Abstract Background: Mesenchymal stem/stromal cell (MSC)-Oral Cancer interactions remain poorly characterised, and almost all existing work uses two-dimensional monolayer culture, which reproduces neither tumour architecture nor diffusion gradients. Aim: To compare bone marrow (BMMSC-CM) and dental pulp (DPSC-CM) stem cell-conditioned media on the metabolic activity of OECM-1 oral squamous carcinoma cells across 2D monolayer, 3D spheroid, and 3D scaffold culture. Methods: OECM-1 cells in each format were treated with 10% or 50% BMMSC-CM or DPSC-CM, or medium alone in three independent biological replicates. Metabolic activity was measured on days 3, 5, and 7 by Alamar Blue (monolayer, scaffold) and ATPlite 3D (spheroids). One-way ANOVA with Tukey’s HSD was applied at each time point, plus 2-way ANOVA for the concentration × day interaction. Results: In monolayer, DPSC-CM reduced metabolic activity significantly only at Day 7 ( P = 0.004), with a significant concentration × day interaction ( P = 0.007); BMMSC-CM had no significant effect ( P = 0.139–0.442). In spheroids, the direction reversed; DPSC-CM increased ATP content at Days 3 ( P = 0.020) and 5 ( P = 0.001) but not Day 7 ( P = 0.271); BMMSC-CM showed significant concentration-dependent differences at Days 3 ( P = 0.006) and 7 ( P = 0.010) but not Day 5 ( P = 0.878). In scaffolds, neither medium had a significant effect ( P = 0.195; P = 0.455). Conclusions: Effects were model-dependent and, for DPSC-CM, reversed between monolayer and spheroid culture; two 3D models of the same cell line did not agree. Monolayer findings should not be extrapolated without mechanistic characterisation.
Abstract Background: Salivary gland carcinomas (SGCs) are rare neoplasms characterized by marked histological heterogeneity and a lack of uniform treatment strategies. Human epidermal growth factor receptor 2 (HER2) has emerged as a potential biomarker and therapeutic target in various epithelial malignancies. However, its expression profile in SGCs remains underexplored. This study aimed to evaluate the immunohistochemical expression of HER2 in malignant SGCs and to compare it with normal salivary gland tissues, with the intent of assessing its therapeutic relevance across different histological subtypes. Materials and Methods: Formalin-fixed, paraffin-embedded specimens of malignant SGCs ( n = 20) and normal salivary glands ( n = 20) were assessed using immunohistochemistry. HER2 expression was scored according to the American Society of Clinical Oncology/College of American Pathologists (0 to 3+), and findings were statistically analysed across subtypes. Results: HER2 expression was absent (score 0) in all normal salivary gland samples. Among the malignant tumours, 15% (3/20) showed weak membranous immunoreactivity (score 1+), while none demonstrated moderate or strong positivity (2+ or 3+). HER2 expression was observed in 40% of adenoid cystic carcinoma (ACC) cases and 20% of polymorphous adenocarcinoma (PAC) cases. No expression was observed in mucoepidermoid carcinoma, acinic cell carcinoma, or carcinoma ex pleomorphic adenoma. Statistical comparison revealed no significant difference in HER2 expression among subtypes ( P = 0.365). Conclusions: The study indicates weak HER2 expression in a subset of malignant salivary gland tumours, specifically in ACC and PACs, with complete absence in normal tissues. These findings suggest limited but potentially meaningful scope for HER2-targeted therapies in select histological subtypes.
Abstract Oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMDs) are major challenges in global health. Convolutional neural network (CNN)-based deep learning and artificial intelligence (AI) models have demonstrated superior results when used automatically. However, no prior meta-analysis examines the pooled diagnostic performance of AI models. An electronic search was performed in MEDLINE via PubMed, Scopus, Web of Science, Springer Link, and Elsevier up to 30 June 2025, without a period restriction. The articles that investigated OSCC and OPMDs using AI and CNN-based deep learning on clinicopathological images were included for review. Quality assessment of articles was performed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). A bivariate random-effects model was used to estimate the pooled sensitivity and specificity, I² values, receiver-operating characteristic (ROC) curves, and diagnostic odds ratios (DOR) were calculated using RevMan 5.4 and Open Meta-Analyst for Sierra software. Publication bias was evaluated using Deeks’ funnel plot. Only ten studies, totalling more than 47,124 clinical photos, satisfied the inclusion requirements out of the 175 original records that were found. Transfer learning is a common training method, and the majority of research employed CNN-based models for analysis, such as ResNet, EfficientNet, VGG, InceptionV3, and DenseNet. The results showed that the pooled diagnostic odds ratio was 87.43 (95% confidence interval [CI]: 42.18–181.26) with a pooled sensitivity of 0.86 (95% CI: 0.84–0.89), and pooled specificity of 0.92 (95% CI: 0.89–0.95). There is no statistically significant evidence of publication bias according to the Deeks funnel plot asymmetry test ( P = 0.31).
Abstract Background: Oral epithelial dysplasia (OED) represents a histopathological spectrum of oral potentially malignant disorders that may progress to oral squamous cell carcinoma (OSCC). Angiogenesis plays a pivotal role in tumour initiation, progression, and metastasis. Endoglin (CD105) is a specific marker of neoangiogenesis, while mast cells are known to influence angiogenesis through the release of pro-angiogenic mediators. Evaluating CD105-based microvessel density (MVD) and toluidine blue-stained mast cell density (MCD) may provide valuable insight into the biological behaviour of dysplastic and malignant oral lesions Aims: To assess and compare endoglin (CD105) expression and mast cell density across different grades of oral epithelial dysplasia and oral squamous cell carcinoma, and to evaluate their correlation with disease progression. Materials and Methods: Histopathologically confirmed cases of oral epithelial dysplasia (mild, moderate, and severe) and oral squamous cell carcinoma (well, moderately, and poorly differentiated) were included. Pyogenic granuloma served as the control group. Immunohistochemical staining for endoglin (CD105) was performed to evaluate mean vascular density, and mast cells were identified using toluidine blue stain. Quantification was carried out in selected hotspot areas under high-power magnification. Data were analysed using appropriate statistical tests. A P value <0.05 was considered statistically significant. Results: A progressive increase in Endoglin-positive microvessel density was observed from dysplasia to carcinoma, with the highest values in poorly differentiated OSCC. Mast cell density showed an increase in dysplastic lesions but demonstrated a variable trend with advancing carcinoma grades. Conclusions: Angiogenesis, as assessed by endoglin (CD105), increases significantly with disease progression from dysplasia to carcinoma. Mast cells may play a modulatory role in early angiogenesis, though their role in advanced malignancy remains controversial.
