METnet: A novel deep learning model predicting MET dysregulation in non-small-cell lung cancer on computed tomography images.

Journal: Computers in biology and medicine
Published Date: Feb 13, 2024

Abstract

BACKGROUND: Mesenchymal epithelial transformation (MET) is a key molecular target for diagnosis and treatment of non-small cell lung cancer (NSCLC). The corresponding molecularly targeted therapeutics have been approved by Food and Drug Administration (FDA), achieving promising results. However, current detection of MET dysregulation requires biopsy and gene sequencing, which is invasive, time-consuming and difficult to obtain tumor samples.

Authors

  • Yige Sun
    Department of Radiology, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, 150010, Heilongjiang, P.R. China; Genomics Research Center (Key Laboratory of Gut Microbiota and Pharmacogenomics of Heilongjiang Province, State-Province Key Laboratory of Biomedicine-Pharmaceutics of China), College of Pharmacy, Harbin Medical University, Harbin, 150081, China.
  • Jirui Guo
    Department of Colorectal SurgeryThe Sixth Affiliated Hospital, Sun Yat-sen University Guangzhou 510655 China.
  • Yang Liu
    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
  • Nan Wang
    Department of Gastroenterology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
  • Yanwei Xu
    Beidahuang Group Neuropsychiatric Hospital, Jiamusi, 154000, China.
  • Fei Wu
    Zhejiang University, 38 Zheda Road, Hangzhou 310058, Zhejiang, China.
  • Jianxin Xiao
    Department of Radiology, Harbin Medical University Cancer Hospital, 150 Haping Road, Harbin, 150010, Heilongjiang, P.R. China.
  • Yingpu Li
    Department of Oncological Surgery, Harbin Medical University Cancer Hospital, Harbin, 150000, Heilongjiang Province, China. liyingpu@hrbmu.edu.cn.
  • Xinxin Wang
    School of Science, Tianjin University of Commerce, Tianjin 300134, China.
  • Yang Hu
    Kweichow Moutai Co., Ltd, Renhuai, Guizhou 564501, China.
  • Yang Zhou
    State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou, China.

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