Aberrant CpG methylation of the TFAP2A gene constitutes a mechanism for loss of TFAP2A expression in human metastatic melanoma

Metastatic melanoma is a deadly treatment-resistant form of skin cancer whose global incidence is on the rise. During melanocyte transformation and melanoma progression the expression profile of many genes changes. Among these, a gene implicated in several steps of melanocyte development, TFAP2A, is frequently silenced; however, the molecular mechanism of TFAP2A silencing in human melanoma remains unknown. In this study, we measured TFAP2A mRNA expression in primary human melanocytes compared to 11 human melanoma samples by quantitative real-time RT-PCR. In addition, we assessed CpG DNA methylation of the TFAP2A promoter in these samples using bisulfite sequencing. Compared to primary melanocytes, which showed high TFAP2A mRNA expression and no promoter methylation, human melanoma samples showed decreased TFAP2A mRNA expression and increased promoter methylation. We further show that increased CpG methylation correlates with decreased TFAP2A mRNA expression. Using The Cancer Genome Atlas, we further identified TFAP2A as a gene displaying among the most decreased expression in stage 4 melanomas vs. non-stage 4 melanomas, and whose CpG methylation was frequently associated with lack of mRNA expression. Based on our data, we conclude that TFAP2A expression in human melanomas can be silenced by aberrant CpG methylation of the TFAP2A promoter. We have identified aberrant CpG DNA methylation as an epigenetic mark associated with TFAP2A silencing in human melanoma that could have significant implications for the therapy of human melanoma using epigenetic modifying drugs.     

Novel markers of gene methylation and expression in breast cancer

An optimized methylation-sensitive restriction fingerprinting technique was used to search for differentially methylated CpG islands in the tumor genome and detected seven genes subject to abnormal epigenetic regulation in breast cancer: SEMA6B, BIN1, VCPIP1, LAMC3, KCNH2, CACNG4, and PSMF1. For each gene, the rate of promoter methylation and changes in expression were estimated in tumor and morphologically intact paired specimens of breast tissue (N = 100). Significant methylation rates of 38, 18, and 8% were found for SEMA6B, BIN1, and LAMC3, respectively. The genes were not methylated in morphologically intact breast tissue. The expression of SEMA6B, BIN1, VCPIP1, LAMC3, KCNH2, CACNG4, and PSMF1 was decreased in 44–94% of tumor specimens by the real-time RT-PCR assay. The most profound changes in SEMA6B and LAMC3 suggest that these genes can be included in biomarker panels for breast cancer diagnosis. Fine methylation mapping of the most frequently methylated CpG islands (SEMA6B, BIN1, and LAMC3) provides a fundamental basis for developing efficient methylation tests for these genes.     

CpG island methylation pattern in different human tissues and its correlation with gene expression

The study on DNA methylation pattern in different human tissues attracts increasing interest nowadays, but a systematic analysis of CpG island methylation pattern between both somatic tissues and gametocyte is still lacking. In this work, we analyzed the CpG island methylation data of sperm and other 11 somatic tissues from Human Epigenome Project, and found that the CpG island methylation profiles are highly correlated between somatic tissues, while the methylation profile in sperm is quite distinct. Furthermore, we observed that in the six tissues investigated, there is no obvious correlation between the methylation level of promoter CpG islands and corresponding gene expression across different tissues.     

DNA methylation regulates tissue-specific expression of Shank3

Tissue-specific gene expression can be controlled by epigenetic modifications such as DNA methylation. SHANK3, together with its homologues SHANK1 and SHANK2, has a central functional and structural role in excitatory synapses and is involved in the human chromosome 22q13 deletion syndrome. In this report, we show by DNA methylation analysis in lymphocytes, brain cortex, cerebellum and heart that the three SHANK genes possess several methylated CpG boxes, but only SHANK3 CpG islands are highly methylated in tissues where protein expression is low or absent and unmethylated where expression is present. SHANK3 protein expression is significantly reduced in hippocampal neurons after treatment with methionine, while HeLa cells become able to express SHANK3 after treatment with 5-Aza-2'-deoxycytidine. Altogether, these data suggest the existence of a specific epigenetic control mechanism regulating SHANK3, but not SHANK1 and SHANK2, expression.     

A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression

Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.     

