腺苷酸环化酶3缺失对小鼠主要嗅觉表皮组织内DNA甲基化的影响

腺苷酸环化酶3 (adenylate cyclaseⅢ,AC3)是嗅觉系统中的重要成分,AC3缺失后小鼠的主要嗅觉表皮组织(main olfactory epidermal,MOE)随年龄增长逐渐变薄,MOE内基因表达谱发生改变. DNA甲基化在动物发育、基因表达调控中具有重要作用.为了探讨AC3缺失后小鼠MOE内基因启动子甲基化水平的改变以及对基因表达的影响,本文采用DNA甲基化免疫共沉淀芯片(methylated DNA immunoprecipitation chip,MeDIP-chip)筛选AC3缺失小鼠MOE内启动子区甲基化差异表达基因,利用甲基化特异PCR (methylation-specific PCR,MSP)、实时荧光定量PCR (qRT-PCR)进一步检测部分甲基化差异基因的DNA甲基化水平改变和表达差异.结果表明,AC3缺失小鼠中有1 978个基因启动子的甲基化水平发生了改变,占总探针数的9%,其中727个基因启动子甲基化水平升高,1 251个甲基化水平降低.功能分析表明,这些启动子甲基化发生改变的基因主要涉及的功能分别与嗅觉受体、神经发育、cAMP信号通路、ATP结合、钙离子调控、乙酰化修饰、转录因子等相关. MSP检测表明,嗅觉受体基因Olfr1153、Olfr231、Olfr378、Olfr651、Olfr691启动子区的甲基化水平升高,Cngb1、Pde4a和Olfr1394基因启动子区的甲基化水平降低. qRT-PCR结果显示,基因Cngb1、Hcn4、Olfm1、Olfr1394、Olfr1153、Olfr231、Olfr378、Olfr691的表达水平显著下降,而Pde4a和Olfr651基因的表达水平显著升高.总之,AC3缺失后MOE内嗅觉受体基因、神经发育相关基因、cAMP信号通路等相关基因启动子甲基化水平发生显著改变,影响核苷酸切除修复、DNA复制、错配修复等信号通路的传导,从而综合调控小鼠MOE内的基因表达数量和水平.     

帕金森病多巴胺神经细胞的差异表达基因分析

帕金森病(Parkinson’s disease,PD)是一种常见的神经退行性疾病,影响群体广泛。该文分析了帕金森病多巴胺细胞的表达和DNA甲基化信息,识别出了新的表达或者DNA甲基化异常的基因,并分析了这些基因与帕金森病的关联。结果表明:相比于正常细胞,帕金森病细胞中与微管形成相关的基因表达上调,这些基因包括SLAIN1、TAGLN3和TUBB2B;天然免疫关联的基因(如LY96)下调。另一个上调基因SCG5推测与免疫应激响应相关。DNA甲基化变化在启动子区显著,除了调节基因转录,这些变化可能通过PRC1和Pc G复合物改变染色质的活性水平。此外,表达水平和DNA甲基化同时调整的基因与轴突定向、胞内运输、神经元分化及迁移等功能有关。以上结果提供了对帕金森病机理特征的新的认识。     

抑制mTOR信号通路可增强5-aza-dC对胃癌细胞生长的抑制作用

本实验主要研究哺乳动物雷帕霉素靶蛋白（mTOR）信号通路与DNA甲基化在人胃癌细胞生存活力、细胞周期、相关基因及蛋白表达方面的相互作用．分别单独或联合DNA甲基化酶抑制剂5-氮杂-2’-脱氧胞苷（5-aza-dC）、mTOR抑制剂雷帕霉素（rapamycin,RAPA）和P13K抑制剂LY294002干预人胃癌MKN45和SGC7901细胞,以MTT检测细胞生存活力,流式细胞术检测细胞周期,real-timePCR检测PTEN,p27^Kip1基因表达情况,亚硫酸氢盐修饰后测序检测DNA甲基化改变,蛋白免疫印迹检测相关蛋白表达情况．结果发现单独应用5-aza-dC对胃癌细胞的抑制作用不明显,当其联合mTOR信号通路抑制剂时则显著抑制胃癌细胞生长（P〈0．01）;抑制mTOR信号通路可增强5-aza-dC使细胞阻滞在G2期的作用;联合用药还能提高抑癌基因PTEN,p27^Kip1的表达,但不影响DNA甲基化状态;LY294002及RAPA使Akt,p70S6K及4E-BPl磷酸化表达显著下降（P〈0．01）,但5-aza-dE并不增强这一效应．以上研究提示mTOR信号通路抑制剂可间接促进DNA甲基化酶抑制剂对胃癌细胞的抑制作用,为肿瘤的治疗提供新思路．     

