摘要
Abstract
To screen out the differentially expressed genes in osteosarcoma tissues by bioinformatics and to investigate its relationship with the prognosis of patients.Methods We performed RNA-Seq to screen out the differentially expressed genes (DEGs)in osteosarcoma and matched normal tissues of four osteosarcoma patients followed by the Gene Oncology (GO) enrichment.In addition, we selected 258 cases of osteosarcoma tissue specimens in the Cancer Genome Atlas (TCGA) HCC data to analyze the influence of DEGs on survival time of patients by using based on Kaplan-Meier curve analysis.Results In total, 875 DEGs were identified in four pairs of osteosarcoma specimens, including down-regulated 529 genes and 346 up-regulated genes.According to GO enrichment, 14 significant GO terms in the biological process were identified.In the six biological process types, the DEGs were mainly enriched in exogenous metabolic processes, cell adhesion, extracellular matrix composition, and steroid metabolism process;in the 8 cell composition types, the DEGs were mainly enriched in the extracellular domain, extracellular space, collagen trimer, nucleosome and so on.Two novel genes (NQO1 and ALDH3A1) were significantly associated with poor prognosis in the TCGA osteosarcoma cohort (n=258).The average survival time in 233 cases with over-expression and 25 cases with low-expression of NQO1 was (2763±15) and (1568±13) days, respectively.The average survival time in 233 cases with over-expression and 25 cases with low-expression of ALDH3A1 was (2725±11) and (1421±14) days, respectively.The expression of other genes had no significant effect on the survival time of the patients (all P>0.05).Conclusion We identified 875 DEGs that mainly enrich in biological process and cellular component and the low-expression of NQO1 and ALDH3A1 is significantly associated with poor prognosis for osteosarcoma.关键词
骨肉瘤/基因本体功能显著性富集分析/基因筛选/转录组测序/生物信息学/生存时间Key words
osteosarcoma/Gene Oncology enrichment/gene screening/transcriptome sequencing/bioinformatics/survival time分类
医药卫生
