Abstract
Objective To investigate the multiomics immune-related lncRNA analysis of oral squamous cell carcinoma and its correlation with prognosis. Methods Through the bioinformatics database, a total of 346 oral squamous cell carcinoma (OSCC) related samples were retrieved. Bioinformatics analysis screened out the difference lncRNAs in the sample tissue and normal tissue, combined with literature research to clarify the target. The biological functions of differentially expressed lncRNAs were predicted. The differential expression network of differentially expressed lncRNAs and mRNAs was established. The correlation analysis software was used to analyze the correlation between oral squamous cell carcinoma multiomics immune-related lncRNA and prognosis. Results 3054 lncRNAs in OSCC tissues are highly correlated with immune genes. 76 immune-related lncRNAs were different in tumor and adjacent tissues. Cancer Hallmark, Phenotype, and Subcellular Location analysis were completed. The results showed that lncRNAs can participate in tumor cell invasion, metastasis, proliferation, and apoptosis. Select the 15 most important lncRNAs above, draw Kaplan-Meier curve to complete the survival curve analysis, and complete the analysis and arrangement of the relevant data. LINC00460, CASC9, and HCG22 were screened for subsequent analysis. Complete the GO and KEGG enrichment analysis. LINC00460, CASC9, and macrophages M0 are positively correlated; CASC9 is negatively correlated with macrophages M1; LINC00460 is positively correlated with macrophages M1; HCG22 is associated with mast cells resting positive correlation; LINC00460 was negatively correlated with mast cell resting. CASC9 and HCG22 were significantly correlated with the age and stage of OSCC patients; 2 key lncRNA and 79 miRNAs were extracted from the database, to complete 86 pairs of interactions; the target mRNAs were predicted based on the above miRNAs. A total of 631 pairs of interactions were predicted (including 21 miRNAs and 562 mRNAs), and the regulatory mechanism of key gene ceRNA network was constructed. Conclusion The differential expression of multiple lncRNAs and mRNAs was screened, and the downregulated lncRNAs were more than the upregulated lncRNAs. The lncRNA LINC00460, CASC9, and HCG22 had a strong correlation with prognosis.
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