Volume 28, Issue 1 (Iran South Med J 2025)
Iran South Med J 2025, 28(1): 473-490 |
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Bazi Z, Aalikhani M. Bioinformatics Analysis of Glioma Neoantigens: Identifying Novel Targets for Immunotherapy. Iran South Med J 2025; 28 (1) :473-490
URL: http://ismj.bpums.ac.ir/article-1-2224-en.html
URL: http://ismj.bpums.ac.ir/article-1-2224-en.html
1- Department of Medical Biotechnology, School of Advanced Medical Technologies, Golestan University of Medical Sciences, Gorgan, Iran
Cancer Research Center, Golestan University of Medical Sciences, Gorgan, Iran
2- Department of Medical Biotechnology, School of Paramedicine, Bushehr University of Medical Sciences, Bushehr, Iran ,aalikhanip@gmail.com
Cancer Research Center, Golestan University of Medical Sciences, Gorgan, Iran
2- Department of Medical Biotechnology, School of Paramedicine, Bushehr University of Medical Sciences, Bushehr, Iran ,
Abstract: (15 Views)
Background: Glioma is one of the most prevalent and aggressive brain cancers, and its treatment poses significant challenges due to tumor heterogeneity and therapeutic resistance. Neoantigens, tumor-specific antigens arising from genetic mutations, have been recognized as promising targets for immunotherapy. This study employs advanced bioinformatics tools to identify potential neoantigens for the prospective treatment of glioma.
Materials and Methods: Gene expression data for high- and low-grade gliomas were extracted from the GEPIA2 database, followed by the identification of significantly upregulated genes in glioma patients. Through analysis of cellular localization, reported mutations, and transcript/protein expression levels using specialized bioinformatics and cancer-related databases, candidate genes for glioma immunotherapy were selected as potential neoantigens. Additionally, their association with glioma subtypes and patient survival was examined.
Results: Four genes, including SERPINA3, C3, TNC, and ITGB2 were identified as novel potential neoantigens. These genes exhibit high expression levels and multiple mutations, demonstrating a direct correlation with patient survival and tumor progression. Moreover, their expression is elevated in aggressive glioma subtypes, influencing immune evasion and cellular migration.
Conclusion: The findings of this study introduce new targets for glioma immunotherapy. Among them, SERPINA3, due to its high expression, extensive mutations, and significant impact on patient survival, may serve as a primary focus for future immunotherapeutic studies. Further experimental validation and neoantigen-based therapeutic designs will constitute the next steps in this investigation.
Materials and Methods: Gene expression data for high- and low-grade gliomas were extracted from the GEPIA2 database, followed by the identification of significantly upregulated genes in glioma patients. Through analysis of cellular localization, reported mutations, and transcript/protein expression levels using specialized bioinformatics and cancer-related databases, candidate genes for glioma immunotherapy were selected as potential neoantigens. Additionally, their association with glioma subtypes and patient survival was examined.
Results: Four genes, including SERPINA3, C3, TNC, and ITGB2 were identified as novel potential neoantigens. These genes exhibit high expression levels and multiple mutations, demonstrating a direct correlation with patient survival and tumor progression. Moreover, their expression is elevated in aggressive glioma subtypes, influencing immune evasion and cellular migration.
Conclusion: The findings of this study introduce new targets for glioma immunotherapy. Among them, SERPINA3, due to its high expression, extensive mutations, and significant impact on patient survival, may serve as a primary focus for future immunotherapeutic studies. Further experimental validation and neoantigen-based therapeutic designs will constitute the next steps in this investigation.
Type of Study: Original |
Subject:
Blood and cancer
Received: 2025/05/10 | Accepted: 2025/08/10 | Published: 2025/10/19
Received: 2025/05/10 | Accepted: 2025/08/10 | Published: 2025/10/19
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