Nucleostemin upregulation and STAT3 activation as early events in oral epithelial dysplasia progression to squamous cell carcinoma

Type 17 immune response promotes oral epithelial cell proliferation in periodontitis

OBJECTIVES

This study aims to investigate the effects of type 17 immune response on the proliferation of oral epithelial cells in periodontitis.

DESIGN

A time-dependent ligature induced periodontitis mouse model was utilized to explore gingival hyperplasia and the infiltration of interleukin 17A (IL-17A) positive cells. Immunohistochemistry and flow cytometry were employed to determine the localization and expression of IL-17A in the ligature induced periodontitis model. A pre-existing single-cell RNA sequencing dataset, comparing individuals affected by periodontitis with healthy counterparts, was reanalyzed to evaluate IL-17A expression levels. We examined proliferation markers, including proliferating cell nuclear antigen (PCNA), signal transducer and activator of transcription (STAT3), Yes-associated protein (YAP), and c-JUN, in the gingival and tongue epithelium of the periodontitis model. An anti-IL-17A agent was administered daily to observe proliferative changes in the oral mucosa within the periodontitis model. Cell number quantification, immunofluorescence, and western blot analyses were performed to assess the proliferative responses of human normal oral keratinocytes to IL-17A treatment in vitro.

RESULTS

The ligature induced periodontitis model exhibited a marked infiltration of IL-17A-positive cells, alongside significant increase in thickness of the gingival and tongue epithelium. IL-17A triggers the proliferation of human normal oral keratinocytes, accompanied by upregulation of PCNA, STAT3, YAP, and c-JUN. The administration of an anti-IL-17A agent attenuated the proliferation in oral mucosa.

CONCLUSIONS

These findings indicate that type 17 immune response, in response to periodontitis, facilitates the proliferation of oral epithelial cells, thus highlighting its crucial role in maintaining the oral epithelial barrier.

New insights into the role of the oral leukoplakia microenvironment in malignant transformation

Oral leukoplakia is the most frequent and potentially malignant lesion of the oral cavity. Although dysplasia grading remains the main factor for risk assessment, challenges persist in determining the exact risk of transformation, and the literature has focused on studying alternative biomarkers. The interaction between dysplastic epithelial cells and the microenvironment starts early, and the communication is mainly mediated by lymphocytes, inflammatory factors, fibroblasts, and the extracellular matrix, leading to dysplastic progression. Leukoplakia-infiltrating leukocytes (LILs) and leukoplakia-associated fibroblasts (LAFs) play crucial roles in the dysplastic microenvironment. The immune response is related to intraepithelial T lymphocyte infiltration, mechanisms of immunosuppression coordinated by regulatory T cells, M2 macrophage polarization, and increased numbers of Langerhans cells; in contrast, fibroblastic and extracellular matrix factors are associated with increased numbers of pro-tumorigenic myofibroblasts, increased expression of metalloproteinases vs. decreased expression of TIMPs, and increased expression of chemokines and other inflammatory mediators. The microenvironment offers insights into the progression of leukoplakia to carcinoma, and understanding the complexity of the oral microenvironment in potentially malignant diseases aids in determining the risk of malignant transformation and proposing new therapeutic alternatives.

Oral Cavity Squamous Cell Carcinoma: Review of Pathology, Diagnosis, and Management

Squamous cell carcinoma of the oral cavity presents a significant global health burden, primarily due to risk factors such as tobacco smoking, smokeless tobacco use, heavy alcohol consumption, and betel quid chewing. Common clinical manifestations of oral cavity cancer include visible lesions and sores, often accompanied by pain in advanced stages. Diagnosis relies on a comprehensive assessment involving detailed history, physical examination, and biopsy. Ancillary imaging studies and functional evaluations aid in accurate staging and facilitate treatment planning. Prognostic information is obtained from histopathological factors, such as tumor grade, depth of invasion, lymphovascular invasion, and perineural invasion. Notably, lymph node metastasis, found in approximately half of the patients, carries significant prognostic implications. Effective management necessitates a multidisciplinary approach to optimize patient outcomes. Surgical resection is the backbone of treatment, aimed at complete tumor removal while preserving functional outcomes. Adjuvant therapies, including radiation and chemotherapy, are tailored according to pathological factors. Further work in risk stratification and treatment is necessary to optimize outcomes in squamous cell carcinoma of the oral cavity.

