Single-cell sequencing analysis and transcriptome analysis constructed the macrophage related gene-related signature in lung adenocarcinoma and verified by an independent cohort

BackgroundRecent studies have emphasized the close relationship between macrophages and tumor immunity, and the prognosis of lung adenocarcinoma (LUAD) patients is intimately linked to this. Nonetheless, the prognostic signature and classification of different immune patterns in LUAD patients based on the macrophages is largely unexplored.MethodsTwo sc-RNAseq datasets of LUAD patients were collected and reprocessed. The differentially expressed genes (DEGs) related to macrophages between LUAD tissues and normal lung tissues were then identified. Based upon the above genes, three distinct immune patterns in the TCGA-LUAD cohort were identified. The ssGSEA and CIBERSORT were applied for immune profiling and characterization of different subtypes. A four-gene prognostic signature for LUAD patients was established based on the DEGs between the subtypes using stepwise multi-Cox regression. TCGA-LUAD cohort was used as training set. Five GEO-LUAD datasets and an independent cohort containing 112 LUAD samples were used for validation. TIDE (tumor immune dysfunction and exclusion) and drug sensitivity analyses were also performed.ResultsMacrophage-related differentially expressed genes were found out using the publicly available scRNA-seq data of LUAD. Three different immune patterns which were proved to have distinct immune infiltration characteristics in the TCGA-LUAD cohort were recognized based on the above macrophage-related genes. Thereafter, 174 DEGs among the above three different immune patterns were figured out; on the basis of this, a four-gene prognostic signature was constructed. This signature distinguished the prognosis of LUAD patients well in various GSE datasets as well as our independent cohort. Further analyses revealed that patients which had a higher risk score also accompanied with a lower immune infiltration level and a worse response to several immunotherapy biomarkers.ConclusionThis study highlighted that macrophage were significantly associated with TME diversity and complexity. The four-gene prognostic signature could be used for predicting outcomes and immune landscapes for patients with LUAD.     

INHA acts as a novel and potential biomarker in lung adenocarcinoma and shapes the immune-suppressive tumor microenvironment

BackgroundINHA expression has been correlated with the development, growth, and progression of multiple cancer types. However, the biological role of INHA has not been investigated in patients with lung adenocarcinoma (LUAD). Here, we performed a comprehensive bioinformatics analysis of the LUAD dataset to determine the mechanisms underlying the regulation of tumorigenesis by INHA.Materials and methodsINHA expression and clinical information of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) database. Protein levels in LUAD cell lines and human lung epithelial cells were examined by western blotting. Next, the prognostic value of INHA in LUAD was assessed using Cox regression analysis, while the potential biological functions and the impact on the immune microenvironment of INHA were investigated using gene set enrichment analysis (GSEA) and single sample GSEA (ssGSEA). Finally, the effect of INHA on LUAD cell proliferation and invasion was determined in vitro and in vivo.ResultsWe found significantly high mRNA and protein expression levels of INHA in LUAD tissues and cell lines. Additionally, a higher expression of INHA was linked to a shorter overall survival (OS) and a worse pathological stage, while INHA expression was associated with immune cell infiltration and immune-related markers in the LUAD tumor microenvironment. LUAD with high INHA expression tends to be a cold tumor. Furthermore, GO and KEGG enrichment analysis indicated that INHA-related genes were enriched in the cell adhesion and immune signaling pathways of LUAD. INHA promoted LUAD cell proliferation and invasion, in vitro and in vivo, by inducing the EGFR pathway.ConclusionOur findings revealed that INHA is overexpressed in LUAD and is linked to a poor prognosis. Our study demonstrates the potential of INHA as an immunotherapeutic and predictive biomarker in LUAD.     

Knockdown of CTRP6 reduces the deposition of intramuscular and subcutaneous fat in pigs via different signaling pathways

