Estrogen receptor α polymorphisms and postmenopausal breast cancer risk

Item does not contain fulltextBACKGROUND: The estrogen receptor alpha (ESR1) is a mediator of estrogen response in the breast. The most studied variants in this gene are the PvuII and XbaI polymorphisms, which have been associated to lower sensitivity to estrogen. We evaluated whether these polymorphisms were associated with breast cancer risk by means of an association study in a population of Caucasian postmenopausal women from the Rotterdam study and a meta-analysis of published data. METHODS: The PvuII and XbaI polymorphisms were genotyped in 3,893 women participants of the Rotterdam Study. Baseline information was obtained through a questionnaire. We conducted logistic regression analyses to assess the risk of breast cancer by each of the ESR1 genotypes. Meta-analyses of all publications on these relations were done by retrieving literature from Pubmed and by further checking the reference lists of the articles obtained. RESULTS: There were 38 women with previously diagnosed breast cancer. During follow-up, 152 were additionally diagnosed. The logistic regression analyses showed no difference in risk for postmenopausal breast cancer in carriers of the PvuII or XbaI genotypes neither in overall, incident or prevalent cases. No further evidence of a role of these variants was found in the meta-analysis. CONCLUSIONS: Our results suggest that the ESR1 polymorphisms do not play a role in breast cancer risk in Caucasian postmenopausal women

Comprehensive profiling of DNA methylation in colorectal cancer reveals subgroups with distinct clinicopathological and molecular features

<p>Abstract</p> <p>Background</p> <p>Most previous studies of the CpG island methylator phenotype (CIMP) in colorectal cancer (CRC) have been conducted on a relatively small numbers of CpG sites. In the present study we performed comprehensive DNA methylation profiling of CRC with the aim of characterizing CIMP subgroups.</p> <p>Methods</p> <p>DNA methylation at 1,505 CpG sites in 807 cancer-related genes was evaluated using the Illumina GoldenGate^®methylation array in 28 normal colonic mucosa and 91 consecutive CRC samples. Methylation data was analyzed using unsupervised hierarchical clustering. CIMP subgroups were compared for various clinicopathological and molecular features including patient age, tumor site, microsatellite instability (MSI), methylation at a consensus panel of CpG islands and mutations in <it>BRAF </it>and <it>KRAS</it>.</p> <p>Results</p> <p>A total of 202 CpG sites were differentially methylated between tumor and normal tissue. Unsupervised hierarchical clustering of methylation data from these sites revealed the existence of three CRC subgroups referred to as CIMP-low (CIMP-L, 21% of cases), CIMP-mid (CIMP-M, 14%) and CIMP-high (CIMP-H, 65%). In comparison to CIMP-L tumors, CIMP-H tumors were more often located in the proximal colon and showed more frequent mutation of <it>KRAS </it>and <it>BRAF </it>(<it>P </it>< 0.001).</p> <p>Conclusions</p> <p>Comprehensive DNA methylation profiling identified three CRC subgroups with distinctive clinicopathological and molecular features. This study suggests that both <it>KRAS </it>and <it>BRAF </it>mutations are involved with the CIMP-H pathway of CRC rather than with distinct CIMP subgroups.</p

Tissue specific DNA methylation of CpG islands in normal human adult somatic tissues distinguishes neural from non-neural tissues

Although most CpG islands are generally thought to remain unmethylated in all adult somatic tissues, recent genome-wide approaches have found that some CpG islands have distinct methylation patterns in various tissues, with most differences being seen between germ cells and somatic tissues. Few studies have addressed this among human somatic tissues and fewer still have studied the same sets of tissues from multiple individuals. In the current study, we used Restriction Landmark Genomic Scanning to study tissue specific methylation patterns in a set of 12 human tissues collected from multiple individuals. We identified 34 differentially methylated CpG islands among these tissues, many of which showed consistent patterns in multiple individuals. Of particular interest were striking differences in CpG island methylation, not only among brain regions, but also between white and grey matter of the same region. These findings were confirmed for selected loci by quantitative bisulfite sequencing. Cluster analysis of the RLGS data indicated that several tissues clustered together, but the strongest clustering was in brain. Tissues from different brain regions clustered together, and, as a group, brain tissues were distinct from either mesoderm or endoderm derived tissues which demonstrated limited clustering. These data demonstrate consistent tissue specific methylation for certain CpG islands, with clear differences between white and grey matter of the brain. Furthermore, there was an overall pattern of tissue specifically methylated CpG islands that distinguished neural tissues from non-neural