Abstract
Background: Although low-grade glioma (LGG) has a good prognosis, it is prone to malignant transformation into high-grade glioma. It has been confirmed that the characteristics of inflammatory factors and immune microenvironment are closely related to the occurrence and development of tumors. It is necessary to clarify the role of inflammatory genes and immune infiltration in LGG. Methods: We downloaded the transcriptome gene expression data and corresponding clinical data of LGG patients from the TCGA and GTEX databases to screen prognosis-related differentially expressed inflammatory genes with the difference analysis and single-factor Cox regression analysis. The prognostic risk model was constructed by LASSO Cox regression analysis, which enables us to compare the overall survival rate of high- and low-risk groups in the model by Kaplan–Meier analysis and subsequently draw the risk curve and survival status diagram. We analyzed the accuracy of the prediction model via ROC curves and performed GSEA enrichment analysis. The ssGSEA algorithm was used to calculate the score of immune cell infiltration and the activity of immune-related pathways. The CellMiner database was used to study drug sensitivity. Results: In this study, 3 genes (CALCRL, MMP14, and SELL) were selected from 9 prognosis-related differential inflammation genes through LASSO Cox regression analysis to construct a prognostic risk model. Further analysis showed that the risk score was negatively correlated with the prognosis, and the ROC curve showed that the accuracy of the model was better. The age, grade, and risk score can be used as independent prognostic factors (p < 0.001). GSEA analysis confirmed that 6 immune-related pathways were enriched in the high-risk group. We found that the degree of infiltration of 12 immune cell subpopulations and the scores of 13 immune functions and pathways in the high-risk group were significantly increased by applying the ssGSEA method (p < 0.05). Finally, we explored the relationship between the genes in the model and the susceptibility of drugs. Conclusion: This study analyzed the correlation between the inflammation-related risk model and the immune microenvironment. It is expected to provide a reference for the screening of LGG prognostic markers and the evaluation of immune response.
Highlights
Glioma is the most common primary malignant tumor of the central nervous system, and its rate of fatality and disability are both high (Lapointe et al, 2018; Ferlay et al, 2019)
Our research has discovered that some inflammationrelated genes may act as early warning markers and were considered to be related to the poor prognosis of low-grade glioma (LGG), and we clarified its relevance to the immune microenvironment, which may provide an important basis for the evaluation of the clinical efficacy of immunotherapy
ABCA1, APLNR, BTG2, C3AR1, CALCRL, CD14, CYBB, HIF1A, MMP14, MYC, SELL, and SLC4A4 were upregulated in LGG tumor tissues, and SCN1B was downregulated in tumor tissues (Figure 1A)
Summary
Glioma is the most common primary malignant tumor of the central nervous system, and its rate of fatality and disability are both high (Lapointe et al, 2018; Ferlay et al, 2019). Cytokines, which are produced by chronic inflammation, induce gene mutations, change the expression and transformation of oncogenes and tumor suppressor genes, inhibit cell apoptosis, evoke angiogenesis, and result in abnormal inflammatory signal transduction pathways. It is of great significance to effectively control chronic inflammation in the process of inhibiting tumor occurrence and enhancing antitumor immune response. It is this idea that is the starting point of this article to carry out research, hoping to provide a certain reference for related research on tumor inflammation and immunity. It has been confirmed that the characteristics of inflammatory factors and immune microenvironment are closely related to the occurrence and development of tumors. It is necessary to clarify the role of inflammatory genes and immune infiltration in LGG
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