Identification of differentially expressed genes and biological characteristics of colorectal cancer by integrated bioinformatics analysis

Colorectal cancer (CRC) ranks as one of the most common malignant tumors worldwide. Its mortality rate has remained high in recent years. Therefore, the aim of this study was to identify significant differentially expressed genes (DEGs) involved in its pathogenesis, which may be used as novel biomarkers or potential therapeutic targets for CRC. The gene expression profiles of GSE21510, GSE32323, GSE89076, and GSE113513 were downloaded from the Gene Expression Omnibus (GEO) database. After screening DEGs in each GEO data set, we further used the robust rank aggregation method to identify 494 significant DEGs including 212 upregulated and 282 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by DAVID and the KOBAS online database, respectively. These DEGs were shown to be significantly enriched in different cancer-related functions and pathways. Then, the STRING database was used to construct the protein–protein interaction network. The module analysis was performed by the MCODE plug-in of Cytoscape based on the whole network. We finally filtered out seven hub genes by the cytoHubba plug-in, including PPBP, CCL28, CXCL12, INSL5, CXCL3, CXCL10, and CXCL11. The expression validation and survival analysis of these hub genes were analyzed based on The Cancer Genome Atlas database. In conclusion, the robust DEGs associated with the carcinogenesis of CRC were screened through the GEO database, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for CRC.     

鸡胚公母性腺差异表达基因的基因芯片杂交筛选

采用Affymetrix公司鸡基因组芯片对9日龄鸡胚公母性腺总RNA进行了芯片杂交, 并对基因表达谱进行了分析。统计结果显示, 9日龄母鸡性腺表达基因数19 368个, 公鸡性腺表达基因数19 493个; 公母性腺绝对差异表达基因,即公鸡性腺表达而母鸡性腺不表达基因145个, 母鸡性腺表达而公鸡性腺不表达基因189个。绝对差异表达基因功能分类结果显示, 参与细胞组成、细胞加工和分子结合基因占多数, 部分基因参与细胞器组成、代谢加工、生物学调控以及催化反应和细胞信号转导等。值得注意的是, 本研究发现了一些已经报道同性别决定和分化有一定关联的基因, 如ASW、CHD1和SOX9等, 同时也发现了一些未知其同性腺分化和发育有关联的基因和编码假想蛋白的表达序列。进一步分析这些基因和表达序列的生物学功能和表达模式, 将对鸟类性别决定和分化机制的了解提供有益参考。     

差异表达基因的分离策略

生命活动的各个进程伴随着不同基因的选择性开启和关闭。如何有效地分离克隆各种差异表达的基因,成为分子生物学研究的一个努力方向,大量差异基因分离策略因之问世。本文扼要介绍了近年来发展的几种主要分离策略,并详细介绍一种新的差异基因分离方法--抑制差减杂交。     

寒冷适应差异表达基因的研究

为寻找寒冷适应机体表达上调的相关基因,以Balb／C小鼠建立寒冷适应模型,分别提取肌肉和肝脏RNA,运用代表性差异分析(RDA)方法,寻找寒冷适应表达上调的相关基因片段,进行序列分析和同源性比较。结果显示,在肌肉和肝脏中有部分表达上调的基因片段,经狭线杂交验证,其中3条基因表达存在显著差异。这些新发现的机体寒冷适应相关基因为进一步理解寒冷适应的分子机制提供了帮助。     

Adaptive thresholds to detect differentially expressed genes in microarray data

To detect changes in gene expression data from microarrays, a fixed threshold for fold difference is used widely. However, it is not always guaranteed that a threshold value which is appropriate for highly expressed genes is suitable for lowly expressed genes. In this study, aiming at detecting truly differentially expressed genes from a wide expression range, we proposed an adaptive threshold method (AT). The adaptive thresholds, which have different values for different expression levels, are calculated based on two measurements under the same condition. The sensitivity, specificity and false discovery rate (FDR) of AT were investigated by simulations. The sensitivity and specificity under various noise conditions were greater than 89.7% and 99.32%, respectively. The FDR was smaller than 0.27. These results demonstrated the reliability of the method.     

