Predicted Role of NAD Utilization in the Control of Circadian Rhythms during DNA Damage Response.

The circadian clock is a set of regulatory steps that oscillate with a period of approximately 24 hours influencing many biological processes. These oscillations are robust to external stresses, and in the case of genotoxic stress (i.e. DNA damage), the circadian clock responds through phase shifting with primarily phase advancements. The effect of DNA damage on the circadian clock and the mechanism through which this effect operates remains to be thoroughly investigated. Here we build an in silico model to examine damage-induced circadian phase shifts by investigating a possible mechanism linking circadian rhythms to metabolism. The proposed model involves two DNA damage response proteins, SIRT1 and PARP1, that are each consumers of nicotinamide adenine dinucleotide (NAD), a metabolite involved in oxidation-reduction reactions and in ATP synthesis. This model builds on two key findings: 1) that SIRT1 (a protein deacetylase) is involved in both the positive (i.e. transcriptional activation) and negative (i.e. transcriptional repression) arms of the circadian regulation and 2) that PARP1 is a major consumer of NAD during the DNA damage response. In our simulations, we observe that increased PARP1 activity may be able to trigger SIRT1-induced circadian phase advancements by decreasing SIRT1 activity through competition for NAD supplies. We show how this competitive inhibition may operate through protein acetylation in conjunction with phosphorylation, consistent with reported observations. These findings suggest a possible mechanism through which multiple perturbations, each dominant during different points of the circadian cycle, may result in the phase advancement of the circadian clock seen during DNA damage.

Using drug response data to identify molecular effectors, and molecular "omic" data to identify candidate drugs in cancer.

The current convergence of molecular and pharmacological data provides unprecedented opportunities to gain insights into the relationships between the two types of data. Multiple forms of large-scale molecular data, including but not limited to gene and microRNA transcript expression, DNA somatic and germline variations from next-generation DNA and RNA sequencing, and DNA copy number from array comparative genomic hybridization are all potentially informative when one attempts to recognize the panoply of potentially influential events both for cancer progression and therapeutic outcome. Concurrently, there has also been a substantial expansion of the pharmacological data being accrued in a systematic fashion. For cancer cell lines, the National Cancer Institute cell line panel (NCI-60), the Cancer Cell Line Encyclopedia (CCLE), and the collaborative Genomics of Drug Sensitivity in Cancer (GDSC) databases all provide subsets of these forms of data. For the patient-derived data, The Cancer Genome Atlas (TCGA) provides analogous forms of genomic information along with treatment histories. Integration of these data in turn relies on the fields of statistics and statistical learning. Multiple algorithmic approaches may be chosen, depending on the data being considered, and the nature of the question being asked. Combining these algorithms with prior biological knowledge, the results of molecular biological studies, and the consideration of genes as pathways or functional groups provides both the challenge and the potential of the field. The ultimate goal is to provide a paradigm shift in the way that drugs are selected to provide a more targeted and efficacious outcome for the patient.

Heat shock protein 90α (HSP90α), a substrate and chaperone of DNA-PK necessary for the apoptotic response.

The "apoptotic ring" is characterized by the phosphorylation of histone H2AX at serine 139 (γ-H2AX) by DNA-dependent protein kinase (DNA-PK). The γ-H2AX apoptotic ring differs from the nuclear foci patterns observed in response to DNA-damaging agents. It contains phosphorylated DNA damage response proteins including activated Chk2, activated ATM, and activated DNA-PK itself but lacks MDC1 and 53BP1, which are required to initiate DNA repair. Because DNA-PK can phosphorylate heat shock protein 90α (HSP90α) in biochemical assays, we investigated whether HSP90α is involved in the apoptotic ring. Here we show that HSP90α is phosphorylated by DNA-PK on threonines 5 and 7 early during apoptosis and that both phosphorylated HSP90α and DNA-PK colocalize in the apoptotic ring. We also show that DNA-PK is a client of HSP90α and that HSP90α is required for full DNA-PK activation, γ-H2AX formation, DNA fragmentation, and apoptotic body formation. In contrast, HSP90 inhibition by geldanamycin markedly enhances TRAIL-induced DNA-PK and H2AX activation. Together, our results reveal that HSP90α is a substrate and chaperone of DNA-PK in the apoptotic response. The response of phosphorylated HSP90α to TRAIL and its localization to the γ-H2AX ring represent epigenetic features of apoptosis that offer insights for studying and monitoring nuclear apoptosis.

PathVisio-Faceted Search: an exploration tool for multi-dimensional navigation of large pathways.

