Time series analysis combined with transcriptome sequencing to explore characteristic genes and potential molecular mechanisms associated with ultrasound-guided microwave ablation of glioma.

Abstract

Objective: This study aimed to explore marker genes and their potential molecular mechanisms involved in US-guided MWA for glioma in mice.

Method: The differentially expressed genes (DEGs1 and DEGs2) and lncRNAs (DELs1 and DELs2) were obtained between Non (glioma tissues without MWA) and T0 groups (0h after MWA), as well as between Non and T24 groups (24h after MWA). The down-regulation cluster genes (CONDOWNDEGs) and upregulation cluster genes (CONUPDEGs) were identified by time series analysis. Candidate genes were obtained by overlapping CONDOWNDEGs with downregulation DEGs (DOWNDEGs)1 and DOWNDEGs2, as well as CONUPDEGs with up-regulation DEGs (UPDEGs)1 and UPDEGs2. The expressions of immune checkpoints and inflammatory factors, gene set enrichment analysis (GSEA), and protein subcellular localization were performed. The eXpression2Kinases (X2K), GeneMANIA, transcription factor (TF), and competing endogenous (ce) RNA regulatory networks were conducted. The expression of marker genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR).

Results: Five marker genes (IL32, VCAM1, IL34, NFKB1 and CXCL13) were identified, which were connected with immune-related functions. Two immune checkpoints (CD96 and TIGIT) and six inflammatory factors played key roles in US-guided MWA for glioma. ceRNA regulatory networks revealed that miR-625-5p, miR-625-3p, miR-31-5p and miR-671-5p were associated with target genes. qRT-PCR indicated both IL32, VCAM1, and NFKB1 were potential markers under US-guided MWA-related time series analysis.

Conclusion: The use of US-guided MWA might be a practical method for influencing the function of target genes, regulating time frames to decrease inflammation, and stimulating immune responses in glioma therapy.