International Journal of Molecular Medical Science, 2025, Vol.15, No.1, 9-19 http://medscipublisher.com/index.php/ijmms 14 Additionally, proteins such as Heat Shock Protein 90 (HSP90) have been implicated in stabilizing and maintaining the function of various oncogenic proteins, further supporting tumor survival and progression. The complex interactions between these proteins, including YAP, and other molecular factors underscore the multifactorial nature of OSCC progression. Understanding these dynamics is crucial for identifying new therapeutic targets and improving treatment outcomes for OSCC patients. 5 Clinical Application of Genomic Biomarkers for Early Detection in Oral Cancer 5.1 Screening and early detection Genomic biomarkers play a crucial role in the screening and early detection of OSCC, which is essential for improving patient outcomes, as early detection is strongly associated with higher survival rates. Circulating tumor DNA (ctDNA) has emerged as a promising non-invasive tool for screening, allowing the detection of tumor-specific mutations and methylation patterns even at early stages of the disease (Campos-Carrillo et al., 2019). Advances in liquid biopsy technologies have enabled the identification of specific DNA mutations and methylation markers in ctDNA, providing new avenues for early diagnosis and intervention (Phallen et al., 2017). In addition to ctDNA, salivary biomarkers have gained traction as a convenient and non-invasive approach for oral cancer screening. Salivary miRNAs and protein markers have been identified as sensitive indicators of early-stage OSCC, offering a method for detecting changes associated with tumorigenesis without the need for invasive procedures (Khurshid et al., 2018). For instance, miR-21 and miR-31 have been shown to differentiate between healthy individuals and early-stage oral cancer patients with high accuracy. The combined use of multiple biomarkers can further enhance diagnostic accuracy and sensitivity. Multi-marker panels that integrate various genetic and protein biomarkers have significantly improved the ability to detect OSCC at an early stage (Wang, 2024). This approach is particularly useful for large-scale screening programs in high-risk populations, providing an early warning system that enables clinicians to intervene before the disease progresses, thereby improving patient outcomes and quality of life. 5.2 Monitoring disease progression The dynamic nature of OSCC requires continuous monitoring to assess treatment response and detect potential recurrences. Genomic biomarkers such as ctDNA provide a valuable tool for tracking disease progression and detecting residual disease after treatment. Studies have shown that rising ctDNA levels can indicate early disease progression even before clinical symptoms appear, allowing for timely intervention (Bronkhorst et al., 2019). Monitoring specific genetic alterations through ctDNA analysis enables a personalized approach to follow-up care, providing insights into tumor evolution and the emergence of resistance mutations. This is particularly useful for assessing Minimal Residual Disease (MRD) after surgical resection or radiotherapy, offering a real-time method to evaluate the effectiveness of ongoing treatment (Nakamura et al., 2020). For example, a decrease in ctDNA levels during treatment typically correlates with a positive therapeutic response, while an increase may suggest relapse. Salivary and serum miRNA biomarkers are also useful for monitoring the progression of OSCC. These biomarkers exhibit dynamic changes during disease progression, providing a non-invasive method for real-time assessment of patient response to therapy (Khurshid et al., 2018). This approach is particularly beneficial for patients requiring long-term management, as it reduces the need for repeated tissue biopsies and allows for more frequent monitoring. 5.3 Prognostic value Genomic biomarkers also play an important role in determining the prognosis of OSCC (oral squamous cell carcinoma) patients. Through Next-Generation Sequencing technology (NGS), specific gene expression profiles and mutations can be identified, providing prognostic information and helping clinicians stratify patients based
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