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Background   Accumulating evidence has demonstrated the pivotal role of long noncoding RNAs (lncRNAs) in competing endogenous RNA (ceRNA) networks for predicting survival and evaluating prognosis in cancer patients. However, the pathogenesis of head and neck squamous cell carcinoma (HNSCC) remains unclear, and prognostic biomarkers for HNSCC are still lacking.Methods   A total of 546 RNA sequencing profiles of HNSCC patients with clinical outcome data were obtained from the Cancer Genome Atlas (TCGA) database, providing a large sample of RNA sequencing data. From these, 71 Long noncoding RNAs lncRNAs, 8 microRNAs (miRNAs), and 16 messenger RNAs (mRNAs) were identified to construct a HNSCC-specific ceRNA network (fold change >2, P < 0.05). Univariate and multivariate Cox proportional regression models were used to assess independent indicators of prognosis. Then the expression of lncRNAs harboring prognostic value was validated in human HNSCC cell lines and tumor samples from our cohort and another two datasets from GEO (Gene Expression Omnibus) databases.Results   As a result, a 3-mRNA signature and 6-lncRNA signature were identified. The six-lncRNA signature exhibited the highest prognostic value. Notably, in the six lncRNAs, HOTTIP showed the greatest prognostic value and was significantly correlated with clinical stage and histological grade of HNSCC patients. Furthermore, it was proved that HOTTIP was upregulated in HNSCC cell lines and cancerous tissues compared with corresponding normal cell lines and normal tissues. Functional assessment analysis revealed that HOTTIP might play a key role in the oncogenesis and progression of HNSCC.Conclusion   The present study deepened our understanding of the ceRNA-related regulatory mechanism in the pathogenesis of HNSCC and identified candidate prognostic biomarkers for clinical outcome prediction in HNSCC. HOTTIP may function as a key candidate biomarker in HNSCC and serve as a prognostic marker for HNSCC patients.

HOTTIP Functions as a Key Candidate Biomarker in Head and Neck Squamous Cell Carcinoma by Integrated Bioinformatic Analysis