关键词: 胃肿瘤, 核仁小 RNA, 预后, 基因表达谱, 癌基因, 因素分析, 统计学

Abstract: Abstract:Objective To identify snoRNA, which may be related to prognosis of gastric cancer. Methods Ninetygastric cancer patients who diagnosed at Tianjin Medical University Cancer Institute and Hospital were randomly collected in this study, and their clinical data were followed up. A total of 405 snoRNA expression profiles were analyzed in 90 gastric cancer patients. Patients were classified as "low expression" group or "high expression" group according to the median expression of each snoRNA expression, which was calculated by univariate and multivariate survival analysis. We also screened out the snoRNAs, in which patients were survived differently. Patients were classified as high, middle, or low risk groups based on the snoRNA risk score. Values of age, gender, smoking, drinking, histological differentiation (well, moderately-differentiated and poorly differentiated), clinical stage (Ⅰ+Ⅱstage and Ⅲ+Ⅳstage), tumor size (<5 cm and ≥5 cm), tumor location (upper 1/3 and others) and snoRNA isk score (high, middle, and low risk group) were assessed by multivariate Cox analysis. Results There were significant differences in overall survival and (or) progression-free survival rates in 19 patients with high and low snoRNAs expressions (P < 0.05). Results of multivariate Cox analysis showed that patients with high expression of ACA61， ACA27 and U36A showed a higher overall survival and progression-free survival rates, while patients with high expression of ENSG00000206898 showed a lower overall survival and progression-free survival survival rates (P < 0.01). SnoRNA risk score is an independent prognostic factor or patients with gastric cancer. Compared with low risk group, patients in middle risk group and in high risk group showed a shorter overall survival and progression-free survival rates (P < 0.001). Conclusion The expressions of ACA61, ACA27, U36A and ENSG00000206898 are independent prognostic factors of gastric cancer. Low expressions of the first three indexes and high expressions of the last one predict a bad prognosis.

Key words: gastric neoplasms, RNA, small nucleolar, prognosis, gene expression profiling, oncogenes, factor analysis, statistical