Glioma is a common intracranial tumor, and the factors that contribute to its development and progression are not fully understood. In-depth studies at the molecular level will help to elucidate the pathogenesis of glioma and predict the prognosis of patients. Cuprotosis is associated with genetic disorders and tumors and has the potential to be a therapeutic strategy(3, 16–18). Recently, several studies have shown that lncRNAs are involved in the development of multiple cancers and that different types of lncRNAs predictive features are used to predict the prognosis of cancer patients (19–21). However, the role of cuprotosis-related lncRNAs in glioma patients has not been reported. Our study identified multiple prognostic cuprotosis-related lncRNAs for the first time and successfully constructed a formula for cuprotosis-related lncRNAs with powerful predictive features, and introduced the role of cuprotosis-related lncRNAs in predicting glioma prognosis and immune status.
This study first extracted ten genes involved in cuprotosis closely and then identified 12 prognostic cuprotosis-related lncRNAs for prognostic signatures using reliable biological analysis. After analysis, AC084824.4, AC104117.3, AC121761.2, AL391834.1, DNAJC9-AS1, LINC01503, RNF219-AS1, SNAI3-AS1 were regarded as protective factors; AL355974.2, CRNDE, LINC02328, TMEM220-AS1 were regarded as risk factors. And among these lncRNAs, the biological functions of some lncRNAs with were confirmed. For example, high expression of CRNDE promotes the malignant progression of gliomas (22). LINC01503 plays an essential role in HCC through the MAPK/ERK pathway(23). TMEM220-AS1 regulates hepatocellular carcinoma by regulating the miR-484/MAGI1 axis(24). Then, we constructed an RS model containing these 12 lncRNAs. Based on the RS model, we divided glioma patients into low-risk and high-risk groups; patients in the high-risk group were shown to have a significantly worse prognosis in both TCGA and CGGA data. To evaluate the reliability of the prognostic features, on the one hand, the risk-risk model was validated by the Kaplan-Meier curve and ROC curve; the correlation analysis of clinical variables and risk scores also increased the reliability of the model.On the other hand, the one-three-and five-year nomograms reported that the model was a good predictor of OS prognosis in glioma patients. The calibration curves further confirmed that the model was accurate. We also analyzed the expression levels of 12 lncRNAs using the TCGA and CGGA databases to verify the reliability of the prognostic features. All genes showed similar trends except for AC084824.4 in the CGGA data. Most importantly, the expression levels of genes that are risk factors increased with increasing tumor grade, while the expression levels of protective genes were reversed.
GSEA shows systemic-lupus-erythematosus, cell-cycle, n-glycan-biosynthesis, amino-sugar-and-nucleotide-sugar-metabolism, leukocyte-transendothelial-migration ware mainly enriched in at-risk groups. It is well known that intracellular metabolic processes such as nucleotides, amino acids, and glutathione play an irreplaceable role in cancer. For example, aberrant glycosylation of cells leads to abnormal expression of membrane-localized glycans, triggering a malignant transformation of cells(25). N-glycans play an essential role in breast and oral cancers(26, 27). Glutathione affects tumor development by altering the sensitivity to oxidative stress in astrocytic tumors(28). The ssGSEA results showed a significant increase in most cells (macrophages, CD8+ T cells, Neutrophils, mast cells, Tregs, etc.) in the high-risk group. Some studies found that the degree of tumor immune cell infiltration correlated with the prognosis of tumor patients. For example, CD8+ T-cell infiltration was associated with a poor prognosis in BC patients (29). High infiltration of tumor-associated macrophages is associated with poor prognosis in glioma and thyroid cancer(30, 31). The degree of MC infiltration in mouse and human gliomas is proportional to the malignancy of the tumor(32, 33). A high ratio of neutrophils to lymphocytes predicts a poorer OS in BC patients(34). Pathological grading of gliomas is positively correlated with infiltrating neutrophils(35). lncRNA HOXA-AS2 promotes Tregs proliferation and immune tolerance via miR-302a/KDM2A axis, thus promoting glioma progression and poor prognosis (36). An increase in Treg and MDSC in mouse gliomas leads to decreased overall survival (37).In addition to increased tumor immune cell infiltration, immune-related pathways were significantly higher in the high-risk group. In other words, although the immune function was more active in the high-risk group, the decreased anti-tumor immunity of patients in the high-risk group may have contributed to their poor prognosis. This also suggests a new idea for immunotherapy of glioma. Glioma immunotherapy has been a hot topic in recent years (38). Therefore, we also performed an analysis of immune checkpoint expression between high-risk and low-risk groups, hoping to provide some direction for glioma immunotherapy. We studied the sensitivity of immune-related drugs among patients and found that high-risk patients may be sensitive to Cisplatin, Etoposide, Rapamycin, and resistant to Lenalidomide, PAC-1. This implies that high-risk groups may benefit from treatment with multiple immune-related drugs. We hope that the above study provides a basis for precise, individualized treatment of glioma patients.
Although the RS model we constructed has a strong predictive effect. However, there are still some limitations. First, more data are needed to validate the model and improve it. Second, cuprotosis is a newly discovered mode of cell death, and studies about its associated lncRNAs are limited; more studies are needed to elucidate the specific mechanism of how our discovered cuprotosis-related lncRNAs induce cuprotosis.