The regulation of porcine subcutaneous (SC) and intramuscular (IM) fat deposition significantly affects pork quality and the lean meat percentage of the carcass, respectively. The adipokine C1q/tumor necrosis factor-related protein 6 (CTRP6), plays a significant role in regulating animal fat deposition. The purpose of this study was to understand the effects of CTRP6 gene knockdown in IM and SC adipocytes by RNA-seq analysis. A total of 1830 and 2936 differentially expressed genes (DEGs) were identified in SC and IM adipocytes, respectively. 844 were down- and 2092 were upregulated in SC adipocytes, while 648 were down- and 1182 were upregulated in IM adipocytes. Furthermore, 1778 DEGs were detected only in SC adipocytes, 672 DEGs only in IM adipocytes, and 1158 DEGs in both types of adipocytes. GO analysis indicated that DEGs involved in adipocyte differentiation were significantly enriched in both SC and IM adipocytes following treatment with CTRP6-siRNA. Moreover, KEGG pathway enrichment analysis revealed differences of metabolic regulation between IM and SC adipocytes. With CTRP6-silencing, the signaling pathways related to Ras and arachidonic acid metabolism were significantly enriched in IM adipocytes, while four other signaling pathways, encompassing the TNF, MAPK, p53 and adipokine pathway were specifically enriched in SC adipocytes. Interestingly, the effect of CTRP6-siRNA treatment was attenuated by the specific Ras activator ML-097 in IM adipocytes, while the specific p53 activator SJ-172550 had the corresponding effect in SC adipocytes. Altogether, we suggest that CTRP6 may be a differential regulator of the development and metabolism of IM and SC adipose tissues.     

Differences in potential key genes and pathways between primary and radiation-associated angiosarcoma of the breast

BackgroundAngiosarcoma of the breast is a high-grade malignant soft tissue tumor, it can be divided into primary and radiation-associated angiosarcoma(secondary). However, the differences between primary and secondary angiosarcomas in terms of pathogenesis, clinical behavior, early diagnosis biomarkers, genetic abnormalities, and therapeutic targets remain to be fully elucidated. At the same time, due to its rarity, most of current information relating to angiosarcoma is provided by case reports. Therefore, exploring the mechanisms of primary and secondary breast angiosarcoma have important value for the discovery of new biomarkers and research into potential therapeutic targets.MethodsThe differentially expressed genes (DEGs) between 36 cases of primary angiosarcoma and 54 cases of secondary angiosarcoma were screened. Then, the DEGs were used to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Then, a protein-protein interaction (PPI) network was constructed using the STRING database.ResultsA total of 18 DEGs were identified, of which 13 were upregulated and 5 were downregulated in secondary breast angiosarcoma. The GO enrichment analysis showed that the DEGs were most enriched in metabolism, energy pathways, and protein metabolism in biological processes. The enriched signaling pathways of DEGs were the transforming growth factor-β (TGF-β), Wnt, Hippo and PI3K-Akt signaling pathways. Then, the PPI network was conducted and hub genes were identified and they were involved in thyroid hormone, Hippo and other signaling pathways.ConclusionThis study lay the foundation for the discovery of effective and reliable molecular biomarkers and essential therapeutic targets for these malignancies.     

基于转录组的不同火龙果品种抗性差异分析

不同的品种抗性不同,为进一步探究不同火龙果品种之间的抗性差异,为后续火龙果抗性育种提供参考,该研究利用Illumina HiSeq 2000测序平台对'普通白肉'(BR)和'厄瓜多尔黄龙'(EY)两个品种进行转录组测序分析,并参考GO Ontology、KEGG等公共数据库对差异表达基因进行功能分类与富集分析.结果表明...     

NaCl胁迫下哈茨木霉ACCC32524的转录组和代谢组分析

【目的】通过分析NaCl胁迫下哈茨木霉(Trichoderma harzianum)ACCC32524转录组和代谢组数据,研究差异表达基因及次级代谢产物的变化情况,初步探索响应NaCl胁迫的分子机制。【方法】利用Illumina HiSeq XTen高通量测序平台完成0、0.4、0.6 mol/L NaCl浓度胁迫培养下哈茨木霉ACCC32524的转录组测序,GC-TOF-MS技术完成对0mol/L和0.6mol/LNaCl胁迫培养下的差异次级代谢产物检测,利用相关软件及数据库对差异表达基因(DEGs)和次级代谢产物的注释、筛选和分类,并进行RT-qPCR验证。【结果】本研究分别得到0.4 mol/L和0.6 mol/L NaCl胁迫下417和733条差异表达基因;GO富集分析显示,分别有318和582条差异表达基因注释到生物学过程、分子功能和细胞组分3个一级分类和40个二级分类;COG分类结果表明分别有232和414条转录本为20个类别,涉及差异表达基因最多的分别为氨基酸的转运和代谢、一般功能预测、碳水化合物的转运和代谢;KEGG代谢途径分析结果表明,分别有75和96条基因归到25个代谢通路中(P≤0.05),其中涉及差异基因最多的是氨基酸的生物合成和2-氧代羧酸代谢通路。从转录组数据中共筛选出与渗透调节、离子转运、活性氧清除等22个耐盐相关基因。0 mol/L和0.6 mol/L NaCl胁迫下的代谢组数据中共筛选出101个差异次级代谢产物,包括8种积累量上调和93种下调物质,其中36个得到定性,分属于糖类、有机酸和氨基酸等9个分类中。RT-qPCR验证挑选的差异表达基因的表达量变化,均与RNA-seq分析结果一致。【结论】NaCl胁迫下引起哈茨木霉ACCC32524基因及次级代谢产物发生明显变化,细胞代谢途径发生明显偏移,这些进程共同作用减少NaCl对细胞的毒害作用,为木霉菌的耐盐机理研究提供重要信息。     

