The majority of studies on human cancers published to date focus on coding genes. More recently, however, non-coding RNAs (ncRNAs) are gaining growing recognition as important regulatory components. Here we characterise the ncRNA landscape in 442 head and neck squamous cell carcinomas (HNSCs) from the cancer genome atlas (TCGA). HNSCs represent an intriguing case to study the potential role of ncRNA as a function of viral presence, especially as HPV is potentially oncogenic. Thus, we identify HPV16-positive (HPV16+) and HPV-negative (HPV-) tumours and study the expression of ncRNAs on both groups. Overall, the ncRNAs comprise 36% of all differentially expressed genes, with antisense RNAs being the most represented ncRNA type (12.6%). Protein-coding genes appear to be more frequently downregulated in tumours compared with controls, whereas ncRNAs show significant upregulation in tumours, especially in HPV16+ tumours. Overall, expression of pseudogenes, antisense and short RNAs is elevated in HPV16+ tumours, while the remaining long non-coding RNA types are more active in all HNSC tumours independent of HPV status. In addition, we identify putative regulatory targets of differentially expressed ncRNAs. Among these 'targets' we find several well-established oncogenes, tumour suppressors, cytokines, growth factors and cell differentiation genes, which indicates the potential involvement of ncRNA in the control of these key regulators as a direct consequence of HPV oncogenic activity. In conclusion, our findings establish the ncRNAs as crucial transcriptional components in HNSCs. Our results display the great potential for the study of ncRNAs and the role they have in human cancers.
Pubmed ID: 29263803 RIS Download
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Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.
View all literature mentionsBioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. An integrated software suite for functional analysis of experimental data. The scope of data types includes microarray and SAGE gene expression, SNPs and CGH arrays, proteomics, metabolomics, pathway analysis, Y2H and other custom interactions. MetaCore is based on a proprietary manually curated database of human protein-protein, protein-DNA and protein compound interactions, metabolic and signaling pathways and the effects of bioactive molecules in gene expression.
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