Biomedical subjects

Wendell D Jones

Publications and source records attributed to Wendell D Jones.

3 recordsLinked to original sources

PubMed2006

DNA methylation-dependent silencing of CST6 in human breast cancer cell lines.

Cystatin M (CST6) is a candidate breast cancer tumor suppressor that is expressed in normal and premalignant breast epithelium, but not in metastatic breast cancer cell lines. CST6 is subject to epigenetic silencing in MCF-7 breast cancer cells related to methylation of the CpG island that encompasses the CST6 proximal promoter region and exon 1. In the current study, CST6 CpG island methylation and expression status was examined in a panel of breast cancer cell lines. Seven of 12 (58%) cell lines lack detectable expression of CST6 and treatment of these cells with 5-aza-2'-deoxycytidine resulted in a significant increase in CST6 expression, suggesting that the loss of expression may be related to methylation-dependent epigenetic silencing. Bisulfite sequencing of CST6 in a subset of breast cancer cell lines revealed CpG island hypermethylation in CST6-negative cells, and an absence of CpG island methylation in cells that express CST6. The extent of regional methylation was strongly associated with the lack of expression of CST6 among these cell lines. In particular, hypermethylation of the proximal promoter was significantly associated with CST6 gene silencing, and methylation of a number of individual CpGs was found to be statistically correlated with extinction of gene expression. These results establish a strong link between CST6 promoter hypermethylation and loss of CST6 expression in breast cancer cell lines, and suggest that methylation-dependent epigenetic silencing of CST6 may represent an important mechanism for loss of CST6 during breast carcinogenesis in vivo.

Antimetabolites, Antineoplastic↗

PubMed2006

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

Equipment Design↗

PubMed2006

Using RNA sample titrations to assess microarray platform performance and normalization techniques.

We have assessed the utility of RNA titration samples for evaluating microarray platform performance and the impact of different normalization methods on the results obtained. As part of the MicroArray Quality Control project, we investigated the performance of five commercial microarray platforms using two independent RNA samples and two titration mixtures of these samples. Focusing on 12,091 genes common across all platforms, we determined the ability of each platform to detect the correct titration response across the samples. Global deviations from the response predicted by the titration ratios were observed. These differences could be explained by variations in relative amounts of messenger RNA as a fraction of total RNA between the two independent samples. Overall, both the qualitative and quantitative correspondence across platforms was high. In summary, titration samples may be regarded as a valuable tool, not only for assessing microarray platform performance and different analysis methods, but also for determining some underlying biological features of the samples.

Algorithms↗