Background/Objectives: Oral squamous cell carcinoma (OSCC) is the most prevalent malignancy of the oral cavity and is frequently diagnosed at an advanced stage, resulting in poor prognosis and limited treatment options. Identifying reliable biomarkers that can predict tumor progression and serve as therapeutic targets remains an urgent clinical need. Methods: To identify key molecular drivers in OSCC, we performed an integrative bioinformatics analysis of five OSCC-related microarray datasets from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified and subjected to functional enrichment, protein–protein interaction (PPI) network construction, and hub gene ranking using Cytoscape. Candidate genes were further validated using TCGA, UALCAN, and the Human Protein Atlas. In vitro functional assays were performed to evaluate the effect of TK1 knockdown on cell migration. Results: A total of 138 common DEGs were identified across datasets. GO enrichment revealed that these genes were associated with cell proliferation, extracellular matrix organization, and metastasis-related processes. Thymidine kinase 1 (TK1) was identified as a key hub gene and found to be consistently overexpressed in OSCC tissues. Kaplan–Meier analysis showed that high TK1 expression correlated with poor overall survival in head and neck cancer. TK1 knockdown in OSCC cell lines significantly impaired cell migration and wound-healing ability. Conclusions: Our findings suggest that TK1 plays an active role in promoting OSCC progression and may serve as a prognostic biomarker and potential therapeutic target for metastatic OSCC.

Sparganii Rhizoma and Curcumae Rhizoma (SRCR) are natural herbs used in traditional Chinese medicine to treat tumors and activate blood circulation. Previous studies have shown that SRCR possesses notable antitumor activity; however, the mechanism underlying anticancer activity in human oral squamous cell carcinoma (OSCC) has yet to be fully elucidated. The risk factors of OSCC include smoking, alcohol consumption, poor oral hygiene, and human papillomavirus infection. OSCC is highly metastatic and responds poorly to chemotherapy; thus, alternative treatment options are imperative. In this study, we found that SRCR induced death in OSCC cells but not in normal cells (HGF-1cells). SRCR has also shown to induce the production of reactive oxygen species in OSCC cells, sequentially promoting calcium release and stress in the endoplasmic reticulum, which resulted in mitochondrial dysfunction and subsequent apoptosis. Furthermore, SRCR has shown to inhibit the migration of OSCC cells by reducing matrix metalloproteinase-12 and -13. Our findings demonstrate that SRCR exerts anticancer activities in OSCC by inducing cell apoptosis and suppressing cell migration.

Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small-cell lung cancer and is frequently diagnosed at advanced stages with metastasis, contributing to its poor prognosis. Identifying key metastasis-related biomarkers is critical for improving early diagnosis and therapeutic targeting. Methods: We analyzed four GEO microarray datasets (GSE32863, GSE27262, GSE40275, and GSE33356) and TCGA data to identify differentially expressed genes (DEGs) in LUAD. Functional enrichment of DEGs was analyzed using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, and a Cancer Hallmark Enrichment Plot. Hub gene analysis was conducted using Cytoscape. Hub genes were evaluated for their expression, prognostic significance (via the Kaplan–Meier plotter), and clinical correlation using additional platforms (TCGA, Lung Cancer Explorer, TNMplot, and the Human Protein Atlas). Results: A total of 333 consistently dysregulated DEGs were identified, enriched in pathways related to metastasis, including angiogenesis, immune escape, and ECM interaction. Ten hub genes (AURKA, TOP2A, CCNB2, CENPF, MCM4, TPX2, KIF20A, ASPM, MELK, and NEK2) were identified through network analysis. Among these, MCM4 showed strong upregulation in LUAD and was significantly associated with poor overall survival. Notably, MCM4 expression also correlated with post-progression survival and markers of invasiveness. Immunohistochemistry and transcriptomic analyses confirmed MCM4 overexpression at both mRNA and protein levels. Additionally, MCM4 expression was positively correlated with various matrix metalloproteinases, supporting its role in promoting tumor invasiveness. Conclusions: MCM4 is a novel potential biomarker for LUAD metastasis and prognosis. Its consistent upregulation, association with metastatic markers, and clinical significance suggest it may serve as a candidate target for diagnostic use or therapeutic intervention in advanced LUAD.

Osteosarcoma (OS) is the most common primary malignant bone tumor in adolescents, and outcomes for metastatic disease have remained poor, highlighting the need for molecular biomarkers. We integrated three Gene Expression Omnibus (GEO) mRNA expression datasets (GSE12865, GSE14359, and GSE246405) to identify differentially expressed genes (DEGs) between OS and non-malignant bone-related controls. Overlapping DEGs were used to build a protein–protein interaction network, and hub genes were prioritized using multiple network topology algorithms. Prognostic associations were evaluated using the R2 Genomics Platform. Putative upstream miRNAs targeting the top candidate were obtained from prediction databases and intersected with dysregulated circulating miRNAs from GSE65071 (localized OS plasma vs. healthy controls). Functional enrichment analyses (Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and cancer hallmarks) were performed to contextualize the candidate signature. We identified 107 overlapping DEGs and prioritized eight hub genes. CD81 was significantly associated with overall survival (Bonferroni-adjusted p = 0.043) and showed reduced expression in OS tissues and cell line models. hsa-miR-582-5p was nominated as a candidate miRNA predicted to target CD81 and was upregulated in OS plasma. Enrichment results linked the signature to angiogenesis, extracellular matrix remodeling, focal adhesion, and metastasis-associated signatures. These findings support CD81 as a candidate prognostic biomarker and nominate a putative hsa-miR-582-5p–CD81 relationship for future validation.

Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) is characterized by an extensive desmoplastic microenvironment; however, reproducible stromal-associated biomarkers linked to disease progression remain limited. This study therefore aimed to identify and validate a biologically relevant stromal/extracellular matrix (ECM)-associated candidate biomarker for PDAC. Methods: Three GEO bulk transcriptomic PDAC cohorts (GSE15471, GSE16515, and GSE62452) were integrated for differential expression, functional enrichment, protein–protein interaction, and hub-gene analyses. Candidates identified as a promising biomarker were further evaluated using the following: public proteomic and survival resources; head-to-head receiver operating characteristic (ROC) comparisons against COL1A1, COL3A1, and COL5A1; a progression cohort (GSE43288); and single-nucleus RNA sequencing data (GSE202051). Results: Among 206 shared differentially expressed genes, COL5A2 was the only consensus hub retained across multiple network-ranking methods. COL5A2 protein expression was found to be elevated in tumor tissue and associated with worse overall and disease-free survival. In ROC analyses, COL5A2 exhibited stable tumor-versus-non-tumor discrimination across GSE15471, GSE16515, and GSE62452 (AUC = 0.932, 0.760, and 0.782, respectively) and significantly outperformed COL3A1 in two cohorts. In GSE43288, COL5A2 expression increased along the normal–pancreatic intraepithelial neoplasia–PDAC axis and remained positively associated with ECM and cancer-associated fibroblast (CAF) signature scores after adjustment for disease group. Reanalysis of GSE202051 restricted to the original 18 untreated PDAC specimens revealed that COL5A2 expression was concentrated in fibroblast-lineage compartments, with CAFs accounting for the largest overall contribution and myCAFs demonstrating the strongest per-specimen expression enrichment. Conclusions: COL5A2 is a reproducible stromal/ECM-associated candidate biomarker linked to PDAC progression, with predominant expression in fibroblast/CAF compartments.