AUTHOR=Chen Zigui , Liu Chao , Zhang Chunyuan , Xia Ying , Peng Jun , Miao Changfeng , Luo Qisheng 

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

JOURNAL=Frontiers in Immunology

VOLUME=Volume 15 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1475206

DOI=10.3389/fimmu.2024.1475206

ISSN=1664-3224

ABSTRACT=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.