基于转录组的八角挥发油合成相关基因挖掘与分析

为更好地挖掘八角(Illicium verum)挥发油合成相关基因，该文对挥发油性状差异显著的优良无性系桂角69号及普通品种砧01号叶片进行了转录组测序及组装注释，并对差异表达基因进行了GO分类和KEGG通路分析。结果表明：(1)转录本经组装后获得84 182条序列，使用NR、NT、Swiss-Prot、KEGG、KOG、GO和Pfam数据库进行序列比对，共注释了59 161条序列，筛选出30 572个差异表达基因。与砧01号相比，桂角69号叶片中上调基因有15 025个，下调基因有15 547个。(2)GO分类结果显示共有20 287个差异基因被注释。KEGG分析结果表明，有21 600个差异基因被注释到133条KEGG通路上，其中挥发油合成相关的单萜生物合成通路、萜类骨架生物合成通路、苯丙素合成通路中的芳樟醇合酶、月桂烯合酶、香叶基香叶基焦磷酸合酶、肉桂酰辅酶A还原酶、咖啡酸3-O-甲基转移酶、肉桂醇脱氢酶等关键酶基因呈差异表达。(3)转录因子分析发现差异表达基因分布于31个转录因子家族，其中MYB家族序列数量最多。该文利用转录组测序技术分析八角优良无性系与普通品种叶片的差异基因及...     

Identification of hub genes and pathways in adrenocortical carcinoma by integrated bioinformatic analysis

Adrenocortical carcinoma (ACC), a rare malignant neoplasm originating from adrenal cortical cells, has high malignancy and few treatments. Therefore, it is necessary to explore the molecular mechanism of tumorigenesis, screen and verify potential biomarkers, which will provide new clues for the treatment and diagnosis of ACC. In this paper, three gene expression profiles (GSE10927, GSE12368 and GSE90713) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained using the Limma package. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched by DAVID. Protein‐protein interaction (PPI) network was evaluated by STRING database, and PPI network was constructed by Cytoscape. Finally, GEPIA was used to validate hub genes’ expression. Compared with normal adrenal tissues, 74 up‐regulated DEGs and 126 down‐regulated DEGs were found in ACC samples; GO analysis showed that up‐regulated DEGs were enriched in organelle fission, nuclear division, spindle, et al, while down‐regulated DEGs were enriched in angiogenesis, proteinaceous extracellular matrix and growth factor activity; KEGG pathway analysis showed that up‐regulated DEGs were significantly enriched in cell cycle, cellular senescence and progesterone‐mediated oocyte maturation; Nine hub genes (CCNB1, CDK1, TOP2A, CCNA2, CDKN3, MAD2L1, RACGAP1, BUB1 and CCNB2) were identified by PPI network; ACC patients with high expression of 9 hub genes were all associated with worse overall survival (OS). These hub genes and pathways might be involved in the tumorigenesis, which will offer the opportunities to develop the new therapeutic targets of ACC.     

