This Research Topic was developed to examine how next-generation technologies, including artificial intelligence (AI), machine learning (ML), liquid biopsy, advanced imaging, and molecular profiling, are reshaping the landscape of oral cancer care and how multidisciplinary integration provides the framework necessary to translate these advances into clinical practice. Increasingly, progress in oral oncology is not defined by isolated innovations but by the convergence of technological advancements and coordinated clinical expertise. The four contributions in this collection reflect this vision by spanning biomaterial science, surgical innovation, multidisciplinary oncologic care, and computational pathology.dental restorative materials: a bulk-fill composite (3M™ Filtek™ Bulk Fill), a nanohybrid composite (Charisma Topaz One), and an alkasite-based restorative material (Cention N). Ninety disc-shaped specimens were irradiated using two fractionation protocols (70 Gy in 35 fractions and 45 Gy in 5 fractions). Vickers microhardness testing and scanning electron microscopy revealed a statistically significant decrease in surface microhardness and micromorphological degradation (p < 0.05) in all materials. The bulk-fill composite exhibited the greatest resistance to aging-related changes. These findings emphasize the importance of collaboration between oncologists and dental professionals in planning head and neck radiotherapy, considering the significant morbidity associated with postradiation tooth extractions.Qi et al. refined the nasolabial flap for total lower lip reconstruction after malignant tumor excision, addressing microstomia and its functional limitations. Two elderly male patients with squamous cell carcinoma of the lower lip underwent bilateral full-thickness strip flap reconstruction using the buccal mucosa for vermilion reconstruction. At 12 months, both patients had normal mouth opening, maintained oral competence, satisfactory aesthetics, and no tumor recurrence. Patient-reported outcomes using the Visual Analog Scale indicated preserved mastication, speech, and swallowing functions. The nasolabial flap is a practical and reliable option for reconstructing full-thickness lower lip defects after oncologic resection surgery. Taken together, these contributions illustrate that modern oral cancer care is inherently multidimensional. No single discipline or innovation is sufficient; rather, meaningful progress arises from the alignment of surgical expertise, material science, and coordinated evidence-based clinical decision-making.The future of oral oncology will be shaped by the integration of artificial intelligence, biomarker-driven precision medicine, and data-centric clinical ecosystems to improve patient outcomes. The challenge is no longer technological capability, but effective clinical integration across diverse settings. Liquid biopsy is particularly promising, as circulating tumor DNA (ctDNA), salivary microRNA signatures, exosomal RNA, and cell-free DNA from biofluids offer noninvasive early detection and real-time monitoring (6,7). Salivabased tests are especially appealing for oral cancer diagnosis, given their simplicity, low cost, and repeatability (8). However, broader adoption depends on standardized assays and validation across diverse populations. AI continues to reshape diagnosis and treatment, with tools already improving disease detection and classification using imaging, digital pathology, and intraoral photographs (9,10), as exemplified by the semi-supervised segmentation approach in this Research Topic. Beyond lesion identification, AI can also integrate multimodal datasets combining clinical, imaging, and molecular information to generate predictive models for treatment response, recurrence risk, and functional outcomes (11); it should support rather than replace clinical judgment (12). Multiomics approaches further strengthen the precision medicine paradigm by integrating genomic, transcriptomic, proteomic, and metabolomic profiling, enabling a deeper characterization of tumor heterogeneity and biological behavior (13). Digital health, telemedicine, and remote monitoring tools strengthen survivorship care (14). Despite these advances, challenges remain. AI requires robust validation across diverse populations, regulatory clarity, and clinician acceptance. Biomarker research must shift from discovery to clinically actionable tools. Equity is crucial, as the oral cancer burden is higher in low-and middle-income countries with limited access to diagnostics and advanced care. Emerging technologies, such as AI-driven screening, label-efficient learning, smartphone diagnostics, and saliva assays, should be developed for scalability, cost-effectiveness, and accessibility. These efforts ensure broader implementation and reduce global inequities in oral cancer detection and treatment.The message of this research topic is both urgent and optimistic: oral cancer care has been constrained by conventional approaches, but next-generation technologies within a multidisciplinary framework are reshaping it. The critical barrier is the effective translation of these findings into routine clinical practice. Progress in oral oncology will result from coordinated developments across the surgical, diagnostic, computational, and translational domains. Advances in resilient biomaterials, reconstructive techniques, AIdriven diagnostics, label-efficient deep learning, and biomarker discovery are shifting toward precise, patient-centered care. The impact will be defined by enabling earlier detection, personalized treatment, improved functional outcomes, and quality of life. This is the promise and responsibility of integrated oral cancer care.
Chakraborty et al. (Thu,) studied this question.
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