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The role of long non-coding RNA (lncRNA) expression in human head and neck squamous cell carcinoma (HNSCC) is still poorly understood. In this study, UCSD researchers aimed at establishing the onco-lncRNAome profiling of HNSCC and to identify lncRNAs correlating with prognosis and patient survival.
The Atlas of Noncoding RNAs in Cancer (TANRIC) database was employed to retrieve the lncRNA expression information generated from The Cancer Genome Atlas (TCGA) HNSCC RNA-sequencing data. RNA-sequencing data from HNSCC cell lines were also considered for this study. Bioinformatics approaches, such as differential gene expression analysis, survival analysis, principal component analysis, and Co-LncRNA enrichment analysis were performed.
Using TCGA HNSCC RNA-sequencing data from 426 HNSCC and 42 adjacent normal tissues, the researchers found 728 lncRNA transcripts significantly and differentially expressed in HNSCC. Among the 728 lncRNAs, 55 lncRNAs were significantly associated with poor prognosis, such as overall survival and/or disease-free survival. Next, they found 140 lncRNA transcripts significantly and differentially expressed between Human Papilloma Virus (HPV) positive tumors and HPV negative tumors. Thirty lncRNA transcripts were differentially expressed between TP53 mutated and TP53 wild type tumors. Co-LncRNA analysis suggested that protein-coding genes that are co-expressed with these deregulated lncRNAs might be involved in cancer associated molecular events. With consideration of differential expression of lncRNAs in a HNSCC cell lines panel (n=22), they found several lncRNAs that may represent potential targets for diagnosis, therapy and prevention of HNSCC.
Differential expression analysis between tumor and normal tissues in the HNSCC TCGA
(A) Heatmap of 728 differentially expressed lncRNAs in comparison between tumor and normal tissues. (B) Representative differentially expressed lncRNAs between tumor and normal tissues. (C) Gene Ontology (GO) enrichment analysis for protein-coding genes co-expressed with 728 lncRNAs with visualization by REViGO algorism.
LncRNAs profiling could provide novel insights into the potential mechanisms of HNSCC oncogenesis.
