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ORIGINAL RESEARCH article

Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Volume 15 - 2024 | doi: 10.3389/fimmu.2024.1475206
This article is part of the Research Topic Unveiling Biomarkers and Mechanisms in the Tumor-Immune Nexus View all 19 articles

Machine learning-based discovery of UPP1 as a key oncogene in tumorigenesis and immune escape in gliomas

Provisionally accepted
Zigui Chen Zigui Chen 1Chao Liu Chao Liu 2*Chunyuan Zhang Chunyuan Zhang 3,4*Ying Xia Ying Xia 1Jun Peng Jun Peng 1*Changfeng Miao Changfeng Miao 5*Qisheng Luo Qisheng Luo 3,4
  • 1 Department of Neurosurgery, Haikou Affiliated Hospital of Central South University Xiangya School of Medicine , Haikou, China, Haikou,, Hainan, China
  • 2 Department of Neurosurgery, Central Hospital of Zhuzhou, Zhuzhou, China
  • 3 Department of Neurosurgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
  • 4 Guangxi Engineering Research Center for Biomaterials in Bone and Joint Degenerative Diseases, Baise, Guangxi, China
  • 5 Department of Neurosurgery Second Branche, Hunan Provincial People’s Hospital (The First affiliated Hospital of Hunan Normal University), Changsha, Anhui Province, China

The final, formatted version of the article will be published soon.

    Gliomas are the most common and aggressive type of primary brain tumor, with a poor prognosis despite current treatment approaches. Understanding the molecular mechanisms underlying glioma development and progression is critical for improving therapies and patient outcomes. The current study comprehensively analyzed large-scale single-cell RNA sequencing and bulk RNA sequencing of glioma samples. By utilizing a series of advanced computational methods, this integrative approach identified the gene UPP1 (Uridine Phosphorylase 1) as a novel driver of glioma tumorigenesis and immune evasion. High levels of UPP1 were linked to poor survival rates in patients. Functional experiments demonstrated that UPP1 promotes tumor cell proliferation and invasion and suppresses anti-tumor immune responses. Moreover, UPP1 was found to be an effective predictor of mutation patterns, drug response, immunotherapy effectiveness, and immune characteristics. These findings highlight the power of combining microscopic and macroscopic data from over 3,000 samples, along with diverse machine learning methods, to identify valuable clinical markers involved in glioma pathogenesis. Identifying UPP1 as a tumor growth and immune escape driver may be a promising therapeutic target for this devastating disease.

    Keywords: UPP1, Glioma, Immunotherapy, machine learning, single-cell sequencing

    Received: 03 Aug 2024; Accepted: 30 Aug 2024.

    Copyright: © 2024 Chen, Liu, Zhang, Xia, Peng, Miao and Luo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Chao Liu, Department of Neurosurgery, Central Hospital of Zhuzhou, Zhuzhou, China
    Chunyuan Zhang, Department of Neurosurgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, 533000, China
    Jun Peng, Department of Neurosurgery, Haikou Affiliated Hospital of Central South University Xiangya School of Medicine , Haikou, China, Haikou,, Hainan, China
    Changfeng Miao, Department of Neurosurgery Second Branche, Hunan Provincial People’s Hospital (The First affiliated Hospital of Hunan Normal University), Changsha, Anhui Province, China

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