Artificial Intelligence Applications in Oral Cancer and Oral Dysplasia.

Oral squamous cell carcinoma (OSCC) is a highly unpredictable disease with devastating mortality rates that have not changed over the past decades, in the face of advancements in treatments and biomarkers, which have improved survival for other cancers. Delays in diagnosis are frequent, leading to more disfiguring treatments and poor outcomes for patients. The clinical challenge lies in identifying those patients at the highest risk of developing OSCC. Oral epithelial dysplasia (OED) is a precursor of OSCC with highly variable behavior across patients. There is no reliable clinical, pathological, histological, or molecular biomarker to determine individual risk in OED patients. Similarly, there are no robust biomarkers to predict treatment outcomes or mortality in OSCC patients. This review aims to highlight advancements in artificial intelligence (AI)-based methods to develop predictive biomarkers of OED transformation to OSCC or predictive biomarkers of OSCC mortality and treatment response. Biomarkers such as S100A7 demonstrate promising appraisal for the risk of malignant transformation of OED. Machine learning-enhanced multiplex immunohistochemistry workflows examine immune cell patterns and organization within the tumor immune microenvironment to generate outcome predictions in immunotherapy. Deep learning (DL) is an AI-based method using an extended neural network or related architecture with multiple "hidden" layers of simulated neurons to combine simple visual features into complex patterns. DL-based digital pathology is currently being developed to assess OED and OSCC outcomes. The integration of machine learning in epigenomics aims to examine the epigenetic modification of diseases and improve our ability to detect, classify, and predict outcomes associated with epigenetic marks. Collectively, these tools showcase promising advancements in discovery and technology, which may provide a potential solution to addressing the current limitations in predicting OED transformation and OSCC behavior, both of which are clinical challenges that must be addressed in order to improve OSCC survival.

Artificial intelligence-based epigenomic, transcriptomic and histologic signatures of tobacco use in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) biomarker studies rarely employ multi-omic biomarker strategies and pertinent clinicopathologic characteristics to predict mortality. In this study we determine for the first time a combined epigenetic, gene expression, and histology signature that differentiates between patients with different tobacco use history (heavy tobacco use with ≥10 pack years vs. no tobacco use). Using The Cancer Genome Atlas (TCGA) cohort (n = 257) and an internal cohort (n = 40), we identify 3 epigenetic markers (GPR15, GNG12, GDNF) and 13 expression markers (IGHA2, SCG5, RPL3L, NTRK1, CD96, BMP6, TFPI2, EFEMP2, RYR3, DMTN, GPD2, BAALC, and FMO3), which are dysregulated in OSCC patients who were never smokers vs. those who have a ≥ 10 pack year history. While mortality risk prediction based on smoking status and clinicopathologic covariates alone is inaccurate (c-statistic = 0.57), the combined epigenetic/expression and histologic signature has a c-statistic = 0.9409 in predicting 5-year mortality in OSCC patients.

The Effect of Calcium Hydroxide Pastes on Isolated Vital Nerve Fibers.

INTRODUCTION: Calcium hydroxide pastes (CHPs), commonly used for disinfecting root canals during endodontic treatment, are generally considered safe. However, accidental extrusions result in minimal injuries and little to no discomfort, except when extruded pastes come into contact with nerve bundles, such as the inferior alveolar nerve. Currently, there is a lack of information about the possible role of specific paste vehicles on the extent of nerve injury. The purpose of this study was to compare the role that paste vehicles, such as water or methylcellulose, may play when nerve fibers are exposed to CHP. METHODS: Isolated sciatic nerves of Sprague-Dawley rats were exposed to either water-based or methylcellulose-based CHP for varying durations of time (30, 60, or 90 minutes). Histopathological changes, including axonal edema, myelin alterations, and loss of cellular outlines, were assessed, and the degrees of changes were compared using chi-square intraclass correlation coefficient tests. RESULTS: Both groups exposed to the pastes demonstrated varying degrees of histopathologic changes, including axonal edema, myelin changes, and loss of cellular outlines, at different exposure times. The water-based calcium hydroxide paste induced these changes more rapidly than the methylcellulose-based paste. Similar patterns were observed in the scanning electron microscopic findings. Exposure time emerged as an important difference in the effects of the 2 pastes. In each of these tests, all observations of water-based paste exposure were rated as moderate to severe, whereas the observed cellular changes (axonal, myelin, and intact cellular outline) were rated as mild to moderate after exposure to methylcellulose-based paste for the same exposure durations. The chi-square tests indicated a statistically significant association between the material and each of the outcomes (axonal changes: χ²15 = 81.0, P < .001; myelin changes: χ²15 = 81.0, P < .001; intact cellular outline, χ²15 = 81.0, P < .001). The intraclass correlation coefficient value was 0.93. CONCLUSIONS: The study demonstrates that axonal and myelin damage increase with longer exposure times, with water-based CHP causing more damage than methylcellulose-based CHP at each time point.