Consistency of predictive signature genes and classifiers generated using different microarray platforms.

Microarray-based classifiers and associated signature genes generated from various platforms are abundantly reported in the literature; however, the utility of the classifiers and signature genes in cross-platform prediction applications remains largely uncertain. As part of the MicroArray Quality Control Phase II (MAQC-II) project, we show in this study 80-90% cross-platform prediction consistency using a large toxicogenomics data set by illustrating that: (1) the signature genes of a classifier generated from one platform can be directly applied to another platform to develop a predictive classifier; (2) a classifier developed using data generated from one platform can accurately predict samples that were profiled using a different platform. The results suggest the potential utility of using published signature genes in cross-platform applications and the possible adoption of the published classifiers for a variety of applications. The study reveals an opportunity for possible translation of biomarkers identified using microarrays to clinically validated non-array gene expression assays.

Capturing genomic signatures of DNA sequence variation using a standard anonymous microarray platform.

Comparative genomics, using the model organism approach, has provided powerful insights into the structure and evolution of whole genomes. Unfortunately, only a small fraction of Earth's biodiversity will have its genome sequenced in the foreseeable future. Most wild organisms have radically different life histories and evolutionary genomics than current model systems. A novel technique is needed to expand comparative genomics to a wider range of organisms. Here, we describe a novel approach using an anonymous DNA microarray platform that gathers genomic samples of sequence variation from any organism. Oligonucleotide probe sequences placed on a custom 44 K array were 25 bp long and designed using a simple set of criteria to maximize their complexity and dispersion in sequence probability space. Using whole genomic samples from three known genomes (mouse, rat and human) and one unknown (Gonystylus bancanus), we demonstrate and validate its power, reliability, transitivity and sensitivity. Using two separate statistical analyses, a large numbers of genomic 'indicator' probes were discovered. The construction of a genomic signature database based upon this technique would allow virtual comparisons and simple queries could generate optimal subsets of markers to be used in large-scale assays, using simple downstream techniques. Biologists from a wide range of fields, studying almost any organism, could efficiently perform genomic comparisons, at potentially any phylogenetic level after performing a small number of standardized DNA microarray hybridizations. Possibilities for refining and expanding the approach are discussed.

Adaptation of estrogen-regulated genes in long-term estradiol deprived MCF-7 breast cancer cells.

First line treatment of hormone dependent breast cancer initially causes tumor regression but later results in adaptive changes and tumor re-growth. Responses to second line treatments occur but tumors again begin to progress after a period of 12???18??months. In depth understanding of the adaptive process would allow the identification of targets to abrogate the development of hormonal resistance and prolong the efficacy of endocrine therapy. We have developed a model system to examine adaptive changes in human MCF-7 breast cancer cells. Upon deprivation of estradiol for a prolonged period of time, a maneuver analogous to surgical oophorectomy in pre-menopausal women and use of aromatase inhibitors in post-menopausal patients, tumor cells adapt and become hypersensitive to estradiol. We reasoned that the expression pattern of multiple genes would change in response to estradiol deprivation and that cDNA microarrays would provide an efficient means of assessing these changes. Accordingly, we examined the transcriptional responses to estradiol in long-term estradiol deprived (LTED) MCF-7 cells with a cDNA microarray containing 1901 known genes and ESTs. To assess the changes induced by long-term estradiol deprivation, we compared the effects of estradiol administration in LTED cells with those in MCF-7 cells, which we had previously reported, and confirmed with real time PCR using the parental and LTED cells. Seven genes and one EST were induced by estradiol in LTED but not in wild type MCF-7 cells, whereas ten genes were down-regulated by estradiol only in LTED cells. The expression of seven genes increased concurrently and five decreased in response to estradiol in both cell types. From these observations, we generated testable hypotheses regarding several genes including DKFZP, RAP-1, ribosomal protein S6, and TM4SF1. Based upon the known functions of these genes and the patterns of observed changes, we postulate that divergent regulation of these genes may contribute to the different biologic responses to estrogen in these cell lines. These results provide targets for further mechanistic studies in our experimental system. Our findings indicate that long-term estradiol deprivation causes expression changes in multiple genes and emphasizes the complexity of the process of cellular adaptation.

Progress in the application of DNA microarrays.

Microarray technology has been applied to a variety of different fields to address fundamental research questions. The use of microarrays, or DNA chips, to study the gene expression profiles of biologic samples began in 1995. Since that time, the fundamental concepts behind the chip, the technology required for making and using these chips, and the multitude of statistical tools for analyzing the data have been extensively reviewed. For this reason, the focus of this review will be not on the technology itself but on the application of microarrays as a research tool and the future challenges of the field.

