Current Advances of Nitric Oxide in Cancer and Anticancer Therapeutics.

Nitric oxide (NO) is a short-lived, ubiquitous signaling molecule that affects numerous critical functions in the body. There are markedly conflicting findings in the literature regarding the bimodal effects of NO in carcinogenesis and tumor progression, which has important consequences for treatment. Several preclinical and clinical studies have suggested that both pro- and antitumorigenic effects of NO depend on multiple aspects, including, but not limited to, tissue of generation, the level of production, the oxidative/reductive (redox) environment in which this radical is generated, the presence or absence of NO transduction elements, and the tumor microenvironment. Generally, there are four major categories of NO-based anticancer therapies: NO donors, phosphodiesterase inhibitors (PDE-i), soluble guanylyl cyclase (sGC) activators, and immunomodulators. Of these, NO donors are well studied, well characterized, and also the most promising. In this study, we review the current knowledge in this area, with an emphasis placed on the role of NO as an anticancer therapy and dysregulated molecular interactions during the evolution of cancer, highlighting the strategies that may aid in the targeting of cancer.

Tumor Microenvironment and Nitric Oxide: Concepts and Mechanisms.

The cancer tissue exists not as a single entity, but as a combination of different cellular phenotypes which, taken together, dramatically contribute to the entirety of their ecosystem, collectively termed as the tumor microenvironment (TME). The TME is composed of both immune and nonimmune cell types, stromal components, and vasculature-all of which cooperate to promote cancer progression. Not all immune cells, however, are immune-suppressive; some of them can promote the immune microenvironment to fight the invading and uncontrollably dividing cell populations at the initial stages of tumor growth. Yet, many of these processes and cellular phenotypes fall short, and the immune ecosystem more often than not ends up stabilizing in favor of the "resistant" resident cells that begin clonal expansion and may progress to metastatic forms. Stromal components, making up the extracellular matrix and basement membrane, are also not the most innocuous: CAFs embedded throughout secrete proteases that allow the onset of one of the most invasive processes-angiogenesis-through destruction of the ECM and the basement membrane. Vasculature formation, because of angiogenesis, is the largest invader of the TME and the reason metastasis happens. Vasculature is so sporadic and omnipresent in the TME that most drug therapies are mainly focused on stopping this uncontrollable process. As the tumor continues to grow, different processes are constantly supplying it with the ingredients favorable for tumor progression and eventual metastasis. For example, angiogenesis promotes blood vessel formation that will allow the bona fide escape of tumor cells to take place. Another process like hypoxia will present itself in several forms throughout the tumor (mild or acute, cycling or permanent), starting mechanisms such as epithelial to mesenchymal transitions (EMT) of resident cells and inadvertently placing the cells in such a stressful condition that production of ROS and DNA damage is unavoidable. DNA damage can induce mutagenicity while allowing resistant cells to survive. This is where drugs and treatments can subsequently suffer in effectiveness. Finally, another molecule has just surfaced as being a very important player in the TME: nitric oxide. Often overlooked and equated with ROS and initially assigned in the category of pathogenic molecules, nitric oxide can definitely do some damage by causing metabolic reprogramming and promotion of immunosuppressive phenotypes at low concentrations. However, its actions seem to be extremely dose-dependent, and this issue has become a hot target of current treatment goals. Shockingly, nitric oxide, although omnipresent in the TME, can have a positive effect on targeting the TME broadly. Thus, while the TME is a myriad of cellular phenotypes and a combination of different tumor-promoting processes, each process is interconnected into one whole: the tumor microenvironment.

A Comprehensive Drosophila melanogaster Transcription Factor Interactome.

Combinatorial interactions among transcription factors (TFs) play essential roles in generating gene expression specificity and diversity in metazoans. Using yeast 2-hybrid (Y2H) assays on nearly all sequence-specific Drosophila TFs, we identified 1,983 protein-protein interactions (PPIs), more than doubling the number of currently known PPIs among Drosophila TFs. For quality assessment, we validated a subset of our interactions using MITOMI and bimolecular fluorescence complementation assays. We combined our interactome with prior PPI data to generate an integrated Drosophila TF-TF binary interaction network. Our analysis of ChIP-seq data, integrating PPI and gene expression information, uncovered different modes by which interacting TFs are recruited to DNA. We further demonstrate the utility of our Drosophila interactome in shedding light on human TF-TF interactions. This study reveals how TFs interact to bind regulatory elements in vivo and serves as a resource of Drosophila TF-TF binary PPIs for understanding tissue-specific gene regulation.

Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds.

Transcription factors (TFs) control cellular processes by binding specific DNA motifs to modulate gene expression. Motif enrichment analysis of regulatory regions can identify direct and indirect TF binding sites. Here, we created a glossary of 108 non-redundant TF-8mer "modules" of shared specificity for 671 metazoan TFs from publicly available and new universal protein binding microarray data. Analysis of 239 ENCODE TF chromatin immunoprecipitation sequencing datasets and associated RNA sequencing profiles suggest the 8mer modules are more precise than position weight matrices in identifying indirect binding motifs and their associated tethering TFs. We also developed GENRE (genomically equivalent negative regions), a tunable tool for construction of matched genomic background sequences for analysis of regulatory regions. GENRE outperformed four state-of-the-art approaches to background sequence construction. We used our TF-8mer glossary and GENRE in the analysis of the indirect binding motifs for the co-occurrence of tethering factors, suggesting novel TF-TF interactions. We anticipate that these tools will aid in elucidating tissue-specific gene-regulatory programs.

Survey of variation in human transcription factors reveals prevalent DNA binding changes.

Sequencing of exomes and genomes has revealed abundant genetic variation affecting the coding sequences of human transcription factors (TFs), but the consequences of such variation remain largely unexplored. We developed a computational, structure-based approach to evaluate TF variants for their impact on DNA binding activity and used universal protein-binding microarrays to assay sequence-specific DNA binding activity across 41 reference and 117 variant alleles found in individuals of diverse ancestries and families with Mendelian diseases. We found 77 variants in 28 genes that affect DNA binding affinity or specificity and identified thousands of rare alleles likely to alter the DNA binding activity of human sequence-specific TFs. Our results suggest that most individuals have unique repertoires of TF DNA binding activities, which may contribute to phenotypic variation.

A direct fate exclusion mechanism by Sonic hedgehog-regulated transcriptional repressors.

Sonic hedgehog (Shh) signaling patterns the vertebrate spinal cord by activating a group of transcriptional repressors in distinct neural progenitors of somatic motor neuron and interneuron subtypes. To identify the action of this network, we performed a genome-wide analysis of the regulatory actions of three key ventral determinants in mammalian neural tube patterning: Nkx2.2, Nkx6.1 and Olig2. Previous studies have demonstrated that each factor acts predominantly as a transcriptional repressor, at least in part, to inhibit alternative progenitor fate choices. Here, we reveal broad and direct repression of multiple alternative fates as a general mechanism of repressor action. Additionally, the repressor network targets multiple Shh signaling components providing negative feedback to ongoing Shh signaling. Analysis of chromatin organization around Nkx2.2-, Nkx6.1- and Olig2-bound regions, together with co-analysis of engagement of the transcriptional activator Sox2, indicate that repressors bind to, and probably modulate the action of, neural enhancers. Together, the data suggest a model for neural progenitor specification downstream of Shh signaling, in which Nkx2.2 and Olig2 direct repression of alternative neural progenitor fate determinants, an action augmented by the overlapping activity of Nkx6.1 in each cell type. Integration of repressor and activator inputs, notably activator inputs mediated by Sox2, is probably a key mechanism in achieving cell type-specific transcriptional outcomes in mammalian neural progenitor fate specification.

Modular evolution of DNA-binding preference of a Tbrain transcription factor provides a mechanism for modifying gene regulatory networks.

Gene regulatory networks (GRNs) describe the progression of transcriptional states that take a single-celled zygote to a multicellular organism. It is well documented that GRNs can evolve extensively through mutations to cis-regulatory modules (CRMs). Transcription factor proteins that bind these CRMs may also evolve to produce novelty. Coding changes are considered to be rarer, however, because transcription factors are multifunctional and hence are more constrained to evolve in ways that will not produce widespread detrimental effects. Recent technological advances have unearthed a surprising variation in DNA-binding abilities, such that individual transcription factors may recognize both a preferred primary motif and an additional secondary motif. This provides a source of modularity in function. Here, we demonstrate that orthologous transcription factors can also evolve a changed preference for a secondary binding motif, thereby offering an unexplored mechanism for GRN evolution. Using protein-binding microarray, surface plasmon resonance, and in vivo reporter assays, we demonstrate an important difference in DNA-binding preference between Tbrain protein orthologs in two species of echinoderms, the sea star, Patiria miniata, and the sea urchin, Strongylocentrotus purpuratus. Although both orthologs recognize the same primary motif, only the sea star Tbr also has a secondary binding motif. Our in vivo assays demonstrate that this difference may allow for greater evolutionary change in timing of regulatory control. This uncovers a layer of transcription factor binding divergence that could exist for many pairs of orthologs. We hypothesize that this divergence provides modularity that allows orthologous transcription factors to evolve novel roles in GRNs through modification of binding to secondary sites.

