The promoter connection

Loss of the NKX3.1 tumorsuppressor promotes the TMPRSS2-ERG fusion gene expression in prostate cancer

BACKGROUND

In normal prostate epithelium the TMPRSS2 gene encoding a type II serine protease is directly regulated by male hormones through the androgen receptor. In prostate cancer ERG protooncogene frequently gains hormonal control by seizing gene regulatory elements of TMPRSS2 through genomic fusion events. Although, the androgenic activation of TMPRSS2 gene has been established, little is known about other elements that may interact with TMPRSS2 promoter sequences to modulate ERG expression in TMPRSS2-ERG gene fusion context.

METHODS

Comparative genomic analyses of the TMPRSS2 promoter upstream sequences and pathway analyses were performed by the Genomatix Software. NKX3.1 and ERG genes expressions were evaluated by immunoblot or by quantitative Real-Time PCR (qRT-PCR) assays in response to siRNA knockdown or heterologous expression. QRT-PCR assay was used for monitoring the gene expression levels of NKX3.1-regulated genes. Transcriptional regulatory function of NKX3.1 was assessed by luciferase assay. Recruitment of NKX3.1 to its cognate elements was monitored by Chromatin Immunoprecipitation assay.

RESULTS

Comparative analysis of the TMPRSS2 promoter upstream sequences among different species revealed the conservation of binding sites for the androgen inducible NKX3.1 tumor suppressor. Defects of NKX3.1, such as, allelic loss, haploinsufficiency, attenuated expression or decreased protein stability represent established pathways in prostate tumorigenesis. We found that NKX3.1 directly binds to TMPRSS2 upstream sequences and negatively regulates the expression of the ERG protooncogene through the TMPRSS2-ERG gene fusion.

CONCLUSIONS

These observations imply that the frequently noted loss-of-function of NKX3.1 cooperates with the activation of TMPRSS2-ERG fusions in prostate tumorigenesis.

Genome-wide analysis of regions similar to promoters of histone genes

Background

The purpose of this study is to: i) develop a computational model of promoters of human histone-encoding genes (shortly histone genes), an important class of genes that participate in various critical cellular processes, ii) use the model so developed to identify regions across the human genome that have similar structure as promoters of histone genes; such regions could represent potential genomic regulatory regions, e.g. promoters, of genes that may be coregulated with histone genes, and iii/ identify in this way genes that have high likelihood of being coregulated with the histone genes.

Results

We successfully developed a histone promoter model using a comprehensive collection of histone genes. Based on leave-one-out cross-validation test, the model produced good prediction accuracy (94.1% sensitivity, 92.6% specificity, and 92.8% positive predictive value). We used this model to predict across the genome a number of genes that shared similar promoter structures with the histone gene promoters. We thus hypothesize that these predicted genes could be coregulated with histone genes. This hypothesis matches well with the available gene expression, gene ontology, and pathways data. Jointly with promoters of the above-mentioned genes, we found a large number of intergenic regions with similar structure as histone promoters.

Conclusions

This study represents one of the most comprehensive computational analyses conducted thus far on a genome-wide scale of promoters of human histone genes. Our analysis suggests a number of other human genes that share a high similarity of promoter structure with the histone genes and thus are highly likely to be coregulated, and consequently coexpressed, with the histone genes. We also found that there are a large number of intergenic regions across the genome with their structures similar to promoters of histone genes. These regions may be promoters of yet unidentified genes, or may represent remote control regions that participate in regulation of histone and histone-coregulated gene transcription initiation. While these hypotheses still remain to be verified, we believe that these form a useful resource for researchers to further explore regulation of human histone genes and human genome. It is worthwhile to note that the regulatory regions of the human genome remain largely un-annotated even today and this study is an attempt to supplement our understanding of histone regulatory regions.

A guide to the integrated application of on-line data mining tools for the inference of gene functions at the systems level

Genes function in networks to achieve a common biological response. Thus, inferences into the biological role of individual genes can be gained by analyzing their association with other genes with more precisely defined functions. Here, we present a guide, using the well-characterized Arabidopsis thaliana pathogenesis-related protein 2 gene (PR-2) as an example, to document how the sequential use of web-based tools can be applied to integrate information from different databases and associate the function of an individual gene with a network of genes and additionally identify specific biological processes in which they collectively function. The analysis begins by performing a global expression correlation analysis to build a functionally associated gene network. The network is subsequently analyzed for Gene Ontology enrichment, stimuli and mutant-specific transcriptional responses and enriched putative promoter regulatory elements that may be responsible for their correlated relationships. The results for the PR-2 gene are entirely consistent with the published literature documenting the accuracy of this type of analysis. Furthermore, this type of analysis can also be performed on other organisms with the appropriate data available and will greatly assist in understanding individual gene functions in a systems context.