人类抑癌基因beclin 1在胃癌和直结肠癌中表达下调的研究

人类抑癌基因beclin 1通过自噬作用调节细胞生长,但在胃癌和直结肠癌中其表达水平和调控机制仍不清楚．通过检测胃癌和直结肠肿瘤组织中beclin 1基因的表达水平,及DNA异常甲基化和杂合子缺失对其表达的影响,发现与癌旁组织相比,35％的胃癌标本和30％的直结肠癌标本中beclin 1基因表达显著下调．同时发现,beclin 1基因5’端存在一高密度CpG岛,在胃癌和直结肠癌中beclin 1的启动子区域和第二个内含子区域存在甲基化,而杂合子缺失仅在胃癌中发生．这些发现表明beclin 1基因的异常甲基化和杂合子缺失对其在胃癌和直结肠癌中的表达起调控作用．     

肾透明细胞癌Caki-1细胞系差异表达基因的生物信息学分析

目的比较肾透明细胞癌Caki-1细胞系与正常肾上皮细胞系ASE-5063中的差异表达基因（DEGs）,寻找潜在的肾透明细胞癌特异性分子标志物。 方法利用GEO数据库自带的GEO2R在线分析工具分析基因芯片GSE78179,将筛选出的DEGs分别导入Metascape、STRING以及Cytoscape进行综合分析并筛选出核心基因。最后使用FunRich等软件对筛选出的核心基因进行GO和KEGG富集分析。 结果共筛选出562个DEGs,其中上调基因345个,下调基因217个。进一步使用MCODE筛选出36个关键基因,GO功能分析发现这些基因与细胞粘附分子活性、趋化因子活性、细胞通讯和信号转导等密切相关;KEGG通路富集结果则表明差异基因主要集中在趋化因子信号通路、TNF信号通路以及NF-κB信号通路等多种与肿瘤相关的通路上。 结论运用生物信息学方法筛选出肾透明细胞癌Caki-1细胞系中DEGs,其中数个核心基因广泛参与多种肿瘤的病理进程,但尚未在肾透明细胞癌有相关研究报道,提示其可能是治疗肾透明细胞癌的潜在靶点。     

DNMT3a通过提升基因内部甲基化介导紫杉醇诱导的LINE-1异常表达

药物诱导的长散在重复序列LINE-1异常激活可促进细胞基因组不稳定,而基因组不稳定是促进肿瘤发生发展和耐药表型形成的重要因素。因此,探索LINE-1异常激活的分子机制具有重要的理论和临床意义。DNA甲基化是调控基因表达的重要方式,已知DNA甲基转移酶家族成员DNMT3a不仅能通过促进基因启动子甲基化抑制基因表达,还可通过增强基因内部甲基化上调基因表达。本实验室前期研究发现,将乳腺癌细胞暴露于化疗药物可诱导LINE-1异常高表达,但LINE-1启动子甲基化水平并无显著改变。本研究进一步探讨了在化疗药物压力下DNMT3a是否可通过增强LINE-1基因内部甲基化水平促进LINE-1在乳腺癌细胞中的异常高表达。ChIP实验和甲基分析结果显示,用化疗药物紫杉醇(PTX)处理乳腺癌细胞,不仅可以诱导DNMT3a表达,而且可以促进DNMT3a与LINE-1基因内部区域的结合,提升其基因内部甲基化水平,进而上调LINE-1的表达水平。利用表达载体增加细胞内DNMT3a的表达水平,可显著上调LINE-1基因内部的甲基化及基因的表达水平,而下调DNMT3a的表达可有效抑制LINE-1表达。上述研究结果表明,DNMT3a介导的基因非启动子区甲基化在药物诱导的LINE-1异常激活中发挥重要作用,为认识LINE-1在乳腺癌化疗耐药性形成过程中异常激活的机制提供了新思路。     

