Integrating multi-omics and machine learning survival frameworks to build a prognostic model based on immune function and cell death patterns in a lung adenocarcinoma cohort.

Journal: Frontiers in immunology
Published Date: Sep 13, 2024

Abstract

INTRODUCTION: The programmed cell death (PCD) plays a key role in the development and progression of lung adenocarcinoma. In addition, immune-related genes also play a crucial role in cancer progression and patient prognosis. However, further studies are needed to investigate the prognostic significance of the interaction between immune-related genes and cell death in LUAD.

Authors

  • Yiluo Xie
    Department of Clinical Medicine, Bengbu Medical University, Bengbu, China.
  • Huili Chen
    Research Center of Clinical Laboratory Science, Bengbu Medical University, Bengbu, China.
  • Mei Tian
    Huashan Hospital and Human Phenome Institute, Fudan University, Shanghai, China; tianmei@fudan.edu.cn hzhang21@zju.edu.cn.
  • Ziqang Wang
    Research Center of Clinical Laboratory Science, Bengbu Medical University, Bengbu, China.
  • Luyao Wang
    Department of Genetics, School of Life Sciences, Bengbu Medical University, Bengbu, China.
  • Jing Zhang
    MOEMIL Laboratory, School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu, China.
  • Xiaojing Wang
    Anhui Province Key Laboratory of Respiratory Tumor and Infectious Disease, First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
  • Chaoqun Lian
    Research Center of Clinical Laboratory Science, Bengbu Medical University, Bengbu, China.

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