Genome-Wide Identification of a Novel Eight-lncRNA Signature to Improve Prognostic Prediction in Head and Neck Squamous Cell Carcinoma.

FRONTIERS IN ONCOLOGY(2019)

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摘要
Objectives: LncRNAs are essential survival prognostic indicators with important biological functions in tumorigenesis and tumor progression. This study aimed to establish a long non-coding RNA (lncRNA) signature that can effectively predict the prognosis of patients with head and neck squamous cell carcinoma (HNSCC) and explore the potential functions of these lncRNAs. Materials and Methods: We re-annotated RNA sequencing and obtained exhaustive RNA-seq data of 269 patients with comprehensive clinical information from the GEO database. Then an 8-lncRNA signature capable of predicting the survival prognosis of HNSCC patients and a nomogram containing this signature were established. Weighted Co-expression Network Construction (WGCNA), Gene Set Enrichment Analysis (GSEA), and Gene Ontology (GO) enrichment were then applied to predict the possible biological functions of the signature and each individual lncRNA. Results: Eight lncRNAs associated with survival in HNSCC patients, including AC010624.1, AC130456.4, LINC00608, LINC01300, MIR99AHG, AC008655.1, AC055758.2, and AC118553.1, were obtained by univariate regression, cox LASSO regression, and multivariate regression. Functionally, patients with high signature scores had abnormal immune functions via GSEA. AC010624.1 and AC130456.4 may participate in epidermal cell differentiation and skin development, and MIR99AHG in the formation of cellular structures. Other lncRNAs in the signature may also participate in important biological processes. Conclusions: Therefore, we established an 8-lncRNA signature that can effectively guide clinical prediction of the prognosis of patients with HNSCC, and individuals with high signature scores may have abnormal immune function.
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head and neck squamous cell carcinoma (HNSCC),long non-coding RNA (lncRNA),prognostic signature,weighted co-expression network construction (WGCNA),gene set enrichment analysis (GSEA)
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