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Transcriptome profiles of moderate dysplasia in oral mucosa associated with malignant conversion

ABSTRACT: Oral malignancies are among the top most deadly cancers in the world. Early diagnosis of oral premalignant and malignant lesions is essential for treatment decision-making and prognosis improvement. In this study, we systematically evaluated the gene expression patterns during the pathogenesis of oral moderate dysplasia. RNA sequencing detected 21556 genes in moderate dysplasia and paired normal tissues from three patients. Hierarchical clustering analysis revealed distinct gene expression patterns between the moderate dysplasia samples. 346 differentially expressed genes that may contribute to the pathogenesis of moderate dysplasia were identified. Among these genes, ISG15 and MAGEA family showed different transcription profiles that close related with the alterations of gene expression patterns in moderate dysplasia samples and paired normal tissues. We speculated that, as the potential marker to signal the risk of malignant transformation, ISG15 and MAGEA together with their close related misexpressed genes may involve in two different pathways during the malignant conversion from oral dysplasia to oral squamous cell carcinoma.

ORGANISM(S): Homo sapiens

PROVIDER: GSE72627 | GEO | 2017/06/28

SECONDARY ACCESSION(S): PRJNA294509

REPOSITORIES: GEO

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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.

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Transcriptome profiles of moderate dysplasia in oral mucosa associated with malignant conversion

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