The role of molecular biomarkers in the diagnosis, prognosis, and treatment stratification of oral squamous cell carcinoma: A comprehensive review

One of the most common cancers targeting the area of the head and neck is oral squamous cell carcinoma (OSCC), carrying a heavy global health cost. With a high incidence of metastasis and recurrence, the outlook for OSCC remains dismal despite advancements in treatment. This has sparked an investigation into molecular biomarkers, which have the potential to improve early diagnosis, forecast patient outcomes, and direct therapeutic approaches. An extensive summary of the function of molecular biomarkers in OSCC diagnosis, prognosis, and medical care stratification is given in this article. Complex genetic mutations, epigenetic changes, and dysregulated signalling pathways are all part of the aetiology of OSCC. Tumor protein p53 (Tp53), Epidermal growth factor receptor (EGFR-targeted), Cyclin D1 (CCND1), and Human papilloma virus (HPV) status are examples of molecular biomarkers that have demonstrated potential in recognising disease at an early stage and identifying malignant changes. The non-invasive detection capabilities of diagnostic biomarkers such as salivary proteins, circulating tumour DNA (ctDNA), and microRNAs are being explored more and more because they may provide early intervention and better patient outcomes. Prognostically, tumour aggressiveness, recurrence risk, and overall survival have all been linked to biomarkers such as matrix metalloproteinases (MMPs), E-cadherin, and different cytokines. Furthermore, immune checkpoints such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed death-ligand 1 (PD-L1) are becoming recognised as important markers of the tumour microenvironment's function in the course of the disease and its reaction to immunotherapy. The significance of biomarkers in personalised medicine has been further highlighted by the recognition of subgroups with elevated risk that might gain benefit from more aggressive treatment options thanks to the genetic profiling of OSCC. Predictive biomarkers are essential for therapy classification because they allow therapeutic regimens to be tailored. For example, (Kirsten rat sarcoma viral oncogene homologous) KRAS mutations and EGFR expression influence the effectiveness of targeted therapies, and the existence of specific epigenetic markers influences choices about radiation or chemotherapy. It is expected that the incorporation of multi-omics techniques, which integrate transcriptome, proteome, and genomic data, will improve these tactics and increase accuracy in O