Dataset Information

Methylation patterns of the IFN-? gene in cervical cancer tissues.

ABSTRACT: To explore the relationship between methylation of interferon gamma (IFN-?) gene and tumorigenesis in cervical cancer tissues, the biopsy specimens of cervical cancer and cervical intraepithelial neoplasia (CIN) (I-III) patients as well as normal controls were collected and analyzed.The methylation of the IFN-? gene was verified by using methylation-specific PCR and DNA sequencing analysis, and the expression levels of IFN-? mRNA were detected using quantitative real-time reverse transcriptase-polymerase chain reaction (qRT-PCR).The methylation rates of the IFN-? gene were significantly higher in cervical cancer tissues (15/43, 34.9%) than those in CIN (3/23, 13.0% of CIN I; 6/39, 15.4% of CIN II/III) and normal cervical tissues (2/43, 4.7%) (P < 0.01). Furthermore, the mRNA expression of IFN-? in cervical tumors with methylation (0.71 ± 0.13, n = 8) was lower than that in those without methylation (1.58 ± 0.32, n = 27) (P < 0.05). Likewise, the IFN-? expression levels in CIN II/III tissues with methylation (0.87 ± 0.16, n = 5) were significantly (P < 0.01) lower compared to those without methylation (2.12 ± 0.27, n = 32).The hypermethylation of IFN-? gene may be related with tumorigenesis of cervical cancer.

SUBMITTER: Ma D

PROVIDER: S-EPMC4160705 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Methylation patterns of the IFN-γ gene in cervical cancer tissues.

Ma Dong D Jiang Chunyang C Hu Xiaoli X Liu Huibin H Li Qingzhao Q Li Tingting T Yang Yanyan Y Li Ou O

Scientific reports 20140911

<h4>Objective</h4>To explore the relationship between methylation of interferon gamma (IFN-γ) gene and tumorigenesis in cervical cancer tissues, the biopsy specimens of cervical cancer and cervical intraepithelial neoplasia (CIN) (I-III) patients as well as normal controls were collected and analyzed.<h4>Methods</h4>The methylation of the IFN-γ gene was verified by using methylation-specific PCR and DNA sequencing analysis, and the expression levels of IFN-γ mRNA were detected using quantitative ...[more]

PMID: 25208560

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Project description:BackgroundDNA methylation is an epigenetic event that may regulate gene expression. Because of this regulation role, aberrant DNA methylation is often associated with many diseases. Within-sample DNA co-methylation is the similarity of methylation in nearby cytosine sites of a chromosome. It is important to study co-methylation patterns. However, it is not well studied yet, and it is unclear to us what co-methylation patterns normal DNA samples have. Are the co-methylation patterns of the same tissue across several samples different? Are the co-methylation patterns of various tissues of the same sample different? To answer these questions, we conduct analyses using two sets of data: 3-sample-1-tissue (3S1T) and 1-sample-8-tissue (1S8T).ResultsTo study the co-methylation patterns of the two datasets, 3S1T and 1S8T, we investigate the following questions: How often does one methylation state change to other methylation states and how is this change associated with chromosome distance? Based on the 3S1T data, we find there is not significant co-methylation difference among the same spleen tissues of three different samples. However, the analysis results of 1S8T data show that there were significant differences among eight tissues of one sample. For both 3S1T and 1S8T data, we find that the no/low methylation state A and high/full methylation state D tend to remain the same along a chromosome region. We also find that the low/partial methylation state B and partial/high methylation state C tend to change to higher methylation states along a chromosome. Finally, we find that lengths of most co-methylation regions are very short with only a few hundred base pairs. In fact, only a small proportion of methylated regions are longer than 1000 base pairs.ConclusionsIn this paper, we have addressed a few questions regarding within-sample co-methylation patterns in normal tissues. Our statistical analysis results and answers may help researchers to better understand the biological process of DNA methylation. This may pave the way to develop better analysis methods for future methylation research.

Dataset Information

Methylation patterns of the IFN-? gene in cervical cancer tissues.

Publications

Methylation patterns of the IFN-γ gene in cervical cancer tissues.

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