DNA Microarray Studies of Hematopoietic Subpopulations

BRB-ArrayTools is an integrated software system for the comprehensive analysis of DNA microarray experiments. It was developed by professional biostatisticians experienced in the design and analysis of DNA microarray studies and incorporates methods developed by leading statistical laboratories. The software is designed for use by biomedical scientists who wish to have access to state-of-the-art statistical methods for the analysis of gene expression data and to receive training in the statistical analysis of high dimensional data. The software provides the most extensive set of tools available for predictive classifier development and complete cross-validation. It offers extensive links to genomic websites for gene annotation and analysis tools for pathway analysis. An archive of over 100 datasets of published microarray data with associated clinical data is provided and BRB-ArrayTools automatically imports data from the Gene Expression Omnibus public archive at the National Center for Biotechnology Information.

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Temporal and differential gene expression of Singapore grouper iridovirus

Journal of General Virology ◽

10.1099/vir.0.82219-0 ◽

2006 ◽

Vol 87 (10) ◽

pp. 2907-2915 ◽

Cited By ~ 38

Author(s):

Li Ming Chen ◽

Fan Wang ◽

Wenjun Song ◽

Choy Leong Hew

Keyword(s):

Gene Expression ◽

Dna Microarray ◽

Open Reading Frames ◽

Economic Losses ◽

Viral Dna ◽

Temporal Gene Expression ◽

Dna Microarray Data ◽

Drug Treatments ◽

Microarray Studies

Singapore grouper iridovirus (SGIV), an iridovirus in the genus Ranavirus, is a major pathogen that results in significant economic losses in grouper aquaculture. To investigate further its infective mechanisms, for the first time, a viral DNA microarray was generated for the SGIV genome to measure the expression of its predicted open reading frames simultaneously in vitro. By using the viral DNA microarray, the temporal gene expression of SGIV was characterized and the DNA microarray data were consistent with the results of real-time RT-PCR studies. Furthermore, different-stage viral genes (i.e. immediate-early, early and late genes) of SGIV were uncovered by combining drug treatments and DNA microarray studies. These results should offer important insights into the replication and pathogenesis of iridoviruses.

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Power and sample size for DNA microarray studies

Statistics in Medicine ◽

10.1002/sim.1335 ◽

2002 ◽

Vol 21 (23) ◽

pp. 3543-3570 ◽

Cited By ~ 99

Author(s):

Mei-Ling Ting Lee ◽

G. A. Whitmore

Keyword(s):

Sample Size ◽

Dna Microarray ◽

Microarray Studies

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A Unified Computational Framework to Compare Direct and Sequential False Discovery Rate Algorithms for Exploratory DNA Microarray Studies

Journal of Data Science ◽

10.6339/jds.2005.03(4).239 ◽

2021 ◽

Vol 3 (4) ◽

pp. 331-352

Author(s):

Danh V. Nguyen

Keyword(s):

False Discovery Rate ◽

Dna Microarray ◽

Computational Framework ◽

False Discovery ◽

Microarray Studies

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TGFBR3 is lost in prostate cancer, contributing to malignant transformation

Journal of Clinical Oncology ◽

10.1200/jco.2006.24.18_suppl.14552 ◽

2006 ◽

Vol 24 (18_suppl) ◽

pp. 14552-14552

Author(s):

N. Sharifi ◽

E. Hurt ◽

W. L. Farrar

Keyword(s):

Prostate Cancer ◽

Malignant Transformation ◽

Cell Lines ◽

Cancer Cell ◽

Dna Microarray ◽

Prostate Cancer Cell ◽

Tgf Beta ◽

Early Disease ◽

Prostate Cancer Cell Lines ◽

Microarray Studies

14552 Background: Resistance to transforming growth factor-beta (TGF-beta) is common in solid tumors. Alterations of TGF-beta biology in prostate cancer are complex, with a downregulation of this cytokine reported in early disease and upregulation of TGF-beta in advanced disease. Mechanisms of TGF-beta resistance in early disease are not well understood. We have investigated the function of TGF-beta receptor 3 (TGFBR3) to determine its role in prostate cancer. Methods: We undertook an analysis of the data in seven published DNA microarray studies of nonneoplastic prostate tissue versus prostate cancer specimens using oncomine. Of the genes we identified as known to be directly involved in the TGF-beta pathway, loss of TGFBR3 was most significantly associated with prostate cancer. We determined TGFBR3 expression in prostate cancer cell lines and the immortalized prostate epithelial cell line RWPE-1. To assess the consequences of loss of TGFBR3 expression, we created an shRNA construct and stably infected RWPE-1 cells. We analyzed gene expression changes by DNA microarray analysis and confirmed changes by Western Blot. We then searched TGFBR3 regulated genes based on our knockdown studies in the data set from the seven previously published studies. Furthermore, we evaluated the phenotypic consequences of TGFBR3 knockdown. Results: TGFBR3 expression was significantly lost in 6 of 7 microarray studies. TGFBR3 was downregulated in 3 of 4 of prostate cancer cell lines, compared with RWPE-1. DNA microarray analysis of TGFBR3 knockdown in RWPE-1 cells showed that expression of DPYSL3, Vimentin, COCH, SERPINF1, PMP22, LTBP1 and BMP4 were decreased both with TGFBR3 knockdown and in the transition to prostate cancer. Of these genes, vimentin expression was most dramatically downregulated in TGFBR3 knockdown cells and we showed that vimentin protein expression was completely lost. The phenotypic consequence of TGFBR3 knockdown in RWPE-1 cells was formation of colonies that appear to reflect loss of contact inhibition. Conclusions: TGFBR3 is lost in prostate cancer. TGFBR3 knockdown leads to colony formation by immortalized prostate epithelial cells. Our data suggests that loss of TGFBR3 contributes to malignant transformation of the prostate. No significant financial relationships to disclose.

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