Project description:Analysis of various of up-regulated and down-regulated genes in normal oral mucosa and different stages of OSF. The report provides a data analysis methodology for identification of co-expressed gene patterns, as emerging clusters, in global transcriptome of oral mucosal pre-malignant and malignant conditions in comparison to their normal counterparts. Microarray based study of global gene expression is often used to extract molecular signatures underlying cancer progression. Such endeavors endorse self organizing map, a type of artificial neural network to analyze high dimensional pre-processed transcriptome data to segregate hotspot genes in component plane for disease subtypes. This report provides a data analysis methodology for identification of co-expressed gene patterns, as emerging clusters, in global transcriptome of oral mucosal pre-malignant and malignant conditions in comparison to their normal counterparts. Four exclusive cluster patterns, each involving 100 − 300 genes, were identified from component planes for oral study groups. Gene expression associated with each pattern belonged to 32 biological processes. The transcription and RNA processing, and angiogenesis were dominant in normal oral condition, while immunity, cellular differentiation and migration, neuron signalling, connective tissue organization, tumor suppression, and enzyme regulation showed predominance in oral squamous cell carcinoma. In dysplasia skeletal and ligament development processes were dominant while in non-dysplastic sub-mucous fibrosis cytoskeleton reorganization and neuron signalling were pre-dominant. In dysplasia an intermediate pattern with nine different dominant functional processes was identified. This analysis demonstrated utility of self organizing map to capture dominant enriched patterns as visual plots and revealed six common biological processes like transcription and RNA processing, cytoskeleton reorganization, angiogenesis, immunity, neuron signalling, and connective tissue remodeling in the pathogenesis of oral cancer. In fact it could provide an intuitive understanding of molecular course in carcinogenesis and may contribute for combinatorial biomarker discovery.

Project description:Epigenetic modifications, such as aberrant DNA promoter methylation is frequently observed in cervical cancer. Identification of hypermethylated regions maybe useful for discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3) or worse may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions were characterised using genome-wide methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methyl-DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium resulting in the identification of hypermethylated differentially methylated regions (DMRs). Validation of 9 selected DMRs by MSP or BSP in cervical tissue revealed methylation in 63.2-94.7% high-grade CIN and in 59.3-100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was applied exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples (p<0.001). Clinical validation of both markers in cervical scrapings from patients referred with an abnormal cervical smear, confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion (p<0.001) and the ROC analysis was discriminative (p<0.005). These possible methylation markers represent COL25A1 and KATNAL2 promoters and their observed increased methylation upon progression is in agreement with their biological function (cytoskeleton regulation). In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and could be potential biomarkers for early detection. Epigenetic modifications, such as aberrant DNA promoter methylation is frequently observed in cervical cancer. Identification of hypermethylated regions maybe useful for discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3) or worse may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions were characterised using genome-wide methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methyl-DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium resulting in the identification of hypermethylated differentially methylated regions (DMRs). Validation of 9 selected DMRs by MSP or BSP in cervical tissue revealed methylation in 63.2-94.7% high-grade CIN and in 59.3-100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was applied exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples (p<0.001). Clinical validation of both markers in cervical scrapings from patients referred with an abnormal cervical smear, confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion (p<0.001) and the ROC analysis was discriminative (p<0.005). These possible methylation markers represent COL25A1 and KATNAL2 promoters and their observed increased methylation upon progression is in agreement with their biological function (cytoskeleton regulation). In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and could be potential biomarkers for early detection. MeDIP with subsequent microarray analysis was performed on DNA isolated from frozen macrodissected epithelial tissue of CIN3 lesions (n=15) and normal cervices (n=10).

Project description:Epigenetic modifications, such as aberrant DNA promoter methylation is frequently observed in cervical cancer. Identification of hypermethylated regions maybe useful for discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3) or worse may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions were characterised using genome-wide methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methyl-DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium resulting in the identification of hypermethylated differentially methylated regions (DMRs). Validation of 9 selected DMRs by MSP or BSP in cervical tissue revealed methylation in 63.2-94.7% high-grade CIN and in 59.3-100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was applied exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples (p<0.001). Clinical validation of both markers in cervical scrapings from patients referred with an abnormal cervical smear, confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion (p<0.001) and the ROC analysis was discriminative (p<0.005). These possible methylation markers represent COL25A1 and KATNAL2 promoters and their observed increased methylation upon progression is in agreement with their biological function (cytoskeleton regulation). In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and could be potential biomarkers for early detection. Epigenetic modifications, such as aberrant DNA promoter methylation is frequently observed in cervical cancer. Identification of hypermethylated regions maybe useful for discrimination between normal cervical epithelium and high-grade cervical intraepithelial neoplasia (CIN2/3) or worse may improve current cervical cancer population-based screening programs. In this study, the DNA methylome of high-grade CIN lesions were characterised using genome-wide methylation screening to identify potential biomarkers for early diagnosis of cervical neoplasia. Methyl-DNA Immunoprecipitation (MeDIP) combined with DNA microarray was used to compare DNA methylation profiles of epithelial cells derived from high-grade CIN lesions with normal cervical epithelium resulting in the identification of hypermethylated differentially methylated regions (DMRs). Validation of 9 selected DMRs by MSP or BSP in cervical tissue revealed methylation in 63.2-94.7% high-grade CIN and in 59.3-100% cervical carcinomas. QMSP for the two most significant high-grade CIN-specific methylation markers was applied exploring test performance in a large series of cervical scrapings. Frequency and relative level of methylation were significantly different between normal and cancer samples (p<0.001). Clinical validation of both markers in cervical scrapings from patients referred with an abnormal cervical smear, confirmed that frequency and relative level of methylation were related with increasing severity of the underlying CIN lesion (p<0.001) and the ROC analysis was discriminative (p<0.005). These possible methylation markers represent COL25A1 and KATNAL2 promoters and their observed increased methylation upon progression is in agreement with their biological function (cytoskeleton regulation). In conclusion, our newly identified hypermethylated DMRs represent specific DNA methylation patterns in high-grade CIN lesions and could be potential biomarkers for early detection.

Dataset Information

Genome-wide analysis of gene expression in Normal Cervical mucosa, Cervical intraepithelial neoplasia and Cervical squamous cell carcinoma

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