Analyzing Pooled Microarray Gene Expression Data to Uncover Common Pathways in Periodontitis and Oral Squamous Cell Carcinoma from the Gene Expression Omnibus.

Periodontitis and oral squamous cell carcinoma (OSCC) are prevalent oral diseases with distinct etiologies, yet they share certain molecular and biological characteristics. Gene expression datasets from the gene expression omnibus (GEO) repository (GSE30784 for OSCC and GSE10334 for periodontitis) were analyzed. Data preprocessing and differential gene expression analysis using GEO2R identified common differentially expressed genes (DEGs), and FunRich software facilitated the construction of a protein-protein interaction (PPI) network on the STRING database. Cytoscape, coupled with the CytoHubba plugin, identified Cluster of Differentiation 19 (CD19) and Von Willebrand Factor (VWF) as the top hub genes, with Complement C3 (C3) also highly ranked. Functional enrichment analysis highlighted pathways such as the B-cell receptor signaling pathway, complement and coagulation cascades, and hematopoietic cell lineage. Additionally, miRNet analysis identified key miRNAs, including hsa-mir-26a-5p, hsa-mir-129-2-3p, and hsa-mir-27a-3p, associated with these pathways. These findings suggested an association of molecular mechanisms between periodontitis and OSCC, with identified hub genes and miRNAs potentially serving as therapeutic targets.

Unraveling the Molecular Complexity of Adenoid Cystic Carcinoma (ACC): A Comprehensive Exploration of Hub Genes, Protein-Protein Interaction (PPI) Networks, microRNA (miRNA) Involvement, and Drug-Gene Interactions (DGIs).

Background Adenoid cystic carcinoma (ACC) poses clinical challenges with its unique histology and potential for perineural invasion, recurrence, and distant metastases. Recent genomic advancements have unveiled key genetic alterations in ACC, offering insights into its pathogenesis. Aim This study aims to unravel the intricate molecular landscape of ACC through a comprehensive analysis of gene expression patterns. By integrating data from multiple microarray datasets, the study explores differentially expressed genes (DEGs), their functional enrichment, protein-protein interactions (PPI), hub genes, microRNA (miRNA) involvement, transcription factors, and potential drug-gene interactions. Methods Three microarray datasets (GSE88804, GSE153002, and GSE36820) related to ACC were selected from the Gene Expression Omnibus (GEO) repository. DEGs were identified using GEO2R and further analyzed for commonalities and differences. Functional enrichment analysis, including Gene Set Enrichment Analysis (GSEA), provided insights into biological processes, cellular components, molecular functions, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with ACC. PPI networks and hub genes were identified using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) (STRING Consortium, Lausanne, Switzerland) database and Cytoscape (Cytoscape Consortium, California, United States). The study also explored miRNAs, transcription factors, and potential drug-gene interactions. Results The integrated analysis revealed 339 common upregulated and 643 downregulated DEGs in ACC. Functional and pathway enrichment analyses unveiled the involvement of these genes in critical cellular processes, signaling cascades, and pathways. The PPI network, comprising 904 nodes and 4139 edges, highlighted the complexity of interactions. Hub genes, including KIF11, BUB1, and DLGAP5, were identified, shedding light on their pivotal roles in cell cycle regulation. The study also identified miRNAs (e.g., hsa-mir-7-5p and hsa-mir-138-5p) and transcription factors (e.g., E2F1 and TP53) associated with ACC. Drug-gene interactions have identified potential therapeutic options, including amsacrine and rucaparib. Conclusions The ACC gene expression highlights a nuanced molecular landscape, identifying pivotal hub genes such as KIF11 and CDK1 as potential therapeutic targets for ACC, given their roles in cell cycle progression. The dysregulation of microRNAs and transcription factors adds complexity to ACC's molecular profile. Exploration of drug-gene interactions reveals promising therapeutic strategies, involving FDA-approved drugs such as amsacrine and rucaparib, providing avenues for personalized interventions.

Legal age determined by a new threshold value of third molar maturity index in subjects with impacted mandibular third molars: An orthopantomographic study in south Indian adolescents.

Third molars are one of the few biological markers available for age estimation in juveniles, especially for the estimation of the 18-year-age threshold. Literature has indicated that impaction has an influence on the development of third molars, which could possibly result in age misclassifications. The present study is intended to identify an alternative cut-off value of the third molar maturity index (I3M) in impacted mandibular third molars and also to evaluate its applicability in estimating the major (≥ 18 years)/minor (< 18 years) status. A total of 1330 digital orthopantomograms (OPGs) of 665 male and 665 female south Indian adolescents aged from 15 to 22 years were collected and assessed. Eight hundred forty OPGs (63.1%) represented test sample, and 490 OPGs (36.9%) represented validation sample. I3M was measured for the total sample. Logistic regression, receiver operating characteristic (ROC) curve analysis, and Youden's index were used to test the performance of the method in the test sample. An alternative cut-off value of I3M < 0.17 was established for the highest value of the Youden's index of 0.598 for both sexes. When tested in validation sample, it has resulted in sensitivity and specificity values of 0.91 (95% CI; 0.86-0.95) and 0.90 (95% CI; 0.78-0.91) in males and 0.86 (95% CI; 0.80-0.92) and 0.90 (95% CI; 0.83-0.95) in females. In conclusion, cut-off value of I3M < 0.17 could accurately discriminate adults from minors with impacted mandibular third molars. However, more work is needed to be done among a more diverse sample to confirm these findings.

Salivaomics for Oral Cancer Detection: An Insight.

Early detection is very crucial for successful management of oral cancer or any disease as such. Oral squamous cell carcinoma (OSCC) accounts for nearly 90% of malignancy of oral cavity. In the field of cancer research, there is always an ongoing quest for newer methods to lower the morbidity and mortality associated with OSCC. Saliva, a readily available noninvasive biofluid with constant contact with oral cancer lesion, offers an appealing alternative to serum and tissue testing. This review throws light on incorporation of newer technologies for harnessing the saliva to its fullest potential with increased specificity and sensitivity toward identification of cancer-specific molecular signatures for the development of point-of-care applications that could be used at the clinical setting.

Hemangiomatous ameloblastoma: Case report with a brief review.

Ameloblastoma is a benign epithelial odontogenic tumor with many histological variants. Hemangiomatous ameloblastoma (HA) is a very rare variant which shows unique histopathological features varying from conventional ameloblastoma. We present a case of a 35-year-old female patient with a swelling over right lower back region of jaw, showing mixed radiolucent-opacity. Incisional biopsy showed microscopic features of desmoplastic ameloblastoma showing extensive desmoplasia and compressed odontogenic epithelial islands. Excisional biopsy revealed ameloblastomatous areas with extensive vascular component microscopically. Based on these findings, a diagnosis of HA was made.