Biomedical subjects

Robert C Gentleman

Publications and source records attributed to Robert C Gentleman.

6 recordsLinked to original sources

PubMed2006

Combined cDNA array comparative genomic hybridization and serial analysis of gene expression analysis of breast tumor progression.

To identify genetic changes involved in the progression of breast carcinoma, we did cDNA array comparative genomic hybridization (CGH) on a panel of breast tumors, including 10 ductal carcinoma in situ (DCIS), 18 invasive breast carcinomas, and two lymph node metastases. We identified 49 minimal commonly amplified regions (MCRs) that included known (1q, 8q24, 11q13, 17q21-q23, and 20q13) and several uncharacterized (12p13 and 16p13) regional copy number gains. With the exception of the 17q21 (ERBB2) amplicon, the overall frequency of copy number alterations was higher in invasive tumors than that in DCIS, with several of them present only in invasive cancer. Amplification of candidate loci was confirmed by quantitative PCR in breast carcinomas and cell lines. To identify putative targets of amplicons, we developed a method combining array CGH and serial analysis of gene expression (SAGE) data to correlate copy number and expression levels for each gene within MCRs. Using this approach, we were able to distinguish a few candidate targets from a set of coamplified genes. Analysis of the 12p13-p12 amplicon identified four putative targets: TEL/ETV6, H2AFJ, EPS8, and KRAS2. The amplification of all four candidates was confirmed by quantitative PCR and fluorescence in situ hybridization, but only H2AFJ and EPS8 were overexpressed in breast tumors with 12p13 amplification compared with a panel of normal mammary epithelial cells. These results show the power of combined array CGH and SAGE analysis for the identification of candidate amplicon targets and identify H2AFJ and EPS8 as novel putative oncogenes in breast cancer.

Breast Neoplasms↗

PubMed2006

Data standards for flow cytometry.

Flow cytometry (FCM) is an analytical tool widely used for cancer and HIV/AIDS research, and treatment, stem cell manipulation and detecting microorganisms in environmental samples. Current data standards do not capture the full scope of FCM experiments and there is a demand for software tools that can assist in the exploration and analysis of large FCM datasets. We are implementing a standardized approach to capturing, analyzing, and disseminating FCM data that will facilitate both more complex analyses and analysis of datasets that could not previously be efficiently studied. Initial work has focused on developing a community-based guideline for recording and reporting the details of FCM experiments. Open source software tools that implement this standard are being created, with an emphasis on facilitating reproducible and extensible data analyses. As well, tools for electronic collaboration will assist the integrated access and comprehension of experiments to empower users to collaborate on FCM analyses. This coordinated, joint development of bioinformatics standards and software tools for FCM data analysis has the potential to greatly facilitate both basic and clinical research--impacting a notably diverse range of medical and environmental research areas.

Cell Separation↗

PubMed2005

Association of valproate-induced teratogenesis with histone deacetylase inhibition in vivo.

Chemically induced birth defects are an important public health and human problem. Here we use Xenopus and zebrafish as models to investigate the mechanism of action of a well-known teratogen, valproic acid (VPA). VPA is a drug used in treatment of epilepsy and bipolar disorder but causes spina bifida if taken during pregnancy. VPA has several biochemical activities, including inhibition of histone deacetylases (HDACs). To investigate the mechanism of action of VPA, we compared its effects in Xenopus and zebrafish embryos with those of known HDAC inhibitors and noninhibitory VPA analogs. We found that VPA and other HDAC inhibitors cause very similar and characteristic developmental defects whereas VPA analogs with poor inhibitory activity in vivo have little teratogenic effect. Unbiased microarray analysis revealed that the effects of VPA and trichostatin A (TSA), a structurally unrelated HDAC inhibitor, are strikingly concordant. The concordance is apparent both by en masse correlation of fold-changes and by detailed similarity of dose-response profiles of individual genes. Together, the results demonstrate that the teratogenic effects of VPA are very likely mediated specifically by inhibition of HDACs.

Abnormalities, Drug-Induced↗

PubMed2004

Bioconductor: open software development for computational biology and bioinformatics.

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples.

Computational Biology↗

PubMed2004

Genomic representations using concatenates of Type IIB restriction endonuclease digestion fragments.

We have developed a method for genomic representation using Type IIB restriction endonucleases. Representation by concatenation of restriction digests, or RECORD, is an approach to sample the fragments generated by cleavage with these enzymes. Here, we show that the RECORD libraries may be used for digital karyotyping and for pathogen identification by computational subtraction.

Bacteria↗

PubMed2003

Open source software for the analysis of microarray data.

DNA microarray assays represent the first widely used application that attempts to build upon the information provided by genome projects in the study of biological questions. One of the greatest challenges with working with microarrays is collecting, managing, and analyzing data. Although several commercial and noncommercial solutions exist, there is a growing body of freely available, open source software that allows users to analyze data using a host of existing techniques and to develop their own and integrate them within the system. Here we review three of the most widely used and comprehensive systems, the statistical analysis tools written in R through the Bioconductor project (http://www.bioconductor.org), the Java-based TM4 software system available from The Institute for Genomic Research (http://www.tigr.org/software), and BASE, the Web-based system developed at Lund University (http://base.thep.lu.se).

Database Management Systems↗