Difficulty in precise decision making on necessity of surgery is a major problem when managing oral squamous cell carcinomas (OSCCs) with clinically negative neck. Therefore, use of clinical and histopathological parameters in combination would be important to improve patient management. The main objective is to develop a model that predicts the presence of nodal metastasis in patients with OSCC.623 patients faced neck dissections with buccal mucosal or tongue squamous cell carcinoma (SCC) were selected from patients’ records. Demographic data, clinical information, nodal status, Depth of invasion (DOI) and pattern of invasion (POI) were recorded. The parameters which showed a significant association with nodal metastasis were used to develop a multivariable predictive model (PM). Univariate logistic regression was used to estimate the strengths of those associations in terms of odds ratios (OR). This showed statistically significant associations between status of the nodal metastasis and each of the following 4 histopathological parameters individually: size of the tumour (T), site, POI, and DOI. Specifically, OR of nodal metastasis for tongue cancers relative to buccal mucosal cancers was 1.89, P-value < 0.001. Similarly, ORs for POI type 3 and 4 relative to type 2 were 1.99 and 5.83 respectively. A similar relationship was found with tumour size; ORs for T2, T3, and T4 compared to T1 were 2.79, 8.27 and 8.75 respectively. These four histopathological parameters were then used to develop a predictive model for nodal metastasis. This model showed that probability of nodal metastasis is higher among tongue cancers with increasing POI, with increasing T, and with larger depths while other characteristics remained unchanged. The proposed model provides a way of using combinations of histopathological parameters to identify patients with higher risks of nodal metastasis for surgical management.

Harvesting, expanding, and re‐implanting osteogenic mesenchymal stem cells (MSCs) avoids the donor‐site morbidity associated with autogenous grafting from bone marrow. Mesenchymal stem cells sourced from the palatal periosteum could be an alternative to isolation of such cells using bone marrow aspiration procedures. For safe use in human therapy, MSCs should be expanded in culture medium that is free from animal or human‐derived serum. In this study we localized, quantified, and characterized MSCs from palatal periosteum cultured in serum‐free, xeno‐free Essential 8 medium. A portion of the palatal periosteum tissues from three patients were dual‐immunostained with MSC‐specific markers (CD105, CD90, and CD73). The remaining portions were expanded in culture, and the isolated MSCs were analyzed using flow cytometry and tri‐lineage differentiation. Palatal periosteum sections were found to contain CD105‐, CD90‐, and CD73‐positive cells. The cultured cells were 73.0 ± 6.7% (mean ± SD) positive for all three MSC‐specific markers and were without hematopoietic stem cell (HSC) markers 0.5 ± 0.3% (mean ± SD). Tri‐lineage differentiation analysis confirmed that palatal periosteum cells could become adipoblasts, chondroblasts, and osteoblasts. The results demonstrate that palatal‐derived MSCs could be detected in situ within small niches, and when expanded in serum‐free, xeno‐free medium represent a viable source of MSCs for clinical use.

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Background Lymph node metastasis in oral squamous cell carcinoma (OSCC) is influenced by clinical and histopathological variables. The aim of this study was to develop a simple model to predict nodal metastasis of OSCC in clinically negative necks (cN0). Methods Data from patients who underwent surgery for treatment of OSCC of the tongue or buccal mucosa with neck dissection were used for model development and validation. Results Nodal metastasis was significantly associated with gender, age, tumor size, site, pattern of invasion and depth of invasion on univariate analysis. All the five variables except age were retained at the variable selection step of the model development and were used in the final model because it was not significant at 0.10 significance level after adjusting for other variables. Regression coefficients of the model were used to estimate risks of nodal metastases for each combination of clinicopathological characteristics. A 10‐fold cross‐validation was used to assess the model. The average of the resultant 10 AUCs (along with its 95% confidence interval estimated using bootstrap) was used as the overall validated measure of the model. A risk chart was produced using probability of nodal metastasis predicted by the model for each combination of five characteristics. The model's ability to identify patients with nodal metastases as assessed by the area under the ROC curve (AUC) was 0.752. Conclusion The model based on established clinicopathological variables has been internally validated on a large cohort of patients and offers practicability for use in OSCCs of the tongue and buccal mucosa.