CancerMHL: the database of integrating key DNA methylation, histone modifications and lncRNAs in cancer.

The discovery of key epigenetic modifications in cancer is of great significance for the study of disease biomarkers. Through the mining of epigenetic modification data relevant to cancer, some researches on epigenetic modifications are accumulating. In order to make it easier to integrate the effects of key epigenetic modifications on the related cancers, we established CancerMHL (http://www.positionprediction.cn/), which provide key DNA methylation, histone modifications and lncRNAs as well as the effect of these key epigenetic modifications on gene expression in several cancers. To facilitate data retrieval, CancerMHL offers flexible query options and filters, allowing users to access specific key epigenetic modifications according to their own needs. In addition, based on the epigenetic modification data, three online prediction tools had been offered in CancerMHL for users. CancerMHL will be a useful resource platform for further exploring novel and potential biomarkers and therapeutic targets in cancer. Database URL: http://www.positionprediction.cn/.

Discovered Key CpG Sites by Analyzing DNA Methylation and Gene Expression in Breast Cancer Samples.

Breast cancer is the most common cancer in the world, and DNA methylation plays a key role in the occurrence and development of breast cancer. However, the effect of DNA methylation in different gene functional regions on gene expression and the effect of gene expression on breast cancer is not completely clear. In our study, we computed and analyzed DNA methylation, gene expression, and clinical data in the TCGA database. Firstly, we calculated the distribution of abnormal DNA methylated probes in 12 regions, found the abnormal DNA methylated probes in down-regulated genes were highly enriched, and the number of hypermethylated probes in the promoter region was 6.5 times than that of hypomethylated probes. Secondly, the correlation coefficients between abnormal DNA methylated values in each functional region of differentially expressed genes and gene expression values were calculated. Then, co-expression analysis of differentially expressed genes was performed, 34 hub genes in cancer-related pathways were obtained, of which 11 genes were regulated by abnormal DNA methylation. Finally, a multivariate Cox regression analysis was performed on 27 probes of 11 genes. Three DNA methylation probes (cg13569051 and cg14399183 of GSN, and cg25274503 of CAV2) related to survival were used to construct a prognostic model, which has a good prognostic ability. Furthermore, we found that the cg25274503 hypermethylation in the promoter region inhibited the expression of the CAV2, and the hypermethylation of cg13569051 and cg14399183 in the 5'UTR region inhibited the expression of GSN. These results may provide possible molecular targets for breast cancer.

Discovering the key genes and important DNA methylation regions in breast cancer.

BACKGROUND: Breast cancer is the malignant tumor with the highest incidence in women. DNA methylation has an important effect on breast cancer, but the effect of abnormal DNA methylation on gene expression in breast cancer is still unclear. Therefore, it is very important to find therapeutic targets related to DNA methylation. RESULTS: In this work, we calculated the DNA methylation distribution and gene expression level in cancer and para-cancerous tissues for breast cancer samples. We found that DNA methylation in key regions is closely related to gene expression by analyzing the relationship between the distribution characteristics of DNA methylation in different regions and the change of gene expression level. Finally, the 18 key genes (17 tumor suppressor genes and 1 oncogene) related to prognosis were confirmed by the survival analysis of clinical data. Some important DNA methylation regions in these genes that result in breast cancer were found. CONCLUSIONS: We believe that 17 TSGs and 1 oncogene may be breast cancer biomarkers regulated by DNA methylation in key regions. These results will help to explore DNA methylation biomarkers as potential therapeutic targets for breast cancer.

The effect of key DNA methylation in different regions on gene expression in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common cancer with high morbidity and mortality. As we all know, the alteration of DNA methylation has a crucial impact on the occurrence of HCC. However, the mechanism of the effect of DNA methylation in different regions on gene expression is still unclear. Here, by computing and analyzing the distribution of differential methylation in 12 different regions in HCC tissues and adjacent normal tissues, not only the hypermethylation of CpG islands and global hypomethylation were found, but also a stable distribution pattern of differential methylation in HCC was found. Then the correlations between DNA methylations in different regions and gene expressions were calculated, and the diversity of correlations in different regions was determined. The key genes of differential methylation and differential expression related to the survival of HCC patients were obtained by using Cox regression analysis, a four-gene prognostic risk scoring model was constructed, and the prognostic performance was well verified. The regions of the differentially methylated CpG sites corresponding to the four key genes were located and their influences on the expression were analyzed. The results indicate that the promoter, first exon, 5'UTR, sixth exon, N_Shore, and S_Shore hypomethylation promotes the expression of key oncogenes, which together lead to the occurrence of HCC. These results might help to study the role of DNA methylation in HCC and provide potential biomarkers for the diagnosis of HCC.

Identification of key genes and important histone modifications in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death in the world. It has been reported that HCC is closely related to the changes of histone modifications. However, finding histone modification patterns in key genes which related to HCC is still an important task. In our study, the patterns of 11 kinds of histone modifications in the promoter regions for the different types of genes were analyzed by hierarchical screening for hepatocyte (normal) cell line and HepG2 (tumor) cell line. The important histone modifications and their key modification regions in different types of genes were found. The results indicate that these important genes may play a pivotal role in the occurrence of HCC. By analyzing the differences of histone modifications and gene expression levels for these important genes between the two cell lines, we found that the signals of H3K4me3, H3K27ac, H3K9ac, and H3K4me2 in HCC are significantly stronger. The changed regions of important histone modifications in 17 key genes were also identified. For example, the H3K4me3 signals increased 150 times in regions (-1500, -500) bp and (0, 1000) bp of ARHGAP5 in tumor cell line than in normal cell line. Finally, a prognostic risk scoring model was constructed, and the effects of key genes on the prognosis of HCC were verified by the survival analysis. Our results may provide a more precise potential therapeutic targets for identifying key genes and histone modifications in HCC as new biomarkers.

MicroRNA-9 regulates the proliferation, migration and invasion of human glioma cells by targeting CDH1.

PURPOSE: Glioma causes significant mortality worldwide. The currently available treatment strategies are flawed and the therapeutic targets are limited. Accumulating evidence suggests that microRNAs (miRs) are involved in the development and progression of different cancers. Herein, the therapeutic potential of miR-9 was explored in human glioma cells. METHODS: The qRT-PCR was used for expression analysis. WST-1 assay was used for determination of cell viability. Acridine orange (AO) / ethidium promide (EB) and annexin V/propidium iodide (PI) were used for the detection of apoptosis. Flow cytometry was used for cell cycle analysis. Wound healing and transwell assays were used to monitor cell migration and invasion. Protein expression was determined by western blot analysis. RESULTS: The results showed that miR-9 is significantly downregulated in glioma cells. Overexpression of miR-9 caused significant inhibition in the proliferation of U87 glioma cells. The miR-9-triggered growth inhibition was mainly due to the induction of apoptosis which was concomitant with increase in the Bax/Bcl-2 ratio. Overexpression of miR-9 also induced arrest of U87 glioma cells at G2/M checkpoint of cell cycle. Additionally, transwell and wound healing assays showed that miR-9 caused significant decrease in the migration and invasion of U87 glioma cells. Bioinformatics analysis showed that miR-9 exerts its effects by inhibiting Cadherin-1 (CDH1). However, overexpression of CDH1 could nullify the effects of miR-9 on the growth, migration and invasion of glioma cells. CONCLUSION: Taken together, miR-9 may exhibit therapeutic implications in the treatment of glioma.