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PubMed2026

Establishing a genetic mutation panel for predicting malignant transformation of oral leukoplakia: A prospective cohort study.

OBJECTIVE: To investigate somatic mutations in the whole genes of tissue samples from patients with oral leukoplakia (OLK), as the most typical precursor of oral cancer; and identify the specific genes as a mutational panel for predicting OLK malignant transformation. METHODS: A total of 123 consecutive OLK patients with long-term follow-up (median, 73 months) were prospectively enrolled, and divided into training set (n = 92) and independent test set (n = 31) based on chronological order of enrollment. Genomic DNA was isolated from the fresh-frozen biopsy tissues and somatic mutations in all genes were measured by whole-exome sequencing. RESULTS: We constructed a 3-gene (TP53, CASP8, and CYP2B6) mutational panel for risk stratification (any mutation vs. no mutation) of OLK malignant transformation. Kaplan-Meier analysis showed that the prognostic power of the 3-gene panel (log-rank P < 0.0001) for risk stratification in malignant progression was better than that of pathological grade in the training and test set, respectively. Multivariate Cox regression analysis revealed that this panel was an independent variable significantly associated with progression in the training (hazard ratio [HR] = 8.05; P < 0.001) and test set (HR = 11.26; P = 0.0421), respectively. The area under the curve (AUC) with 95 % confidence interval was 0.770 (0.648-0.892) and 0.877 (0.705-1.000) in the training and test set, respectively, for predicting malignant transformation in OLK patients. CONCLUSIONS: We established a 3-gene (TP53, CASP8, and CYP2B6) mutational panel as risk stratification model could effectively predict OLK malignant transformation, outperforming pathological grading-based assessment. Such genetic markers may provide a foundation for developing personalized management strategies.

Humans↗

PubMed2026

Tissue-based genomic instability markers for predicting malignant transformation in oral leukoplakia and proliferative verrucous leukoplakia: a systematic review.

OBJECTIVES: Although several biomarkers have been described for predicting malignant transformation in oral leukoplakias (OLs) and proliferative verrucous leukoplakias (PVLs), no systematic review has comprehensively evaluated tissue-based genomic instability markers. This review aimed to evaluate the evidence for these markers and their potential role in biomarker panel development. METHODS: A systematic review across PubMed, Embase and Cochrane Library was performed to identify studies evaluating the differences in tissue-based genomic markers between OL and PVL patients with and without malignant transformation. RESULTS: 34 observational studies comprising 3,237 patients were included, and genomic aberrations were categorised into DNA-level, chromosomal, and gene-specific alterations. For studies on OLs, DNA-level and chromosomal markers for which individual studies reported associations with malignant transformation included aneuploidy, impaired DNA repair capacity, loss of heterozygosity, chromosomal instability, and copy number alterations. Multiple gene-specific alterations also showed associations (e.g., TP53, MKI67, FGFR1), but findings varied across studies. The genomic markers of PVLs differed substantially, with fewer consistent predictors found. No meta-analysis was performed as all included studies were observational. CONCLUSIONS: Genomic instability across multiple levels contributes to malignant transformation, and represents a promising biological framework for predicting malignant transformation for OLs. While no single marker reliably demonstrates sufficient predictive performance, the integration of complementary genomic alterations with clinical and histopathological risk factors may provide a basis for the development of robust multi-marker panels. Future prospective studies using standardised detection methods and multivariable prediction models are required before clinical implementation. SYSTEMATIC REVIEW REGISTRATION: identifier CRD42024585830.

carcinoma↗

PubMed2026

Multimodal risk assessment for oral potentially malignant disorders: Integrating patient-centered and specimen-derived data.