An 11-gene-based prognostic signature for uveal melanoma metastasis based on gene expression and DNA methylation profile

Uveal melanoma (UM) is the most common intraocular tumor worldwide. We proposed to identify a vital gene signature that has prognostic value for UM metastasis. For this purpose, we obtained a published DNA methylation and gene expression data set associated with UM from the Gene Expression Omnibus. The genes whose aberrant expression significantly associated with UM patients’ metastasis-free survival (MFS) were identified by applying a univariate Cox proportional hazards model to the gene expression data set followed by a robust likelihood-based survival analysis to screen the optimal prognostic gene signatures (PGS). A formula for calculating the risk score that represents UM metastasis risk was constructed by including the PGSs’ expression values weighted by their regression coefficients, which were obtained by a multivariate Cox regression analysis. As a result, aberrant expression of 2884 genes were found to be significantly associated with UM patients’ MFS, which were referred to as MFSGs, and 11 out of those MFSGs, GJC1, TCEA1, MFSD3, FAF2, TLCD1, GPAA1, CYC1, ASAP1, JPH1, LDB3, and KDELR3, were identified as PGSs through which we could accurately separate UM samples with shorter MFS from those with longer MFS. By combining the DNA methylation data set and MFSGs, we further identified 265 MFSGs, which contained CpG sites that significantly hyper- or hypo-methylated in UM samples compared with control samples. Functional enrichment analysis and pathway crosstalk analysis of those genes indicated significant enrichment of cancer-related pathways. In conclusion, we identified an 11-gene-based prognostic signature and several gene biomarkers for UM metastasis, which should be helpful for selecting an appropriate treatment method for specific patients with UM.     

A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression

Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.     

非编码RNA与基因表达调控

近年来,随着对基因组的深入研究,发现真核生物中存在许多形态和功能各异的非编码RNA分子,这类RNA分子并不表达蛋白质,但它们在基因转录水平、转录后水平及翻译水平起了重要的调控作用。具有调控作用的RNA分子种类非常丰富,如长链非编码RNA(long non-coding RNA,lncRNA)、miRNA、PIWI相互作用RNA(PIWI-interacting RNA,piRNA)、内源性小干扰RNA(endogenous small interfering RNA,endo-siRNA)、竞争性内源RNA(competitive endogenous RNA,ceRNA)等,它们使基因表达过程更为丰富、严谨和有序。本文综述几类典型的非编码RNA对基因表达的调节作用,以助于理解细胞中RNA分子调节网络的功能和机制。     

DNA甲基化异常与肿瘤耐药

肿瘤耐药是导致肿瘤化疗失败的主要原因, 其产生机制复杂多样, 是多种因素共同作用的结果。近年来, 表观遗传改变在肿瘤耐药中的作用日益受到关注。DNA甲基化是一种重要的表观遗传修饰, 在调节基因表达和维持基因组稳定性中扮演着重要角色。原发性或获得性耐药的肿瘤细胞大多伴随DNA异常甲基化, 越来越多的证据显示, DNA甲基化异常是肿瘤细胞耐药表型产生的重要机制。文章就DNA甲基化异常与肿瘤细胞耐药的关系及相关作用机制进行了综述。     

甲基化修饰在细菌表观调控中的功能

为了适应复杂多变的生存环境,微生物通常需要在保证基因组序列不变的前提下不断调整胞内代谢网络。表观调控可以在不改变DNA序列的情况下对基因表达进行调控,因此成为细菌中重要的调控方式。作为一种DNA修饰,DNA甲基化修饰是生物体中最常见的表观调控工具。在本文中我们全面、深入解析了两种孤儿甲基转移酶:DNA腺嘌呤甲基转移酶(DNA adenine methyltransferase,Dam)和细胞周期调控甲基转移酶(Cell cycle-regulated methyltransferase,Ccr M)在原核生物中的表观调控功能。我们主要探讨了DNA甲基化参与的细胞生理过程包括DNA复制起始、DNA错配修复、基因表达调控、致病性和相变异等方面。同时,我们结合三维基因组研究技术基因组结构捕获(Chromosome conformation capture,3C)技术和新型DNA磷硫酰化修饰讨论了该领域的发展前景。     

Identification of novel epigenetically modified genes in human melanoma via promoter methylation gene profiling

The inactivation of tumor-related genes through the aberrant methylation of promoter CpG islands is thought to contribute to tumor initiation and progression. We therefore investigated promoter methylation events involved in cutaneous melanoma by screening 30 genes of interest for evidence of promoter hypermethylation, examining 20 melanoma cell lines and 40 freshly procured melanoma samples. Utilizing quantitative methylation-specific PCR, we identified five genes (SOCS1, SOCS2, RAR-beta 2, TNFSF10C, and TNFSF10D) with hypermethylation frequencies ranging from 50% to 80% in melanoma cell lines as well as freshly procured tissue samples. Eighteen genes (LOX, RASSF1A, WFDC1, TM, APC, TFPI2, TNFSF10A, CDKN2A, MGMT, TIMP3, ASC, TPM1, IRF8, CIITA-PIV, CDH1, SYK, HOXB13, and DAPK1) were methylated at lower frequencies (2-30%). Two genes (CDKN1B and PTEN), previously reported as methylated in melanoma, and five other genes (RECK, IRF7, PAWR, TNFSF10B, and Rb) were not methylated in the samples screened here. Daughter melanoma cell lines showed identical methylation patterns when compared with original samples from which they were derived, as did synchronous metastatic lesions from the same patient. We identified four genes (TNFSF10C, TNFSF10D, LOX, and TPM1) that have never before been identified as hypermethylated in melanoma, with an overall methylation frequency of 60, 80, 50, and 10%, respectively, hypothesizing that these genes may play an important role in melanoma progression.     

