Analysis of 13,023 genes in 11 breast and 11 colorectal cancers revealed that individual tumors accumulate an average of ˜90 mutant genes but that only a subset of these contribute to the neoplastic process. Using stringent criteria to delineate this subset, we identified 189 genes (average of 11 per tumor) that were mutated at significant frequency. The vast majority of these genes were not known to be genetically altered in tumors and are predicted to affect a wide range of cellular functions, including transcription, adhesion, and invasion. These data define the genetic landscape of two human cancer types, provide new targets for diagnostic and therapeutic intervention and monitoring.

/pdf/consensus-coding-sequences-of-human-breast-and-colorectal-15edxp2i8x.pdf

Consensus coding sequences of human breast and colorectal cancers

Transcription factors are adaptor molecules that detect regulatory sequences in the DNA and target the assembly of protein complexes that control gene expression. Yet much of the DNA in the eukaryotic cell is in nucleosomes and thereby occluded by histones, and can be further occluded by higher-order chromatin structures and repressor complexes. Indeed, genome-wide location analyses have revealed that, for all transcription factors tested, the vast majority of potential DNA-binding sites are unoccupied, demonstrating the inaccessibility of most of the nuclear DNA. This raises the question of how target sites at silent genes become bound de novo by transcription factors, thereby initiating regulatory events in chromatin. Binding cooperativity can be sufficient for many kinds of factors to simultaneously engage a target site in chromatin and activate gene expression. However, in cases in which the binding of a series of factors is sequential in time and thus not initially cooperative, special "pioneer transcription factors" can be the first to engage target sites in chromatin. Such initial binding can passively enhance transcription by reducing the number of additional factors that are needed to bind the DNA, culminating in activation. In addition, pioneer factor binding can actively open up the local chromatin and directly make it competent for other factors to bind. Passive and active roles for the pioneer factor FoxA occur in embryonic development, steroid hormone induction, and human cancers. Herein we review the field and describe how pioneer factors may enable cellular reprogramming.

/pdf/pioneer-transcription-factors-establishing-competence-for-2bchvboktu.pdf

Pioneer transcription factors: establishing competence for gene expression

The Long Noncoding RNAs NEAT1 and MALAT1 Bind Active Chromatin Sites

The androgen receptor (AR) plays a central role in establishing an oncogenic cascade that drives prostate cancer progression. Some prostate cancers escape androgen dependence and are often associated with an aggressive phenotype. The oestrogen receptor alpha (ERα) is expressed in prostate cancers, independent of AR status. However, the role of ERα remains elusive. Using a combination of chromatin immunoprecipitation (ChIP) and RNA-sequencing data, we identified an ERα-specific non-coding transcriptome signature. Among putatively ERα-regulated intergenic long non-coding RNAs (lncRNAs), we identified nuclear enriched abundant transcript 1 (NEAT1) as the most significantly overexpressed lncRNA in prostate cancer. Analysis of two large clinical cohorts also revealed that NEAT1 expression is associated with prostate cancer progression. Prostate cancer cells expressing high levels of NEAT1 were recalcitrant to androgen or AR antagonists. Finally, we provide evidence that NEAT1 drives oncogenic growth by altering the epigenetic landscape of target gene promoters to favour transcription.

/pdf/the-oestrogen-receptor-alpha-regulated-lncrna-neat1-is-a-270orlu8qc.pdf

The oestrogen receptor alpha-regulated lncRNA NEAT1 is a critical modulator of prostate cancer

In the year 2003 there was a 17% increase in the number of publications citing work performed using optical biosensor technology compared with the previous year. We collated the 962 total papers for 2003, identified the geographical regions where the work was performed, highlighted the instrument types on which it was carried out, and segregated the papers by biological system. In this overview, we spotlight 13 papers that should be on everyone's 'must read' list for 2003 and provide examples of how to identify and interpret high-quality biosensor data. Although we still find that the literature is replete with poorly performed experiments, over-interpreted results and a general lack of understanding of data analysis, we are optimistic that these shortcomings will be addressed as biosensor technology continues to mature.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmr.753

