Integrative Bioinformatics Analysis Identifies NEK2 as a Potential Biomarker in Head and Neck Squamous Cell Carcinoma

Area of Science:

• Oncology
• Bioinformatics
• Molecular Biology

Background:

• Head and neck squamous cell carcinoma (HNSC) is a prevalent cancer with complex molecular underpinnings.
• Understanding the regulatory networks of differentially expressed genes (DEGs) is crucial for identifying potential therapeutic targets.

Purpose of the Study:

• To explore the function and regulatory networks of DEGs in HNSC using bioinformatics.
• To identify key genes and pathways involved in HNSC development and progression.

Main Methods:

• Utilized Cancer RNA-Seq Nexus (CRN) and Oncomine databases for gene expression profiling.
• Performed Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) analysis on DEGs.
• Constructed and analyzed protein-protein interaction (PPI) networks using STRING and Cytoscape.
• Validated findings using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) data.

Main Results:

• Identified a PPI network of 101 genes, with 12 key genes selected based on Degree and MCODE scores.
• Observed the expression of eight hub genes in HNSC tissues.
• Found that NIMA-related kinase 2 (NEK2) expression is significant in different HNSC stages.
• Survival analysis indicated NEK2's important prognostic value in HNSC.

Conclusions:

• NEK2 plays a significant role in HNSC and holds potential as a biomarker.
• This study provides insights into the molecular mechanisms of HNSC, offering a reference for future research and therapeutic strategies.