Identification of key genes and pathways of thyroid cancer by integrated bioinformatics analysis

Thyroid cancer is a common endocrine malignancy with a rapidly increasing incidence worldwide. Although its mortality is steady or declining because of earlier diagnoses, its survival rate varies because of different tumour types. Thus, the aim of this study was to identify key biomarkers and novel therapeutic targets in thyroid cancer. The expression profiles of GSE3467, GSE5364, GSE29265 and GSE53157 were downloaded from the Gene Expression Omnibus database, which included a total of 97 thyroid cancer and 48 normal samples. After screening significant differentially expressed genes (DEGs) in each data set, we used the robust rank aggregation method to identify 358 robust DEGs, including 135 upregulated and 224 downregulated genes, in four datasets. Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analyses of DEGs were performed by DAVID and the KOBAS online database, respectively. The results showed that these DEGs were significantly enriched in various cancer-related functions and pathways. Then, the STRING database was used to construct the protein–protein interaction network, and modules analysis was performed. Finally, we filtered out five hub genes, including LPAR5, NMU, FN1, NPY1R, and CXCL12, from the whole network. Expression validation and survival analysis of these hub genes based on the The Cancer Genome Atlas database suggested the robustness of the above results. In conclusion, these results provided novel and reliable biomarkers for thyroid cancer, which will be useful for further clinical applications in thyroid cancer diagnosis, prognosis and targeted therapy.     

筛选差异表达基因方法的新进展

了解不同细胞或同类细胞在不同发育阶段、不同生理状态下的基因表达状况,可以为研究生命活动过程提供重要信息。以差别筛选、削减杂交等基本方法为出发点,研究基因表达差异的方法不断完善,先后出现了DDRT—PCR、RDA、SSH、cDNA微阵列(基因芯片)、基因表达的系统分析(SAGE)等技术。本着重对这些方法的优缺点及改进进行论述和评介,并对技术的发展趋势进行了分析。     

Identification of differentially expressed genes in synovial tissue of rheumatoid arthritis and osteoarthritis in patients

Rheumatoid arthritis (RA) and osteoarthritis (OA) are the common joints disorder in the world. Although they have showed the analogous clinical manifestation and overlapping cellular and molecular foundation, the pathogenesis of RA and OA were different. The pathophysiologic mechanisms of arthritis in RA and OA have not been investigated thoroughly. Thus, the aim of study is to identify the potential crucial genes and pathways associated with RA and OA and further analyze the molecular mechanisms implicated in genesis. First, we compared gene expression profiles in synovial tissue between RA and OA from the National Center of Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. Gene Expression Series (GSE) 1919, GSE55235, and GSE36700 were downloaded from the GEO database, including 20 patients of OA and 21 patients of RA. Differentially expressed genes (DEGs) including “CXCL13,” “CD247,” “CCL5,” “GZMB,” “IGKC,” “IL7R,” “UBD///GABBR1,” “ADAMDEC1,” “BTC,” “AIM2,” “SHANK2,” “CCL18,” “LAMP3,” “CR1,” and “IL32.” Second, Gene Ontology analyses revealed that DEGs were significantly enriched in integral component of extracellular space, extracellular region, and plasma membrane in the molecular function group. Signaling pathway analyses indicated that DEGs had common pathways in chemokine signaling pathway, cytokine-cytokine receptor interaction, and cytosolic DNA-sensing pathway. Third, DEGs showed the complex DEGs protein-protein interaction network with the Coexpression of 83.22%, Shared protein domains of 8.40%, Colocalization of 4.76%, Predicted of 2.87%, and Genetic interactions of 0.75%. In conclusion, the novel DEGs and pathways between RA and OA identified in this study may provide new insight into the underlying molecular mechanisms of RA.     

