LINC00662通过调控miR⁃106a⁃5p/CAV1轴影响肝癌细胞对索拉非尼药物的敏感性

目的:探究长链非编码RNA⁃LINC00662对诱导肝细胞癌(HCC)细胞索拉非尼耐药的机制。方法:以HCC细胞(HepG2、HCCLM3),索拉非尼耐药肝癌细胞HCC⁃SR(HepG2⁃SR、HCCLM3⁃SR)为研究对象,通过实时荧光定量聚合酶链反应(RT⁃qPCR)和Western blotting检测各组细胞中LINC00662、miR⁃106a⁃5p和小窝蛋白⁃1(CAV1)表达水平。将si⁃LINC00662、miR⁃106a⁃5p模拟物分别转染HCC⁃SR细胞,通过细胞活性试剂盒(CCK⁃8)检测细胞对索拉非尼药物敏感性。且进一步通过双荧光素酶报告实验、RT⁃qPCR、Western blotting确定LINC00662与miR⁃106a⁃5p、miR⁃106a⁃5p与CAV1之间的靶向关系。结果:HCC⁃SR细胞中LINC00662和CAV1相对表达显著升高,miR⁃106a⁃5p表达显著降低(P<0.01,P<0.001);干扰LINC00662表达或过表达miR⁃106a⁃5p,HCC⁃SR细胞对索拉非尼药物敏感性显著升高(P<0.05,P<0.01)。且LINC00662靶向负性调控miR⁃106a⁃5p表达,miR⁃106a⁃5p靶向负性调控CAV1表达(P<0.05)。结论:LINC00662可以作为miR⁃106a⁃5p的竞争性内源性RNA(ceRNA)促进CAV1的表达,介导HCC细胞索拉菲尼的耐药性,干扰LINC00662表达可抑制HCC细胞索拉非尼耐药,增加索拉非尼的敏感性。

益智仁研究文献计量学分析

目的分析我国目前已发表的与中药益智仁研究相关的文献特征和研究现况。方法检索中国知识资源总库(CNKI) 1963年1月1日至2019年9月31日收录的益智仁研究相关文献,从发表年份、方向、类型、机构、研究内容、基金支持、应用等方面进行文献计量学分析。结果纳入文献566篇,文献数量在2010年后迅速增长,占文献总数的38.1%;文献发表单位以全国中医药大学为主;22.12%的文献受到了各级科研基金的资助,文章类型多倾向于对疾病的治疗作用,且研究方向多样化。结论益智仁在中医药领域的药效与研究已日益加强,研究方式及学科范畴呈丰富多样化,仍需更进一步系统研究,以形成较完善的治疗体系。

卵巢癌致病关键靶基因分析及体外细胞实验验证

目的:通过多芯片整合的生物信息学方法挖掘与卵巢癌发病高度关联的靶基因,并通过体外细胞实验进行验证,为卵巢癌的靶向研究提供关键基因及重要理论依据。方法:(1)对基因表达综合数据库中与卵巢癌相关数据集GSE38666、GSE40595和GSE54388进行差异基因(DEGs)筛选,其中包括26个正常样本和65个卵巢癌样本。(2)通过DAVID在线数据库对筛选的DEGs进行基因本体功能注释,明确DEGs的生物学属性特征。(3)通过京都基因与基因组百科进行富集分析,获得DEGs的主要作用通路。(4)基于STRING数据库运用CytoScape软件完成DEGs蛋白质-蛋白质相互作用网络的构建,并结合GEPIA 2等数据库筛选出关键基因。(5)采用qRT-PCR对卵巢癌细胞关键基因的表达进行验证。结果:从GSE38666、GSE40595和GSE54388 3个数据集中筛选出238个共同表达的DEGs,其中168个表达上调,70个表达下调,在卵巢癌中主要富集于有丝分裂核分裂、纺锤体、染色体区域和DNA解旋酶,主要参与细胞周期、DNA复制、氧化磷酸化和氨基酸的生物合成等生物过程,影响卵巢癌的发生、发展。其中IFI27、EPCAM、CXCR4、PEA15、CLDN3和CAPG 6个差异表达基因与卵巢癌高度相关,体外细胞实验结果与其一致。结论:多芯片整合的生物信息学方法是筛选卵巢癌靶基因的有效方法,IFI27、EPCAM、CXCR4、PEA15、CLDN3和CAPG与卵巢癌发生、发展高度相关,有望成为卵巢癌致病关键靶基因,需要进行深入研究。

Analysis of key pathogenic target genes of ovarian cancer and experimental verification of cells in vitro

Objective:To mine genes highly related to the pathogenesis of ovarian cancer by using multichip integrated bioinformatics methods and verify them in cells,which provided key genes and important theoretical basis for targeted research of ovarian cancer.Methods:Three datasets,GSE38666,GSE40595 and GSE54388,were downloaded from the Gene Expression Integrated Database database for differential gene(DEGs)screening,including 26 normal samples and 65 ovarian cancer samples.Gene ontology functional annotation of selected DEGs was performed through DAVID online database to clarify the biological characteristics of DEGs.The main pathways of DEGs were obtained by enrichment analysis using Kyoto gene and genomic encyclopedia method.Based on the STRING database,the DEGs protein-protein interaction network was constructed by using CytoScape software,and the key genes were screened by GEPIA2 database to verify the expression at the cell level.Results:A total of 238 DEGs were screened from GSE38666,GSE40595 and GSE54388 datasets,of which 168 DEGs were upregulated and 70 DEGs were down-regulated.The co-expressed DEGs were mainly enriched in biological functions such as mitotic nuclear division,spindle,chromosomal region and DNA helicase activity in ovarian cancer.They were mainly involved in biological processes such as cell cycle,DNA replication,oxidative phosphorylation and biosynthesis of amino acids,thereby affecting the occurrence and development of ovarian cancer.Six genes were highly expressed and associated with the development of ovarian cancer,including IFI27,EPCAM,CXCR4,PEA15,CLDN3 and CAPG.Cell verification showed that the mRNA expression of the six genes in ovarian cancer cells was higher than that in normal ovarian cells(P<0.05),which was consistent with the previous screening results.Conclusion:Multi-chip integrated bioinformatics is an effective method to find ovarian cancer target genes.IFI27,EPCAM,CXCR4,PEA15,CLDN3 and CAPG are highly correlated with the occurrence and development of ovarian cancer,which can be used as target genes for ovarian cancer research.