Preparing Well for Esophageal Endoscopic Detection Using a Hybrid Model and Transfer Learning

Early detection of esophageal cancer through endoscopic imaging is pivotal for effective treatment. However, the intricacies of endoscopic diagnosis, contingent on the physician's expertise, pose challenges. Esophageal cancer features often manifest ambiguously, leading to potential confusions with other inflammatory esophageal conditions, thereby complicating diagnostic accuracy. In recent times, computer-aided diagnosis has emerged as a promising solution in medical imaging, particularly within the domain of endoscopy. Nonetheless, contemporary AI-based diagnostic models heavily rely on voluminous data sources, limiting their applicability, especially in scenarios with scarce datasets. To address this limitation, our study introduces novel data training strategies based on transfer learning, tailored to optimize performance with limited data. Additionally, we propose a hybrid model integrating EfficientNet and Vision Transformer networks to enhance prediction accuracy. Conducting rigorous evaluations on a carefully curated dataset comprising 1002 endoscopic images (comprising 650 white-light images and 352 narrow-band images), our model achieved exceptional outcomes. Our combined model achieved an accuracy of 96.32%, precision of 96.44%, recall of 95.70%, and f1-score of 96.04%, surpassing state-of-the-art models and individual components, substantiating its potential for precise medical image classification. The AI-based medical image prediction platform presents several advantageous characteristics, encompassing superior prediction accuracy, a compact model size, and adaptability to low-data scenarios. This research heralds a significant stride in the advancement of computer-aided endoscopic imaging for improved esophageal cancer diagnosis.

GNL3 and PA2G4 as Prognostic Biomarkers in Prostate Cancer

Prostate cancer is a multifocal and heterogeneous disease common in males and remains the fifth leading cause of cancer-related deaths worldwide. The prognosis of prostate cancer is variable and based on the degree of cancer and its stage at the time of diagnosis. Existing biomarkers for the prognosis of prostate cancer are unreliable and lacks specificity and sensitivity in guiding clinical decision. There is need to search for novel biomarkers having prognostic and predictive capabilities in guiding clinical outcomes. Using a bioinformatics approach, we predicted GNL3 and PA2G4 as biomarkers of prognostic significance in prostate cancer. A progressive increase in the expression of GNL3 and PA2G4 was observed during cancer progression having significant association with poor survival in prostate cancer patients. The Receiver Operating Characteristics of both genes showed improved area under the curve against sensitivity versus specificity in the pooled samples from three different GSE datasets. Overall, our analysis predicted GNL3 and PA2G4 as prognostic biomarkers of clinical significance in prostate cancer.

Azoxystrobin induces apoptosis via PI3K/AKT and MAPK signal pathways in oral leukoplakia progression

Background: Oral leukoplakia (OLK) is one of the oral potentially malignant disorders (OPMDs) with an increased risk of developing oral squamous cell carcinoma (OSCC). There is no ideal therapeutic drug yet. Our previous study showed azoxystrobin (AZOX) inhibited the viability of OLK cells and the incidence of mouse tongue cancer. However, its specific mechanism has not been clarified. Here, we used network pharmacology with experimental validation to investigate the roles and mechanisms of AZOX in OLK.

Methods: The targets of AZOX and OLK were obtained from online databases. The overlapping genes were identified by the Jvenn database. STRING and Cytoscape software were used to construct the PPI network. GO and KEGG enrichment analyses were used to analyze the biological function. Molecular docking and CETSA were used to verify the direct binding between AZOX and its key targets. 4NQO induced mouse tongue carcinogenesis model was constructed to clarify the treatment response of AZOX in vivo. TUNEL staining was performed to detect the effect of AZOX on apoptosis in mouse OLK tissues. CCK8 assay, flow cytometry, and western blot were used to detect the effect of AZOX on cell proliferation and apoptosis in DOK cells. The expression of PI3K/AKT and MAPK markers were analyzed by immunohistochemistry in vivo or by western blot in vitro.

Results: Venn diagram showed 457 overlapping targets, which were involved in the PI3K/AKT, MAPK, and apoptosis pathways, and the top 5 hub modules were TP53, STAT3, AKT1, MAPK1, and PIK3R1. AZOX was bound with the highest force to AKT and PI3K by AutoDock Vina. PyMOL software visualized that AZOX could fit in the binding pocket of the AKT and PI3K. The carcinogenesis rate of the mouse OLK in the high-dose AZOX group was significantly reduced. AZOX induced apoptosis in the OLK tissues and DOK cells, and the expression of PI3K, AKT, p-ERK was decreased, and the expression of p-p38 and p-JNK was increased. CETSA indicated that AZOX might have a direct binding with AKT and PI3K.