PURPOSE: The PathVisio-Faceted Search plugin helps users explore and understand complex pathways by overlaying experimental data and data from webservices, such as Ensembl BioMart, onto diagrams drawn using formalized notations in PathVisio. The plugin then provides a filtering mechanism, known as a faceted search, to find and highlight diagram nodes (e.g. genes and proteins) of interest based on imported data. The tool additionally provides a flexible scripting mechanism to handle complex queries. AVAILABILITY: The PathVisio-Faceted Search plugin is compatible with PathVisio 3.0 and above. PathVisio is compatible with Windows, Mac OS X and Linux. The plugin, documentation, example diagrams and Groovy scripts are available at http://PathVisio.org/wiki/PathVisioFacetedSearchHelp. The plugin is free, open-source and licensed by the Apache 2.0 License.

PathVisio-Validator: a rule-based validation plugin for graphical pathway notations.

PURPOSE: The PathVisio-Validator plugin aims to simplify the task of producing biological pathway diagrams that follow graphical standardized notations, such as Molecular Interaction Maps or the Systems Biology Graphical Notation. This plugin assists in the creation of pathway diagrams by ensuring correct usage of a notation, and thereby reducing ambiguity when diagrams are shared among biologists. Rulesets, needed in the validation process, can be generated for any graphical notation that a developer desires, using either Schematron or Groovy. The plugin also provides support for filtering validation results, validating on a subset of rules, and distinguishing errors and warnings.

PathVisio-MIM: PathVisio plugin for creating and editing Molecular Interaction Maps (MIMs).

MOTIVATION: A plugin for the Java-based PathVisio pathway editor has been developed to help users draw diagrams of bioregulatory networks according to the Molecular Interaction Map (MIM) notation. Together with the core PathVisio application, this plugin presents a simple to use and cross-platform application for the construction of complex MIM diagrams with the ability to annotate diagram elements with comments, literature references and links to external databases. This tool extends the capabilities of the PathVisio pathway editor by providing both MIM-specific glyphs and support for a MIM-specific markup language file format for exchange with other MIM-compatible tools and diagram validation. AVAILABILITY: The PathVisio-MIM plugin is freely available and works with versions of PathVisio 2.0.11 and later on Windows, Mac OS X and Linux. Information about MIM notation and the MIMML format is available at http://discover.nci.nih.gov/mim. The plugin, along with diagram examples, instructions and Java source code, may be downloaded at http://discover.nci.nih.gov/mim/mim_pathvisio.html.

A formal MIM specification and tools for the common exchange of MIM diagrams: an XML-Based format, an API, and a validation method.

BACKGROUND: The Molecular Interaction Map (MIM) notation offers a standard set of symbols and rules on their usage for the depiction of cellular signaling network diagrams. Such diagrams are essential for disseminating biological information in a concise manner. A lack of software tools for the notation restricts wider usage of the notation. Development of software is facilitated by a more detailed specification regarding software requirements than has previously existed for the MIM notation. RESULTS: A formal implementation of the MIM notation was developed based on a core set of previously defined glyphs. This implementation provides a detailed specification of the properties of the elements of the MIM notation. Building upon this specification, a machine-readable format is provided as a standardized mechanism for the storage and exchange of MIM diagrams. This new format is accompanied by a Java-based application programming interface to help software developers to integrate MIM support into software projects. A validation mechanism is also provided to determine whether MIM datasets are in accordance with syntax rules provided by the new specification. CONCLUSIONS: The work presented here provides key foundational components to promote software development for the MIM notation. These components will speed up the development of interoperable tools supporting the MIM notation and will aid in the translation of data stored in MIM diagrams to other standardized formats. Several projects utilizing this implementation of the notation are outlined herein. The MIM specification is available as an additional file to this publication. Source code, libraries, documentation, and examples are available at http://discover.nci.nih.gov/mim.

Predicted functions of MdmX in fine-tuning the response of p53 to DNA damage.