The CLAMP protein links the MSL complex to the X chromosome during Drosophila dosage compensation.

The Drosophila male-specific lethal (MSL) dosage compensation complex increases transcript levels on the single male X chromosome to equal the transcript levels in XX females. However, it is not known how the MSL complex is linked to its DNA recognition elements, the critical first step in dosage compensation. Here, we demonstrate that a previously uncharacterized zinc finger protein, CLAMP (chromatin-linked adaptor for MSL proteins), functions as the first link between the MSL complex and the X chromosome. CLAMP directly binds to the MSL complex DNA recognition elements and is required for the recruitment of the MSL complex. The discovery of CLAMP identifies a key factor required for the chromosome-specific targeting of dosage compensation, providing new insights into how subnuclear domains of coordinate gene regulation are formed within metazoan genomes.

Highly parallel assays of tissue-specific enhancers in whole Drosophila embryos.

Transcriptional enhancers are a primary mechanism by which tissue-specific gene expression is achieved. Despite the importance of these regulatory elements in development, responses to environmental stresses and disease, testing enhancer activity in animals remains tedious, with a minority of enhancers having been characterized. Here we describe 'enhancer-FACS-seq' (eFS) for highly parallel identification of active, tissue-specific enhancers in Drosophila melanogaster embryos. Analysis of enhancers identified by eFS as being active in mesodermal tissues revealed enriched DNA binding site motifs of known and putative, previously uncharacterized mesodermal transcription factors. Naive Bayes classifiers using transcription factor binding site motifs accurately predicted mesodermal enhancer activity. Application of eFS to other cell types and organisms should accelerate the cataloging of enhancers and understanding how transcriptional regulation is encoded in them.

Evaluation of methods for modeling transcription factor sequence specificity.

Genomic analyses often involve scanning for potential transcription factor (TF) binding sites using models of the sequence specificity of DNA binding proteins. Many approaches have been developed to model and learn a protein's DNA-binding specificity, but these methods have not been systematically compared. Here we applied 26 such approaches to in vitro protein binding microarray data for 66 mouse TFs belonging to various families. For nine TFs, we also scored the resulting motif models on in vivo data, and found that the best in vitro-derived motifs performed similarly to motifs derived from the in vivo data. Our results indicate that simple models based on mononucleotide position weight matrices trained by the best methods perform similarly to more complex models for most TFs examined, but fall short in specific cases (<10% of the TFs examined here). In addition, the best-performing motifs typically have relatively low information content, consistent with widespread degeneracy in eukaryotic TF sequence preferences.

Neural-specific Sox2 input and differential Gli-binding affinity provide context and positional information in Shh-directed neural patterning.

In the vertebrate neural tube, regional Sonic hedgehog (Shh) signaling invokes a time- and concentration-dependent induction of six different cell populations mediated through Gli transcriptional regulators. Elsewhere in the embryo, Shh/Gli responses invoke different tissue-appropriate regulatory programs. A genome-scale analysis of DNA binding by Gli1 and Sox2, a pan-neural determinant, identified a set of shared regulatory regions associated with key factors central to cell fate determination and neural tube patterning. Functional analysis in transgenic mice validates core enhancers for each of these factors and demonstrates the dual requirement for Gli1 and Sox2 inputs for neural enhancer activity. Furthermore, through an unbiased determination of Gli-binding site preferences and analysis of binding site variants in the developing mammalian CNS, we demonstrate that differential Gli-binding affinity underlies threshold-level activator responses to Shh input. In summary, our results highlight Sox2 input as a context-specific determinant of the neural-specific Shh response and differential Gli-binding site affinity as an important cis-regulatory property critical for interpreting Shh morphogen action in the mammalian neural tube.

Curated collection of yeast transcription factor DNA binding specificity data reveals novel structural and gene regulatory insights.