DNA甲基化与癌症

DNA甲基化是重要的表观遗传修饰,主要发生在DNA的CpG岛. DNA的甲基化通过DNA甲基转移酶（DNA methyltransferases, DNMTs）完成. DNA甲基化参与了细胞分化、基因组稳定性、X染色体失活、基因印记等多种细胞生物学过程.单基因水平及基因组范围内的DNA甲基化改变在肿瘤发生发展中亦发挥重要作用. 抑癌基因的异常甲基化引起的表达抑制,可导致肿瘤细胞的增殖失控和侵袭转移,并参与肿瘤组织的血管生成过程.在许多肿瘤的研究中都发现了基因组整体DNA低甲基化所导致的染色体不稳定性. 本文从DNA的异常高甲基化和低甲基化两方面论述了DNA甲基化在细胞恶变发生发展过程中的改变及其影响,并阐述了DNA甲基化改变在肿瘤诊断和治疗中的作用.     

基于hMeDIP-seq分析肝癌小鼠癌组织中肝癌相关信号分子基因的羟甲基化

本研究通过hMeDIP-Seq技术和生物信息学分析,从肝细胞癌模型小鼠肝癌组织和肝组织基因组羟甲基化的角度研究肝癌相关信号通路,以期探讨肝癌相关信号分子基因的羟甲基化分布及其与基因表达的关系。研究结果表明,肝癌组织中共有52个具有显著统计学意义的肝癌相关信号分子基因发生了羟(FDR0.05),而肝组织的则没有出现有统计学意义的相关羟甲基化信号分子基因。而且,这些信号分子基因的羟甲基化位点全部分布在基因表达的调控区域(外显子外),包括启动子-转录启始位点区、内含子区和基因间区。由于DNA羟甲基化是激活基因表达的重要手段,因此,这些区域的羟甲基化表明这些基因在肝癌组织中处于激活状态,并得到了RT-q PCR实验的抽样证明。由此可见,肝癌组织基因组上发生的羟甲基化与肝癌相关;它们通过激活大量的信号分子基因引起肝癌相关信号通路的异常活化,从而引起肝癌的发生或迁移。     

阿霉素诱导下的肝癌细胞HepG2中微小RNA差异表达分析

旨在研究阿霉素诱导引起的DNA损伤压力下,肝癌细胞Hep G2中参与DNA损伤应答的mi RNA,并分析这些mi RNA靶基因参与肝癌DNA损伤应答相关的生物学进程与通路。通过小RNA测序检测阿霉素处理肝癌细胞Hep G2前后mi RNA的差异表达情况,使用GO与KEGG通路富集方法对差异表达mi RNA靶基因进行功能富集分析。结果显示,共检测出显著表达差异mi RNA 68个,其中上调13个,下调55个。mi RNA靶基因的功能分析结果显示,53条mi RNAs靶基因显著富集于调控细胞增殖、细胞凋亡、细胞迁移和细胞周期等与DNA损伤应答以及肿瘤相关的生物进程和信号通路,包括p53信号通路、癌症通路、Wnt信号通路和MAPK信号通路等。研究表明,在阿霉素诱导下,Hep G2中的差异表达mi RNAs与DNA损伤相关的肿瘤生物学进程以及信号通路显著相关,预示这些mi RNAs在阿霉素引发的肝细胞癌DNA损伤应答中起着重要的作用。     

ABCA1对滋养细胞基因表达谱的影响

该文从基因学角度探讨了ABCA1对人滋养细胞功能的影响。在人滋养细胞中调控ABCA1的表达,通过表达谱芯片检测ABCA1表达改变后滋养细胞中基因及相关信号通路的改变,Western blot及qRT-PCR验证芯片结果。结果显示,上调ABCA1表达时,有197个基因表达升高,有190个基因表达下降;而下调ABCA1表达时,有335个基因表达升高, 459个基因表达下降。GO和KEGG分析表明, ABCA1表达上升或下降后可导致滋养细胞内多个信号通路发生改变。qRT-PCR及Western blot检测发现,与阴性对照组相比, ABCA1上调后细胞中S1PR1的m RNA及蛋白水平明显升高,而CCL8、CXCL10与CXCL11的mRNA及蛋白水平明显降低;下调ABCA1的表达后,细胞中S1PR1的mRNA及蛋白水平明显降低,而CCL8、CXCL10与CXCL11的mRNA及蛋白水平明显升高,与芯片的结果完全一致。这些结果表明, ABCA1可通过调控多个信号通路而影响滋养细胞功能。     

Reproducibility and concordance of differential DNA methylation and gene expression in cancer

Background

Hundreds of genes with differential DNA methylation of promoters have been identified for various cancers. However, the reproducibility of differential DNA methylation discoveries for cancer and the relationship between DNA methylation and aberrant gene expression have not been systematically analysed.

