Comprehensive Characterization of the Immune Microenvironment Based on Nested Resampling Machine Learning Framework Identifies TRAF3 Interacting Protein 3 as a Promising Regulator to Improve the Resistance to Immunotherapy in Glioma.

Journal: Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Published Date: Jul 26, 2025

Abstract

Diffuse glioma, the most prevalent and malignant intracranial tumor, presents a formidable challenge due to its immunosuppressive microenvironment, which complicates conventional therapeutic approaches. This study conducted a comprehensive prognostic meta-analysis involving 2,968 patients with diffuse glioma and established a comprehensive machine learning framework with nested resampling of 18 machine learning algorithms, and developed the Immune Glioma Survival Signature (IGLoS). This signature, comprising CCL19, ICOSLG, IL11, PTGES, TNFAIP3, and TRAF3IP3, has been demonstrated to predict survival outcomes across a range of cancers and to correlate with tumor progression at the level of multi-omics. It is noteworthy that the IGLoS score enables precise patient stratification for personalized cancer treatments and elucidates pivotal resistance mechanisms to immunotherapy. Furthermore, siRNA screening has underscored the critical role of TRAF3IP3 in modulating PDL1 expression and immune pathways, with implications on the ERK pathway and NFATC2 involvement. Through single-cell analysis of published and in-house datasets, TRAF3IP3 exhibited selective enrichment in NPC-like and MES-like tumor cells, and showed a dual functionality in mediating T-Cell Exhaustion. Targeting TRAF3IP3 emerges as a promising avenue to combat immunotherapy resistance, particularly in glioma, thus paving the way for precision medicine.

Authors

  • Yanbo Yang
    Department of Neurosurgery, China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100000, China.
  • Fei Wang
    Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States.
  • Yulian Zhang
    Shaanxi Provincial Clinical Research Center for Geriatric Medicine, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China.
  • Run Huang
    Suzhou Medical College of Soochow University, Suzhou, Jiangsu, 215127, China.
  • Chuanpeng Zhang
    Department of Neurosurgery, Peking University China-Japan Friendship School of Clinical Medicine, Beijing, 100000, China.
  • Lu Zhao
    Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.
  • Hanhan Dang
    Department of Neurosurgery, China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100000, China.
  • Xinyu Tao
    State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, 650201, China.
  • Yue Lu
    Department of Gastroenterology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
  • Dengfeng Lu
    Department of Neurosurgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China.
  • Yunsheng Zhang
    Department of Neurosurgery, China-Japan Friendship Hospital, Beijing, 100000, China.
  • Kun He
    1 Department of Hepatobiliary Surgery, The Second Affiliated Hospital of Chongqing Medical University , Chongqing, China .
  • Jiancong Weng
    Department of Neurosurgery, China-Japan Friendship Hospital, Beijing, 100000, China.
  • Zhouqing Chen
    Department of Neurosurgery & Brain and Nerve Research Laboratory, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province 215006, China. Electronic address: zqchen6@163.com.
  • Zhong Wang
    Department of Intensive Care Unit, The First Hospital of China Medical University, Shenyang, Liaoning, China.
  • Yanbing Yu
    Department of Neurosurgery, China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100000, China.

Keywords

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