基于高通量转录组测序技术的无精子症患者睾丸组织比较转录组分析

本研究探讨不同程度无精子症患者睾丸组织的转录组差异,了解差异表达基因(DEG)在功能、分类和代谢通路的不同,揭示无精子症患者精子发生分子机制,为促进男性不育研究的发展提供理论基础.选取1份非梗阻性无精子症和4份梗阻性无精子症患者睾丸组织样品(从无精子到有精子),进行RNA提取和文库构建,利用Illumina HiSeqTM2500高通量测序,构建无精子症患者睾丸组织转录组文库,并用生物信息学方法进行分析.结果发现,样品比对基因组数据库的平均比对率为94.38%,共检测2 242个属于预测新的蛋白质编码基因的转录本.得到差异表达基因统计结果为:NOA vs. OA1基因上调8 045,下调1 150;OA1 vs. OA2基因上调1 538,下调420;OA2 vs. OA3基因上调1 275,下调1 690;OA3 vs. OA4基因上调1 834,下调1 853.比较5例无精子症睾丸组织的差异基因KEGG,主要富集在RNA降解通路、基底细胞瘤通路、癌通路、黑色素生成通路和调节干细胞多能性等信号通路. PRM1、PRM2、TNP1、UBXN6、CXCL16、NUPR2、CCDC136和CRISP2等基因的表达呈递增趋势,并具有时序特异性.此外,5例无精子症睾丸组织的表达基因有不同程度的基因融合.综上,基因融合可能和无精子症相关,并且不同程度无精子症患者睾丸组织的差异表达基因数量、功能、分类和代谢通路不同.本研究筛选出精子发生、精子运动等差异表达基因,丰富了无精子症患者睾丸组织转录组信息,为开展无精子症患者睾丸组织相关基因及分子调控机制的研究奠定基础.     

Identification of Key Genes and Pathways Involved in the Heterogeneity of Intrinsic Growth Ability Between Neurons After Spinal Cord Injury in Adult Zebrafish

In the adult central nervous system (CNS), axon regeneration is a major hurdle for functional recovery after trauma. The intrinsic growth potential of an injured axon varies widely between neurons. The underlying molecular mechanisms of such heterogeneity are largely unclear. In the present study, the adult zebrafish dataset GSE56842 were downloaded. Differentially expressed genes (DEGs) were sorted and deeply analyzed by bioinformatics methods. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed with the DAVID. A DEGs-associated protein–protein interaction network was constructed from the STRING database and visualized with Cytoscape software. In total, 621 DEGs were identified. GO analysis showed that the biological processes of DEGs focused mainly on the Notch signaling pathway, cell differentiation and positive regulation of neuron differentiation. The molecular functions mainly included calcium-transporting ATPase activity and calcium ion binding and structural constituents of the cytoskeleton. The cellular components included the plasma membrane, spectrin, and cytoplasmic and membrane-bound vesicles. KEGG pathway analysis showed that these DEGs were mainly involved in the metabolic pathway and Notch signaling pathway, and subnetworks revealed that genes within modules were involved in the metabolic pathway, Wnt signaling pathway, and calcium signaling pathway. This study identified DEG candidate genes and pathways involved in the heterogeneity of the intrinsic growth ability between neurons after spinal cord injury in adult zebrafish, which could facilitate our understanding of the molecular mechanisms underlying axon regeneration, and these candidate genes and pathways could be therapeutic targets for the treatment of CNS injury.

     

肺腺癌诊断标志物筛选及免疫细胞浸润分析

用生物信息学方法筛选肺腺癌(Lung adenocarcinoma,LUAD)的诊断生物标志物,并分析肺腺癌中免疫细胞浸润情况。从GEO和TCGA数据库下载肺腺癌的表达数据集,利用R软件筛选肺腺癌与正常肺组织间的差异表达基因(DEGs),使用DAVID网站对DEGs进行GO及KEGG富集分析,使用STRING及Cytoscape等工具对DEGs构建蛋白相互作用网络并筛选hub基因;利用Kaplan-Meier法对DEGs进行生存分析,并对hub基因进行ROC分析筛选诊断生物标志物,利用GSEA预测有预后价值的基因参与的信号通路;并用Cibersort软件反卷积算法分析肺腺癌中免疫细胞浸润情况。共得到肺腺癌的234个DEGs,这些基因主要参与信号转导、物质代谢、免疫反应等相关信号通路;构建PPI网络筛选出的20个hub基因中8个存在预后价值(CCNA2、DLGAP5、HMMR、MMP1、MMP9、MMP13、SPP1、TOP2A),ROC分析中DLGAP5、SPP1值分别是0.703、0.706;DLGAP5、SPP1基因表达水平与肺腺癌组织浆细胞、未活化的CD4⁺记忆细胞、调节T细胞、巨噬细胞M0、M1、M2及中性粒细胞浸润密切相关(P＜0.05)。肺腺癌中DLGAP5、SPP1具有较高诊断价值且参与肺腺癌组织免疫细胞浸润;DLGAP5、SPP1基因可作为肺腺癌诊断的生物标志物,可为肺腺癌的靶向治疗研究提供新思路。     