Survey of the year 2003 commercial optical biosensor literature

Estrogens and their receptors are important in human development, physiology and disease. In this study, we utilized an integrated genome-wide molecular and computational approach to characterize the interaction between the activated estrogen receptor (ER) and the regulatory elements of candidate target genes. Of around 19,000 genes surveyed in this study, we observed 137 ER-regulated genes in T-47D cells, of which only 89 were direct target genes. Meta-analysis of heterogeneous in vitro and in vivo datasets showed that the expression profiles in T-47D and MCF-7 cells are remarkably similar and overlap with genes differentially expressed between ER-positive and ER-negative tumors. Computational analysis revealed a significant enrichment of putative estrogen response elements (EREs) in the cis-regulatory regions of direct target genes. Chromatin immunoprecipitation confirmed ligand-dependent ER binding at the computationally predicted EREs in our highest ranked ER direct target genes, NRIP1, GREB1 and ABCA3. Wider examination of the cis-regulatory regions flanking the transcriptional start sites showed species conservation in mouse-human comparisons in only 6% of predicted EREs. Only a small core set of human genes, validated across experimental systems and closely associated with ER status in breast tumors, appear to be sufficient to induce ER effects in breast cancer cells. That cis-regulatory regions of these core ER target genes are poorly conserved suggests that different evolutionary mechanisms are operative at transcriptional control elements than at coding regions. These results predict that certain biological effects of estrogen signaling will differ between mouse and human to a larger extent than previously thought.

/pdf/discovery-of-estrogen-receptor-a-target-genes-and-response-2e3r2pj9nk.pdf

Discovery of estrogen receptor α target genes and response elements in breast tumor cells

Background: Transcription factor binding sites (TFBS) impart specificity to cellular transcriptional responses and have largely been defined by consensus motifs derived from a handful of validated sites. The low specificity of the computational predictions of TFBSs has been attributed to ubiquity of the motifs and the relaxed sequence requirements for binding. We posited that the inadequacy is due to limited input of empirically verified sites, and demonstrated a multiplatform approach to constructing a robust model. Results: Using the TFBS for the estrogen receptor (ER)α (estrogen response element [ERE]) as a model system, we extracted EREs from multiple molecular and genomic platforms whose binding to ERα has been experimentally confirmed or rejected. In silico analyses revealed significant sequence information flanking the standard binding consensus, discriminating ERE-like sequences that bind ERα from those that are nonbinders. We extended the ERE consensus by three bases, bearing a terminal G at the third position 3' and an initiator C at the third position 5', which were further validated using surface plasmon resonance spectroscopy. Our functional human ERE prediction algorithm (h-ERE) outperformed existing predictive algorithms and produced fewer than 5% false negatives upon experimental validation.

/pdf/multiplatform-genome-wide-identification-and-modeling-of-1cmat81mqj.pdf

Multiplatform genome-wide identification and modeling of functional human estrogen receptor binding sites.

The nuclear hormone receptors liver X receptor alpha (LXRalpha) (NR1H3) and LXRbeta (NR1H2) are established regulators of cholesterol, lipid, and glucose metabolism and are attractive drug targets for the treatment of diabetes and cardiovascular disease. Adrenal steroid hormones including glucocorticoids and mineralocorticoids are known to interfere with glucose metabolism, insulin signaling, and blood pressure regulation. Here we present genome-wide expression profiles of LXR-responsive genes in both the adrenal and the pituitary gland. LXR activation in cultured adrenal cells inhibited expression of multiple steroidogenic genes and consequently decreased adrenal steroid hormone production. In addition, LXR agonist treatment elevated ACTH mRNA expression and hormone secretion from pituitary cells both in vitro and in vivo. Reduced expression of the glucocortioid-activating enzyme 11beta-hydroxysteroid dehydrogenase 1 in pituitary cells upon LXR activation suggests blunting of the negative feedback of glucocorticoids by LXRs. In conclusion, LXRs independently interfere with the hypothalamic-pituitary-adrenal axis regulation at the level of the pituitary and the adrenal gland.

/pdf/liver-x-receptors-regulate-adrenal-steroidogenesis-and-27ju30kjul.pdf

Ai Li Yeo

Papers

Discovery of estrogen receptor α target genes and response elements in breast tumor cells

Multiplatform genome-wide identification and modeling of functional human estrogen receptor binding sites.

Liver X Receptors Regulate Adrenal Steroidogenesis and Hypothalamic-Pituitary-Adrenal Feedback