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ORIGINAL RESEARCH article

Front. Genet.
Sec. Computational Genomics
Volume 15 - 2024 | doi: 10.3389/fgene.2024.1403587
This article is part of the Research Topic Computational Genomic and Precision Medicine View all articles

Prognostic Value of Four Immune-Related Genes in Lower-Grade Gliomas: A Biomarker Discovery Study

Provisionally accepted
Shuowen Wang Shuowen Wang 1Zijun Wang Zijun Wang 2Zhuo Liu Zhuo Liu 3Jianxin Wu Jianxin Wu 1*
  • 1 Beijing Tongren Hospital, Capital Medical University, Beijing, China
  • 2 Beijing Shijitan Hospital, Capital Medical University, Beijing, Beijing Municipality, China
  • 3 Capital Institute of Pediatrics, Beijing, Beijing Municipality, China

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

    The tumor microenvironment and IRGs are highly correlated with tumor occurrence, progression, and prognosis. However, their roles in grade II and III gliomas, termed LGGs in this study, remain to be fully elucidated. Our research aims to develop immune-related features for risk stratification and prognosis prediction in LGG. Here, we found that the ESTIMATE score, immune score and stromal score of high-immunity, high-grade and isocitrate dehydrogenase (IDH) wild-type glioma were higher than those of the corresponding group, and the tumor purity was lower. Higher ESTIMATE scores, stromal scores and immune scores indicated a poor prognosis in patients with LGG. We found that the patient's immune states were associated with overall survival, and we established a risk model to predict the prognosis of LGG. A total of 412 differentially expressed immune-related genes (DEIRGs) were obtained by differential analysis using LGG samples in the TCGA database and normal samples in the GTEx database. Through univariate Cox, LASSO, and multivariate Cox regression analyses, We ultimately identified four optimal prognostic DEIRGs (KLRC3, MR1, PDIA2 and RFXAP) and established a predictive model. Compared to other molecular features, our predictive model demonstrates superior accuracy. Furthermore, the prognostic value of the model was shown to be good and was verified by testing using both the Chinese Glioma Genome Atlas (CGGA) as a testing set and the entire set of TCGA and CGGA. In addition, we built a nomogram with the prognostic model and clinical variables, and it showed a better prognostic value. The current results show that the risk model of the four identified prognostic DEIRGs (PDEIRGs) is a valuable prognostic model in LGG patients. The predictive four-gene signature and the nomogram established in this study can assist personalized treatment for patients with LGG.

    Keywords: Lower-grade gliomas1, TCGA2, GTEx3, immune-related genes4, CGGA = Chinese Glioma Genome Atlas5

    Received: 19 Mar 2024; Accepted: 30 Jul 2024.

    Copyright: © 2024 Wang, Wang, Liu and Wu. 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: Jianxin Wu, Beijing Tongren Hospital, Capital Medical University, Beijing, 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.