Identification of differentially expressed genes related to metabolic syndrome induced with high-fat diet in E3 rats

Understanding the genes differentially expressing in aberrant organs of metabolic syndrome (MetS) facilitates the uncovering of molecular mechanisms and the identification of novel therapeutic targets for the disease. This study aimed to identify differentially expressed genes related to MetS in livers of E3 rats with high-fat-diet-induced metabolic syndrome (HFD-MetS). E3 rats were fed with high-fat diet for 24 weeks to induce MetS. Then, suppression subtractive hybridization (SSH) technology was used to identify the genes differentially expressed between HFD-MetS and control E3 rat livers. Twenty positive recombinant clones were chosen randomly from forward subtractive library and sent to sequence. BLAST analysis in GenBank database was used to determine the property of each cDNA fragment. In total, 11 annotated genes, 3 ESTs, and 2 novel gene fragments were identified by SSH technology. The expression of four genes (Alb, Pip4k2a, Scd1, and Tf) known to be associated with MetS and other five genes (Eif1, Rnase4, Rps12, Rup2, and Tmsb4) unknown to be relevant to MetS was significantly up-regulated in the livers of HFD-MetS E3 rats compared with control rats using real-time quantitative PCR (RT-qPCR). By analyzing the correlations between the expression of these nine genes and serum concentrations of TG, Tch, HDL-C, and LDL-C, we found that there were significant positive correlations between TG and the expression of five genes (Alb, Eif1, Pip4k2a, Rps12, and Tmsb4x), Tch and three genes (Rnase4, Scd1, and Tmsb4x), and LDL-C and two genes (Rnase4 and Scd1), as well there were significant negative correlations between HDL-C and the expression of three genes (Rup2, Scd1, and Tf). This study provides important clues for unraveling the molecular mechanisms of MetS.     

Identification of differentially expressed genes and the role of PDK4 in CD14+ monocytes of coronary artery disease

Background. Coronary artery disease (CAD) is a chronic inflammatory disease caused by development of atherosclerosis (AS), which is the leading cause of mortality and disability. Our study aimed to identify the differentially expressed genes (DEGs) in CD14⁺ monocytes from CAD patients compared with those from non-CAD controls, which might pave the way to diagnosis and treatment for CAD. Methods. The RNA-sequencing (RNA-seq) was performed by BGISEQ-500, followed by analyzing with R package to screening DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by R package. In addition, we validated the results of RNA-seq using real-time quantitative polymerase chain reaction (RT-qPCR). Furthermore, we explored the function of selected ten genes in LDL-treated CD14⁺ monocytes by RT-qPCR. Results. a total of 2897 DEGs were identified, including 753 up- and 2144 down-regulated genes in CD14⁺ monocytes from CAD patients. These DEGs were mainly enriched in plasma membrane and cell periphery of cell component, immune system process of biological process, NF-κB signaling pathway, cell adhesion molecules signaling pathway and cytokine–cytokine receptor interaction signaling pathway. In LDL-treated CD14⁺ monocytes, the mRNA expression of pyruvate dehydrogenase kinase 4 (PDK4) was significantly up-regulated. Conclusion. In the present study, we suggested that PDK4 might play a role in progression of CAD. The study will provide some pieces of evidence to investigate the role and mechanism of key genes in the pathogenesis of CAD.     

转化的大鼠胚胎成纤维细胞系差异表达基因的筛选研究

来源于转化的大鼠胚胎成纤维细胞系的两株细胞,A1－5细胞与B4细胞相比表现出非常强的抗辐射性并伴随不同寻常强的G2延迟效应;用PCR选择性抑制消减杂交方法对这两株细胞进行差减,希望找到对A1－5细胞表现出的不同寻常的表型起关键作用的某一个或某一些基因。结果得到了160个差减转化子,逐个进行序列测定,并进行Dot blot杂交,共得到35个差异表达基因片段（EST）。通过对美国国家生物技术信息中心（NCBI）的非冗余序列库（NT）、鼠EST库及人EST库的BLAST进行同源检索,发现其中21个代表了尚未登录的新基因,另外14个分别与已知基因高度同源。