Exploring the prognosis, immune response, and therapeutic prospects of Parthanatos-related miRNAs in low-grade gliomas

The low-grade gliomas (LGG) are chronic aggressive brain tumors that often result in shortened survival rates due to recurrences and disease progression. Parthanatos, a programmed cell death pathway associated with PARP-1 activation and AIF, is potentially instrumental in tumor development. miRNAs play a key role in regulating tumourigenesis and progression, but few studies have been conducted on Parthanatos-associated miRNAs. We collected miRNA and mRNA datasets from LGG patients from TCGA and CGGA databases and corresponding clinical information. Gene sets related to Parthanatos were obtained through the Genecard database. We used IHC data to validate the differences in Parthanatos-related genes (PRGs) expression in glioma and normal brain tissue. A protein-protein interaction network of PRGs was established using the STRING database, and significantly related miRNAs were screened by Spearman correlation analysis. NMF clustering analysis and a Parthanatos-related miRNA-based prognostic index (PCMI) explored the heterogeneity of miRNA expression patterns. In addition, we assessed the potential role of miRNAs in immune invasion and therapeutic response in the tumor microenvironment and predicted the sensitivity of common chemotherapeutic and targeted therapeutic agents by prophetic and OncoPredict using the CMap database to identify possible therapeutic agents. The miRNAs associated with Parthanatos were successfully identified, and a prognostic model consisting of 9 miRNAs was constructed. The model showed good predictive efficacy in both training and validation datasets. Significant differences in survival, clinicopathological characteristics, and immune microenvironment invasion were observed between patients in the high-risk and low-risk groups. Drugs such as Fasudil were identified as possible therapeutic candidates by drug sensitivity analysis and CMap prediction. The miRNAs associated with Parthanatos were successfully identified, and a prognostic model consisting of 9 miRNAs was constructed. The model showed good predictive efficacy in both training and validation datasets. In the low-risk group, immune microenvironment invasion and survival differed significantly from the high-risk group . Drugs such as Fasudil were identified as possible therapeutic candidates by drug sensitivity analysis and CMap prediction.