Identification of Biomarkers for Early Diagnosis of Acute Myocardial Infarction

Acute myocardial infarction (AMI) is a common disease with serious consequences in mortality and cost. Here we aim to screen the differentially expressed genes (DEGs) as biomarkers for early diagnosis of AMI. The microarray data of AMI was downloaded from Gene Expression Omnibus (GEO), including two independent types of research GSE66360 and GSE62646. The DEGs between control and processed samples were screened out by using limma package. Meanwhile, we performed functional analysis of GO terms and/or KEGG pathways to observe the enriched pathways of the DEGs. Finally, regression analysis of raw data was performed by using packet affyPLM in R language. Dataset GSE62646 contained 53 DEGs (FC log2>1 and P value <0.05) between first‐day samples from 28 STEMI patients and control samples from 14 patients without myocardial infarction history. There were 12 up‐regulated and 41 down‐regulated genes, 35 DEGs annotated. In GSE66360, a total of 3034 DEGs between 32 AMI patients and 38 healthy persons were obtained, including 1861 up‐regulated and 1173 down‐regulated DEGs. The comparison of the DEGs in two datasets revealed four common up‐regulated genes (EGR1, STAB1, SOCS3, TMEM176A). In enrichment analysis, STAB1, SOCS3, EGR1 involved in metabolic regulation and signaling pathways related to coronary artery disease with a characteristic change (P < 0.05). The DEGs, especially the four up‐regulated common genes, could serve as biomarkers for early diagnosis of AMI. Additionally, the relative biological pathways these DEGs enriched in might provide a good reference to explore the molecular expression mechanism of AMI. J. Cell. Biochem. 119: 650–658, 2018. © 2017 Wiley Periodicals, Inc.     

沙葱萤叶甲卵滞育的转录组学分析

【目的】建立沙葱萤叶甲Galeruca daurica滞育卵转录组数据库,挖掘卵滞育相关的基因以及代谢和信号通路,在转录组水平探讨卵滞育的分子机制。【方法】采用Illumina NovaSeq6000高通量测序平台对沙葱萤叶甲滞育卵与解除滞育卵进行转录组测序,并进行生物信息学分析;利用DESeq软件分析沙葱萤叶甲滞育卵与解除滞育卵中的差异表达基因,对差异表达基因进行KEGG通路富集分析;利用qRT PCR技术对10个差异表达基因的表达模式进行验证。【结果】基于沙葱萤叶甲滞育卵与解除滞育卵转录组测序结果,共获得53 389个unigene,其中差异表达基因2 145个,24个差异表达基因与保幼激素信号及脂肪酸生物合成和降解相关。与解除滞育卵相比,滞育卵转录组中1 297个基因上调表达,富集于124条KEGG通路,其中核糖体通路显著富集;848个基因下调表达,富集于73条KEGG通路,其中MAPK信号通路和糖胺聚糖生物合成通路显著富集。qRT-PCR结果表明,随机选取的10个差异表达基因的表达趋势与RNA-Seq转录组测序结果完全一致。【结论】保幼激素,脂肪酸生物合成和降解,核糖体,MAPK信号及糖胺聚糖生物合成等通路可能在沙葱萤叶甲卵滞育调控中起着重要的作用。     

Identification of core genes and outcomes in hepatocellular carcinoma by bioinformatics analysis

Hepatocellular carcinoma (HCC) is the most common malignant liver disease in the world. However, the mechanistic relationships among various genes and signaling pathways are still largely unclear. In this study, we aimed to elucidate potential core candidate genes and pathways in HCC. The expression profiles GSE14520, GSE25097, GSE29721, and GSE62232, which cover 606 tumor and 550 nontumour samples, were downloaded from the Gene Expression Omnibus (GEO) database. Furthermore, HCC RNA-seq datasets were also downloaded from the Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were filtered using R software, and we performed gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using the online databases DAVID 6.8 and KOBAS 3.0. Furthermore, the protein-protein interaction (PPI) network complex of these DEGs was constructed by Cytoscape software, the molecular complex detection (MCODE) plug-in and the online database STRING. First, a total of 173 DEGs (41 upregulated and 132 downregulated) were identified that were aberrantly expressed in both the GEO and TCGA datasets. Second, GO analysis revealed that most of the DEGs were significantly enriched in extracellular exosomes, cytosol, extracellular region, and extracellular space. Signaling pathway analysis indicated that the DEGs had common pathways in metabolism-related pathways, cell cycle, and biological oxidations. Third, 146 nodes were identified from the DEG PPI network complex, and two important modules with a high degree were detected using the MCODE plug-in. In addition, 10 core genes were identified, TOP2A, NDC80, FOXM1, HMMR, KNTC1, PTTG1, FEN1, RFC4, SMC4, and PRC1. Finally, Kaplan-Meier analysis of overall survival and correlation analysis were applied to these genes. The abovementioned findings indicate that the identified core genes and pathways in this bioinformatics analysis could significantly enrich our understanding of the development and recurrence of HCC; furthermore, these candidate genes and pathways could be therapeutic targets for HCC treatment.     