Tumor suppressor protein p53 is regulated by two structurally homologous proteins, Mdm2 and MdmX. In contrast to Mdm2, MdmX lacks ubiquitin ligase activity. Although the essential interactions of MdmX are known, it is not clear how they function to regulate p53. The regulation of tumor suppressor p53 by Mdm2 and MdmX in response to DNA damage was investigated by mathematical modeling of a simplified network. The simplified network model was derived from a detailed molecular interaction map (MIM) that exhibited four coherent DNA damage response pathways. The results suggest that MdmX may amplify or stabilize DNA damage-induced p53 responses via non-enzymatic interactions. Transient effects of MdmX are mediated by reservoirs of p53ratioMdmX and Mdm2ratioMdmX heterodimers, with MdmX buffering the concentrations of p53 and/or Mdm2. A survey of kinetic parameter space disclosed regions of switch-like behavior stemming from such reservoir-based transients. During an early response to DNA damage, MdmX positively or negatively regulated p53 activity, depending on the level of Mdm2; this led to amplification of p53 activity and switch-like response. During a late response to DNA damage, MdmX could dampen oscillations of p53 activity. A possible role of MdmX may be to dampen such oscillations that otherwise could produce erratic cell behavior. Our study suggests how MdmX may participate in the response of p53 to DNA damage either by increasing dependency of p53 on Mdm2 or by dampening oscillations of p53 activity and presents a model for experimental investigation.

Ataxia telangiectasia mutated activation by transcription- and topoisomerase I-induced DNA double-strand breaks.

Ataxia telangiectasia mutated (ATM), the deficiency of which causes a severe neurodegenerative disease, is a crucial mediator for the DNA damage response (DDR). As neurons have high rates of transcription that require topoisomerase I (TOP1), we investigated whether TOP1 cleavage complexes (TOP1cc)-which are potent transcription-blocking lesions-also produce transcription-dependent DNA double-strand breaks (DSBs) with ATM activation. We show the induction of DSBs and DDR activation in post-mitotic primary neurons and lymphocytes treated with camptothecin, with the induction of nuclear DDR foci containing activated ATM, gamma-H2AX (phosphorylated histone H2AX), activated CHK2 (checkpoint kinase 2), MDC1 (mediator of DNA damage checkpoint 1) and 53BP1 (p53 binding protein 1). The DSB-ATM-DDR pathway was suppressed by inhibiting transcription and gamma-H2AX signals were reduced by RNase H1 transfection, which removes transcription-mediated R-loops. Thus, we propose that Top1cc produce transcription arrests with R-loop formation and generate DSBs that activate ATM in post-mitotic cells.

SCLC-CellMiner: A Resource for Small Cell Lung Cancer Cell Line Genomics and Pharmacology Based on Genomic Signatures.

CellMiner-SCLC (https://discover.nci.nih.gov/SclcCellMinerCDB/) integrates drug sensitivity and genomic data, including high-resolution methylome and transcriptome from 118 patient-derived small cell lung cancer (SCLC) cell lines, providing a resource for research into this "recalcitrant cancer." We demonstrate the reproducibility and stability of data from multiple sources and validate the SCLC consensus nomenclature on the basis of expression of master transcription factors NEUROD1, ASCL1, POU2F3, and YAP1. Our analyses reveal transcription networks linking SCLC subtypes with MYC and its paralogs and the NOTCH and HIPPO pathways. SCLC subsets express specific surface markers, providing potential opportunities for antibody-based targeted therapies. YAP1-driven SCLCs are notable for differential expression of the NOTCH pathway, epithelial-mesenchymal transition (EMT), and antigen-presenting machinery (APM) genes and sensitivity to mTOR and AKT inhibitors. These analyses provide insights into SCLC biology and a framework for future investigations into subtype-specific SCLC vulnerabilities.

Molecular interaction maps of bioregulatory networks: a general rubric for systems biology.

A standard for bioregulatory network diagrams is urgently needed in the same way that circuit diagrams are needed in electronics. Several graphical notations have been proposed, but none has become standard. We have prepared many detailed bioregulatory network diagrams using the molecular interaction map (MIM) notation, and we now feel confident that it is suitable as a standard. Here, we describe the MIM notation formally and discuss its merits relative to alternative proposals. We show by simple examples how to denote all of the molecular interactions commonly found in bioregulatory networks. There are two forms of MIM diagrams. "Heuristic" MIMs present the repertoire of interactions possible for molecules that are colocalized in time and place. "Explicit" MIMs define particular models (derived from heuristic MIMs) for computer simulation. We show also how pathways or processes can be highlighted on a canonical heuristic MIM. Drawing a MIM diagram, adhering to the rules of notation, imposes a logical discipline that sharpens one's understanding of the structure and function of a network.

4-nitroquinoline-1-oxide induces the formation of cellular topoisomerase I-DNA cleavage complexes.

