Identification of Biomarkers for Diagnosis and Prognosis of Head and Neck Cancer: Bioinformatics Approach

Abstract

Head and neck cancer (HNC) is the seventh most commonly diagnosed malignancy worldwide, and its incidence is expected to increase in coming years. Current diagnostic methods for HNC are often limited by suboptimal accuracy and speed, which can negatively impact therapeutic decision-making and patient outcomes. To address the shortcomings of conventional diagnostics, biomarker detection has attracted increasing clinical interest as a promising alternative. However, a major challenge is the identification of biomarkers with sufficient accuracy and sensitivity for HNC. The integration of bioinformatics tools with omics data analysis has proven to be a robust approach for biomarker discovery. In this study, we outline a bioinformatics protocol aimed at identifying differentially expressed genes (DEGs) in HNC and evaluating the diagnostic and prognostic relevance of specific genes, including FN1, LGALS3, MMP9, TIMP1, MMP2, and TIMP2, in this pathology. In addition, we performed an enrichment analysis for the genes of interest. The prognostic significance of the selected genes was evaluated in relation to patient survival. This study contributes to the growing body of knowledge by identifying potential biomarkers with diagnostic and prognostic utility in this malignancy.