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Methylation profiles of thirty four promoter-CpG islands and concordant methylation behaviours of sixteen genes that may contribute to carcinogenesis of astrocytoma.

ABSTRACT: BACKGROUND:Astrocytoma is a common aggressive intracranial tumor and presents a formidable challenge in the clinic. Association of altered DNA methylation patterns of the promoter CpG islands with the expression profile of cancer-related genes, has been found in many human tumors. Therefore, DNA methylation status as such may serve as an epigenetic biomarker for both diagnosis and prognosis of human tumors, including astrocytoma. METHODS:We used the methylation specific PCR in conjunction with sequencing verification to establish the methylation profile of the promoter CpG island of thirty four genes in astrocytoma tissues from fifty three patients (The WHO grading: I: 14, II: 15, III: 12 and IV: 12 cases, respectively). In addition, compatible tissues (normal tissues distant from lesion) from three non-astrocytoma patients were included as the control. RESULTS:Seventeen genes (ABL, APC, APAF1, BRCA1, CSPG2, DAPK1, hMLH1, LKB1, PTEN, p14ARF, p15INK4b, p27KIP1, p57KIP2, RASSF1C, RB1, SURVIVIN, and VHL) displayed a uniformly unmethylated pattern in all the astrocytoma and non-astrocytoma tissues examined. However, the MAGEA1 gene that was inactivated and hypermethylated in non-astrocytoma tissues, was partially demethylated in 24.5% of the astrocytoma tissues (co-existence of the hypermethylated and demethylated alleles). Of the astrocytoma associated hypermethylated genes, the methylation pattern of the CDH13, cyclin a1, DBCCR1, EPO, MYOD1, and p16INK4a genes changed in no more than 5.66% (3/53) of astrocytoma tissues compared to non-astrocytoma controls, while the RASSF1A, p73, AR, MGMT, CDH1, OCT6, MT1A, WT1, and IRF7 genes were more frequently hypermethylated in 69.8%, 47.2%, 41.5%, 35.8%, 32%, 30.2%, 30.2%, 30.2% and 26.4% of astrocytoma tissues, respectively. Demethylation mediated inducible expression of the CDH13, MAGEA1, MGMT, p73 and RASSF1A genes was established in an astrocytoma cell line (U251), demonstrating that expression of these genes is likely regulated by DNA methylation. AR gene hypermethylation was found exclusively in female patients (22/27, 81%, 0/26, 0%, P < 0.001), while the IRF7 gene hypermethylation preferentially occurred in the male counterparts (11/26, 42.3% to 3/27, 11%, P < 0.05). Applying the mathematic method "the Discovery of Association Rules", we have identified groups consisting of up to three genes that more likely display the altered methylation patterns in concert in astrocytoma. CONCLUSIONS:Of the thirty four genes examined, sixteen genes exhibited astrocytoma associated changes in the methylation profile. In addition to the possible pathological significance, the established concordant methylation profiles of the subsets consisting of two to three target genes may provide useful clues to the development of the useful prognostic as well as diagnostic assays for astrocytoma.

SUBMITTER: Yu J

PROVIDER: S-EPMC520749 | biostudies-literature | 2004 Sep

REPOSITORIES: biostudies-literature

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Methylation profiles of thirty four promoter-CpG islands and concordant methylation behaviours of sixteen genes that may contribute to carcinogenesis of astrocytoma.

Yu Jian J Zhang Hongyu H Gu Jun J Lin Song S Li Junhua J Lu Wei W Wang Yifei Y Zhu Jingde J

BMC cancer 20040914

<h4>Background</h4>Astrocytoma is a common aggressive intracranial tumor and presents a formidable challenge in the clinic. Association of altered DNA methylation patterns of the promoter CpG islands with the expression profile of cancer-related genes, has been found in many human tumors. Therefore, DNA methylation status as such may serve as an epigenetic biomarker for both diagnosis and prognosis of human tumors, including astrocytoma.<h4>Methods</h4>We used the methylation specific PCR in con ...[more]

PMID: 15367334

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Project description:BackgroundHepatocellular carcinoma (HCC) presents one of the major health threats in China today. A better understanding of the molecular genetics underlying malignant transformation of hepatocytes is critical to success in the battle against this disease. The methylation state of C5 of the cytosine in the CpG di-nucleotide that is enriched within or near the promoter region of over 50 % of the polymerase II genes has a drastic effect on transcription of these genes. Changes in the methylation profile of the promoters represent an alternative to genetic lesions as causative factors for the tumor-specific aberrant expression of the genes.MethodsWe have used the methylation specific PCR method in conjunction with DNA sequencing to assess the methylation state of the promoter CpG islands of twenty genes. Aberrant expression of these genes have been attributed to the abnormal methylation profile of the corresponding promoter CpG islands in human tumors.ResultsWhile the following sixteen genes remained the unmethylated in all tumor and normal tissues: CDH1, APAF1, hMLH1, BRCA1, hTERC, VHL, RARbeta, TIMP3, DAPK1, SURVIVIN, p14ARF, RB1, p15INK4b, APC, RASSF1c and PTEN, varying degrees of tumor specific hypermethylation were associated with the p16INK4a, RASSF1a, CASP8 and CDH13 genes. For instance, the p16INK4a was highly methylated in HCC (17/29, 58.6%) and less significantly methylated in non-cancerous tissue (4/29. 13.79%). The RASSF1a was fully methylated in all tumor tissues (29/29, 100%), and less frequently methylated in corresponding non-cancerous tissue (24/29, 82.75%).ConclusionsFurthermore, co-existence of methylated with unmethylated DNA in some cases suggested that both genetic and epigenetic (CpG methylation) mechanisms may act in concert to inactivate the p16INK4a and RASSF1a in HCC. Finally, we found a significant association of cirrhosis with hypermethylation of the p16INK4a and hypomethylation of the CDH13 genes. For the first time, the survey was carried out on such an extent that it would not only provide new insights into the molecular mechanisms underscoring the aberrant expression of the genes in this study in HCC, but also offer essential information required for a good methylation-based diagnosis of HCC.

Project description:Hypermethylation 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).MLDA 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.MLDA 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

Methylation profiles of thirty four promoter-CpG islands and concordant methylation behaviours of sixteen genes that may contribute to carcinogenesis of astrocytoma.

Publications

Methylation profiles of thirty four promoter-CpG islands and concordant methylation behaviours of sixteen genes that may contribute to carcinogenesis of astrocytoma.

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