of Machine Perception and Children's Intelligence Development, Chongqing University of Education, Chongqing, 400067, China. Electronic address: Zhaoyou1991sdtz@163.com.
  • Ke Jiang
    Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Key Laboratory for MRI, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.
  • Zhenyu Hang
    Liyang Branch of the First Affiliated Hospital of Nanjing Medical University, The Affliated Liyang People's Hospital of Kangda College of Nanjing Medical University, Changzhou, Jiangsu, China.
  • Xin Huang
    Department of ophthalmology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
  • Hongxiang Ma
    Liyang Branch of the First Affiliated Hospital of Nanjing Medical University, The Affliated Liyang People's Hospital of Kangda College of Nanjing Medical University, Changzhou, Jiangsu, China.
  • Li Wang
    College of Marine Electrical Engineering, Dalian Maritime University, Dalian, China.
  • Zihao Li
    School of Mechanical Engineering and Automation, Harbin Institute of Technology(Shenzhen), Shenzhen, 518055, China.
  • Ming Wu
    Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL 60611, USA; Department of Physical Medicine & Rehabilitation, Northwestern University Medical School, Chicago, IL 60611, USA. Electronic address: w-ming@northwestern.edu.
  • Jun Fan
    Department of Pathology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Weiping Luo
    Liyang Branch of the First Affiliated Hospital of Nanjing Medical University, The Affliated Liyang People's Hospital of Kangda College of Nanjing Medical University, Changzhou, Jiangsu, China.
  • Chao Qin
    Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Weiwen Zhou
    Guangdong Medical University, Zhanjiang, PR China.
  • Jun Nie
    Liyang Branch of the First Affiliated Hospital of Nanjing Medical University, The Affliated Liyang People's Hospital of Kangda College of Nanjing Medical University, Changzhou, Jiangsu, China. Niejun_uro@163.com.