DNA content and clinicopathological features aid in distinguishing ameloblastic carcinoma from ameloblastoma.

BACKGROUND: Ameloblastoma and ameloblastic carcinoma are epithelial odontogenic tumors that can be morphologically similar. In the present study, we evaluated the DNA content and Ki-67 index in the two tumors. METHODS: The paraffin blocks of the tumors were selected to obtain sections for the immunohistochemical reactions and preparation of the cell suspension for acquisition in a flow cytometer. The Random Forest package of the R software was used to verify the contribution of each variable to classify lesions into ameloblastoma or ameloblastic carcinoma. RESULTS: Thirty-two ameloblastoma and five ameloblastic carcinoma were included in the study. In our sample, we did not find statistically significant differences in Ki-67 labeling rates. A higher fraction of cells in 2c (G1) was correlated with the diagnosis of ameloblastoma, whereas higher rates of 5c-exceeding rate (5cER) were correlated with ameloblastic carcinoma. The Random Forest model highlighted histopathological findings and parameters of DNA ploidy study as important features for distinguishing ameloblastoma from ameloblastic carcinoma. CONCLUSION: Our findings suggest that the parameters of the DNA ploidy study can be ancillary tools in the classification of ameloblastoma and ameloblastic carcinoma.

Feasibility study of ResNet-50 in the distinction of intraoral neural tumors using histopathological images.

BACKGROUND: Neural tumors are difficult to distinguish based solely on cellularity and often require immunohistochemical staining to aid in identifying the cell lineage. This article investigates the potential of a Convolutional Neural Network for the histopathological classification of the three most prevalent benign neural tumor types: neurofibroma, perineurioma, and schwannoma. METHODS: A model was developed, trained, and evaluated for classification using the ResNet-50 architecture, with a database of 30 whole-slide images stained in hematoxylin and eosin (106, 782 patches were generated from and divided among the training, validation, and testing subsets, with strategies to avoid data leakage). RESULTS: The model achieved an accuracy of 70% (64% normalized), and showed satisfactory results for differentiating two of the three classes, reaching approximately 97% and 77% as true positives for neurofibroma and schwannoma classes, respectively, and only 7% for perineurioma class. The AUROC curves for neurofibroma and schwannoma classes was 0.83%, and 0.74% for perineurioma. However, the specificity rate for the perineurioma class was greater (83%) than in the other two classes (neurofibroma with 61%, and schwannoma with 60%). CONCLUSION: This investigation demonstrated significant potential for proficient performance with a limitation regarding the perineurioma class (the limited feature variability observed contributed to a lower performance).

Oral manifestations of amyloidosis and the diagnostic applicability of oral tissue biopsy.

BACKGROUND: Amyloidosis exhibits a variable spectrum of systemic signs and oral manifestations that can be difficult to diagnose. This study aimed to characterize the clinical, demographic, and microscopic features of amyloidosis in the oral cavity. METHODS: This collaborative study involved three Brazilian oral pathology centers and described cases with a confirmed diagnosis of amyloidosis on available oral tissue biopsies. Clinical data were obtained from medical records. H&E, Congo-red, and immunohistochemically stained slides were analyzed. RESULTS: Twenty-six oral biopsies from 23 individuals (65.2% males; mean age: 59.6 years) were included. Oral involvement was the first sign of the disease in 67.0% of cases. Two patients had no clinical manifestation in the oral mucosa, although the histological analysis confirmed amyloid deposition. Amyloid deposits were distributed in perivascular (88.0%), periacinar and periductal (80.0%), perineurial (80.0%), endoneurial (33.3%), perimuscular (88.2%), intramuscular (94.1%), and subepithelial (35.3%) sites as well as around fat cells (100.0%). Mild/moderate inflammation was found in 65.4% of cases and 23.1% had giant cells. CONCLUSIONS: Amyloid deposits were consistently found in oral tissues, exhibiting distinct deposition patterns. Oral biopsy is less invasive than internal organ biopsy and enables the reliable identification of amyloid deposits even in the absence of oral manifestations. These findings corroborate the relevance of oral biopsy for the diagnosis of amyloidosis.

