Parantu K. Shah

A cis-regulatory map of the Drosophila genome

Systematic annotation of gene regulatory elements is a major challenge in genome science. Direct mapping of chromatin modification marks and transcriptional factor binding sites genome-wide has successfully identified specific subtypes of regulatory elements. In Drosophila several pioneering studies have provided genome-wide identification of Polycomb response elements, chromatin states, transcription factor binding sites, RNA polymerase II regulation and insulator elements; however, comprehensive annotation of the regulatory genome remains a significant challenge. Here we describe results from the modENCODE cis-regulatory annotation project. We produced a map of the Drosophila melanogaster regulatory genome on the basis of more than 300 chromatin immunoprecipitation data sets for eight chromatin features, five histone deacetylases and thirty-eight site-specific transcription factors at different stages of development. Using these data we inferred more than 20,000 candidate regulatory elements and validated a subset of predictions for promoters, enhancers and insulators in vivo. We identified also nearly 2,000 genomic regions of dense transcription factor binding associated with chromatin activity and accessibility. We discovered hundreds of new transcription factor co-binding relationships and defined a transcription factor network with over 800 potential regulatory relationships.

A Comprehensive Map of Insulator Elements for the Drosophila Genome

Insulators are DNA sequences that control the interactions among genomic regulatory elements and act as chromatin boundaries. A thorough understanding of their location and function is necessary to address the complexities of metazoan gene regulation. We studied by ChIP–chip the genome-wide binding sites of 6 insulator-associated proteins—dCTCF, CP190, BEAF-32, Su(Hw), Mod(mdg4), and GAF—to obtain the first comprehensive map of insulator elements in Drosophila embryos. We identify over 14,000 putative insulators, including all classically defined insulators. We find two major classes of insulators defined by dCTCF/CP190/BEAF-32 and Su(Hw), respectively. Distributional analyses of insulators revealed that particular sub-classes of insulator elements are excluded between cis-regulatory elements and their target promoters; divide differentially expressed, alternative, and divergent promoters; act as chromatin boundaries; are associated with chromosomal breakpoints among species; and are embedded within active chromatin domains. Together, these results provide a map demarcating the boundaries of gene regulatory units and a framework for understanding insulator function during the development and evolution of Drosophila.

A Small Molecule Inhibitor of Ubiquitin-Specific Protease-7 Induces Apoptosis in Multiple Myeloma Cells and Overcomes Bortezomib Resistance

Bortezomib therapy has proven successful for the treatment of relapsed/refractory, relapsed, and newly diagnosed multiple myeloma (MM); however, dose-limiting toxicities and the development of resistance limit its long-term utility. Here, we show that P5091 is an inhibitor of deubiquitylating enzyme USP7, which induces apoptosis in MM cells resistant to conventional and bortezomib therapies. Biochemical and genetic studies show that blockade of HDM2 and p21 abrogates P5091-induced cytotoxicity. In animal tumor model studies, P5091 is well tolerated, inhibits tumor growth, and prolongs survival. Combining P5091 with lenalidomide, HDAC inhibitor SAHA, or dexamethasone triggers synergistic anti-MM activity. Our preclinical study therefore supports clinical evaluation of USP7 inhibitor, alone or in combination, as a potential MM therapy.

Information extraction from full text scientific articles: Where are the keywords?

BackgroundTo date, many of the methods for information extraction of biological information from scientific articles are restricted to the abstract of the article. However, full text articles in electronic version, which offer larger sources of data, are currently available. Several questions arise as to whether the effort of scanning full text articles is worthy, or whether the information that can be extracted from the different sections of an article can be relevant.ResultsIn this work we addressed those questions showing that the keyword content of the different sections of a standard scientific article (abstract, introduction, methods, results, and discussion) is very heterogeneous.ConclusionsAlthough the abstract contains the best ratio of keywords per total of words, other sections of the article may be a better source of biologically relevant data.

Genomic analysis of estrogen cascade reveals histone variant H2A.Z associated with breast cancer progression.