Conclusion: AZOX may induce apoptosis via PI3K/AKT and MAPK pathways in OLK. This study reveals the potential therapeutic targets of AZOX in OLK.

The multifaceted role of STAT3 pathway and its implication as a potential therapeutic target in oral cancer

Oral cancer is one of the leading causes of cancer-related deaths, and it has become a matter of serious concern due to the alarming rise in its incidence rate worldwide. Despite recent advancements in oral cancer treatment strategies, there are no significant improvements in patient's survival rate. Among the numerous cell signaling pathways involved in oral cancer development and progression, STAT3 is known to play a multifaceted oncogenic role in shaping the tumor pathophysiology. STAT3 hyperactivation in oral cancer contributes to survival, proliferation, invasion, epithelial to mesenchymal transition, metastasis, immunosuppression, chemoresistance, and poor prognosis. A plethora of pre-clinical and clinical studies have documented the role of STAT3 in the initiation and development of oral cancer and showed that STAT3 inhibition holds significant potential in the prevention and treatment of this cancer. However, to date, targeting STAT3 activation mainly involves inhibiting the upstream signaling molecules such as JAK and IL-6 receptors. The major challenge in targeting STAT3 lies in the complexity of its phosphorylation- and dimerization-independent functions, which are not affected by disrupting the upstream regulators. The present review delineates the significance of the STAT3 pathway in regulating various hallmarks of oral cancer. In addition, it highlights the STAT3 inhibitors identified to date through various preclinical and clinical studies that can be employed for the therapeutic intervention in oral cancer treatment.

Designing a Mucoadhesive ChemoPatch to Ablate Oral Dysplasia for Cancer Prevention

Oral cancer has a high mortality rate, and its treatment often causes debilitating complications. More than 90% of oral cancers are oral squamous cell carcinomas (OSCCs) that may develop from clinically recognizable oral premalignant lesions (OPLs). To eradicate OPLs before they turn into cancers, a non-invasive topical formulation is developed based on a novel combination of synergistically acting oxaliplatin (OXP) and mycophenolate (MPS) embedded in a controlled-release mucoadhesive patch fabricated by computer-aided 3D printing. After multiple rounds of testing and optimization, a v6.4 ChemoPatch is designed, which shows sustained release of OXP and MPS in vitro, minimal side leakage of drugs, an average elastic modulus of 2.38 MPa, and suitable drug stability at 4 °C or below for up to 12 months. In vivo analyses show almost all patches adhere to the dorsal tongue surface for 4 hours, and display a sustained release of OXP and MPS to tongue tissue for 3-4 hours. When applied in the 4-nitroquinoline-1-oxide-induced OPL rat model, the OXP-MPS patch significantly ablates dysplastic lesions with no damage to normal epithelial cells and minimal systemic absorption and side effects. This study reports the design of a novel mucoadhesive ChemoPatch as a noninvasive therapy to treat OPLs.

On the Cutting Edge of Oral Cancer Prevention: Finding Risk-Predictive Markers in Precancerous Lesions by Longitudinal Studies

Early identification and management of precancerous lesions at high risk of developing cancers is the most effective and economical way to reduce the incidence, mortality, and morbidity of cancers as well as minimizing treatment-related complications, including pain, impaired functions, and disfiguration. Reliable cancer-risk-predictive markers play an important role in enabling evidence-based decision making as well as providing mechanistic insight into the malignant conversion of precancerous lesions. The focus of this article is to review updates on markers that may predict the risk of oral premalignant lesions (OPLs) in developing into oral squamous cell carcinomas (OSCCs), which can logically be discovered only by prospective or retrospective longitudinal studies that analyze pre-progression OPL samples with long-term follow-up outcomes. These risk-predictive markers are different from those that prognosticate the survival outcome of cancers after they have been diagnosed and treated, or those that differentiate between different lesion types and stages. Up-to-date knowledge on cancer-risk-predictive markers discovered by longitudinally followed studies will be reviewed. The goal of this endeavor is to use this information as a starting point to address some key challenges limiting our progress in this area in the hope of achieving effective translation of research discoveries into new clinical interventions.