Artificial intelligence and radiomics in the diagnosis of intraosseous lesions of the gnathic bones: A systematic review.

BACKGROUND: The purpose of this systematic review (SR) is to gather evidence on the use of machine learning (ML) models in the diagnosis of intraosseous lesions in gnathic bones and to analyze the reliability, impact, and usefulness of such models. This SR was performed in accordance with the PRISMA 2022 guidelines and was registered in the PROSPERO database (CRD42022379298). METHODS: The acronym PICOS was used to structure the inquiry-focused review question "Is Artificial Intelligence reliable for the diagnosis of intraosseous lesions in gnathic bones?" The literature search was conducted in various electronic databases, including PubMed, Embase, Scopus, Cochrane Library, Web of Science, Lilacs, IEEE Xplore, and Gray Literature (Google Scholar and ProQuest). Risk of bias assessment was performed using PROBAST, and the results were synthesized by considering the task and sampling strategy of the dataset. RESULTS: Twenty-six studies were included (21 146 radiographic images). Ameloblastomas, odontogenic keratocysts, dentigerous cysts, and periapical cysts were the most frequently investigated lesions. According to TRIPOD, most studies were classified as type 2 (randomly divided). The F1 score was presented in only 13 studies, which provided the metrics for 20 trials, with a mean of 0.71 (±0.25). CONCLUSION: There is no conclusive evidence to support the usefulness of ML-based models in the detection, segmentation, and classification of intraosseous lesions in gnathic bones for routine clinical application. The lack of detail about data sampling, the lack of a comprehensive set of metrics for training and validation, and the absence of external testing limit experiments and hinder proper evaluation of model performance.

Histopathological risk assessment in multisite epithelial dysplasia: A meta-analysis.

OBJECTIVE: Histopathological grading of oral epithelial dysplasia (OED) is the current standard for stratifying cancer progression risk but is associated with subjectivity and variability. This problem is not commonly seen regarding the grading of epithelial dysplasia in other sites. This systematic review aims to compare grading systems for oral, anal, penile, and cervical epithelial dysplasia to determine their predictive accuracy for recurrence and malignant transformation (MT) outcomes. METHODS: The review protocol was registered in PROSPERO (CRD42023403035) and was reported according to the PRISMA checklist. A comprehensive search was performed in the main databases and gray literature. The risk of bias in individual studies was analyzed using the Joanna Briggs Institute checklist for each study design. RESULTS: Forty-six studies were deemed eligible and included in this systematic review, of which 45 were included in the quantitative analysis. Meta-analysis revealed that the binary system demonstrated a higher predictive ability for MT/recurrence of OED compared to multilevel systems. Higher predictive accuracy of MT was also observed for binary grading systems in anal intraepithelial neoplasia. CONCLUSIONS: No significant difference was found between the current grading systems of epithelial dysplasia in different body parts. However, binary grading systems have shown better clinical outcomes.

ChatGPT and dentistry: a step toward the future.

This article aims to explore the integration of ChatGPT, an advanced conversational artificial intelligence model, in the field of dentistry. The review primarily consists of information related to the capabilities and functionalities of ChatGPT and how these abilities can aid dental professionals. This study includes data from research papers, case studies, and relevant literature on language models, as well as papers on dentistry, patient communication, dental education, and clinical decision-making. A systematic approach was used to select relevant studies and literature. The selection criteria focused on papers that specifically discussed the integration of language models, ChatGPT in particular, in dentistry and their applications. The study findings revealed that ChatGPT has significant potential to revolutionize dentistry by offering various applications and benefits. It can enhance patient engagement and understanding through personalized oral health information and guidance. In dental education, ChatGPT can provide interactive learning, case studies, and virtual patient simulations. ChatGPT can also assist researchers in analyzing dental literature, identifying patterns, and generating insights. Moreover, it supports dentists with evidence-based recommendations, treatment options, and diagnostic support. Integrating ChatGPT in dentistry can be highly beneficial, but it is crucial to address ethical considerations, accuracy, and privacy concerns. Responsible implementation and continuous improvement of its functionalities are necessary to ensure that patient care and outcomes are improved.

Development and validation of a multivariable model for prediction of malignant transformation and recurrence of oral epithelial dysplasia.

