Multiomics Analysis of Disulfidptosis Patterns and Integrated Machine Learning to Predict Immunotherapy Response in Lung Adenocarcinoma.

Journal: Current medicinal chemistry
Published Date: Jan 1, 2024

Abstract

BACKGROUND: Recent studies have unveiled disulfidptosis as a phenomenon intimately associated with cellular damage, heralding new avenues for exploring tumor cell dynamics. We aimed to explore the impact of disulfide cell death on the tumor immune microenvironment and immunotherapy in lung adenocarcinoma (LUAD).

Authors

  • Junzhi Liu
    Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China; State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application, Nanjing, Jiangsu 210023, China.
  • Huimin Li
    a Department of Pharmacy , Special Drugs R&D Center of People's Armed Police Forces , Logistics University of Chinese People's Armed Police Forces , Tianjin , China.
  • Nannan Zhang
    Research Centre for Medical Robotics and Minimally Invasive Surgical Devices, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
  • Qiuping Dong
    Laboratory of Cancer Cell Biology, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
  • Zheng Liang
    Department of Otorhinolaryngology, Tianjin Medical University General Hospital, Tianjin, 300052, China.

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