We demonstrate an integrated approach to the study of a transcriptional regulatory cascade involved in the progression of breast cancer and we identify a protein associated with disease progression. Using chromatin immunoprecipitation and genome tiling arrays, whole genome mapping of transcription factor‐binding sites was combined with gene expression profiling to identify genes involved in the proliferative response to estrogen (E2). Using RNA interference, selected ERα and c‐MYC gene targets were knocked down to identify mediators of E2‐stimulated cell proliferation. Tissue microarray screening revealed that high expression of an epigenetic factor, the E2‐inducible histone variant H2A.Z, is significantly associated with lymph node metastasis and decreased breast cancer survival. Detection of H2A.Z levels independently increased the prognostic power of biomarkers currently in clinical use. This integrated approach has accelerated the identification of a molecule linked to breast cancer progression, has implications for diagnostic and therapeutic interventions, and can be applied to a wide range of cancers.

PASBio: predicate-argument structures for event extraction in molecular biology.

BackgroundThe exploitation of information extraction (IE), a technology aiming to provide instances of structured representations from free-form text, has been rapidly growing within the molecular biology (MB) research community to keep track of the latest results reported in literature. IE systems have traditionally used shallow syntactic patterns for matching facts in sentences but such approaches appear inadequate to achieve high accuracy in MB event extraction due to complex sentence structure. A consensus in the IE community is emerging on the necessity for exploiting deeper knowledge structures such as through the relations between a verb and its arguments shown by predicate-argument structure (PAS). PAS is of interest as structures typically correspond to events of interest and their participating entities. For this to be realized within IE a key knowledge component is the definition of PAS frames. PAS frames for non-technical domains such as newswire are already being constructed in several projects such as PropBank, VerbNet, and FrameNet. Knowledge from PAS should enable more accurate applications in several areas where sentence understanding is required like machine translation and text summarization. In this article, we explore the need to adapt PAS for the MB domain and specify PAS frames to support IE, as well as outlining the major issues that require consideration in their construction.ResultsWe introduce PASBio by extending a model based on PropBank to the MB domain. The hypothesis we explore is that PAS holds the key for understanding relationships describing the roles of genes and gene products in mediating their biological functions. We chose predicates describing gene expression, molecular interactions and signal transduction events with the aim of covering a number of research areas in MB. Analysis was performed on sentences containing a set of verbal predicates from MEDLINE and full text journals. Results confirm the necessity to analyze PAS specifically for MB domain.ConclusionsAt present PASBio contains the analyzed PAS of over 30 verbs, publicly available on the Internet for use in advanced applications. In the future we aim to expand the knowledge base to cover more verbs and the nominal form of each predicate.

The SMARCA2/4 ATPase domain surpasses the bromodomain as a drug target in SWI/SNF mutant cancers: Insights from cDNA rescue and PFI-3 inhibitor studies

The SWI/SNF multisubunit complex modulates chromatin structure through the activity of two mutually exclusive catalytic subunits, SMARCA2 and SMARCA4, which both contain a bromodomain and an ATPase domain. Using RNAi, cancer-specific vulnerabilities have been identified in SWI/SNF-mutant tumors, including SMARCA4-deficient lung cancer; however, the contribution of conserved, druggable protein domains to this anticancer phenotype is unknown. Here, we functionally deconstruct the SMARCA2/4 paralog dependence of cancer cells using bioinformatics, genetic, and pharmacologic tools. We evaluate a selective SMARCA2/4 bromodomain inhibitor (PFI-3) and characterize its activity in chromatin-binding and cell-functional assays focusing on cells with altered SWI/SNF complex (e.g., lung, synovial sarcoma, leukemia, and rhabdoid tumors). We demonstrate that PFI-3 is a potent, cell-permeable probe capable of displacing ectopically expressed, GFP-tagged SMARCA2-bromodomain from chromatin, yet contrary to target knockdown, the inhibitor fails to display an antiproliferative phenotype. Mechanistically, the lack of pharmacologic efficacy is reconciled by the failure of bromodomain inhibition to displace endogenous, full-length SMARCA2 from chromatin as determined by in situ cell extraction, chromatin immunoprecipitation, and target gene expression studies. Furthermore, using inducible RNAi and cDNA complementation (bromodomain- and ATPase-dead constructs), we unequivocally identify the ATPase domain, and not the bromodomain of SMARCA2, as the relevant therapeutic target with the catalytic activity suppressing defined transcriptional programs. Taken together, our complementary genetic and pharmacologic studies exemplify a general strategy for multidomain protein drug-target validation and in case of SMARCA2/4 highlight the potential for drugging the more challenging helicase/ATPase domain to deliver on the promise of synthetic-lethality therapy.