BACKGROUND: Oral epithelial dysplasia (OED) is the precursor to oral squamous cell carcinoma which is amongst the top ten cancers worldwide. Prognostic significance of conventional histological features in OED is not well established. Many additional histological abnormalities are seen in OED, but are insufficiently investigated, and have not been correlated to clinical outcomes. METHODS: A digital quantitative analysis of epithelial cellularity, nuclear geometry, cytoplasm staining intensity and epithelial architecture/thickness is conducted on 75 OED whole-slide images (252 regions of interest) with feature-specific comparisons between grades and against non-dysplastic/control cases. Multivariable models were developed to evaluate prediction of OED recurrence and malignant transformation. The best performing models were externally validated on unseen cases pooled from four different centres (n = 121), of which 32% progressed to cancer, with an average transformation time of 45 months. RESULTS: Grade-based differences were seen for cytoplasmic eosin, nuclear eccentricity, and circularity in basal epithelial cells of OED (p < 0.05). Nucleus circularity was associated with OED recurrence (p = 0.018) and epithelial perimeter associated with malignant transformation (p = 0.03). The developed model demonstrated superior predictive potential for malignant transformation (AUROC 0.77) and OED recurrence (AUROC 0.74) as compared with conventional WHO grading (AUROC 0.68 and 0.71, respectively). External validation supported the prognostic strength of this model. CONCLUSIONS: This study supports a novel prognostic model which outperforms existing grading systems. Further studies are warranted to evaluate its significance for OED prognostication.

Machine learning for detection and classification of oral potentially malignant disorders: A conceptual review.

Oral potentially malignant disorders represent precursor lesions that may undergo malignant transformation to oral cancer. There are many known risk factors associated with the development of oral potentially malignant disorders, and contribute to the risk of malignant transformation. Although many advances have been reported to understand the biological behavior of oral potentially malignant disorders, their clinical features that indicate the characteristics of malignant transformation are not well established. Early diagnosis of malignancy is the most important factor to improve patients' prognosis. The integration of machine learning into routine diagnosis has recently emerged as an adjunct to aid clinical examination. Increased performances of artificial intelligence AI-assisted medical devices are claimed to exceed the human capability in the clinical detection of early cancer. Therefore, the aim of this narrative review is to introduce artificial intelligence terminology, concepts, and models currently used in oncology to familiarize oral medicine scientists with the language skills, best research practices, and knowledge for developing machine learning models applied to the clinical detection of oral potentially malignant disorders.

Machine learning concepts applied to oral pathology and oral medicine: A convolutional neural networks' approach.

INTRODUCTION: Artificial intelligence models and networks can learn and process dense information in a short time, leading to an efficient, objective, and accurate clinical and histopathological analysis, which can be useful to improve treatment modalities and prognostic outcomes. This paper targets oral pathologists, oral medicinists, and head and neck surgeons to provide them with a theoretical and conceptual foundation of artificial intelligence-based diagnostic approaches, with a special focus on convolutional neural networks, the state-of-the-art in artificial intelligence and deep learning. METHODS: The authors conducted a literature review, and the convolutional neural network's conceptual foundations and functionality were illustrated based on a unique interdisciplinary point of view. CONCLUSION: The development of artificial intelligence-based models and computer vision methods for pattern recognition in clinical and histopathological image analysis of head and neck cancer has the potential to aid diagnosis and prognostic prediction.

FGFR1 is an important prognostic factor in oral leukoplakia and tongue squamous cell carcinoma.

