Machine learning-based bulk RNA analysis reveals a prognostic signature of 13 cell death patterns and potential therapeutic target of SMAD3 in acute myeloid leukemia.

Abstract

Authors

• Xiebing Bao
  National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
• Yao Chen
  Department of Galactophore Surgery, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
• Jie Chang
  School of Chinese Materia Medica, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing 210023, China.
• Jiahui Du
  Jiangsu Province Engineering Research Center of Molecular Target Therapy and Companion Diagnostics in Oncology, Suzhou Vocational Health College, 28 Kehua Road, Suzhou, 215009, China.
• Chen Yang
  Department of Diagnostic Ultrasound Imaging & Interventional Therapy, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China.
• Yijie Wu
  College of Life Science, North China University of Science and Technology, Tangshan, 063210, China.
• Yu Sha
  Jiangsu Province Engineering Research Center of Molecular Target Therapy and Companion Diagnostics in Oncology, Suzhou Vocational Health College, 28 Kehua Road, Suzhou, 215009, China.
• Ming Li
  Radiology Department, Huadong Hospital, Affiliated with Fudan University, Shanghai, China.
• Suning Chen
  NHC Key Laboratory of Thrombosis and Hemostasis, National Clinical Research Center for Haematologic Diseases, Jiangsu Institute of Haematology, The First Affiliated Hospital of Soochow University, Suzhou, China.
• Minfeng Yang
  School of Public Health, Nantong University, No. 9, Seyuan Road, Nantong, 226019, China. minfeng.yang@connect.polyu.hk.
• Song-Bai Liu
  Jiangsu Province Engineering Research Center of Molecular Target Therapy and Companion Diagnostics in Oncology, Suzhou Vocational Health College, 28 Kehua Road, Suzhou, 215009, China. liusongbai@126.com.

Keywords

External Resources