Relationship between expression of coactivators and corepressors of hormone receptors and resistance of ovarian cancers to growth regulation by steroid hormones.

OBJECTIVE: To determine whether aberrant expression of hormone receptor corepressors or coactivators or defects in estrogen receptor-mediated transcription might underlie resistance of ovarian cancers to hormonal therapy. METHODS: Northern analysis, Western analysis, and polymerase chain reaction were used to examine expression of estrogen receptor (ER), progesterone receptor (PR), the nuclear receptor corepressors N-CoR and SMRT, and the steroid receptor coactivator BRG-1 in ovarian cancer cell lines and primary cancers. The effect of BRG-1 transfection on ER-mediated transcription was examined. We also determined the effect of estrogen and the pure estrogen antagonist ICI 182,780 on cell cycle profile and expression of ER. Finally, we examined the ability of estrogen to upregulate expression of known estrogen-responsive genes. RESULTS: Among primary ovarian cancers, 18 of 52 (35%) expressed N-CoR, and 37 of 52 (71%) expressed SMRT, but there was no correlation between expression of corepressors and hormone receptor status. All of the primary ovarian cancers and cell lines expressed BRG-1. Estrogen stimulation of two cell lines expressing ER (SKOV3, OVCA 432) elicited low levels of ER-mediated transcription that was not enhanced by BRG-1 transfection. ICI 182,780 did not induce cell cycle arrest in these cell lines, but there was evidence of downregulation of ER, indicating a ligand-receptor interaction. However, estrogen did not elicit increased transcription of estrogen-responsive genes (PR, myc, fos, pS2). CONCLUSION: Inappropriate expression of the nuclear corepressors N-CoR and SMRT or the coactivator BRG-1 does not underlie the resistance of ovarian cancers to hormonal therapy. Further studies are needed to elucidate the mechanisms underlying the inability of ovarian cancers to undergo ER-mediated transcription if we hope to understand their resistance to hormonal therapy.

Inhibition of mitogen-activated protein kinase and phosphatidylinositol 3-kinase activity in MCF-7 cells prevents estrogen-induced mitogenesis.

Estrogen acts to promote DNA synthesis in the MCF-7 human breast cancer cell line via its interaction with high levels of estrogen receptor. The primary mode of estrogen action has been considered to be through transcriptional activation of genes containing estrogen response elements, including the immediate early genes c-myc and fos. Recent reports have indicated that estrogen, acting through the estrogen receptor, is capable of inducing the mitogen-activated protein kinase (MAPK) cytoplasmic signaling cascade. In this study, specific small molecule inhibitors of MAPK and phosphatidylinositol 3-kinase activity were used to determine the influence of these cascades on estrogen-mediated mitogenesis. Phosphatidylinositol 3-kinase inhibitors, LY294002 and wortmannin, as well as inhibitors of MAPK kinase-1, PD098059 and U0126, decreased the fraction of cells entering DNA synthesis after treatment with 17beta-estradiol. These compounds did not inhibit expression of myc or fos. However, the drugs did prevent the accumulation of cyclin D1 and hyperphosphorylated retinoblastoma protein, indicating that the block occurred at, or prior to, this point in the cell cycle. Although these compounds were effective in preventing estrogen-mediated mitogenesis, the downstream kinases extracellular signal-regulated kinase 1, extracellular signal-regulated kinase 2, and protein kinase B were not activated over basal levels by estrogen treatment. These studies suggest that estrogen initiates mitogenesis by inducing the transcription of immediate early genes, but cytoplasmic signaling pathways play an important role in the control of subsequent events in the cell cycle.

Estrogen-induced mitogenesis of MCF-7 cells does not require the induction of mitogen-activated protein kinase activity.

Estrogen mediates the transcription of responsive genes via its interaction with the estrogen receptor (ER). This ligand-dependent transcriptional activity has been the mechanistic basis for understanding estrogen-induced proliferation. However, recent reports suggest that estrogen stimulation results in activation of the mitogen-activated protein kinase (MAPK) cascade in an ER-dependent manner suggesting that mitogenesis may be mediated through this cytoplasmic signaling cascade. In this study, we demonstrate that estrogen stimulation of MCF-7 cells does not activate MAPK regardless of hormone concentration, serum concentration, or cell density. We also excluded the activation of MAPK through autocrine effects after estrogen treatment. Finally, concentrations required for estrogen-induced mitogenesis and estrogen-mediated transcription were shown to be the same. These results support transcriptional activation as the primary mechanism for estrogen-mediated mitogenesis.