Integrative analysis of gene and miRNA expression profiles with transcription factor–miRNA feed-forward loops identifies regulators in human cancers

We describe here a novel method for integrating gene and miRNA expression profiles in cancer using feed-forward loops (FFLs) consisting of transcription factors (TFs), miRNAs and their common target genes. The dChip-GemiNI (Gene and miRNA Network-based Integration) method statistically ranks computationally predicted FFLs by their explanatory power to account for differential gene and miRNA expression between two biological conditions such as normal and cancer. GemiNI integrates not only gene and miRNA expression data but also computationally derived information about TF–target gene and miRNA–mRNA interactions. Literature validation shows that the integrated modeling of expression data and FFLs better identifies cancer-related TFs and miRNAs compared to existing approaches. We have utilized GemiNI for analyzing six data sets of solid cancers (liver, kidney, prostate, lung and germ cell) and found that top-ranked FFLs account for ∼20% of transcriptome changes between normal and cancer. We have identified common FFL regulators across multiple cancer types, such as known FFLs consisting of MYC and miR-15/miR-17 families, and novel FFLs consisting of ARNT, CREB1 and their miRNA partners. The results and analysis web server are available at http://www.canevolve.org/dChip-GemiNi.

Lessons from a decade of integrating cancer copy number alterations with gene expression profiles

Over the last decade, multiple functional genomic datasets studying chromosomal aberrations and their downstream effects on gene expression have accumulated for several cancer types. A vast majority of them are in the form of paired gene expression profiles and somatic copy number alterations (CNA) information on the same patients identified using microarray platforms. In response, many algorithms and software packages are available for integrating these paired data. Surprisingly, there has been no serious attempt to review the currently available methodologies or the novel insights brought using them. In this work, we discuss the quantitative relationships observed between CNA and gene expression in multiple cancer types and biological milestones achieved using the available methodologies. We discuss the conceptual evolution of both, the step-wise and the joint data integration methodologies over the last decade. We conclude by providing suggestions for building efficient data integration methodologies and asking further biological questions.

Targeting Poly(ADP-Ribose) Polymerase and the c-Myb–Regulated DNA Damage Response Pathway in Castration-Resistant Prostate Cancer

The DNA damage response is an appealing target for androgen inhibitor–resistant prostate cancer. Improving Therapy in Prostate Cancer Blocking androgen receptor (AR) signaling is standard therapy for prostate cancer, but tumor growth often recurs. Li et al. examined the gene expression profile in patient samples of primary and metastatic prostate cancer from patients in which AR signaling was blocked. Metastatic disease, which is associated with androgen inhibitor–resistant relapse, correlated with increased expression of genes encoding proteins in the DNA damage response (DDR) and MYB expression. AR and c-Myb shared a subset of target genes that encode DDR proteins; thus, c-Myb may functionally substitute for AR in the regulation of their common DDR targets. Targeting proteins within the Myb-regulated network in combination with a poly[adenosine 5′-diphosphate (ADP)–ribose] polymerase (PARP) inhibitor, which compromises the DDR, generated synergistic lethality in prostate cancer cells in culture and in mouse xenografts, suggesting potential new options for prostate cancer patients. Androgen deprivation is the standard treatment for advanced prostate cancer (PCa), but most patients ultimately develop resistance and tumor recurrence. We found that MYB is transcriptionally activated by androgen deprivation therapy or genetic silencing of the androgen receptor (AR). MYB silencing inhibited PCa growth in culture and xenografts in mice. Microarray data revealed that c-Myb and AR shared a subset of target genes that encode DNA damage response (DDR) proteins, suggesting that c-Myb may supplant AR as the dominant regulator of their common DDR target genes in AR inhibition–resistant or AR-negative PCa. Gene signatures including AR, MYB, and their common DDR-associated target genes positively correlated with metastasis, castration resistance, tumor recurrence, and decreased survival in PCa patients. In culture and in xenograft-bearing mice, a combination strategy involving the knockdown of MYB, BRCA1, or TOPBP1 or the abrogation of cell cycle checkpoint arrest with AZD7762, an inhibitor of the checkpoint kinase Chk1, increased the cytotoxicity of the poly[adenosine 5′-diphosphate (ADP)–ribose] polymerase (PARP) inhibitor olaparib in PCa cells. Our results reveal new mechanism-based therapeutic approaches for PCa by targeting PARP and the DDR pathway involving c-Myb, TopBP1, ataxia telangiectasia mutated– and Rad3-related (ATR), and Chk1.