Wang Tong, Sun Bohao, Yu Rui, Zhang Jing, Wu Yichen, Wang Delin, Ni Xiaoying, Wang Hao
Department of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.
Department of Pathology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Transl Cancer Res. 2025 May 30;14(5):2690-2706. doi: 10.21037/tcr-24-2045. Epub 2025 May 9.
BACKGROUND: Glioma is a prevalent and aggressive form of brain neoplasm, characterized by a 5-year survival rate of less than 10%. Despite the encouraging outcomes demonstrated by numerous prognostic models for gliomas in preliminary research, these models frequently do not meet anticipated results when subjected to external validation. Our goal is to uncover potential prognostic biomarkers and therapeutic targets by concentrating on mismatch repair-related genes (MRRGs) that are significantly linked to glioma. METHODS: We employed least absolute shrinkage and selection operator (LASSO) Cox regression to develop a multigene signature based on MRRGs. The functional implications of the gene were evaluated through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). We analyzed the correlation between gene expression and immune cell infiltration using single-sample GSEA (ssGSEA). Moreover, we undertook a comprehensive examination of the correlation between expression and several clinical parameters derived from clinical samples obtained from the TCGA database. The parameters assessed encompassed World Health Organization (WHO) grade, isocitrate dehydrogenase (IDH) wild-type status, the status of 1p/19q non-co-deletion, and patient age. Additionally, we executed a thorough prognostic evaluation of EXO1 across various subgroups defined by clinical parameters. Utilizing the "rms" R package, we constructed a nomogram model that amalgamates clinical characteristics and expression levels. Immunohistochemical techniques were utilized to assess expression in sixty glioma cases. RESULTS: A comparative analysis of the expression of 23 MRRGs between glioma and normal samples revealed that 22 MRRGs were upregulated in glioma tissues. Univariate analysis indicated that 20 of these MRRGs were significantly differentially expressed (P<0.05). The LASSO algorithm reduced this set to seven key genes: , , , , , , and . Kaplan-Meier survival analysis confirmed the association between the aberrant expression of these genes and patient survival outcomes. GO and KEGG enrichment analyses highlighted the role of in crucial biological processes and pathways, including the cell cycle and DNA repair mechanisms. Increased expression of was correlated with higher WHO grades, IDH wild type, 1p/19q non-codel, and poor prognosis. A nomogram that combines EXO1 with clinical parameters has been developed to assist in predicting the overall survival probabilities of patients at 1-year intervals. The calibration chart revealed that effectiveness of the nomogram was accurate (c-index =0.850). Immunohistochemical evaluations showed that expression levels were significantly elevated in 60 glioma tissues compared to adjacent non-tumorous tissues. CONCLUSIONS: In summary, our results indicate a marked elevation in expression levels within gliomas, which correlates strongly with clinical pathological characteristics and unfavorable prognosis. Moreover, emerges as a promising candidate biomarker and potential therapeutic target for glioma, likely playing a critical role in mediating immune infiltration within this malignancy.
背景:胶质瘤是一种常见且侵袭性强的脑肿瘤形式,其5年生存率低于10%。尽管众多胶质瘤预后模型在初步研究中显示出令人鼓舞的结果,但这些模型在进行外部验证时常常未达到预期效果。我们的目标是通过关注与胶质瘤显著相关的错配修复相关基因(MRRGs)来发现潜在的预后生物标志物和治疗靶点。 方法:我们采用最小绝对收缩和选择算子(LASSO)Cox回归基于MRRGs开发了一个多基因特征。通过基因本体论(GO)、京都基因与基因组百科全书(KEGG)和基因集富集分析(GSEA)评估该基因的功能意义。我们使用单样本GSEA(ssGSEA)分析基因表达与免疫细胞浸润之间的相关性。此外,我们全面检查了从TCGA数据库获得的临床样本中该基因表达与几个临床参数之间的相关性。评估的参数包括世界卫生组织(WHO)分级、异柠檬酸脱氢酶(IDH)野生型状态、1p/19q非共缺失状态和患者年龄。此外,我们对EXO1在由临床参数定义的各个亚组中进行了全面的预后评估。利用“rms”R包,我们构建了一个整合临床特征和EXO1表达水平的列线图模型。采用免疫组织化学技术评估60例胶质瘤病例中的EXO1表达。 结果:胶质瘤与正常样本之间23个MRRGs表达的比较分析显示,22个MRRGs在胶质瘤组织中上调。单因素分析表明,其中20个MRRGs有显著差异表达(P<0.05)。LASSO算法将这一组基因减少到7个关键基因: 、 、 、 、 、 和 。Kaplan-Meier生存分析证实这些基因的异常表达与患者生存结果之间的关联。GO和KEGG富集分析突出了EXO1在关键生物学过程和途径中的作用,包括细胞周期和DNA修复机制。EXO1表达增加与更高的WHO分级、IDH野生型、1p/19q非共缺失以及不良预后相关。已经开发了一个将EXO1与临床参数相结合的列线图,以帮助预测患者每隔1年的总生存概率。校准图显示列线图的有效性是准确的(c指数=0.850)。免疫组织化学评估显示,与相邻非肿瘤组织相比,60例胶质瘤组织中EXO1表达水平显著升高。 结论:总之,我们的结果表明胶质瘤中EXO1表达水平显著升高,这与临床病理特征和不良预后密切相关。此外,EXO1成为胶质瘤一个有前景的候选生物标志物和潜在治疗靶点,可能在介导这种恶性肿瘤内的免疫浸润中起关键作用。
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