The promoters of human cell cycle genes integrate signals from two tumor suppressive pathways during cellular transformation

Deciphering regulatory events that drive malignant transformation represents a major challenge for systems biology. Here, we analyzed genome-wide transcription profiling of an in vitro cancerous transformation process. We focused on a cluster of genes whose expression levels increased as a function of p53 and p16(INK4A) tumor suppressors inactivation. This cluster predominantly consists of cell cycle genes and constitutes a signature of a diversity of cancers. By linking expression profiles of the genes in the cluster with the dynamic behavior of p53 and p16(INK4A), we identified a promoter architecture that integrates signals from the two tumor suppressive channels and that maps their activity onto distinct levels of expression of the cell cycle genes, which, in turn, correspond to different cellular proliferation rates. Taking components of the mitotic spindle as an example, we experimentally verified our predictions that p53-mediated transcriptional repression of several of these novel targets is dependent on the activities of p21, NFY, and E2F. Our study demonstrates how a well-controlled transformation process allows linking between gene expression, promoter architecture, and activity of upstream signaling molecules.

Androgen receptor binding sites identified by a GREF_GATA model

Changes in transcriptional regulation can be permissive for tumor progression by allowing for selective growth advantage of tumor cells. Tumor suppressors can effectively inhibit this process. The PMEPA1 gene, a potent inhibitor of prostate cancer cell growth is an androgen-regulated gene. We addressed the question of whether or not androgen receptor can directly bind to specific PMEPA1 promoter upstream sequences. To test this hypothesis we extended in silico prediction of androgen receptor binding sites by a modeling approach and verified the actual binding by in vivo chromatin immunoprecipitation assay. Promoter upstream sequences of highly androgen-inducible genes were examined from microarray data of prostate cancer cells for transcription factor binding sites (TFBSs). Results were analyzed to formulate a model for the description of specific androgen receptor binding site context in these sequences. In silico analysis and subsequent experimental verification of the selected sequences suggested that a model that combined a GREF and a GATA TFBS was sufficient for predicting a class of functional androgen receptor binding sites. The GREF matrix family represents androgen receptor, glucocorticoid receptor and progesterone receptor binding sites and the GATA matrix family represents GATA binding protein 1-6 binding sites. We assessed the regulatory sequences of the PMEPA1 gene by comparing our model-based GREF_GATA predictions to weight matrix-based predictions. Androgen receptor binding to predicted promoter upstream sequences of the PMEPA1 gene was confirmed by chromatin immunoprecipitation assay. Our results suggested that androgen receptor binding to cognate elements was consistent with the GREF_GATA model. In contrast, using only single GREF weight matrices resulted in additional matches, apparently false positives. Our findings indicate that complex models based on datasets selected by biological function can be superior predictors as they recognize TFBSs in their functional context.

BEARR: Batch Extraction and Analysis of cis-Regulatory Regions

Transcription factors play important roles in regulating biological and disease processes. Microarray technology has enabled researchers to simultaneously monitor changes in the expression of thousands of transcripts. By identifying specific transcription factor binding sites in the cis-regulatory regions of differentially expressed genes, it is then possible to identify direct targets of transcription factors, model transcriptional regulatory networks and mine the dataset for relevant targets for experimental and clinical manipulation. We have developed web-based software to assist biologists in efficiently carrying out the analysis of microarray data from studies of specific transcription factors. Batch Extraction and Analysis of cis-Regulatory Regions, or BEARR, accepts gene identifier lists from microarray data analysis tools and facilitates identification, extraction and analysis of regulatory regions from the large amount of data that is typically generated in these types of studies. The software is publicly available at http://giscompute.gis.a-star.edu.sg/~vega/BEARR1.0/.

Nuclear factor-kappaB motif and interferon-alpha-stimulated response element co-operate in the activation of guanylate-binding protein-1 expression by inflammatory cytokines in endothelial cells

The large GTPase GBP-1 (guanylate-binding protein-1) is a major IFN-gamma (interferon-gamma)-induced protein with potent anti-angiogenic activity in endothelial cells. An ISRE (IFN-alpha-stimulated response element) is necessary and sufficient for the induction of GBP-1 expression by IFN-gamma. Recently, we have shown that in vivo GBP-1 expression is strongly endothelial-cell-associated and is, in addition to IFN-gamma, also activated by interleukin-1beta and tumour necrosis factor-alpha, both in vitro and in vivo [Lubeseder-Martellato, Guenzi, Jörg, Töpolt, Naschberger, Kremmer, Zietz, Tschachler, Hutzler, Schwemmle et al. (2002) Am. J. Pathol. 161, 1749-1759; Guenzi, Töpolt, Cornali, Lubeseder-Martellato, Jörg, Matzen, Zietz, Kremmer, Nappi, Schwemmle et al. (2001) EMBO J. 20, 5568-5577]. In the present study, we identified a NF-kappaB (nuclear factor kappaB)-binding motif that, together with ISRE, is required for the induction of GBP-1 expression by interleukin-1beta and tumour necrosis factor-alpha. Deactivation of the NF-kappaB motif reduced the additive effects of combinations of these cytokines with IFN-gamma by more than 50%. Importantly, NF-kappaB p50 rather than p65 activated the GBP-1 promoter. The NF-kappaB motif and ISRE were detected in an almost identical spatial organization, as in the GBP-1 promoter, in the promoter regions of various inflammation-associated genes. Therefore both motifs may constitute a cooperative inflammatory cytokine response module that regulates GBP-1 expression. Our findings may open new perspectives for the use of NF-kappaB inhibitors to support angiogenesis in inflammatory diseases including ischaemia.

