Petra Ross-Macdonald

Bristol-Myers Squibb, New York, New York, United States

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Publications (39)317 Total impact

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    ABSTRACT: The BET (bromondomain and extra-terminal) proteins bind acetylated histones and recruit protein complexes to promote transcription elongation. In hematological cancers, BET proteins have been shown to regulate expression of MYC and other genes that are important to disease pathology. Pharmacological inhibition of BET protein binding has been shown to inhibit tumor growth in MYC-dependent cancers such as multiple myeloma. In this study we demonstrate that small cell lung cancer (SCLC) cells are exquisitely sensitive to growth inhibition by the BET inhibitor JQ1. JQ1 treatment has no impact on MYC protein expression, but results in down-regulation of the lineage-specific transcription factor ASCL1. SCLC cells that are sensitive to JQ1 are also sensitive to ASCL1 depletion by RNA interference. Chromatin immunoprecipitation studies confirmed the binding of the BET protein BRD4 to the ASCL1 enhancer, and the ability of JQ1 to disrupt the interaction. The importance of ASCL1 as a potential driver oncogene in SCLC is further underscored by the observation that ASCL1 is over-expressed in >50% of SCLC specimens, an extent greater than that observed for other putative oncogenes (MYC, MYCN, SOX2) previously implicated in SCLC. Our studies have provided a mechanistic basis for the sensitivity of SCLC to BET inhibition, and a rationale for the clinical development of BET inhibitors in this disease with high unmet medical need. Copyright © 2015, American Association for Cancer Research.
    No preview · Article · Aug 2015 · Molecular Cancer Therapeutics
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    ABSTRACT: Peginterferon lambda-1a (Lambda), a type III interferon (IFN), acts through a unique receptor complex with limited cellular expression outside the liver which may result in a differentiated tolerability profile compared to peginterferon alfa (alfa). In Phase 2b clinical studies, Lambda administered in combination with ribavirin (RBV) was efficacious in patients with hepatitis C virus (HCV) infection representing genotypes 1 through 4, and was associated with more rapid declines in HCV RNA compared to alfa plus RBV. To gain insights into potential mechanisms for this finding, we investigated the effects of HCV replication on IFN signaling in primary human hepatocytes (PHH) and in induced hepatocyte-like cells (iHLCs). HCV infection resulted in rapid down-regulation of the type I IFN-α receptor subunit 1 (IFNAR1) transcript in hepatocytes while the transcriptional level of the unique IFN-λ receptor subunit IL28RA was transiently increased. In line with this observation, IFN signaling was selectively impaired in infected cells upon stimulation with alfa but not in response to Lambda. Importantly, in contrast to alfa, Lambda was able to induce IFN-stimulated gene (ISG) expression in HCV-infected hepatocytes, reflecting the onset of innate responses. Moreover, global transcriptome analysis in hepatocytes indicated that Lambda stimulation prolonged the expression of various ISGs that are potentially beneficial to antiviral defense mechanisms. Collectively, these observed effects of HCV infection on IFN receptor expression and signaling within infected hepatocytes provide a possible explanation for the more pronounced early virologic responses observed in patients treated with Lambda compared to alfa.
    Preview · Article · Mar 2015 · PLoS ONE
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    ABSTRACT: It is well established that genomic alterations play an essential role in oncogenesis, disease progression, and response of tumors to therapeutic intervention. The advances of next-generation sequencing technologies (NGS) provide unprecedented capabilities to scan genomes for changes such as mutations, deletions, and alterations of chromosomal copy number. However, the cost of full-genome sequencing still prevents the routine application of NGS in many areas. Capturing and sequencing the coding exons of genes (the “exome”) can be a cost-effective approach for identifying changes that result in alteration of protein sequences. We applied an exome sequencing technology (Roche NimbleGen capture paired with 454 sequencing) to identify sequence variation and mutations in eight commonly used cancer cell lines from a variety of tissue origins (A2780, A549, Colo205, GTL16, NCI-H661, MDA-MB468, PC3, and RD). We showed that this technology can accurately identify sequence variation, providing ~95 % concordance with Affymetrix SNP Array 6.0 performed on the same cell lines. Furthermore, we detected 19 of the 21 mutations reported in Sanger COSMIC database for these cell lines. We identified an average of 2,779 potential novel sequence variations/mutations per cell line, of which 1,904 were non-synonymous. Many non-synonymous changes were identified in kinases and known cancer-related genes. In addition we confirmed that the read depth of exome sequence data can be used to estimate high-level gene amplifications and identify homologous deletions. In summary, we demonstrate that exome sequencing can be a reliable and cost-effective way for identifying alterations in cancer genomes, and we have generated a comprehensive catalogue of genomic alterations in coding regions of eight cancer cell lines. These findings could provide important insights into cancer pathways and mechanisms of resistance to anticancer therapies.
    No preview · Article · Mar 2014

