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A seven-gene CpG-island methylation panel predicts breast cancer progression.

ABSTRACT: DNA methylation regulates gene expression, through the inhibition/activation of gene transcription of methylated/unmethylated genes. Hence, DNA methylation profiling can capture pivotal features of gene expression in cancer tissues from patients at the time of diagnosis. In this work, we analyzed a breast cancer case series, to identify DNA methylation determinants of metastatic versus non-metastatic tumors.CpG-island methylation was evaluated on a 56-gene cancer-specific biomarker microarray in metastatic versus non-metastatic breast cancers in a multi-institutional case series of 123 breast cancer patients. Global statistical modeling and unsupervised hierarchical clustering were applied to identify a multi-gene binary classifier with high sensitivity and specificity. Network analysis was utilized to quantify the connectivity of the identified genes.Seven genes (BRCA1, DAPK1, MSH2, CDKN2A, PGR, PRKCDBP, RANKL) were found informative for prognosis of metastatic diffusion and were used to calculate classifier accuracy versus the entire data-set. Individual-gene performances showed sensitivities of 63-79 %, 53-84 % specificities, positive predictive values of 59-83 % and negative predictive values of 63-80 %. When modelled together, these seven genes reached a sensitivity of 93 %, 100 % specificity, a positive predictive value of 100 % and a negative predictive value of 93 %, with high statistical power. Unsupervised hierarchical clustering independently confirmed these findings, in close agreement with the accuracy measurements. Network analyses indicated tight interrelationship between the identified genes, suggesting this to be a functionally-coordinated module, linked to breast cancer progression.Our findings identify CpG-island methylation profiles with deep impact on clinical outcome, paving the way for use as novel prognostic assays in clinical settings.

SUBMITTER: Li Y

PROVIDER: S-EPMC4438505 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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A seven-gene CpG-island methylation panel predicts breast cancer progression.

Li Yan Y Melnikov Anatoliy A AA Levenson Victor V Guerra Emanuela E Simeone Pasquale P Alberti Saverio S Deng Youping Y

BMC cancer 20150519

<h4>Background</h4>DNA methylation regulates gene expression, through the inhibition/activation of gene transcription of methylated/unmethylated genes. Hence, DNA methylation profiling can capture pivotal features of gene expression in cancer tissues from patients at the time of diagnosis. In this work, we analyzed a breast cancer case series, to identify DNA methylation determinants of metastatic versus non-metastatic tumors.<h4>Methods</h4>CpG-island methylation was evaluated on a 56-gene canc ...[more]

PMID: 25986046

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Project description:BACKGROUND:Loss of BIN1 tumor suppressor expression is abundant in human cancer and its frequency exceeds that of genetic alterations, suggesting the role of epigenetic regulators (DNA methylation). BIN1 re-expression in the DU145 prostate cancer cell line after 5-aza-2'-deoxycytidine treatment was recently reported but no methylation of the BIN1 promoter CpG island was found in DU145. METHODS:Methylation-sensitive arbitrarily-primed PCR was used to detect genomic loci abnormally methylated in breast cancer. BIN1 CpG island fragment was identified among the differentially methylated loci as a result of direct sequencing of the methylation-sensitive arbitrarily-primed PCR product and subsequent BLAST alliance. BIN1 CpG island cancer related methylation in breast and prostate cancers was confirmed by bisulphite sequencing and its methylation frequency was evaluated by methylation sensitive PCR. Loss of heterozygosity analysis of the BIN1 region was performed with two introgenic and one closely adjacent extragenic microsatellite markers.BIN1 expression was evaluated by real-time RT-PCR. RESULTS:We have identified a 3'-part of BIN1 promoter CpG island among the genomic loci abnormally methylated in breast cancer. The fragment proved to be methylated in 18/99 (18%) and 4/46 (9%) breast and prostate tumors, correspondingly, as well as in MCF7 and T47D breast cancer cell lines, but was never methylated in normal tissues and lymphocytes as well as in DU145 and LNCaP prostate cancer cell lines. The 5'-part of the CpG island revealed no methylation in all samples tested. BIN1 expression losses were detected in MCF7 and T47D cells and were characteristic of primary breast tumors (10/13; 77%), while loss of heterozygosity was a rare event in tissue samples (2/22 informative cases; 9%) and was ruled out for MCF7. CONCLUSION:BIN1 promoter CpG island is composed of two parts differing drastically in the methylation patterns in cancer. This appears to be a common feature of cancer related genes and demands further functional significance exploration. Although we have found no evidence of the functional role of such a non-core methylation in BIN1 expression regulation, our data do not altogether rule this possibility out.

