Identificação da expressão de snoRNAS em amostras de câncer de cabeça e pescoço e sua relação com as variáveis clínico – patológicas: Uma análise in silico

Abstract

Head and neck cancer (HNC) is the sixth most common type in the world, with approximately 931 thousand cases registered in 2020. More than 50% of patients are diagnosed at an advanced stage of the disease. Historically, the use of tobacco, alcohol and HPV infection are important risk factors for this malignancy. In addition, additional causes, such as epigenetic changes, need to be considered. Among the epigenetic elements are the small nucleolar RNAs (snoRNAs) that have been the focus of many studies in the last twenty years and their fundamental role in many human diseases, including cancer. Thus, the present study analyzed, through bioinformatics tools, the expression of snoRNAs in PCC samples, as well as correlating these data with clinical-pathological variables. For this purpose, data from the TCGA project were used. The characterization of snoRNAs in terms of type, chromosomal location and genomic sequence was performed using the following tools: central RNA, SnoDB and snoRNA Atlas, HGNC. To identify the expression of snoRNAs and expression in clinicopathological factors, the SNORic platform was used, and the analysis of the unique snoRNAs in each characteristic was performed using the Venn diagram. We observed 346 snoRNAs with differential expression between tumor and non-tumor, 280 with increased expression and 66 with decreased expression, the most expressed being SNORD28 and SNORD7 and the least expressed SNORD114-3. As for those that were associated with worse prognostic factors, SNORD3C stood out in histological grade G3, and SCARNA 15 in pathological stage IV. According to the research carried out in the literature, it was observed that 12 snoRNAs observed as differentially expressed in CCP, have already been addressed in other types of cancer, especially SNORD78. In this way, the data presented elucidate the importance and influence of the deregulation of potential biomolecules, which can be possible tools of great relevance in the prediction of prognosis.