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ORIGINAL RESEARCH article
Front. Immunol.
Sec. Inflammation
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1562070
This article is part of the Research Topic Role of bioinformatics and AI in understanding inflammation and immune microenvironment dynamics View all 6 articles
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BackgroundThe tumor microenvironment plays a crucial role in the progression of both glioma and glioma-induced autoimmune encephalitis. However, there remains a significant lack of effective therapeutic targets for these diseases.MethodWe collected 54 CT images of glioma patients and 54 glioma-induced autoimmune encephalitis patients,respectively.Radiomics features were extracted from tumors and encephalitis regions using Python, followed by dimensionality reduction via random forest and lasso regression, and construction of radiomics-based risk scores. Genomic data matched with clinical information were analyzed to identify key prognostic genes significantly associated with risk scores. Gene expression was validated by immunohistochemistry using our clinical samples. Immune infiltration was evaluated using five algorithms (MCP-counter, EPIC, TIMER, QUANT and IPS). The association between hub genes and immune checkpoint markers as well as immunoregulation-related genes was also analyzed using Spearman correlation.ResultsWe identified 980 radiomics features both in glioma and encephalitis patient images and selected four key features through lasso regression to build a radiomics-based risk score. COL22A1 was strongly correlated with the risk score and identified as the hub prognostic gene. COL22A1 expression was higher in glioblastoma tissues and cell lines, and correlated with clinical factors such as higher age, WHO grade, and IDH mutation status. Immune infiltration analysis indicated associations with diverse immune and stromal cell populations, including CD8⁺T cells, macrophages, and CAFs. COL22A1 was also positively correlated with immune checkpoints and immune-regulated genes.ConclusionOur study highlights the critical role of COL22A1 in gliomas and glioma-Induced Autoimmune Encephalitis, demonstrating its strong association with poor prognosis and its significant involvement in tumor immune regulation.
Keywords: artificial intelligence, Tumor Microenvironment, COL22A1, autoimmune encephalitis, Radiomics
Received: 16 Jan 2025; Accepted: 17 Feb 2025.
Copyright: © 2025 Yan, Chen, Wang, Ding, Qu, Du, Shi, Kahlert and Yu. 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:
Wenjie Shi, Otto von Guericke University Magdeburg, Magdeburg, Germany
Ulf Kahlert, Otto von Guericke University Magdeburg, Magdeburg, Germany
Zhengquan Yu, Soochow University, Suzhou, 215000, Jiangsu Province, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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