Analysis of dysregulation of immune system in pancreatic cancer based on gene expression profile

The aim of this study was to explore the dysregulated expression of the immune system in pancreatic cancer and clarify the pathogenesis of pancreatic cancer. The Dataset GSE15471 was downloaded from GEO database, Student’s t test was used to screen differentially expressed genes (DEGs) between the pancreatic cancer group and the normal control group. Kyoto Encyclopedia of Genes and Genomes (KEGG) provides functional annotation was employed to explore the significant DEGs involved in biological functions. We got 988 significantly DEGs, including 832 up-regulated genes and 156 down-regulated genes. The ratio of up-regulated genes and down-regulated genes was 5.3. Total 13 biological pathways which were significant enriched with DEGs by KEGG pathway enrichment analysis. Finally, we constructed a overall network of the immune system in pancreatic cancer with these biological pathways information. Our study reveals that dysregulated pathways in pancreatic cancer associated with the immune system. Besides, we also identify some important molecular biomarkers of the pancreatic cancer, including CXCR4 and CD4. Dysfunctional pathways and important molecular biomarkers of pancreatic cancer will provide useful information for potential treatment of pancreatic cancer.     

Discovery of core gene families associated with liver metastasis in colorectal cancer and regulatory roles in tumor cell immune infiltration

In this study, we aimed to uncover genes that drive the pathogenesis of liver metastasis in colorectal cancer (CRC), and identify effective genes that could serve as potential therapeutic targets for treating with colorectal liver metastasis patients based on two GEO datasets. Several bioinformatics approaches were implemented. First, differential expression analysis screened out key differentially expressed genes (DEGs) across the two GEO datasets. Based on gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, we identified the enrichment functions and pathways of the DEGs that were associated with liver metastasis in CRC. Second, immune infiltration analysis identified key immune signature gene sets associated with CRC liver metastasis, among which two key immune gene families (CD and CCL) identified as key DEGs were filtered by protein-protein interaction (PPI) network. Some of the members in these gene families were associated with disease free survival (DFS) or overall survival (OS) in two subtypes of CRC, namely COAD and READ. Finally, functional enrichment analysis of the two gene families and their neighboring genes revealed that they were closely associated with cytokine, leukocyte proliferation and chemotaxis. These results are valuable in comprehending the pathogenesis of liver metastasis in CRC, and are of seminal importance in understanding the role of immune tumor infiltration in CRC. Our study also identified potentially effective therapeutic targets for liver metastasis in CRC including CCL20, CCL24 and CD70.     

2型猪链球菌脑膜炎小鼠模型的构建及其转录组学分析

【背景】2型猪链球菌(Streptococcus suis serotype 2, S. suis 2)可感染宿主引起严重的脑膜炎,对养猪业和人类公共卫生安全构成重大威胁。【目的】构建S. suis 2感染小鼠脑膜炎模型,并对其脑组织进行转录组学分析,为揭示S.suis2感染宿主后引起脑膜炎的分子机制和发现潜在的治疗靶点提供理论依据。【方法】采用S. suis 2感染小鼠,并对其脑组织进行病理组织学分析确认构建脑膜炎小鼠后,对其脑组织进行转录组学分析,对比S.suis2感染和未感染小鼠的差异表达基因,并对差异表达基因进行基因本体论(geneontology,GO)功能、京都基因和基因组百科全书(Kyoto encyclopedia of genes and genomes, KEGG)通路富集和韦恩分析。【结果】脑病理组织学分析结果显示,S. suis 2感染的小鼠脑膜中有大量的炎症细胞浸润,并且血管周围出现“袖套”现象,并能从感染小鼠的组织器官中再分离出攻毒的S. suis 2菌株,结果证明构建了S. suis 2感染脑膜炎小鼠模型。转录组学分析结果表明,感染S.suis2与未感染的...