Construction and validation of a prognostic model for glioma: an analysis based on mismatch repair-related genes and their correlation with clinicopathological features.

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.