Toward predicting metastatic progression of melanoma based on gene expression data

Primary and metastatic melanoma tumors share the same cell origin, making it challenging to identify genomic biomarkers that can differentiate them. Primary tumors themselves can be heterogeneous, reflecting ongoing genomic changes as they progress toward metastasizing. We developed a computational method to explore this heterogeneity and to predict metastatic progression of the primary tumors. We applied our method separately to gene expression and to microRNA (miRNA) expression data from ~450 primary and metastatic skin cutaneous melanoma (SKCM) samples from the Cancer Genome Atlas (TCGA). Metastatic progression scores from RNA‐seq data were significantly associated with clinical staging of patients’ lymph nodes, whereas scores from miRNA‐seq data were significantly associated with Clark's level. The loss of expression of many characteristic epithelial lineage genes in primary SKCM tumor samples was highly correlated with predicted progression scores. We suggest that those genes/miRNAs might serve as putative biomarkers for SKCM metastatic progression.     

Racial differences in genome-wide methylation profiling and gene expression in breast tissues from healthy women

Breast cancer is more common in European Americans (EAs) than in African Americans (AAs) but mortality from breast cancer is higher among AAs. While there are racial differences in DNA methylation and gene expression in breast tumors, little is known whether such racial differences exist in breast tissues of healthy women. Genome-wide DNA methylation and gene expression profiling was performed in histologically normal breast tissues of healthy women. Linear regression models were used to identify differentially-methylated CpG sites (CpGs) between EAs (n = 61) and AAs (n = 22). Correlations for methylation and expression were assessed. Biological functions of the differentially-methylated genes were assigned using the Ingenuity Pathway Analysis. Among 485 differentially-methylated CpGs by race, 203 were hypermethylated in EAs, and 282 were hypermethylated in AAs. Promoter-related differentially-methylated CpGs were more frequently hypermethylated in EAs (52%) than AAs (27%) while gene body and intergenic CpGs were more frequently hypermethylated in AAs. The differentially-methylated CpGs were enriched for cancer-associated genes with roles in cell death and survival, cellular development, and cell-to-cell signaling. In a separate analysis for correlation in EAs and AAs, different patterns of correlation were found between EAs and AAs. The correlated genes showed different biological networks between EAs and AAs; networks were connected by Ubiquitin C. To our knowledge, this is the first comprehensive genome-wide study to identify differences in methylation and gene expression between EAs and AAs in breast tissues from healthy women. These findings may provide further insights regarding the contribution of epigenetic differences to racial disparities in breast cancer.     

Aberrant DNA methylation in 5'regions of DNA methyltransferase genes in aborted bovine clones

High rate of abortion and developmental abnormalities is thought to be closely associated with inefficient epigenetic reprogramming of the transplanted nuclei during bovine cloning.It is known that one of the important mechanisms for epigenetic reprogramming is DNA methylation.DNA methylation is established and maintained by DNA methyltransferases(DNMTs),therefore,it is postulated that the inefficient epigenetic reprogramming of transplanted nuclei may be due to abnormal expression of DNMTs.Since DNA methylation can strongly inhibit gene expression,aberrant DNA methylation of DNMT genes may disturb gene expression.But presently,it is not clear whether the methylation abnormality of DNMT genes is related to developmental failure of somatic cell nuclear transfer embryos.In our study,we analyzed methylation patterns of the 5' regions of four DNMT genes including Dnmt3a,Dnmt3b,Dnmtl and Dnmt2 in four aborted bovine clones.Using bisulfite sequencing method,we found that 3 out of 4 aborted bovine clones(AF1,AF2 and AF3)showed either hypermethylation or hypomethylation in the 5' regions of Dnmt3a and Dnmt3b.indicating that Dnmt3a and Dnmt3b genes are not properly reprogrammed.However,the individual AF4 exhibited similar methylation level and pattern to age-matched in vitro fertilized (IVF)fetuses.Besides,we found that tle 5'regions of Dnmtl and Dnmt2 were nearly completely unmethylated in all normal adults.IVF fetuses,sperm and aborted clones.Together,our results suggest that the aberrant methylation of Dnmt3a and Dnmt3b 5' regions is probably associated with the high abortion of bovine clones.