  • No preview · Article · Jan 2014 · Molecular Cancer Therapeutics
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    Full-text · Dataset · Dec 2012
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    ABSTRACT: We report the characterization of BMS-911543, a potent and selective small-molecule inhibitor of the Janus kinase (JAK) family member, JAK2. Functionally, BMS-911543 displayed potent anti-proliferative and pharmacodynamic (PD) effects in cell lines dependent upon JAK2 signaling, and had little activity in cell types dependent upon other pathways, such as JAK1 and JAK3. BMS-911543 also displayed anti-proliferative responses in colony growth assays using primary progenitor cells isolated from patients with JAK2(V617F)-positive myeloproliferative neoplasms (MPNs). Similar to these in vitro observations, BMS-911543 was also highly active in in vivo models of JAK2 signaling, with sustained pathway suppression being observed after a single oral dose. At low dose levels active in JAK2-dependent PD models, no effects were observed in an in vivo model of immunosuppression monitoring antigen-induced IgG and IgM production. Expression profiling of JAK2(V617F)-expressing cells treated with diverse JAK2 inhibitors revealed a shared set of transcriptional changes underlying pharmacological effects of JAK2 inhibition, including many STAT1-regulated genes and STAT1 itself. Collectively, our results highlight BMS-911543 as a functionally selective JAK2 inhibitor and support the therapeutic rationale for its further characterization in patients with MPN or in other disorders characterized by constitutively active JAK2 signaling.
    No preview · Article · Feb 2012 · Leukemia: official journal of the Leukemia Society of America, Leukemia Research Fund, U.K
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    ABSTRACT: Therapeutic development of a targeted agent involves a series of decisions over additional activities that may be ignored, eliminated or pursued. This paper details the concurrent application of two methods that provide a spectrum of information about the biological activity of a compound: biochemical profiling on a large panel of kinase assays and transcriptional profiling of mRNA responses. Our mRNA profiling studies used a full dose range, identifying subsets of transcriptional responses with differing EC(50)s which may reflect distinct targets. Profiling data allowed prioritization for validation in xenograft models, generated testable hypotheses for active compounds, and informed decisions on the general utility of the series.
    No preview · Article · Nov 2011 · Bioorganic & medicinal chemistry

