Dataset Information

Clusterization in head and neck squamous carcinomas based on lncRNA expression: molecular and clinical correlates.

ABSTRACT:

Background

Long non-coding RNAs (lncRNAs) have emerged as key players in a remarkably variety of biological processes and pathologic conditions, including cancer. Next-generation sequencing technologies and bioinformatics procedures predict the existence of tens of thousands of lncRNAs, from which we know the functions of only a handful of them, and very little is known in cancer types such as head and neck squamous cell carcinomas (HNSCCs).

Results

Here, we use RNAseq expression data from The Cancer Genome Atlas (TCGA) and various statistic and software tools in order to get insight about the lncRNome in HNSCC. Based on lncRNA expression across 426 samples, we discover five distinct tumor clusters that we compare with reported clusters based on various genomic/genetic features. Results demonstrate significant associations between lncRNA-based clustering and DNA methylation, TP53 mutation, and human papillomavirus infection. Using "guilt-by-association" procedures, we infer the possible biological functions of representative lncRNAs of each cluster. Furthermore, we found that lncRNA clustering is correlated with some important clinical and pathologic features, including patient survival after treatment, tumor grade, or sub-anatomical location.

Conclusions

We present a landscape of lncRNAs in HNSCC and provide associations with important genotypic and phenotypic features that may help to understand the disease.

SUBMITTER: de Lena PG

PROVIDER: S-EPMC5385094 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease with high mortality. The identification of specific HNSCC biomarkers will increase treatment efficacy and limit the toxicity of current therapeutic strategies. Long non-coding RNAs (lncRNAs) are promising biomarkers. Accordingly, here we investigate the biological role of ZFAS1 and its potential as a biomarker in HNSCC. The expression level of ZFAS1 in HNSCC cell lines was analyzed using qRT-PCR. Based on the HNSCC TCGA data, the ZFAS1 expression profile, clinicopathological features, and expression of correlated genes were analyzed in patient tissue samples. The selected genes were classified according to their biological function using the PANTHER tool. The interaction between lncRNA:miRNA and miRNA:mRNA was tested using available online tools. All statistical analyses were accomplished using GraphPad Prism 5. The expression of ZFAS1 was up-regulated in the metastatic FaDu cell line relative to the less aggressive SCC-25 and SCC-040 and dysplastic DOK cell lines. The TCGA data indicated an up-regulation of ZFAS1 in HNSCCs compared to normal tissue samples. The ZFAS1 levels typically differed depending on the cancer stage and T-stage. Patients with a lower expression of ZFAS1 presented a slightly longer disease-free survival and overall survival. The analysis of genes associated with ZFAS1, as well its targets, indicate that they are linked with crucial cellular processes. In the group of patients with low expression of ZFAS1, we detected the up-regulation of suppressors and down-regulation of genes associated with epithelial-to-mesenchymal transition (EMT) process, metastases, and cancer-initiating cells. Moreover, the negative correlation between ZFAS1 and its host gene, ZNFX1, was observed. The analysis of interactions indicated that ZFAS1 has a binding sequence for miR-150-5p. The expression of ZFAS1 and miR-150-5p is negatively correlated in HNSCC patients. miR-150-5p can regulate the 3'UTR of EIF4E mRNA. In the group of patients with high expression of ZFAS1 and low expression of miR-150-5p, we detected an up-regulation of EIF4E. In HNSCC, ZFAS1 displays oncogenic properties, regulates important processes associated with EMT, cancer-initiating cells, and metastases, and might affect patients' clinical outcomes. ZFAS1 likely regulates the cell phenotype through miR-150-5p and its downstream targets. Following further validation, ZFAS1 might prove a new and valuable biomarker.