Project description:Caveolin-1 (Cav1) is an integral membrane, scaffolding protein found in plasma membrane invaginations (caveolae). Cav1 regulates multiple cancer-associated processes. In breast cancer, a tumor suppressive role for Cav1 has been suggested; however, Cav1 is frequently overexpressed in aggressive breast cancer subtypes, suggesting an oncogenic function in advanced-stage disease. To further delineate Cav1 function in breast cancer progression, we evaluated its expression levels among a panel of cell lines representing a spectrum of breast cancer phenotypes. In basal-like (the most aggressive BC subtype) breast cancer cells, Cav1 was consistently upregulated, and positively correlated with increased cell proliferation, anchorage-independent growth, and migration and invasion. To identify mechanisms of Cav1 gene regulation, we compared DNA methylation levels within promoter 'CpG islands' (CGIs) with 'CGI shores', recently described regions that flank CGIs with less CG-density. Integration of genome-wide DNA methylation profiles ('methylomes') with Cav1 expression in 30 breast cancer cell lines showed that differential methylation of CGI shores, but not CGIs, significantly regulated Cav1 expression. In breast cancer cell lines having low Cav1 expression (despite promoter CGI hypomethylation), we found that treatment with a DNA methyltransferase inhibitor induced Cav1 expression via CGI shore demethylation. In addition, further methylome assessments revealed that breast cancer aggressiveness associated with Cav1 CGI shore methylation levels, with shore hypermethylation in minimally aggressive, luminal breast cancer cells and shore hypomethylation in highly aggressive, basal-like cells. Cav1 CGI shore methylation was also observed in human breast tumors, and overall survival rates of breast cancer patients lacking estrogen receptor ? (ER?) negatively correlated with Cav1 expression. Based on this first study of Cav1 (a potential oncogene) CGI shore methylation, we suggest this phenomenon may represent a new prognostic marker for ER?-negative, basal-like breast cancer.

Project description:We used deep sequencinge technology to profile the transcriptome, gene copy number, and CpG island methylation status simultaneously in eight commonly used breast cell lines to develop a model for how these genomic features are integrated in estrogen receptor positive (ER+) and negative breast cancer. Total mRNA sequence, gene copy number, and genomic CpG island methylation were carried out using the Illumina Genome Analyzer. Sequences were mapped to the human genome to obtain digitized gene expression data, DNA copy number in reference to the non-tumor cell line (MCF10A), and methylation status of 21,570 CpG islands to identify differentially expressed genes that were correlated with methylation or copy number changes. These were evaluated in a dataset from 129 primary breast tumors. Gene expression in cell lines was dominated by ER-associated genes. ER+ and ER- cell lines formed two distinct, stable clusters, and 1,873 genes were differentially expressed in the two groups. Part of chromosome 8 was deleted in all ER- cells and part of chromosome 17 amplified in all ER+ cells. These loci encoded 30 genes that were overexpressed in ER+ cells; 9 of these genes were overexpressed in ER+ tumors. We identified 149 differentially expressed genes that exhibited differential methylation of one or more CpG islands within 5kb of the 5' end of the gene and for which mRNA abundance was inversely correlated with CpG island methylation status. In primary tumors we identified 84 genes that appear to be robust components of the methylation signature that we identified in ER+ cell lines. Our analyses reveal a global pattern of differential CpG island methylation that contributes to the transcriptome landscape of ER+ and ER- breast cancer cells and tumors. The role of gene amplification/deletion appears to more modest, although several potentially significant genes appear to be regulated by copy number aberrations. 8 commonly used breast cancer cell lines were sequenced for mRNA expression, CpG methylation and DNA copy number

Dataset Information

A seven-gene CpG-island methylation panel predicts breast cancer progression.

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A seven-gene CpG-island methylation panel predicts breast cancer progression.

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