Micrometastasis and Isolated Tumor Cells in Oral Squamous Cell Carcinoma: Refining Nodal Staging with Emerging...

Cervical lymph node metastasis significantly influence prognosis in oral squamous cell carcinoma (OSCC), guiding staging, treatment decisions, and overall survival. Sentinel lymph node biopsy (SLNB) offers a minimally invasive approach for early detection of subclinical nodal metastasis, including micrometastases (0.2-2 mm) and isolated tumor cells (ITCs, < 0.2 mm). Despite its success in melanoma and breast cancer, the clinical relevance of micrometastases and ITCs in OSCC remains incompletely defined. This narrative review explores the biological significance, diagnostic challenges, and emerging strategies for detecting micrometastasis and ITCs in OSCC, aiming to inform their potential role in refining staging systems and treatment algorithms.

We performed a comprehensive literature review of SLNB in OSCC, examining data on histopathological detection techniques, molecular markers, artificial intelligence (AI), and radiomics-based tools that enhance diagnostic sensitivity and specificity for occult metastases.

While current guidelines in some countries endorse SLNB for early-stage OSCC, integration of micrometastasis and ITC data into staging remains inconsistent. Studies suggest that ITCs represent early metastatic events with variable prognostic significance. Advanced techniques such as step-serial sectioning, immunohistochemistry, and molecular diagnostics-including ctDNA, gene-expression profiling, and AI-assisted pathology-have shown promise in improving detection accuracy. However, robust prospective data are lacking, and a consensus on the management of minimal nodal disease is yet to be reached.

Accurate identification and interpretation of micrometastasis and ITCs in OSCC represent an evolving frontier in head and neck oncology. Future staging systems should incorporate these elements supported by standardized protocols and high-level evidence. The integration of AI, molecular diagnostics, and radiomics holds the potential to enhance risk stratification and personalize surgical decision-making, reducing overtreatment while ensuring oncologic safety.