BACKGROUND: Fibroblast growth factor receptor 1 is a potential prognostic factor for tongue squamous cell carcinoma and is associated with oral epithelial dysplasia grade in oral leukoplakia. METHODS: Thirty cases of tongue squamous cell carcinoma and 30 cases of oral leukoplakia were analyzed. Fibroblast growth factor receptor 1 and phosphorylated Akt protein expression were analyzed by immunohistochemistry and quantified using a digital algorithm. Fibroblast growth factor receptor 1 gene amplification was analyzed by fluorescent in situ hybridization in the tongue squamous cell carcinoma cases. RESULTS: Clinical appearance and dysplasia grade were correlated with oral leukoplakia malignant transformation. Oral leukoplakia cases presenting high fibroblast growth factor receptor 1 expression showed a higher risk of malignant transformation (p = 0.016, HR: 7.3, 95% CI: 1.4-37.4). Phosphorylated Akt showed faint to no expression in oral leukoplakia, which did not correlate with dysplasia grade or malignant transformation. High expression of fibroblast growth factor receptor 1 and phosohorylated Akt were associated with poor overall survival and disease-free survival in tongue squamous cell carcinoma, although only fibroblast growth factor receptor 1 expression was significantly associated with poor overall survival (p = 0.024; HR: 4.9, 95% CI: 1.2-19.9). Cases presenting double fibroblast growth factor receptor 1/phosphorylated Akt overexpression (n = 8) showed markedly impaired overall survival (p = 0.020; HR: 6.4, 95% CI: 1.3-31.1) and disease-free survival (p = 0.001, HR: 13.0, 95% CI: 3.0-55.7). Fibroblast growth factor receptor 1 amplification was observed in 16.6% of tongue squamous cell carcinoma cases, being correlated with vascular and neural invasion (p = 0.001 and 0.017, respectively), but not with fibroblast growth factor receptor 1 protein expression, overall survival, or disease-free survival. CONCLUSION: Fibroblast growth factor receptor 1 protein expression is an important prognostic factor in oral leukoplakia and tongue squamous cell carcinoma.

Symptomatic subgemmal neurogenous plaque in patients with COVID-19: Is there an association?

BACKGROUND: Subgemmal neurogenous plaques (SNP) are composed of neural structures found in the posterolateral portion of the tongue, rarely biopsied as most of them are asymptomatic or eventually only clinically managed. We aimed to investigate a case series of possible correlation of symptomatic subgemmal neurogenous plaque (SNP) with coronavirus disease 2019 (COVID-19). METHODS: Eleven formalin-fixed paraffin-embedded cases from patients with previous confirmed COVID-19 (by RT-PCR) were retrieved from two pathology files. Histological sections were morphologically studied, and then submitted to immunohistochemical reactions against S-100 and neurofilament proteins, neuron-specific enolase, Glial fibrillary acidic protein (GFAP), synaptophysin, CD56, Ki67, cytokeratins (7, 8-18, 19, 20), nucleocapsid and spike proteins (SARS-CoV-1; and -2) and epithelial membrane antigen (EMA) antibodies. Clinical data were retrieved from the patients' medical files, including the symptoms and the complete history of the progression of the disease. RESULTS: The patients who had COVID-19 included in this study experienced painful lesions in the tongue that corresponded to prominent or altered SNP. Microscopically, neural structures were positive for S-100, GFAP and neurofilament protein. And the cellular proliferative index (by Ki-67) was very low. CONCLUSION: Thus, based on the current results, we hypothesize that symptomatic SNP may be a late manifestation of COVID-19 infection.

Deep learning applied to the histopathological diagnosis of ameloblastomas and ameloblastic carcinomas.

BACKGROUND: Odontogenic tumors (OT) are composed of heterogeneous lesions, which can be benign or malignant, with different behavior and histology. Within this classification, ameloblastoma and ameloblastic carcinoma (AC) represent a diagnostic challenge in daily histopathological practice due to their similar characteristics and the limitations that incisional biopsies represent. From these premises, we wanted to test the usefulness of models based on artificial intelligence (AI) in the field of oral and maxillofacial pathology for differential diagnosis. The main advantages of integrating Machine Learning (ML) with microscopic and radiographic imaging is the ability to significantly reduce intra-and inter observer variability and improve diagnostic objectivity and reproducibility. METHODS: Thirty Digitized slides were collected from different diagnostic centers of oral pathology in Brazil. After performing manual annotation in the region of interest, the images were segmented and fragmented into small patches. In the supervised learning methodology for image classification, three models (ResNet50, DenseNet, and VGG16) were focus of investigation to provide the probability of an image being classified as class0 (i.e., ameloblastoma) or class1 (i.e., Ameloblastic carcinoma). RESULTS: The training and validation metrics did not show convergence, characterizing overfitting. However, the test results were satisfactory, with an average for ResNet50 of 0.75, 0.71, 0.84, 0.65, and 0.77 for accuracy, precision, sensitivity, specificity, and F1-score, respectively. CONCLUSIONS: The models demonstrated a strong potential of learning, but lack of generalization ability. The models learn fast, reaching a training accuracy of 98%. The evaluation process showed instability in validation; however, acceptable performance in the testing process, which may be due to the small data set. This first investigation opens an opportunity for expanding collaboration to incorporate more complementary data; as well as, developing and evaluating new alternative models.

