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Biomedical subjects

Christine E Horak

Publications and source records attributed to Christine E Horak.

8 recordsLinked to original sources
PubMed2006

Translational approaches using metastasis suppressor genes.

Cancer metastasis is a significant contributor to breast cancer patient morbidity and mortality. In order to develop new anti-metastatic therapies, we need to understand the biological and biochemical mechanisms of metastasis. Toward these efforts, we and others have studied metastasis suppressor genes, which halt metastasis in vivo without affecting primary tumor growth. The first metastasis suppressor gene identified was nm23, also known as NDP kinase. Nm23 represents the most widely validated metastasis suppressor gene, based on transfection and knock-out mouse strategies. The biochemical mechanism of metastasis suppression via Nm23 is unknown and likely complex. Two potential mechanisms include binding proteins and a histidine kinase activity. Elevation of Nm23 expression in micrometastatic tumor cells may constitute a translational strategy for the limitation of metastatic colonization in high risk cancer patients. To date, medroxyprogesterone acetate (MPA) has been identified as a candidate compound for clinical testing.

Animals↗
PubMed2005

Medroxyprogesterone acetate elevation of Nm23-H1 metastasis suppressor expression in hormone receptor-negative breast cancer.

BACKGROUND: Reestablishment of metastasis suppressor gene expression may constitute a therapeutic strategy for high-risk breast cancer patients. We previously showed that medroxyprogesterone acetate (MPA), a progestin that has been tested as treatment for advanced breast cancer, elevates expression of the Nm23-H1 metastasis suppressor gene in hormone receptor-negative metastatic human breast carcinoma cell lines in vitro via a glucocorticoid receptor-based mechanism. Here, we tested whether MPA treatment inhibits metastatic colonization of a hormone receptor-negative breast cancer cell line in vivo. METHODS: We tested the soft-agar colony-forming efficiency of untransfected MDA-MB-231T human breast carcinoma cells and MDA-MB-231T cells transfected with antisense Nm23-H1 in the presence and absence of MPA. Pharmacokinetic studies were used to establish dose and injection schedules that led to MPA serum levels in mice similar to those achievable in humans. For in vivo studies, nude mice were injected intravenously with MDA-MB-231T cells. After 4 weeks, mice were randomized to control or MPA arms. Endpoints included incidence, number, and size of gross pulmonary metastases; Nm23-H1 protein expression in gross metastases; and side effects. All statistical tests were two-sided. RESULTS: MPA reduced colony formation of MDA-MB-231T cells by 40%-50% but had no effect on colony formation of Nm23-H1 antisense transfectants. Metastases developed in 100% (95% confidence interval [CI] = 78% to 100% and 77% to 100%, respectively) of control mice injected with MDA-MB-231T cells. In two independent experiments, only 73% (95% CI = 45% to 92%) and 64% (95% CI = 35% to 87%) of mice injected with 2 mg of MPA developed metastases. Mice injected with 2 mg of MPA showed reductions in the mean numbers, per mouse, of all metastases and of large (>3 mm) metastases (P = .04 and .013, respectively). Nm23-H1 was expressed at high levels in 43% of pulmonary metastases in MPA-treated mice but only 13% of metastases in untreated mice. Mice receiving at least 1-mg doses of MPA gained more weight than control-treated mice but exhibited no bone density alterations or abnormal mammary fat pad histology. CONCLUSION: Our preclinical results show that MPA appears to elevate Nm23-H1 metastasis suppressor gene expression, thereby reducing metastatic colonization. The data suggest a new use for an old agent in a molecularly defined subset of breast cancer patients.

Animals↗
PubMed2005

Metastasis gets site specific.

Organ-specific homing and colonization of cancer cells are important and interesting features of metastasis. Molecular programs that contribute to this tropism may be elucidated through gene expression profiling with DNA microarrays. Using experimentally derived breast cancer cells that home specifically to bone or to lung, several investigators have concluded that distinct alterations in gene expression underlie metastasis to these sites. Minn et al. (2005) report a set of genes involved in lung-specific metastasis of breast cancer; the authors have determined the functional contribution of several genes to the metastatic cascade, as well as the relevance of these genes to human disease.

Breast Neoplasms↗
PubMed2003

ExpressYourself: A modular platform for processing and visualizing microarray data.

