Genome-wide transcription factor binding site/promoter databases for the analysis of gene sets and co-occurrence of transcription factor binding motifs

<p>Abstract</p> <p>Background</p> <p>The use of global gene expression profiling is a well established approach to understand biological processes. One of the major goals of these investigations is to identify sets of genes with similar expression patterns. Such gene signatures may be very informative and reveal new aspects of particular biological processes. A logical and systematic next step is to reduce the identified gene signatures to the regulatory components that induce the relevant gene expression changes. A central issue in this context is to identify transcription factors, or transcription factor binding sites (TFBS), likely to be of importance for the expression of the gene signatures.</p> <p>Results</p> <p>We develop a strategy that efficiently produces TFBS/promoter databases based on user-defined criteria. The resulting databases constitute all genes in the Santa Cruz database and the positions for all TFBS provided by the user as position weight matrices. These databases are then used for two purposes, to identify significant TFBS in the promoters in sets of genes and to identify clusters of co-occurring TFBS. We use two criteria for significance, significantly enriched TFBS in terms of total number of binding sites for the promoters, and significantly present TFBS in terms of the fraction of promoters with binding sites. Significant TFBS are identified by a re-sampling procedure in which the query gene set is compared with typically 10⁵gene lists of similar size randomly drawn from the TFBS/promoter database. We apply this strategy to a large number of published ChIP-Chip data sets and show that the proposed approach faithfully reproduces ChIP-Chip results. The strategy also identifies relevant TFBS when analyzing gene signatures obtained from the MSigDB database. In addition, we show that several TFBS are highly correlated and that co-occurring TFBS define functionally related sets of genes.</p> <p>Conclusions</p> <p>The presented approach of promoter analysis faithfully reproduces the results from several ChIP-Chip and MigDB derived gene sets and hence may prove to be an important method in the analysis of gene signatures obtained through ChIP-Chip or global gene expression experiments. We show that TFBS are organized in clusters of co-occurring TFBS that together define highly coherent sets of genes.</p

Independent component analysis reveals new and biologically significant structures in micro array data

BACKGROUND: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem. BSS attempts to separate a mixture of signals into their different sources and refers to the problem of recovering signals from several observed linear mixtures. In the context of micro array data, "sources" may correspond to specific cellular responses or to co-regulated genes. RESULTS: We applied independent component analysis (ICA) to three different microarray data sets; two tumor data sets and one time series experiment. To obtain reliable components we used iterated ICA to estimate component centrotypes. We found that many of the low ranking components indeed may show a strong biological coherence and hence be of biological significance. Generally ICA achieved a higher resolution when compared with results based on correlated expression and a larger number of gene clusters with significantly enriched for gene ontology (GO) categories. In addition, components characteristic for molecular subtypes and for tumors with specific chromosomal translocations were identified. ICA also identified more than one gene clusters significant for the same GO categories and hence disclosed a higher level of biological heterogeneity, even within coherent groups of genes. CONCLUSION: Although the ICA approach primarily detects hidden variables, these surfaced as highly correlated genes in time series data and in one instance in the tumor data. This further strengthens the biological relevance of latent variables detected by ICA

Tiling resolution array CGH and high density expression profiling of urothelial carcinomas delineate genomic amplicons and candidate target genes specific for advanced tumors.

ABSTRACT: BACKGROUND: Urothelial carcinoma (UC) is characterized by nonrandom chromosomal aberrations, varying from one or a few changes in early-stage and low-grade tumors, to highly rearranged karyotypes in muscle-invasive lesions. Recent array-CGH analyses have shed further light on the genomic changes underlying the neoplastic development of UC, and have facilitated the molecular delineation amplified and deleted regions to the level of specific candidate genes. In the present investigation we combine detailed genomic information with expression information to identify putative target genes for genomic amplifications. METHODS: We analyzed 38 urothelial carcinomas by whole-genome tiling resolution array-CGH and high density expression profiling to identify putative target genes in common genomic amplifications. When necessary expression profiling was complemented with Q-PCR of individual genes. RESULTS: Three genomic segments were frequently and exclusively amplified in high grade tumors; 1q23, 6p22 and 8q22, respectively. Detailed mapping of the 1q23 segment showed a heterogeneous amplification pattern and no obvious commonly amplified region. The 6p22 amplicon was defined by a 1.8 Mb core region present in all amplifications, flanked both distally and proximally by segments amplified to a lesser extent. By combining genomic profiles with expression profiles we could show that amplification of E2F3, CDKAL1, SOX4, and MBOAT1 as well as NUP153, AOF1, FAM8A1 and DEK in 6p22 was associated with increased gene expression. Amplification of the 8q22 segment was primarily associated with YWHAZ (14-3-3-zeta) and POLR2K over expression. The possible importance of the YWHA genes in the development of urothelial carcinomas was supported by another recurrent amplicon paralogous to 8q22, in 2p25, where increased copy numbers lead to enhanced expression of YWHAQ (14-3-3-theta). Homozygous deletions were identified at 10 different genomic locations, most frequently affecting CDKN2A/CDKN2B in 9p21 (32%). Notably, the latter occurred mutually exclusive with 6p22 amplifications. CONCLUSION: The presented data indicates 6p22 as a composite amplicon with more than one possible target gene. The data also suggests that amplification of 6p22 and homozygous deletions of 9p21 may have complementary roles. Furthermore, the analysis of paralogous regions that showed genomic amplification indicated altered expression of YWHA (14-3-3) genes as important events in the development of UC

A Molecular Taxonomy for Urothelial Carcinoma.