Methodology/Principal Findings

Using array data for seven types of cancers, we first evaluated the effects of experimental batches on differential DNA methylation detection. Second, we compared the directions of DNA methylation changes detected from different datasets for the same cancer. Third, we evaluated the concordance between methylation and gene expression changes. Finally, we compared DNA methylation changes in different cancers. For a given cancer, the directions of methylation and expression changes detected from different datasets, excluding potential batch effects, were highly consistent. In different cancers, DNA hypermethylation was highly inversely correlated with the down-regulation of gene expression, whereas hypomethylation was only weakly correlated with the up-regulation of genes. Finally, we found that genes commonly hypomethylated in different cancers primarily performed functions associated with chronic inflammation, such as ‘keratinization’, ‘chemotaxis’ and ‘immune response’.

Conclusions

Batch effects could greatly affect the discovery of DNA methylation biomarkers. For a particular cancer, both differential DNA methylation and gene expression can be reproducibly detected from different studies with no batch effects. While DNA hypermethylation is significantly linked to gene down-regulation, hypomethylation is only weakly correlated with gene up-regulation and is likely to be linked to chronic inflammation.     

Integrative analysis identifies potential DNA methylation biomarkers for pan-cancer diagnosis and prognosis

DNA methylation status is closely associated with diverse diseases, and is generally more stable than gene expression, thus abnormal DNA methylation could be important biomarkers for tumor diagnosis, treatment and prognosis. However, the signatures regarding DNA methylation changes for pan-cancer diagnosis and prognosis are less explored. Here we systematically analyzed the genome-wide DNA methylation patterns in diverse TCGA cancers with machine learning. We identified seven CpG sites that could effectively discriminate tumor samples from adjacent normal tissue samples for 12 main cancers of TCGA (1216 samples, AUC > 0.99). Those seven potential diagnostic biomarkers were further validated in the other 9 different TCGA cancers and 4 independent datasets (AUC > 0.92). Three out of the seven CpG sites were correlated with cell division, DNA replication and cell cycle. We also identified 12 CpG sites that can effectively distinguish 26 different cancers (7605 samples), and the result was repeatable in independent datasets as well as two disparate tumors with metastases (micro-average AUC > 0.89). Furthermore, a series of potential signatures that could significantly predict the prognosis of tumor patients for 7 different cancer were identified via survival analysis (p-value < 1e-4). Collectively, DNA methylation patterns vary greatly between tumor and adjacent normal tissues, as well as among different types of cancers. Our identified signatures may aid the decision of clinical diagnosis and prognosis for pan-cancer and the potential cancer-specific biomarkers could be used to predict the primary site of metastatic breast and prostate cancers.     

DNA Methylation Patterns Can Estimate Nonequivalent Outcomes of Breast Cancer with the Same Receptor Subtypes

Breast cancer has various molecular subtypes and displays high heterogeneity. Aberrant DNA methylation is involved in tumor origin, development and progression. Moreover, distinct DNA methylation patterns are associated with specific breast cancer subtypes. We explored DNA methylation patterns in association with gene expression to assess their impact on the prognosis of breast cancer based on Infinium 450K arrays (training set) from The Cancer Genome Atlas (TCGA). The DNA methylation patterns of 12 featured genes that had a high correlation with gene expression were identified through univariate and multivariable Cox proportional hazards models and used to define the methylation risk score (MRS). An improved ability to distinguish the power of the DNA methylation pattern from the 12 featured genes (p = 0.00103) was observed compared with the average methylation levels (p = 0.956) or gene expression (p = 0.909). Furthermore, MRS provided a good prognostic value for breast cancers even when the patients had the same receptor status. We found that ER-, PR- or Her2- samples with high-MRS had the worst 5-year survival rate and overall survival time. An independent test set including 28 patients with death as an outcome was used to test the validity of the MRS of the 12 featured genes; this analysis obtained a prognostic value equivalent to the training set. The predict power was validated through two independent datasets from the GEO database. The DNA methylation pattern is a powerful predictor of breast cancer survival, and can predict outcomes of the same breast cancer molecular subtypes.     