RecQ helicase BLM-deficient cells are characteristically hypersensitive to 4-nitroquinoline-1-oxide (4NQO). We recently reported that isogenic BLM-deficient cells (PNSG13) are more sensitive than BLM-complemented cells (PNSF5) to camptothecin, which specifically traps topoisomerase I cleavage complexes (Top1cc). We now report that PNSG13 are also 3.5-fold more sensitive to 4NQO compared with PNSF5 and that 4NQO induces higher levels of Top1cc and reduced histone gamma-H2AX in PSNG13 than in PNSF5. Similarly, 4NQO induces more Top1cc in primary fibroblasts from a patient with Bloom syndrome than in normal human fibroblasts. 4NQO also induces Top1cc in colon cancer HCT116 and HT29 cells in a time- and concentration-dependent fashion. Of note, distinct from camptothecin, the Top1cc produced by 4NQO accumulate progressively after 4NQO addition and persist following 4NQO removal. The Top1cc induced by 4NQO are detectable by alkaline elution. To examine the functional relevance of the Top1cc induced by 4NQO, we used two stable topoisomerase I small interfering RNA (siRNA) cell lines derived from HCT116 and MCF7 cells. Both topoisomerase I siRNA cell lines are resistant to 4NQO, indicating that Top1cc contribute to the cellular activity of 4NQO. Collectively, these data show that 4NQO is an effective inducer of cellular Top1cc. Because 4NQO does not directly trap Top1cc in biochemical assays, we propose that active metabolites of 4NQO trap Top1cc by forming DNA adducts. Induction of Top1cc and histone gamma-H2AX by 4NQO may contribute to the cellular effects of 4NQO, including its selective activity toward RecQ helicase BLM-deficient cells.

Cancers as wounds that do not heal: differences and similarities between renal regeneration/repair and renal cell carcinoma.

Cancers have been described as wounds that do not heal, suggesting that the two share common features. By comparing microarray data from a model of renal regeneration and repair (RRR) with reported gene expression in renal cell carcinoma (RCC), we asked whether those two processes do, in fact, share molecular features and regulatory mechanisms. The majority (77%) of the genes expressed in RRR and RCC were concordantly regulated, whereas only 23% were discordant (i.e., changed in opposite directions). The orchestrated processes of regeneration, involving cell proliferation and immune response, were reflected in the concordant genes. The discordant gene signature revealed processes (e.g., morphogenesis and glycolysis) and pathways (e.g., hypoxia-inducible factor and insulin-like growth factor-I) that reflect the intrinsic pathologic nature of RCC. This is the first study that compares gene expression patterns in RCC and RRR. It does so, in particular, with relation to the hypothesis that RCC resembles the wound healing processes seen in RRR. However, careful attention to the genes that are regulated in the discordant direction provides new insights into the critical differences between renal carcinogenesis and wound healing. The observations reported here provide a conceptual framework for further efforts to understand the biology and to develop more effective diagnostic biomarkers and therapeutic strategies for renal tumors and renal ischemia.

CellMinerCDB for Integrative Cross-Database Genomics and Pharmacogenomics Analyses of Cancer Cell Lines.

CellMinerCDB provides a web-based resource (https://discover.nci.nih.gov/cellminercdb/) for integrating multiple forms of pharmacological and genomic analyses, and unifying the richest cancer cell line datasets (the NCI-60, NCI-SCLC, Sanger/MGH GDSC, and Broad CCLE/CTRP). CellMinerCDB enables data queries for genomics and gene regulatory network analyses, and exploration of pharmacogenomic determinants and drug signatures. It leverages overlaps of cell lines and drugs across databases to examine reproducibility and expand pathway analyses. We illustrate the value of CellMinerCDB for elucidating gene expression determinants, such as DNA methylation and copy number variations, and highlight complexities in assessing mutational burden. We demonstrate the value of CellMinerCDB in selecting drugs with reproducible activity, expand on the dominant role of SLFN11 for drug response, and present novel response determinants and genomic signatures for topoisomerase inhibitors and schweinfurthins. We also introduce LIX1L as a gene associated with mesenchymal signature and regulation of cellular migration and invasiveness.

Hereditary ataxia SCAN1 cells are defective for the repair of transcription-dependent topoisomerase I cleavage complexes.

Hereditary spinocerebellar ataxia with axonal neuropathy (SCAN1) is caused by an inactivating mutation (H493R) in the enzyme tyrosyl-DNA phosphodiesterase (Tdp1), which removes blocked 3'-termini at DNA strand breaks. Using SCAN1 cells treated with the specific topoisomerase I (Top1) inhibitor camptothecin, we find enhanced levels of Top1 cleavage complexes (Top1cc) and defective reversal of Top1cc in SCAN1 Tdp1-deficient cells, indicating a direct involvement of Tdp1 in the repair of Top1cc. Because the defective removal of Top1cc and the hypersensitivity of SCAN1 cells to camptothecin are not affected by aphidicolin, we propose that Tdp1 is involved in the repair of Top1cc associated with transcription damage in SCAN1 cells.

