A Comprehensive Evaluation of miR-144-3p Expression and Its Targets in Laryngeal Squamous Cell Carcinoma

miRNAs from Inflamed Gingiva Link Gene Signaling to Increased MET Expression

Several array-based microRNA (miRNA) expression studies independently showed increased expression of miRNAs hsa-miR-130a-3p, -142-3p, -144-3p, -144-5p, -223-3p, -17-5p, and -30e-5p in gingiva affected by periodontal inflammation. We aimed to determine direct target genes and signaling pathways regulated by these miRNAs to identify processes relevant to gingival inflammatory responses and tissue homeostasis. We transfected miRNA mimics (mirVana) for each of the 7 miRNAs separately into human primary gingival fibroblasts cultured from 3 different donors. Following RNA sequencing, differential gene expression and second-generation gene set enrichment analyses were performed. miRNA inhibition and upregulation was validated at the transcript and protein levels using quantitative reverse transcriptase polymerase chain reaction, Western blotting, and reporter gene assays. All 7 miRNAs significantly increased expression of the gene MET proto-oncogene, receptor tyrosine kinase (MET). Expression of known periodontitis risk genes CPEB1, ABCA1, and ATP6V1C1 was significantly repressed by hsa-miR-130a-3p, -144-3p, and -144-5p, respectively. The genes WASL, ENPP5, ARL6IP1, and IDH1 showed the most significant and strongest downregulation after hsa-miR-142-3p, -17-5p, -223-3p, and -30e-5p transfection, respectively. The most significantly regulated gene set of each miRNA related to cell cycle (hsa-miRNA-144-3p and -5p [Padj = 4 × 10-40 and Padj = 4 × 10-6], -miR-17-5p [Padj = 9.5 × 10-23], -miR-30e-5p [Padj = 8.2 × 10-18], -miR-130a-3p [Padj = 5 × 10-15]), integrin cell surface interaction (-miR-223-3p [Padj = 2.4 × 10-7]), and interferon signaling (-miR-142-3p [Padj = 5 × 10-11]). At the end of acute inflammation, gingival miRNAs bring together complex regulatory networks that lead to increased expression of the gene MET. This underscores the importance of mesenchymal cell migration and invasion during gingival tissue remodeling and proliferation in restoring periodontal tissue homeostasis after active inflammation. MET, a receptor of the mitogenic hepatocyte growth factor fibroblast secreted, is a core gene of this process.

Poor Prognosis of Oral Squamous Cell Carcinoma Correlates With ITGA6

OBJECTIVES

Oral cancer is the ninth most common cancer worldwide and a leading cause of cancer-related death. Oral squamous cell carcinoma (OSCC) accounts for 90% of all oral cancers. Autophagy is a conserved essential catabolic process related to OSCC. The aim of this study was to elucidate diagnostic and prognostic autophagy-related biomarkers in OSCC.

METHODS

The OSCC gene expression data set was obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between the OSCC samples and adjacent healthy tissues were identified by R software. The Human Autophagy Database was screened, which revealed 222 autophagy-related genes. The autophagy-related DEGs were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were applied. Protein-protein interaction network analysis was performed in the STRING database. cytoHubba in the Cytoscape software was applied to determine the top 10 hub genes. The data set of patients with OSCC from The Cancer Genome Atlas (TCGA) was used to evaluate the prognostic value of the 10 hub genes. The association between prognosis-related hub genes and immune infiltrates was explored.

RESULTS

Twenty-seven autophagy-related DEGs were identified. The top 10 hub genes were CCL2, CDKN2A, CTSB, CTSD, CXCR4, ITGA6, MAP1LC3A, MAPK3, PARP1, and RAB11A. ITGA6 was identified as the most efficient biomarker. Receiver operating characteristic curve analysis indicated that ITGA6 had the highest diagnostic accuracy for OSCC (area under the curve = 0.925). ITGA6 expression was significantly related to immune infiltrates.

CONCLUSIONS

The autophagy-related gene ITGA6 might be an efficient diagnostic and prognostic biomarker in OSCC.

Global microRNA expression profile in laryngeal carcinoma unveils new prognostic biomarkers and novel insights into field cancerization

Laryngeal carcinoma is still a worldwide burden that has shown no significant improvement during the last few decades regarding definitive treatment strategies. The lack of suitable biomarkers for personalized treatment protocols and delineating field cancerization prevents further progress in clinical outcomes. In the light of this perspective, MicroRNAs could be promising biomarkers both in terms of diagnostic and prognostic value. The aim of this prospective study is to find strong prognostic microRNA biomarkers for advanced laryngeal carcinoma and molecular signatures of field cancerization. Sixty patients were enrolled and four samples were collected from each patient: tumor surface and depth, peritumor normal mucosa, and control distant laryngeal mucosa. Initially, a global microRNA profile was conducted in twelve patients from the whole cohort and subsequently, we validated a selected group of 12 microRNAs with RT-qPCR. The follow-up period was 24 months (SD ± 13 months). Microarray expression profile revealed 59 dysregulated microRNAs. The validated expression levels of miR-93-5p (χ²(2) = 4.68, log-rank p = 0.03), miR-144-3p (χ²(2) = 4.53, log-rank p = 0.03) and miR-210-3p (χ²(2) = 4.53, log-rank p = 0.03) in tumor samples exhibited strong association with recurrence-free survival as higher expression levels of these genes predict worse outcome. Tumor suppressor genes miR-144-3p (mean rank 1.58 vs 2.14 vs 2.29, p = 0.000) and miR-145-5p (mean rank 1.57 vs 2.15 vs 2.28, p = 0.000) were significantly dysregulated in peritumor mucosa with a pattern of expression consistent with paired tumor samples thus revealing a signature of field cancerization in laryngeal carcinoma. Additionally, miR-1260b, miR-21-3p, miR-31-3p and miR-31-5p were strongly associated with tumor grade. Our study reports the first global microRNA profile specifically in advanced laryngeal carcinoma that includes survival analysis and investigates the molecular signature of field cancerization. We report two strong biomarkers of field cancerization and three predictors for recurrence in advance stage laryngeal cancer.