DNA microarrays are widely used in biological research; by analyzing differential hybridization on a single microarray slide, one can detect changes in mRNA expression levels, increases in DNA copy numbers and the location of transcription factor binding sites on a genomic scale. Having performed the experiments, the major challenge is to process large, noisy datasets in order to identify the specific array elements that are significantly differentially hybridized. This normally requires aggregating different, often incompatible programs into a multi-step pipeline. Here we present ExpressYourself, a fully integrated platform for processing microarray data. In completely automated fashion, it will correct the background array signal, normalize the Cy5 and Cy3 signals, score levels of differential hybridization, combine the results of replicate experiments, filter problematic regions of the array and assess the quality of individual and replicate experiments. ExpressYourself is designed with a highly modular architecture so various types of microarray analysis algorithms can readily be incorporated as they are developed; for example, the system currently implements several normalization methods, including those that simultaneously consider signal intensity and slide location. The processed data are presented using a web-based graphical interface to facilitate comparison with the original images of the array slides. In particular, Express Yourself is able to regenerate images of the original microarray after applying various steps of processing, which greatly facilities identification of position-specific artifacts. The program is freely available for use at http://bioinfo.mbb.yale.edu/expressyourself.

Algorithms↗
PubMed2002

Complex transcriptional circuitry at the G1/S transition in Saccharomyces cerevisiae.

In the yeast Saccharomyces cerevisiae, SBF (Swi4-Swi6 cell cycle box binding factor) and MBF (MluI binding factor) are the major transcription factors regulating the START of the cell cycle, a time just before DNA replication, bud growth initiation, and spindle pole body (SPB) duplication. These two factors bind to the promoters of 235 genes, but bind less than a quarter of the promoters upstream of genes with peak transcript levels at the G1 phase of the cell cycle. Several functional categories, which are known to be crucial for G1/S events, such as SPB duplication/migration and DNA synthesis, are under-represented in the list of SBF and MBF gene targets. SBF binds the promoters of several other transcription factors, including HCM1, PLM2, POG1, TOS4, TOS8, TYE7, YAP5, YHP1, and YOX1. Here, we demonstrate that these factors are targets of SBF using an independent assay. To further elucidate the transcriptional circuitry that regulates the G1-to-S-phase progression, these factors were epitope-tagged and their binding targets were identified by chIp-chip analysis. These factors bind the promoters of genes with roles in G1/S events including DNA replication, bud growth, and spindle pole complex formation, as well as the general activities of mitochondrial function, transcription, and protein synthesis. Although functional overlap exists between these factors and MBF and SBF, each of these factors has distinct functional roles. Most of these factors bind the promoters of other transcription factors known to be cell cycle regulated or known to be important for cell cycle progression and differentiation processes indicating that a complex network of transcription factors coordinates the diverse activities that initiate a new cell cycle.

Binding Sites↗
PubMed2002

Global analysis of gene expression in yeast.

In the past decade, there has been an intense effort to comprehensively catalogue the expressed genes in the yeast Saccharomyces cerevisiae and to determine the absolute and relative abundance of transcript and protein levels under different cellular conditions. Several methods have been developed to monitor gene expression: DNA microarray analysis, Serial Analysis of Gene Expression (SAGE), kinetic RT-PCR and monitoring expression of beta-galactosidase fusion proteins. These techniques have been used to measure transcript and protein abundance in different developmental states and under different environmental stimuli. A wealth of expression data for yeast is now publicly available through several web sites. The expression information that exists has the obvious benefits of providing a better understanding of the gene expression patterns that accompany changes in a yeast cell's environmental and developmental states. This data has also, however, provided clues to unraveling the complicated questions surrounding gene regulation: why and how is gene expression controlled?

Gene Expression Regulation, Fungal↗
PubMed2002

GATA-1 binding sites mapped in the beta-globin locus by using mammalian chIp-chip analysis.

The expression of the beta-like globin genes is intricately regulated by a series of both general and tissue-restricted transcription factors. The hemapoietic lineage-specific transcription factor GATA-1 is important for erythroid differentiation and has been implicated in regulating the expression of the erythroid-specific genes including the genes of the beta-globin locus. In the human erythroleukemic K562 cell line, only one DNA region has been identified previously as a putative site of GATA-1 interaction by in vivo footprinting studies. We mapped GATA-1 binding throughout the beta-globin locus by using chIp-chip analysis of K562 cells. We found that GATA-1 binds in a region encompassing the HS2 core element, as was previously identified, and an additional region of GATA-1 binding upstream of the gammaG gene. This approach will be of general utility for mapping transcription factor binding sites within the beta-globin locus and throughout the genome.

Animals↗