Variable methylation of the ribosomal RNA genes of the rat.

Both the pattern and level of rRNA gene methylation vary in the rat. This variation reflects stages in the maturation process and perhaps the level of gene expression in different tissues. We studied methylation at a common site, the inner cytosine of the sequence CCGG, by hybridizing 32P-rRNA to DNA digests obtained with endonuclease Msp I (which cleaves CCGG and CMCGG) and its isochizomer, HpaII (which cleaves only CCGG). In the liver, the changing pattern of rRNA gene methylation reflected the late stages of development: the rRNA genes were mostly unmethylated at 14 days gestation; by 18 days gestation, about 30% of them were methylated, and this level persisted into adulthood. In 18-day DNA, the methylation was uniform, but in adult DNA, the methylation pattern was discontinuous, because otherwise methylated genes contained a demethylated region. Similar developmental changes were observed in brain DNA. In a tissue culture cell line, the change from the continuous to the discontinuous pattern of the methylation could be induced by transformation with Kirsten sarcoma virus. And, in adult tissues, the lowest level of rRNA gene methylation was found in rapidly growing jejunal epithelium, and the highest level, in non-growing spermatozoa.     

Methylation of c-myc gene changes in human lymphoproliferative diseases

The degree of methylation at the c-myc proto-oncogene was found to change in human lymphoproliferative diseases, when examined using a methylation-sensitive restriction enzyme. In peripheral blood mononuclear cells (PBMC) c-myc DNA showed hypomethylation in human lymphoproliferative diseases, in comparison to normal subjects matched in age and sex. In cases of chronic lymphocytic leukemia (CLL), the change was amplified in the crisis. When the DNA was examined at the actin gene, no significant change was observed. The results suggest that the change in c-myc proto-oncogene methylation might become an important clue in understanding the relationship between levels of gene expression and methylation in human lymphoproliferative diseases.     

The miRNA aberrant expression dependence on DNA methylation in HeLa cells treated with mitomycin C

The dependence of expression of miRNAs and their precursors (pre-miRNAs) on the DNA methylation level in HeLa cells 8 days after mitomycin C treatment was studied. A massive parallel DNA sequencing method was applied to analyze miRNA expression. 5-Azacytidine (DNA methylation inhibitor) was added to the medium 6 days after mutagenic agent exposure. The results indicated that the change in expression for some mature miRNAs (39 of 61) was accompanied by the change in the expression of their pre-miRNAs, while there were no significant changes in the expression of pre-miRNA for other mature miRNAs (22 of 61). The aberrant expression was maintained by 8 of 61 mature miRNAs and 6 of 55 pre-miRNAs in the induced HeLa cells after 5-azacytidine treatment. In addition, the expression of more than 90% of miRNAs, which indicated a significant change in expression after mitomycin C treatment, does not depend or depends slightly on the DNA methylation level in HeLa cells without mitomycin C treatment. The results suggest that mitomycin C induces aberrant DNA methylation which affects maintenance of changes in the miRNA expression in cell generations after mutagen treatment.     

Analysis of DNA methylation in different maize tissues

DNA methylation plays an important role in gene expression regulation during biological development and tissue differentiation in plants. This study adopted methylation-sensitive Amplified fragment length polymorphism （AFLP） to compare the levels of DNA cytosine methylation at CCGG sites in tassel, bracteal leaf, and ear leaf from maize inbred lines, 18 White and 18 Red, respectively, and also examined specific methylation patterns of the three tissues. Significant differences in cytosine methylation level among the three tissues and the same changing tendency in two inbred lines were detected. Both MSAP （methylation sensitive amplification polymorphism） ratio and full methylation level were the highest in bracteal leaf, and the lowest in tassel. Meanwhile, different methylation levels were observed in the same tissue from the inbred lines, 18 White and 18 Red. Full methylation of internal cytosine was the dominant type in the maize genome. The differential methylation patterns in the three tissues were observed. In addition, sequencing of nine differentially methylated fragments and the subsequent blast search revealed that the cytosine methylated 5 ＇ -CCGG-3 ＇ sequences were distributed in repeating sequences, in the coding and noncoding regions. Southern hybridization was used to verify the methylation polymorphism. These results clearly demonstrated the power of the MSAP technique for large-scale DNA methylation detection in the maize genome, and the complexity of DNA methylation change during plant growth and development. The different methylation levels may be related to specific gene expression in various tissues.