Depicting combinatorial complexity with the molecular interaction map notation.

To help us understand how bioregulatory networks operate, we need a standard notation for diagrams analogous to electronic circuit diagrams. Such diagrams must surmount the difficulties posed by complex patterns of protein modifications and multiprotein complexes. To meet that challenge, we have designed the molecular interaction map (MIM) notation (http://discover.nci.nih.gov/mim/). Here we show the advantages of the MIM notation for three important types of diagrams: (1) explicit diagrams that define specific pathway models for computer simulation; (2) heuristic maps that organize the available information about molecular interactions and encompass the possible processes or pathways; and (3) diagrams of combinatorially complex models. We focus on signaling from the epidermal growth factor receptor family (EGFR, ErbB), a network that reflects the major challenges of representing in a compact manner the combinatorial complexity of multimolecular complexes. By comparing MIMs with other diagrams of this network that have recently been published, we show the utility of the MIM notation. These comparisons may help cell and systems biologists adopt a graphical language that is unambiguous and generally understood.

Chk2 molecular interaction map and rationale for Chk2 inhibitors.

To organize the rapidly accumulating information on bioregulatory networks related to the histone gamma-H2AX-ATM-Chk2-p53-Mdm2 pathways in concise and unambiguous diagrams, we used the molecular interaction map notation (http://discover.nci.nih.gov/min). Molecular interaction maps are particularly useful for networks that include protein-protein binding and posttranslational modifications (e.g., phosphorylation). Both are important for nearly all of the proteins involved in DNA double-strand break signaling. Visualizing the regulatory circuits underlying cellular signaling may help identify key regulatory reactions and defects that can serve as targets for anticancer drugs.

HAUSP-regulated switch from auto- to p53 ubiquitination by Mdm2 (in silico discovery).

Stability of the 'guardian of the genome' tumor suppressor protein p53 is regulated predominantly through its ubiquitination. The ubiquitin-specific protease HAUSP plays an important role in this process. Recent experiments showed that p53 demonstrates a differential response to changes in HAUSP which nature and significance are not understood yet. Here a data-driven mathematical model of the Mdm2-mediated p53 ubiquitination network is presented which offers an explanation for the cause of such a response. The model predicts existence of the HAUSP-regulated switch from auto- to p53 ubiquitination by Mdm2. This switch suggests a potential role of HAUSP as a downstream target of stress signals in cells. The model accounts for a significant amount of experimental data, makes predictions for some rate constants, and can serve as a building block for the larger model describing a complex dynamic response of p53 to cellular stresses.

Properties of switch-like bioregulatory networks studied by simulation of the hypoxia response control system.

A complex bioregulatory network could be more easily comprehended if its essential function could be described by a small "core" subsystem, and if its response characteristics were switch-like. We tested this proposition by simulation studies of the hypoxia response control network. We hypothesized that a small subsystem governs the basics of the cellular response to hypoxia and that this response has a sharp oxygen-dependent transition. A molecular interaction map of the network was prepared, and an evolutionarily conserved core subsystem was extracted that could control the activity of hypoxia response promoter elements on the basis of oxygen concentration. The core subsystem included the hypoxia-inducible transcription factor (HIFalpha:ARNT heterodimer), proline hydroxylase, and the von Hippel-Lindau protein. Simulation studies showed that the same core subsystem can exhibit switch-like responses both to oxygen level and to HIFalpha synthesis rate, thus suggesting a mechanism for hypoxia response promoter element-dependent responses common to both hypoxia and growth factor signaling. The studies disclosed the mechanism responsible for the sharp transitions. We show how parameter sets giving switch-like behavior can be found and how this type of behavior provides a foundation for quantitative studies in cells.

A novel norindenoisoquinoline structure reveals a common interfacial inhibitor paradigm for ternary trapping of the topoisomerase I-DNA covalent complex.

We show that five topoisomerase I inhibitors (two indenoisoquinolines, two camptothecins, and one indolocarbazole) each intercalate between the base pairs flanking the cleavage site generated during the topoisomerase I catalytic cycle and are further stabilized by a network of hydrogen bonds with topoisomerase I. The interfacial inhibition paradigm described for topoisomerase I inhibitors can be generalized to a variety of natural products that trap macromolecular complexes as they undergo catalytic conformational changes that create hotspots for drug binding. Stabilization of such conformational states results in uncompetitive inhibition and exemplifies the relevance of screening for ligands and drugs that stabilize ("trap") these macromolecular complexes.