Dataset Information

Aberrant methylation of Polo-like kinase CpG islands in Plk4 heterozygous mice.

ABSTRACT:

Background

Hepatocellular carcinoma (HCC), one of the most common cancers world-wide occurs twice as often in men compared to women. Predisposing conditions such as alcoholism, chronic viral hepatitis, aflatoxin B1 ingestion, and cirrhosis all contribute to the development of HCC.

Methods

We used a combination of methylation specific PCR and bisulfite sequencing, qReal-Time PCR (qPCR), and Western blot analysis to examine epigenetic changes for the Polo-like kinases (Plks) during the development of hepatocellular carcinoma (HCC) in Plk4 heterozygous mice and murine embryonic fibroblasts (MEFs).

Results

Here we report that the promoter methylation of Plk4 CpG islands increases with age, was more prevalent in males and that Plk4 epigenetic modification and subsequent downregulation of expression was associated with the development of HCC in Plk4 mutant mice. Interestingly, the opposite occurs with another Plk family member, Plk1 which was typically hypermethylated in normal liver tissue but became hypomethylated and upregulated in liver tumours. Furthermore, upon alcohol exposure murine embryonic fibroblasts exhibited increased Plk4 hypermethylation and downregulation along with increased centrosome numbers and multinucleation.

Conclusions

These results suggest that aberrant Plk methylation is correlated with the development of HCC in mice.

SUBMITTER: Ward A

PROVIDER: S-EPMC3047422 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature

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Publications

Aberrant methylation of Polo-like kinase CpG islands in Plk4 heterozygous mice.

Ward Alejandra A Morettin Alan A Shum David D Hudson John W JW

BMC cancer 20110215

<h4>Background</h4>Hepatocellular carcinoma (HCC), one of the most common cancers world-wide occurs twice as often in men compared to women. Predisposing conditions such as alcoholism, chronic viral hepatitis, aflatoxin B1 ingestion, and cirrhosis all contribute to the development of HCC.<h4>Methods</h4>We used a combination of methylation specific PCR and bisulfite sequencing, qReal-Time PCR (qPCR), and Western blot analysis to examine epigenetic changes for the Polo-like kinases (Plks) during ...[more]

PMID: 21324136

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Project description:BackgroundHypermethylation of promoter CpG islands is strongly correlated to transcriptional gene silencing and epigenetic maintenance of the silenced state. As well as its role in tumor development, CpG island methylation contributes to the acquisition of resistance to chemotherapy. Differential Methylation Hybridisation (DMH) is one technique used for genome-wide DNA methylation analysis. The study of such microarray data sets should ideally account for the specific biological features of DNA methylation and the non-symmetrical distribution of the ratios of unmethylated and methylated sequences hybridised on the array. We have therefore developed a novel algorithm tailored to this type of data, Methylation Linear Discriminant Analysis (MLDA).ResultsMLDA was programmed in R (version 2.7.0) and the package is available at CRAN 1. This approach utilizes linear regression models of non-normalised hybridisation data to define methylation status. Log-transformed signal intensities of unmethylated controls on the microarray are used as a reference. The signal intensities of DNA samples digested with methylation sensitive restriction enzymes and mock digested are then transformed to the likelihood of a locus being methylated using this reference. We tested the ability of MLDA to identify loci differentially methylated as analysed by DMH between cisplatin sensitive and resistant ovarian cancer cell lines. MLDA identified 115 differentially methylated loci and 23 out of 26 of these loci have been independently validated by Methylation Specific PCR and/or bisulphite pyrosequencing.ConclusionMLDA has advantages for analyzing methylation data from CpG island microarrays, since there is a clear rational for the definition of methylation status, it uses DMH data without between-group normalisation and is less influenced by cross-hybridisation of loci. The MLDA algorithm successfully identified differentially methylated loci between two classes of samples analysed by DMH using CpG island microarrays.

Dataset Information

Aberrant methylation of Polo-like kinase CpG islands in Plk4 heterozygous mice.

Background

Methods

Results

Conclusions

Publications

Aberrant methylation of Polo-like kinase CpG islands in Plk4 heterozygous mice.

Similar Datasets

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