PURPOSE: Even though urothelial cancer is the fourth most common tumor type among males, progress in treatment has been scarce. A problem in day-to-day clinical practice is that precise assessment of individual tumors is still fairly uncertain; consequently efforts have been undertaken to complement tumor evaluation with molecular biomarkers. An extension of this approach would be to base tumor classification primarily on molecular features. Here, we present a molecular taxonomy for urothelial carcinoma based on integrated genomics. EXPERIMENTAL DESIGN: We use gene expression profiles from 308 tumor cases to define five major urothelial carcinoma subtypes: urobasal A, genomically unstable, urobasal B, squamous cell carcinoma like, and an infiltrated class of tumors. Tumor subtypes were validated in three independent publically available data sets. The expression of 11 key genes was validated at the protein level by immunohistochemistry. RESULTS: The subtypes show distinct clinical outcomes and differ with respect to expression of cell-cycle genes, receptor tyrosine kinases particularly FGFR3, ERBB2, and EGFR, cytokeratins, and cell adhesion genes, as well as with respect to FGFR3, PIK3CA, and TP53 mutation frequency. The molecular subtypes cut across pathologic classification, and class-defining gene signatures show coordinated expression irrespective of pathologic stage and grade, suggesting the molecular phenotypes as intrinsic properties of the tumors. Available data indicate that susceptibility to specific drugs is more likely to be associated with the molecular stratification than with pathologic classification. CONCLUSIONS: We anticipate that the molecular taxonomy will be useful in future clinical investigations. Clin Cancer Res; 1-10. ©2012 AACR

The role of extracellular vesicle fusion with target cells in triggering systemic inflammation

Extracellular vesicles (EVs) play a crucial role in intercellular communication by transferring bioactive molecules from donor to recipient cells. As a result, EV fusion leads to the modulation of cellular functions and has an impact on both physiological and pathological processes in the recipient cell. This study explores the impact of EV fusion on cellular responses to inflammatory signaling. Our findings reveal that fusion renders non-responsive cells susceptible to inflammatory signaling, as evidenced by increased NF-κB activation and the release of inflammatory mediators. Syntaxin-binding protein 1 is essential for the merge and activation of intracellular signaling. Subsequent analysis show that EVs transfer their functionally active receptors to target cells, making them prone to an otherwise unresponsive state. EVs in complex with their agonist, require no further stimulation of the target cells to trigger mobilization of NF-κB. While receptor antagonists were unable to inhibit NF-κB activation, blocking of the fusion between EVs and their target cells with heparin mitigated inflammation in mice challenged with EVs.</p

The role of extracellular vesicle fusion with target cells in triggering systemic inflammation

Extracellular vesicles (EVs) play a crucial role in intercellular communication by transferring bioactive molecules from donor to recipient cells. As a result, EV fusion leads to the modulation of cellular functions and has an impact on both physiological and pathological processes in the recipient cell. This study explores the impact of EV fusion on cellular responses to inflammatory signaling. Our findings reveal that fusion renders non-responsive cells susceptible to inflammatory signaling, as evidenced by increased NF-κB activation and the release of inflammatory mediators. Syntaxin-binding protein 1 is essential for the merge and activation of intracellular signaling. Subsequent analysis show that EVs transfer their functionally active receptors to target cells, making them prone to an otherwise unresponsive state. EVs in complex with their agonist, require no further stimulation of the target cells to trigger mobilization of NF-κB. While receptor antagonists were unable to inhibit NF-κB activation, blocking of the fusion between EVs and their target cells with heparin mitigated inflammation in mice challenged with EVs.</p

Transcriptional profiling of breast cancer metastases identifies liver metastasis-selective genes associated with adverse outcome in luminal A primary breast cancer.

The complete molecular basis of the organ-specificity of metastasis is elusive. This study aimed to provide an independent characterization of the transcriptional landscape of breast cancer metastases with the specific objective to identify liver metastasis-selective genes of prognostic importance following primary tumor diagnosis

Analysis of promoter regions of co-expressed genes identified by microarray analysis

BACKGROUND: The use of global gene expression profiling to identify sets of genes with similar expression patterns is rapidly becoming a widespread approach for understanding biological processes. A logical and systematic approach to study co-expressed genes is to analyze their promoter sequences to identify transcription factors that may be involved in establishing specific profiles and that may be experimentally investigated. RESULTS: We introduce promoter clustering i.e. grouping of promoters with respect to their high scoring motif content, and show that this approach greatly enhances the identification of common and significant transcription factor binding sites (TFBS) in co-expressed genes. We apply this method to two different dataset, one consisting of micro array data from 108 leukemias (AMLs) and a second from a time series experiment, and show that biologically relevant promoter patterns may be obtained using phylogenetic foot-printing methodology. In addition, we also found that 15% of the analyzed promoter regions contained transcription factors start sites for additional genes transcribed in the opposite direction. CONCLUSION: Promoter clustering based on global promoter features greatly improve the identification of shared TFBS in co-expressed genes. We believe that the outlined approach may be a useful first step to identify transcription factors that contribute to specific features of gene expression profiles