摘要
目的研究肺腺癌患者外周血中非编码RNA的表达差异。方法收集新疆医科大学附属肿瘤医院2019年1月—2019年12月呼吸神经内科收治的肺腺癌患者与健康对照组的外周血各4例,利用TRIZOL试剂盒提取两组患者外周血中RNA,采用RNA-Seq高通量测序检测lncRNA表达谱,利用lncTar软件对差异表达的lncRNA和mRNA行共表达分析,进而采用KOBAS软件对mRNA行基因本体论(GO)和京都基因和基因组百科全书(KEGG)分析。结果与对照组相比,肺腺癌患者外周血中有804个差异表达的lncRNA(其中425个表达上调,379个表达下调,P≤0.05),对存在差异的lncRNA靶向的mRNA行GO分析发现,肺腺癌对比健康人主要与翻译起始、mRNA分解过程相关,KEGG主要与核糖体、代谢途径等通路相关。结论LINC02193、SNHG17、TUG1、LINC01503可作为肺腺癌发生发展的标志物,肺腺癌的发生可能与核糖体、代谢途径等通路有关。
Objective Study on expression and function of non-coding RNA in serum of patients with lung adenocarcinoma.Methods The peripheral blood samples of 4 patients with lung adenocarcinoma and the 4 normal controls in the hospital from January to December 2019 were collected.RNA was extracted by TRIZOL kit,lncRNA expression profile was detected by RNA-Seq high-throughput sequencing,and the co-expression of lncRNA and mRNA were analyzed by lncTar software,and then mRNA was analyzed by gene ontology(GO)and Jingdu Encyclopedia of Gene and Genome(KEGG).Results Compared with the control group,there were 804 differentially expressed lncRNA in the sera of the patients with lung adenocarcinoma(425 up-regulated and 379 down-regulated,P≤0.05).GO analysis showed that it was mainly related to translation initiation and mRNA decomposition,and KEGG was mainly related to ribosome and metabolic pathway.Conclusion LINC02193,SNHG17,TUG1,LINC01503 may be used as the markers for occurrence and development of lung adenocarcinoma.The occurrence of lung adenocarcinoma may be related to the pathways,such as ribosomes and metabolic pathways.
作者
牛海文
崔浩波
李宏
曹国磊
何丽丽
曹嘉芮
张迪
罗琴
NIU Haiwen;CUI Haobo;LI Hong;CAO Guolei;HE Lili;CAO Jiarui;ZHANG Di;LUO Qin(Department of Respiratory Neurology,Affiliated Cancer Hospital of Xinjiang Medical University,Urumqi 830011,China)
出处
《新疆医科大学学报》
CAS
2022年第1期15-19,共5页
Journal of Xinjiang Medical University
基金
国家自然科学基金(81760014)
天山青年计划项目(2018Q048)
新疆维吾尔自治区科技支疆项目计划(2019E0281)
新疆维吾尔自治区自然科学基金青年基金(2018D01C272)。
关键词
肺腺癌
高通量测序
非编码RNA
差异表达
lung adenocarcinoma
high-throughput sequencing
non-coding RNA
differential expression