The use of deep learning state-of-the-art architectures for oral epithelial dysplasia grading: A comparative appraisal.

BACKGROUND: Dysplasia grading systems for oral epithelial dysplasia are a source of disagreement among pathologists. Therefore, machine learning approaches are being developed to mitigate this issue. METHODS: This cross-sectional study included a cohort of 82 patients with oral potentially malignant disorders and correspondent 98 hematoxylin and eosin-stained whole slide images with biopsied-proven dysplasia. All whole-slide images were manually annotated based on the binary system for oral epithelial dysplasia. The annotated regions of interest were segmented and fragmented into small patches and non-randomly sampled into training/validation and test subsets. The training/validation data were color augmented, resulting in a total of 81,786 patches for training. The held-out independent test set enrolled a total of 4,486 patches. Seven state-of-the-art convolutional neural networks were trained, validated, and tested with the same dataset. RESULTS: The models presented a high learning rate, yet very low generalization potential. At the model development, VGG16 performed the best, but with massive overfitting. In the test set, VGG16 presented the best accuracy, sensitivity, specificity, and area under the curve (62%, 62%, 66%, and 65%, respectively), associated with the higher loss among all Convolutional Neural Networks (CNNs) tested. EfficientB0 has comparable metrics and the lowest loss among all convolutional neural networks, being a great candidate for further studies. CONCLUSION: The models were not able to generalize enough to be applied in real-life datasets due to an overlapping of features between the two classes (i.e., high risk and low risk of malignization).

Synchronous odontogenic tumors: A systematic review.

This systematic review aimed to incorporate published information about synchronous odontogenic tumors (SOTs) with an analysis of the demographic and clinical characteristics from the cases published in the literature. Case reports and case series of SOT were searched in PubMed, Web of Science, Scopus, and EMBASE. A descriptive statistical analysis was performed. Twenty-eight studies comprising 30 cases of SOTs were included. Considering all cases published, SOTs mostly occurred simultaneously in the maxilla and mandible (n = 19/63.3%). Lesions were bifocal in 13 (43.3% of all the 30 cases) and multifocal in 17 cases (56.7% of all the 30 cases). All SOTs available in the literature presented the same type of lesion, and two of them also involved another different SOT (n = 2/6.7% of all the 30 cases). Out of all published cases, the most frequent SOTs in the literature were odontomas (n = 10/33.3% of all the 30 cases), squamous odontogenic tumors (OTs) (n = 8/26.7% of all the 30 cases), calcifying epithelial OTs (n = 8/26.7% of all the 30 cases), and adenomatoid OTs (n = 2/6.7% of all the 30 cases). Considering all SOTs cases included, the overall recurrence was 13.3%. Inside a subgroup of the lesion, synchronous calcifying epithelial OT presented the highest (25%). Five cases (16.7% of all the 30 cases) had a previously associated syndrome, with two cases of Schimmelpenning syndrome being reported. Among published SOTs, odontomas were the most common. All SOTs available in the scientific literature showed the same type of OT and mainly affected both jaws simultaneously. Only a few of these cases were associated with a syndrome.

Prognostic outcomes of oral squamous cell carcinoma derived from proliferative verrucous leukoplakia: A systematic review.

