Precision reconstructive oncology: Integrating MACC1 and salivary biomarkers into surgical planning for head and neck cancers

Head and neck malignancies pose a unique surgical challenge in which oncologic clearance must be achieved alongside the restoration of speech, swallowing, mastication, and facial aesthetics. Despite advances in ablative and microvascular techniques, reconstructive outcomes remain highly variable, largely due to differences in tumor biological behaviors that are not adequately captured by conventional histopathology alone. Increasing evidence suggests that molecular biomarkers may provide additional insights into tumor aggressiveness, invasive growth patterns, and recurrence risk, thereby influencing reconstructive complexity and long-term functional outcomes. Among these, metastasis-associated colon cancer 1 (MACC1) and salivary-derived miRNAs have emerged as promising indicators of biologically aggressive diseases in head and neck cancer. Elevated MACC1 expression is associated with infiltrative tumors and unpredictable resection margins, factors that frequently necessitate wider composite resections and robust vascularized reconstruction. In parallel, salivary miRNAs offer a non-invasive means of monitoring molecular activity in postoperative settings, where clinical examination and radiologic assessment may be limited by flap volume, fibrosis, or radiation-related changes. When interpreted through a reconstructive framework, these biomarkers may assist in the preoperative prediction of defect behavior, selection of a flap strategy, optimization of reconstruction timing, and individualization of postoperative surveillance and rehabilitation. Although current evidence remains largely translational and hypothesis-generating, the integration of molecular biomarkers into reconstructive decision-making represents a promising step toward precision reconstructive oncology. Future prospective studies correlating biomarker profiles with reconstructive outcomes are required to validate their clinical utility and to support the development of biologically informed reconstructive algorithms.