Screening of potential key pathogenic and intervention targets of low-grade glioma based on bioinformatics.

Background: Sialic acid-binding immunoglobulin-like lectin 8 () is involved in the progression of numerous diseases. This study aimed to examine the relationship between and the prognosis of patients with low-grade glioma (LGG) and the related mechanisms.

Methods: First, screening of the differentially expressed genes (DEGs) in The Cancer Genome Atlas (TCGA) database was performed. The expression was then correlated with the prognosis of patients with LGG and then verified using the Tumor Immune Estimation Resource (TIMER) and TCGA databases. Cox regression was employed to conduct multifactorial analysis and was followed by the construction of an internally validated nomogram based on these results. To investigate the possible mechanisms, we used gene set enrichment analysis (GSEA). We conducted a retrospective analysis of the clinical information of patients with LGG who were treated at Longgang Central Hospital of Shenzhen from January 2018 to December 2020 and from whom tumor and peritumoral tissues were taken during surgery. Expression of essential genes was identified by employing quantitative real-time polymerase chain reaction (qRT-PCR). Multivariate analysis, via Cox regression, was employed to determine the prognostic factors for patients with LGG.

Results: The transcriptional activity of was found to be elevated in LGG neoplastic tissues compared to neighboring nonneoplastic tissues. Overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were improved in patients with LGG with reduced expression of as compared to those with increased expression of . The nomogram's C-index is 0.804 (0.781-0.827). indicating good predictive accuracy. GSEA revealed that might influence LGG biological events by participating in the PD-1, IL3, JAK/STAT, and PI3KCI signal transduction pathways, as well as cytokine and inflammatory response, cell cycle, homeostasis, and extracellular matrix. This study included 72 patients with LGG. qRT-PCR showed upregulated expression in LGG tumor tissues, which was significantly associated with tumor number and metastasis to the lymph nodes (P<0.05). Multivariate analysis using Cox regression identified the high expression of as an independent risk factor in LGG prognosis (P<0.05).

Conclusions: For the prognosis of patients with LGG, the transcriptional activity of is increased in LGG tissues and is an independent risk factor. Interference with could promote tumor progression by regulating the JAK/STAT signaling pathway, indicating that may function as a distinctive predictive biomarker for patients with LGG.