Dataset Information

Bioinformatics analysis of laryngeal squamous cell carcinoma: seeking key candidate genes and pathways.

ABSTRACT:

Background

Laryngeal squamous cell carcinoma (LSCC) is the second most aggressive head and neck squamous cell carcinoma. Although much work has been done to optimize its treatment, patients with LSCC still have poor prognosis. Therefore, figuring out differentially expressed genes (DEGs) contained in the progression of LSCC and employing them as potential therapeutic targets or biomarkers for LSCC is extremely meaningful.

Methods

Overlapping DEGs were screened from two standalone Gene Expression Omnibus datasets, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. By applying STRING and Cytoscape, a protein-protein network was built, and module analysis was carried out. The hub genes were selected by maximal clique centrality with the CytoHubba plugin of Cytoscape. UALCAN and GEPIA data were examined to validate the gene expression findings. Moreover, the connection of the hub genes with LSCC patient overall survival was studied employing The Cancer Genome Atlas. Then, western blot, qRT-PCR, CCK-8, wound healing and transwell assays were bring to use for further verify the key genes.

Results

A total of 235 DEGs were recorded, including 83 upregulated and 152 downregulated genes. A total of nine hub genes that displayed a high degree of connectivity were selected. UALCAN and GEPIA databases verified that these genes were highly expressed in LSCC tissues. High expression of the SPP1, SERPINE1 and Matrix metalloproteinases 1 (MMP1) genes was connected to worse prognosis in patients with LSCC, according to the GEPIA online tool. Western blot and qRT-PCR testify SPP1, SERPINE1 and MMP1 were upregulated in LSCC cells. Inhibition of SPP1, SERPINE1 and MMP1 suppressed cell proliferation, invasion and migration.

Conclusion

The work here identified effective and reliable diagnostic and prognostic molecular biomarkers by unified bioinformatics analysis and experimental verification, indicating novel and necessary therapeutic targets for LSCC.

SUBMITTER: Ma J

PROVIDER: S-EPMC8052978 | biostudies-literature |

REPOSITORIES: biostudies-literature

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