Animal models of tongue squamous cell carcinoma: a scoping review of preclinical evidence and clinical relevance

Abstract Introduction Tongue squamous cell carcinoma (TSCC) presents unique clinical challenges characterized by intricate lingual musculature, early perineural invasion, and a high propensity for occult cervical lymph node metastasis. Despite significant therapeutic advancements, the attrition rate for novel pharmacological agents remains high, largely attributed to the disconnect between preclinical models and clinical reality. Adhering to PRISMA-ScR guidelines, this study aims to systematically map recent advancements in preclinical TSCC models and evaluate their biological fidelity to provide a strategic framework for optimal model selection. Content A systematic search was conducted in PubMed, Embase, and Web of Science for studies published from 1 January 2019 to 31 December 2024. Following the screening of 1,063 records by two reviewers, 183 studies were selected for data extraction. Four major model categories were identified: (1) Chemical induction models (n=25), primarily using 4NQO, serving as the standard for chemoprevention but limited in metastatic potential; (2) Orthotopic transplantation (n=147), which best recapitulates neurovascular interactions and lymph node metastasis; (3) Genetically engineered mouse models (n=6) for dissecting molecular drivers; and (4) Patient-derived xenografts (PDX) or organoids (n=5) acting as avatars for personalized screening. Summary The review highlights that no single model captures the multifaceted biology of TSCC. While orthotopic models are superior for studying metastasis, chemical models remain the gold standard for etiology. However, a recurring limitation across the analyzed literature was the significant inconsistency in evaluation endpoints, which complicates the comparison of results across different preclinical platforms. Outlook To bridge the translational gap, researchers should adopt a clinical-question-oriented framework: utilizing chemical models for etiology, orthotopic systems for metastasis, and humanized models for immunotherapy. Furthermore, standardizing key endpoints, such as depth of invasion, is critical to improving the translational value of these preclinical platforms and ensuring more accurate predictions of clinical outcomes.