BACKGROUND: Transcription factors (TFs) play a central role in regulating gene expression by interacting with cis-regulatory DNA elements associated with their target genes. Recent surveys have examined the DNA binding specificities of most Saccharomyces cerevisiae TFs, but a comprehensive evaluation of their data has been lacking. RESULTS: We analyzed in vitro and in vivo TF-DNA binding data reported in previous large-scale studies to generate a comprehensive, curated resource of DNA binding specificity data for all characterized S. cerevisiae TFs. Our collection comprises DNA binding site motifs and comprehensive in vitro DNA binding specificity data for all possible 8-bp sequences. Investigation of the DNA binding specificities within the basic leucine zipper (bZIP) and VHT1 regulator (VHR) TF families revealed unexpected plasticity in TF-DNA recognition: intriguingly, the VHR TFs, newly characterized by protein binding microarrays in this study, recognize bZIP-like DNA motifs, while the bZIP TF Hac1 recognizes a motif highly similar to the canonical E-box motif of basic helix-loop-helix (bHLH) TFs. We identified several TFs with distinct primary and secondary motifs, which might be associated with different regulatory functions. Finally, integrated analysis of in vivo TF binding data with protein binding microarray data lends further support for indirect DNA binding in vivo by sequence-specific TFs. CONCLUSIONS: The comprehensive data in this curated collection allow for more accurate analyses of regulatory TF-DNA interactions, in-depth structural studies of TF-DNA specificity determinants, and future experimental investigations of the TFs' predicted target genes and regulatory roles.

Using a structural and logics systems approach to infer bHLH-DNA binding specificity determinants.

Numerous efforts are underway to determine gene regulatory networks that describe physical relationships between transcription factors (TFs) and their target DNA sequences. Members of paralogous TF families typically recognize similar DNA sequences. Knowledge of the molecular determinants of protein-DNA recognition by paralogous TFs is of central importance for understanding how small differences in DNA specificities can dictate target gene selection. Previously, we determined the in vitro DNA binding specificities of 19 Caenorhabditis elegans basic helix-loop-helix (bHLH) dimers using protein binding microarrays. These TFs bind E-box (CANNTG) and E-box-like sequences. Here, we combine these data with logics, bHLH-DNA co-crystal structures and computational modeling to infer which bHLH monomer can interact with which CAN E-box half-site and we identify a critical residue in the protein that dictates this specificity. Validation experiments using mutant bHLH proteins provide support for our inferences. Our study provides insights into the mechanisms of DNA recognition by bHLH dimers as well as a blueprint for system-level studies of the DNA binding determinants of other TF families in different model organisms and humans.

Notch and MAML-1 complexation do not detectably alter the DNA binding specificity of the transcription factor CSL.

BACKGROUND: Canonical Notch signaling is initiated when ligand binding induces proteolytic release of the intracellular part of Notch (ICN) from the cell membrane. ICN then travels into the nucleus where it drives the assembly of a transcriptional activation complex containing the DNA-binding transcription factor CSL, ICN, and a specialized co-activator of the Mastermind family. A consensus DNA binding site motif for the CSL protein was previously defined using selection-based methods, but whether subsequent association of Notch and Mastermind-like proteins affects the DNA binding preferences of CSL has not previously been examined. PRINCIPAL FINDINGS: Here, we utilized protein-binding microarrays (PBMs) to compare the binding site preferences of isolated CSL with the preferred binding sites of CSL when bound to the CSL-binding domains of all four different human Notch receptors. Measurements were taken both in the absence and in the presence of Mastermind-like-1 (MAML1). Our data show no detectable difference in the DNA binding site preferences of CSL before and after loading of Notch and MAML1 proteins. CONCLUSIONS/SIGNIFICANCE: These findings support the conclusion that accrual of Notch and MAML1 promote transcriptional activation without dramatically altering the preferred sites of DNA binding, and illustrate the potential of PBMs to analyze the binding site preferences of multiprotein-DNA complexes.

Diversity and complexity in DNA recognition by transcription factors.

Sequence preferences of DNA binding proteins are a primary mechanism by which cells interpret the genome. Despite the central importance of these proteins in physiology, development, and evolution, comprehensive DNA binding specificities have been determined experimentally for only a few proteins. Here, we used microarrays containing all 10-base pair sequences to examine the binding specificities of 104 distinct mouse DNA binding proteins representing 22 structural classes. Our results reveal a complex landscape of binding, with virtually every protein analyzed possessing unique preferences. Roughly half of the proteins each recognized multiple distinctly different sequence motifs, challenging our molecular understanding of how proteins interact with their DNA binding sites. This complexity in DNA recognition may be important in gene regulation and in the evolution of transcriptional regulatory networks.