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Head and neck cancer (HNC) is the leading cancer in Sri Lankan males and second most common cancer among Sri Lankan females. This is the first study, to the best of our knowledge, that has focused on investigating the association between TP53 somatic DNA variants, with p53 protein expression and risk factors in a cohort of Sri Lankan patients with HNC. A total of 44 patients with cancer and 20 healthy controls were studied. In total, 36 genomic DNA sequence variants were found, including several novel variants (two deletions in exons 4 and 6, two in the 3′ untranslated region and several intronic variants). A total of 14 tumour samples carried pathogenic TP53 mutations. A random selection of 24 samples was analysed immunohistochemically for p53 protein expression. All the samples with point missense variants were strongly immuno-positive, whereas, samples with nonsense and frameshift TP53 variants were immuno-negative for p53 immunohistochemical staining. Although, the human papilloma virus is a known risk factor for HNC, results from the present study identified an absence or lower level of infection in the Sri Lankan cohort. [ABSTRACT FROM AUTHOR]

The present study aimed to identify sensitive, specific and independent prognostic biomarkers in head and neck cancer (HNC) based on microRNA expression profiles and other high‑throughput sequencing data in The Cancer Genome Atlas (TCGA) database. Identification of such prognostic biomarkers could provide insight into HNC diagnosis and treatment. The differential expression profiles of microRNAs between HNC tissues and adjacent cancer tissues in the TCGA database were analyzed (log fold‑change >2; P<0.01). Univariate and multivariate Cox regression analyses of the differentially expressed microRNAs were performed to determine those significantly related to the survival of patients with HNC. The identified microRNAs were verified by survival and receiver operating characteristic curve analyses. To better predict prognosis, a combined prognostic model (risk equation) was established based on the risk coefficient of each microRNA, calculated by a multivariate Cox regression analysis, and the risk score was calculated. To explore the signaling pathways related to prognosis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were performed on the differentially expressed genes between the high‑risk and low‑risk groups, grouped according to the median risk score. A total of 89 differentially expressed microRNAs between HNC and adjacent cancer tissues were screened, 11 of which were identified as risk factors related to HNC survival by the univariate Cox regression analysis (P<0.05). The multivariate Cox regression analysis showed that three of the 11 microRNAs, hsa‑miR‑99a, hsa‑miR‑499a and hsa‑miR‑1911 (all P<0.01), were identified as independent risk factors significantly related to patient survival. The risk equation used was as follows: Risk score=(‑0.1597 x hsa‑miR‑99a) + (0.1871 x hsa‑miR‑499a) + (0.1033 x hsa‑miR‑1911). KEGG and GO analyses showed that the JAK‑STAT signaling pathway and some metabolic pathways were associated with HNC prognosis. The present study suggested that hsa‑miR‑99a, hsa‑miR‑499a and hsa‑miR‑1911 may serve as potential prognostic biomarkers in HNC.