BACKGROUND: Oral potentially malignant disorders exhibit heterogeneous malignant transformation risk that clinical approaches fail to adequately predict. Histopathologic dysplasia grading, the reference standard of risk assessment, is associated with poor interobserver reliability and limited prognostic discrimination. It is necessary to define other potential patient- and tissue-associated risk modifiers to improve patient-specific disease prediction. TYPES OF STUDIES REVIEWED: PubMed was queried for patient- and specimen-derived factors as they relate to oral cancer and oral potentially malignant disorders, with preference for systematic review and meta-analysis articles published within the past 5 years. When not available, guidelines from the American Cancer Society, National Cancer Institute, or other national organizations or the most recent best articles were referenced to support the data presented. RESULTS: Within patient-associated factors, validated measures of tobacco and alcohol exposure, clinical lesion characteristics, systemic health factors including metabolic syndrome components, comorbidity risk, and dental health indexes were found. Within specimen-derived data, tissue-based analyses encompassing histopathology and advanced molecular profiling (genomic, epigenomic, transcriptomic, spatial approaches), blood-based germline and somatic mutation analysis, and saliva-based microbiome characterization and inflammatory biomarker assessment were addressed. PRACTICAL IMPLICATIONS: Malignant transformation reflects intersecting patient and specimen risk pathways that affect each patient differently; no single modality captures this complexity. Realizing precision prognostication in oral precancer will require coordinated expansion and standardization of data collection across research groups. This review is intended to guide covariate selection for prospective study design, improve reproducibility, and ultimately enable the development of validated multimodal risk prediction tools for clinical deployment.

Humans↗

PubMed2026

Decoding protein signatures and protein interactions in oral potentially malignant disorders: a systematic review and network analysis.

BACKGROUND: Proteomic profiling offers thorough insights into protein structure and function, as well as it acts as an essential approach for analyzing molecular changes at the tissue level. However, because of the proteome's diversity and dynamic nature, biomarker discovery remains challenging. By combining proteomics with bioinformatics, the level of understanding in relation to molecular interactions and disease processes can be improved. Through an integrative approach, few limitations can be addressed, thereby promoting proteomic profiling for the discovery of new therapeutic targets and novel biomarkers for a variety of disorders. AIM: To identify differentially expressed protein markers and their key molecular pathways associated with Oral Potentially Malignant Disorders. METHODS: Systematic Review was conducted following the PRISMA guidelines and the protocol registered in the International Prospective Register of Systematic Reviews (PROSPERO) with the registration ID number CRD42024557545. A comprehensive literature review was performed using electronic databases, yielding 12,797, studies from which 15 eligible articles were selected. The Newcastle-Ottawa Scale was used to assess the risk of bias. Vote counting was performed to identify proteins reported in more than one study. A bipartite network was constructed using Cytoscape to identify shared and disease-specific protein markers. Lesion-wise protein-protein interaction networks were generated using STRING and analysed in Cytoscape to identify highly interconnected hub proteins, and pathway enrichment analysis for these hubs was performed using Reactome. RESULTS: A total of fifteen studies (Leukoplakia (LK) - n = 1, Proliferative Verrucous Leukoplakia (PVL) - n = 2, Oral Submucous Fibrosis (OSMF) - n = 7, and Oral Lichen Planus (OLP) - n = 5) were included. The Newcastle-Ottawa Scale was used to evaluate methodological quality and the quality of studies included in this systematic review was high for 4 articles and moderate in the remaining 11. The most commonly employed technique was mass spectrometry. A total of 318 candidate proteins (LK - 14, PVL - 82, OSMF - 172, and OLP - 50) were identified across the oral potentially malignant disorders. Key markers identified through vote counting included ERO1A, NUCB1, RHOA, and IL36A for PVL; LUM, KRT1, KRT9, ALB, and VIM for OSMF; and ALB, LYZ, HP, HBB, and AMY1A for OLP. The bipartite network showed that OSMF and OLP shared the highest number of proteins, indicating the strongest overlap among lesions. Network analysis further highlighted distinct hub proteins for each lesion: for LK- AMY1A, AMY1B and APOA1; for PVL- CFL1, RHOA and CDC42; for OSMF- HSP90AA1, ENO1 and SERPINA1; and for OLP- HP, B2M, and ORM1. Lesion-specific pathway enrichment revealed that LK was associated with epithelial differentiation, PVL with oncogenic signaling, OSMF with stress-driven fibrosis, and OLP with immune-mediated inflammation. CONCLUSIONS: Proteomic expression offers insights into disease pathogenesis by identifying important molecular changes across OPMDs. However, the majority of biomarkers are still in the exploratory stage due to the considerable variation in lesion types, sample sources, proteomic techniques, and reporting systems. In order to create reliable and clinically applicable biomarkers, future studies should concentrate on combining multi-omics techniques with large-scale, standardized cohorts.

Humans↗