OBJECTIVE: This study aimed to evaluate prognostic outcomes of PVL-derived oral squamous cell carcinomas (P-OSCC) based on recurrence, new primary tumour, metastasis and survival information. STUDY DESIGN: Five databases and grey literature were searched electronically with the following main keywords (proliferative verrucous leukoplakia, squamous cell carcinoma and malignant transformation) to answer the following review question: 'Are survival outcomes for P-OSCC worse?' based on the PECOS principle. The Joanna Briggs Institute Critical Appraisal tool was used to identify possible biases and assess the quality of each of the primary studies. RESULTS: A total of 21 articles met the inclusion criteria, and the results of this systematic review suggest that P-OSCC can recur and generate new primary tumours; however, metastases are rare. Thus, most patients remain alive for an average period of 5 years. CONCLUSION: Apparently, P-OSCC has better clinical prognostic characteristics than conventional OSCC. There is a lack of information on the main prognostic outcomes of P-OSCC; therefore, specific studies must be performed to achieve a better comparison between P-OSCC and conventional OSCC progression.

Ewing's sarcoma of the head and neck: A systematic review.

OBJECTIVE: The aim of the present study was to conduct a systematic review of head and neck Ewing sarcoma (ES) concerning patients' demographic and clinical features, histopathological findings, treatment, follow-up, and survival rate. MATERIALS AND METHODS: An electronic search was undertaken in four databases. Articles describing case reports or case series were included. Outcomes were evaluated by the Kaplan-Meier method along with Cox regression. RESULTS: The search yielded 186 studies describing 227 ES cases. The mean age was 22.7 years, and males were slightly more affected. Interestingly, more than half the cases were diagnosed up to 20 years. The respiratory tract was the most reported site, followed by the jawbones. Clinically, symptomatic swelling or nodules were described, with a mean duration of 4 months. Management involved multimodal treatment regimens. Local recurrence, lymph node and distant metastasis were observed in 10.7%, 12.6%, and 20.3% of cases, respectively. Statistical analysis revealed that older patients with distant metastasis had a lower overall survival rate (p < 0.05). CONCLUSION: This study provides an overall view of head and neck ES that can assist oral and maxillofacial pathologists with the diagnosis and extend the knowledge of surgeons and oncologists about this condition.

Oral squamous cell carcinomas and oral potentially malignant disorders: A Latin American study.

OBJECTIVE: To determine the frequency of oral squamous cell carcinoma (OSCC) associated or not with oral potentially malignant disorders (OPMD), and the epidemiological profile and traditional risk factors in Latin America. METHODS: A retrospective observational study was conducted in 17 Latin American centres. There were included cases of OSCC, analysing age, gender, OSCC and their association with previous OPMD. Clinicopathological variables were retrieved. The condition of sequential-OSCC versus OSCC-de novo (OSCC-dn) was analysed concerning the aforementioned variables. Quantitative variables were analysed using Student's t-test, and qualitative variables with chi-square. RESULTS: In total, 2705 OSCC were included with a mean age of 62.8 years old. 55.8% were men. 53.75% of the patients were smokers and 38% were common drinkers. The lateral tongue border was the most affected site (24.65%). There were regional variations in OPMD, being leukoplakia the most frequent. Of the overall 2705 OSCC cases, 81.4% corresponded to OSCC-dn, while s-OSCC were 18.6%. Regarding lip vermillion SCC, 35.7% corresponded to de novo lip SCC and 64.3% were associated with previous OPMD. CONCLUSIONS: In Latin America, OSCC-dn seems to be more frequent with regional variations of some clinical and histopathological features. Further prospective studies are needed to analyse this phenomenon.

Sociodemographic and clinical characterization of cases of 1,103 non-syndromic and 66 syndromic odontogenic keratocyst: a Brazilian multicenter study.