Computer modeling of promoter organization as a tool to study transcriptional coregulation

Understanding how the regulation of gene networks is orchestrated is an important challenge for characterizing complex biological processes. Gene transcription is regulated in part by nuclear factors that recognize short DNA sequence motifs, called transcription factor binding sites, in most cases located upstream of the gene coding sequence in promoter and enhancer regions. Genes expressed in the same tissue under similar conditions often share a common organization of at least some of these regulatory binding elements. In this way the organization of promoter motifs represents a "footprint" of the transcriptional regulatory mechanisms at work in a specific biologic context and thus provides information about signal and tissue specific control of expression. Analysis of promoters for organizational features as demonstrated here provides a crucial link between the static nucleotide sequence of the genome and the dynamic aspects of gene regulation and expression.

Chromatin as a tool for the study of genome function in cancer

The transition to malignancy requires an extensive reconfiguration of the genome's expression program that does not result entirely from actual changes in primary DNA sequence-i.e., mutation. Epigenetic-meta-DNA-gene expression states result from an assembly over a given locus of a poorly understood nucleoprotein entity that includes histones and other architectural components of chromatin, nonhistone DNA-bound regulators, and additional chromatin-bound polypeptides. This structure is rapidly reestablished in the wake of the DNA replication fork, thus ensuring its persistence in rapidly proliferating cells and thereby yielding an exceptionally stable mode of gene expression. Chromatin is the perfect vehicle for enabling such genome control. During S phase both covalently modified histones and histone-associated regulatory proteins distribute to the newly synthesized daughter chromatids in a form of "molecular dowry" inherited from the G(1) state of the genome, and impose a specific mode of function on the underlying DNA. An extensively studied example of chromatin-based epigenetic inheritance connects DNA methylation to the targeting of chromatin remodeling and modification. In a broad sense, however, genome reprogramming in cancer is associated with the remodeling of a multitude of regulatory DNA stretches-e.g., promoters, enhancers, locus control regions (LCRs), insulators, etc.-into a specific chromatin architecture. This architectural entity provides a general molecular signature of the cancer epigenome that complements and significantly expands its DNA methylation-based component.

Chromatin remodeling as a guide to transcriptional regulatory networks in mammals

An important challenge of genome biology is a dissection of transcriptional regulatory networks that operate inside the nucleus during ontogeny and disease (Wyrick and Young [2002] Curr. Opin. Genet. Dev. 12:130). Limitations of existing experimental tools greatly complicate such analysis in the human genome: for example, genome-wide expression profiling of cells responding to a stimulus fails to reveal a majority of the genes involved in the functional network of responding to that stimulus [Giaver et al., 2002; Birrell et al., 2002]. This article discusses recent advances in analyzing mammalian transcriptional regulatory circuits [Nikiforov et al., 2002; Weinmann et al., 2002; Ren et al., 2000]. As evidenced by these and other data, paucity of information about the location of regulatory DNA elements in the human genome presents an obstacle to comprehensive transcription network analysis. It has been known since the late 1970s that chromatin over active regulatory DNA stretches is stably remodeled into "nuclease hypersensitive sites" [Elgin, 1988; Gross and Garrard 1988]. Massively parallel analysis of such remodeling in cell nuclei identifies regulatory DNA that is difficult to map comprehensively using other approaches, reveals genes poised for rapid activation, and offers a novel perspective on the "epigenome"--the regulatory program being executed by the genome in a given cell type.

EZ-Retrieve: a web-server for batch retrieval of coordinate-specified human DNA sequences and underscoring putative transcription factor-binding sites

The availability of a draft human genome sequence and ability to monitor the transcription of thousands of genes with DNA microarrays has necessitated the need for new computational tools that can analyze cis-regulatory elements controlling genes that display similar expression patterns. We have developed a tool designated EZ-Retrieve that can: (i) retrieve any particular region of human genome sequence from the NCBI database and (ii) analyze retrieved sequences for putative transcription factor-binding sites (TFBSs) as they appear on the TRANSFAC database. The tool is web-based, user-friendly and offers both batch sequence retrieval and batch TFBS prediction. A major application of EZ-Retrieve is the analysis of co-expressed genes that are highlighted as expression clusters in DNA microarray experiments.