Background: An adequate OSCC macroscopic resection margin (MRM) is essential for effective treatment. This study analyzed the effects of formalin fixation (FF) on the MRM. Material and Methods: A total of 42 patients were enrolled in this study. Tumors from the floor of the mouth (FOM; n = 23), the tongue (TC; n = 10), and the maxilla (MT; n = 9) were studied. A 3D scanner was used to create virtual models, and further analysis was conducted according to the established protocol. Results: The most significant shrinkage was observed in the TC (MRM n = 121; Med. = 1.5 mm; p val. = 7.05 × 10⁻¹⁸), with a maximum shrinkage of 28%. For the FOM (n = 262; Med. = 0.8 mm; p val. = 6.76 × 10⁻¹⁸), the greatest MRM shrinkage was 26%. In the MT group (n = 91; Med. = 0.9 mm; p val. = 2.69 × 10⁻⁹), the shrinkage was 18.7%. Among MRMs >8 mm (n = 159), FF led to 58.5% of them shrinking to ≤8 mm, resulting in a false decrease in the safe MRM (p val. = 1.11 × 10⁻²⁷). Overall, the average shrinkage for all specimens was μ= 2.57 mm (p val. = 8.89 × 10⁻¹⁰) alongside and μ= 2.35 mm (p val. = 4.09 × 10⁻⁶) across. The tumors themselves showed minimal changes: μ= 0.69 mm (p val. = 9.73 × 10⁻³) alongside and μ= 0.8 mm (p val. = 2.52 × 10⁻⁷) across. Conclusion: Formalin fixation (FF) caused the shrinkage of the OSCC MRM, particularly in tongue cancers. Even after proper surgical excision in the postoperative results, the number of normal MRMs was underestimated. This should be considered when interpreting the results of surgical treatment. However, FF had a minimal impact on the overall shrinkage of the tumors themselves.

Background: The histopathological assessment is critical in the comprehensive treatment process for patients diagnosed with oral squamous cell carcinoma (OSCC). A detailed and precise specimen characterization is essential to facilitate effective surgeon–pathologist communication. Methods: In response to this need, a user-friendly virtual communication protocol utilizing a 3D scanner has been developed. This study involved 50 patients with OSCC, whose resected tumors were directly scanned in the operating room and subsequently annotated and characterized using available software. Results: The direct application of annotations and descriptions onto the virtual tumor specimens significantly enhanced the quantity and accuracy of information conveyed to the pathologist. Conclusions: The proposed solution’s repeatability and standardized approach make integration into routine clinical practice feasible, thereby establishing a potential new standard in the field.

Background: Head and neck squamous cell carcinoma (HNSCC) remains the seventh most common cancer worldwide, characterized by late-stage diagnosis and poor 5-year survival rates. Oral squamous cell carcinoma (OSCC) is the most prevalent subtype. The identification of robust diagnostic, prognostic, and predictive markers is essential for personalized treatment monitoring. Methods: Following PRISMA and PICO standards, we conducted a comprehensive review of studies published over the past 10 years across PubMed/MEDLINE, Scopus, and Web of Science. The selection process was facilitated by AI-powered tools (Rayyan QCRI), and study quality was assessed using NOS or QUIPS. Results: 34 articles (including meta-analyses and original trials) were identified. Established clinical markers, such as p16-positivity (HR ≈ 0.55) and PD-L1 (CPS), remain significant. However, the molecular landscape is expanding to include high-risk lncRNA signatures (HR ≈ 2.50), immune checkpoints such as TIGIT (HR ≈ 1.85), and genomic alterations, including IL-10 promoter polymorphisms. We highlight that epigenetic silencing of p16 affects only about 25% of patients, while metabolic regulators (e.g., GLUT-1) and protein markers (e.g., MASPIN) offer critical predictive value for therapy response. Conclusions: The diagnostic and predictive paradigm is shifting toward a multi-omic approach that integrates DNA, RNA, proteins, and metabolic indicators. Future clinical use will rely on AI-driven multimarker panels and non-invasive liquid biopsies to enable real-time monitoring and de-escalation of treatment strategies.