OBJECTIVES: This multicenter study aimed to evaluate cases of non-syndrome and syndromic odontogenic keratocyst, as well as cases of recurrence within these two groups. METHODS: This descriptive, analytical, retrospective cross-sectional study evaluated the sex, age and presence of multiple lesions in 1,169 individuals seen at 10 Brazilian oral and maxillofacial pathology centers. Of these, 1,341 odontogenic keratocysts were analyzed regarding clinical diagnosis, size, site, imaging appearance, signs and symptoms, type of biopsy, treatment, and recurrence. RESULTS: There was a similar distribution by sex. The median age of non-syndromic and syndromic patients was 32 and 17.5 years, respectively. The posterior mandible was the site most affected by small and large lesions in both groups and in recurrent cases. Unilocular lesions were more frequent, also in recurrent cases. Mainly small lesions showed this imaging appearance. Signs and symptoms were absent in most cases. Conservative treatment was the most frequent modality in all age groups, regardless of the patient's condition and recurrence. Recurrences were uncommon. CONCLUSION: This study showed a higher frequency of non-syndromic keratocysts in the population. Clinicopathological features related to the involvement of multiple sites, age, and recurrence may differ between syndromic and non-syndromic cases. Furthermore, we found an association between lesion size and some clinical features and between the time interval to recurrence and the syndromic spectrum. CLINICAL RELEVANCE: To contribute to a better understanding of the distribution and association between clinical, imaging, and sociodemographic characteristics in each spectrum of the lesion.

Adenoid ameloblastoma harbors beta-catenin mutations.

Adenoid ameloblastoma is a very rare benign epithelial odontogenic tumor characterized microscopically by epithelium resembling conventional ameloblastoma, with additional duct-like structures, epithelial whorls, and cribriform architecture. Dentinoid deposits, clusters of clear cells, and ghost-cell keratinization may also be present. These tumors do not harbor BRAF or KRAS mutations and their molecular basis appears distinct from conventional ameloblastoma but remains unknown. We assessed CTNNB1 (beta-catenin) exon 3 mutations in a cohort of 11 samples of adenoid ameloblastomas from 9 patients. Two of the 9 patients were female and 7 male and in 7/9 patients the tumors occurred in the maxilla. Tumors of 4 of these 9 patients harbored CTNNB1 mutations, specifically p.Ser33Cys, p.Gly34Arg, and p.Ser37Phe. Notably, for one patient 3 samples were analyzed including the primary tumour and two consecutive recurrences, and results were positive for the mutation in all three tumors. Therefore, 6/11 samples tested positive for the mutation. In the 6 mutation-positive samples, ghost cells were present in only 2/6, indicating beta-catenin mutations are not always revealed by ghost cell formation. Dentinoid matrix deposition was observed in 5/6 mutation-positive samples and clear cells in all 6 cases. None of the cases harbored either BRAF or KRAS mutations. Beta-catenin immunoexpression was assessed in the samples of 8 patients. Except for one wild-type case, all cases showed focal nuclear expression irrespective of the mutational status. Together with the absence of BRAF mutation, the detection of beta-catenin mutation in adenoid ameloblastomas supports its classification as a separate entity, and not as a subtype of ameloblastoma. The presence of this mutation may help in the diagnosis of challenging cases.

Expression of mitochondrial dynamic markers in adenoid cystic carcinoma.

BACKGROUND: Mitochondrial fission and fusion processes are known as mitochondrial dynamics and the occurrence of imbalances in the mitochondrial activity is related to the pathogenesis of many human cancers. However, the importance of mitochondrial dynamics in malignant salivary gland tumours remains unknown. Therefore, we aimed to investigate its prognostic significance in adenoid cystic carcinoma. METHODS: Fifty-seven formalin-fixed paraffin-embedded cases were retrieved and disposed in tissue microarray. Histological sections were submitted to immunohistochemical reactions against AMT, DRP1, FIS1, MFN1, MFN2 and OPA1 proteins. Clinical data were retrieved from the patients' medical files, including specific and disease-free survival data. RESULTS: It was observed that 50.9% of the cases were strongly positive for AMT and DRP1, and 49.1%, 21.1%, 22.8% and 24.6% strongly positive for FIS1, MFN1, MFN2 and OPA1, respectively. Reactions were observed in both epithelial and myoepithelial components of the tumour. The higher expression of MFN2 was associated with solid microscopic pattern (p = 0.016). DRP1 overexpression showed a trend towards a shorter overall survival (p = 0.054), while negative/weak OPA1 showed a trend towards a lower disease-free survival (p = 0.051) in the univariate analysis, but no mitochondrial marker represented an independent prognostic determinant under multivariate analysis. CONCLUSION: In conclusion, mitochondrial dynamics markers do not seem to carry a prognostic significance for adenoid cystic carcinoma patients, but these proteins may play an important role in its pathogenesis.