OBJECTIVES: The objectives of this study were to investigate the CELSR3 hypermethylation level in oral squamous cell carcinomas (OSCCs) using methylation-sensitive high-resolution melting analysis (MS-HRM) and to correlate CELSR3 methylation with patient demographic and clinicopathological parameters.
MATERIALS AND METHODS: Frozen tissue samples of healthy subjects' normal mucosa and OSCCs were examined with regard to their methylation levels of the CELSR3 gene using MS-HRM.
RESULTS: MS-HRM analysis revealed a high methylation level of CELSR3 in 86% of OSCC cases. Significant correlations were found between CELSR3 quantitative methylation levels with patient ethnicity (P=0.005), age (P=0.024) and pathological stages (P=0.004). A moderate positive correlation between CELSR3 and patient age was also evident (R=0.444, P=0.001).
CONCLUSIONS: CELSR3 promoter hypermethylation may be an important mechanism involved in oral carcinogenesis. It may thus be used as a biomarker in OSCC prognostication.
METHODS AND RESULTS: TQRF was extracted from N. sativa seeds using supercritical fluid extraction. The regulatory effects of TQRF at 80 microg/ml and TQ at 2 microg/ml on LDLR and HMGCR gene expression were investigated in HepG2 cells using quantitative real-time PCR. The TQ content in TQRF was 2.77% (w/w) and was obtained at a temperature of 40 degrees C and a pressure of 600 bar. Treatment of cells with TQRF and TQ resulted in a 7- and 2-fold upregulation of LDLR mRNA level, respectively, compared with untreated cells. The mRNA level of HMGCR was downregulated by 71 and 12%, respectively, compared with untreated cells.
CONCLUSION: TQRF and TQ regulated genes involved in cholesterol metabolism by two mechanisms, the uptake of low-density lipoprotein cholesterol via the upregulation of the LDLR gene and inhibition of cholesterol synthesis via the suppression of the HMGCR gene.
METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls).
RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network.
CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development.
IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization.
METHODS: This descriptive study comprised 5 patients of KCOT associated with NBCCS and 8 patients of nonsyndromic type treated in the Department of Oral Maxillofacial Surgery, Universiti Kebangsaan Malaysia Medical Centre between years 1998 and 2011. The clinical features (site, size, treatment, and recurrence), demographic characteristics, and immunohistochemistry results using antibodies of bcl-2, cyclin D1, p53, and PCNA were examined. The association of the antibody expression and the type of KCOT was analyzed using Fisher exact test.
RESULTS: Altogether there were 13 patients, 5 with syndromic KCOT (1 patient met 3 major criteria of NBCCS) and 8 with sporadic KCOT. The age range for syndromic KCT was 11 to 21 years (mean 16.00 years, SD 4.36) and 10 to 54 years (median 24.50 years, interquartile range 19.00) for the nonsyndromic KCOT. Tumor recurrence occurred in 3 patients (7.7%); 1 patient from the syndromic and 2 patients from the nonsyndromic. The most positive expression was observed in PCNA for both the syndromic and nonsyndromic samples and the least positive expression involved the p53.
CONCLUSION: PCNA, bcl-2 protein, and cyclin D1 expressions could be useful in evaluating the proliferative activity of the tumor and the aggressiveness of the clinical presentation; however, the authors would propose for larger sample size research for more definitive results.