Lip & Oral Cavity

C00-C06WHO Vol. 9

Head & Neck

Prognosis

This section is being prepared by our editorial process.

🔬 Histological Types

📚 Latest Research

2026-09-10

An Atlas of Specificity Protein 1 in Oral Cancer: Networks, Therapeutics, and Priorities: A Scoping Review and scRNA-seq Analysis.

Choi S, et al

A scoping review of 38 studies found that Specificity Protein 1 (Sp1), a zinc-finger transcription factor, is consistently overexpressed in oral squamous cell carcinoma (OSCC) and associated with advanced clinical stage, lymph node metastasis, and poor prognosis, although direct human-tissue evidence was derived from only two studies. Single-cell RNA sequencing analysis of 5,865 cells from 18 tumors confirmed that Sp1-associated transcriptional programs drive epithelial-mesenchymal transition, immune evasion, and oncogenic signaling across distinct tumor cell compartments. Multiple natural and synthetic agents were shown in xenograft and cell-line models to suppress Sp1 activity and induce apoptosis, yet despite this substantial preclinical body of evidence, no Sp1-directed therapy has advanced to clinical testing. The authors identify a critical translational gap and advocate for biomarker-driven combination strategies to convert preclinical promise into meaningful benefit for patients with oral cancer.

International dental journal

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2026-09-10

Global Bibliometric Analysis of Post-Translational Modifications in Oral Squamous Cell Carcinoma.

Yang Y, et al

A global bibliometric analysis of 647 publications on post-translational modifications (PTMs) in oral squamous cell carcinoma (OSCC) reveals a sustained upward trend in research output, with China leading at 355 publications (46.16%), followed by Japan with 129 (16.78%) and the United States with 98 (12.74%). The study, based on a comprehensive Web of Science Core Collection search completed on January 14, 2026, identified that PTM-related research in OSCC has evolved from intracellular molecular mechanisms toward global regulation of the tumor microenvironment, with increasing focus on clinical translation. Current research frontiers center on therapeutic resistance, malignant progression, epithelial-mesenchymal transition (EMT), and patient survival, offering a roadmap for future investigations into targeted therapies and prognostic model development for OSCC patients.

International dental journal

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2026-09-10 • AI

AI-Assisted Three-Class Oral Histopathology: A Reader Study.

Cheng S, et al

A three-class deep learning model (VGG16-BR) trained on 25,576 histopathology patches achieved a test-set accuracy of 0.9065, macro-F1 of 0.9086, and macro-AUC of 0.9628 in distinguishing normal tissue, oral leukoplakia, and oral squamous cell carcinoma, with an OSCC-to-Normal misclassification rate of only 5.1%. When used as a diagnostic aid in a controlled reader study involving six oral pathologists, AI assistance raised mean accuracy from 0.767 to 0.857 in junior readers and from 0.850 to 0.894 in senior readers, while also improving inter-reader agreement and reducing reading time. The benefit of AI assistance was statistically significant (P < .001) and independent of pathologist experience level (P = .265 for interaction). Positioned as an adjunct rather than a replacement for pathologists, this lightweight framework shows particular promise for strengthening early detection of oral premalignant and malignant lesions in resource-limited primary care settings.

International dental journal

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