  • No preview · Article · Jul 2011 · Cancer Research
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    ABSTRACT: It is well established that genomic alterations play an essential role in oncogenesis, disease progression, and response of tumors to therapeutic intervention. The advances of next-generation sequencing technologies (NGS) provide unprecedented capabilities to scan genomes for changes such as mutations, deletions, and alterations of chromosomal copy number. However, the cost of full-genome sequencing still prevents the routine application of NGS in many areas. Capturing and sequencing the coding exons of genes (the "exome") can be a cost-effective approach for identifying changes that result in alteration of protein sequences. We applied an exome-sequencing technology (Roche Nimblegen capture paired with 454 sequencing) to identify sequence variation and mutations in eight commonly used cancer cell lines from a variety of tissue origins (A2780, A549, Colo205, GTL16, NCI-H661, MDA-MB468, PC3, and RD). We showed that this technology can accurately identify sequence variation, providing ∼95% concordance with Affymetrix SNP Array 6.0 performed on the same cell lines. Furthermore, we detected 19 of the 21 mutations reported in Sanger COSMIC database for these cell lines. We identified an average of 2,779 potential novel sequence variations/mutations per cell line, of which 1,904 were non-synonymous. Many non-synonymous changes were identified in kinases and known cancer-related genes. In addition we confirmed that the read-depth of exome sequence data can be used to estimate high-level gene amplifications and identify homologous deletions. In summary, we demonstrate that exome sequencing can be a reliable and cost-effective way for identifying alterations in cancer genomes, and we have generated a comprehensive catalogue of genomic alterations in coding regions of eight cancer cell lines. These findings could provide important insights into cancer pathways and mechanisms of resistance to anti-cancer therapies.
    Full-text · Article · Jun 2011 · PLoS ONE
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    ABSTRACT: Author Summary Transcriptional profiling is arguably the most powerful hypothesis-free method for investigating biological effects of drugs—so why do the experiments typically use outmoded single-dose designs? Such single-dose experiments will co-mingle effects that can occur with different potency (e.g., effects on the known target versus effects on additional undesired targets). Single-dose experiments have little comparability to the dose-response bioassays, which are now used throughout the drug discovery processes. One reason for the disparity between experimental approaches is that existing analytical methods for dose-response bioassays can't cope with the dimensionality of microarray data: a typical bioassay is optimized for one response, then used to run a screen against thousands of compounds; whereas transcriptional profiling measures thousands of non-optimized responses to a single compound. Conversely, existing methods for microarray data analysis can identify patterns, but provide no quantitative dose-response information. To overcome these problems, we developed novel algorithms and visualization methods that allow anyone to apply transcriptional profiling as a conventional dose-response assay. The approach provides far more information than limited-dose designs, yet is economical (12 arrays/compound). With this new analytical framework, it is now possible to identify distinct transcriptional responses at distinct regions of the dose range, to link these impacts to biological pathways, and to make realistic connections to drug targets and to other bioassays.
    Full-text · Article · Sep 2009 · PLoS Computational Biology
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    ABSTRACT: In developing inhibitors of the LIM kinases, the initial lead molecules combined potent target inhibition with potent cytotoxic activity. However, as subsequent compounds were evaluated, the cytotoxic activity separated from inhibition of LIM kinases. A rapid determination of the cytotoxic mechanism and its molecular target was enabled by integrating data from two robust core technologies. High-content assays and gene expression profiling both indicated an effect on microtubule stability. Although the cytotoxic compounds are still kinase inhibitors, and their structures did not predict tubulin as an obvious target, these results provided the impetus to test their effects on microtubule polymerization directly. Unexpectedly, we confirmed tubulin itself as a molecular target of the cytotoxic kinase inhibitor compounds. This general approach to mechanism of action questions could be extended to larger data sets of quantified phenotypic and gene expression data.
    Full-text · Article · Dec 2008 · Molecular Cancer Therapeutics
  • Michael Neubauer · Petra Ross-Macdonald
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    ABSTRACT: Transcriptional profiling, also known as transcriptomics or mRNA expression profiling, has several useful applications in the field of drug discovery. Most recently, there is recognition of its utility for making the connection between compounds that have been optimized through in vitro assays and their activity on the in vivo biology of the disease process. After outlining the state of the art in obtaining and interpreting transcriptional profiling data, two additional aspects of this tool are reviewed. This chapter discusses transcriptional responses in disease models as biomarkers, and their connection to potential pharmacological treatments for disease. It also discusses the characterization of transcriptional selectivity profiles for potential drugs by comparison of their transcriptional changes. This chapter illustrates with literature examples how transcriptional profiling of pharmacological response can be used to address important issues in drug discovery. Recent reviews have explored the use of transcriptional profiling in mechanism of action studies on mammalian models, yeast and in antibiotics discovery and development. The application of transcriptional profiling as a measure of response to toxicants in model systems, and the use of these responses to classify and predict toxicity in new drug candidates, is termed “toxicogenomics,” which is also reviewd in the chapter. .
    No preview · Chapter · Dec 2007
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    ABSTRACT: MOTIVATION: Gene expression profiling is an important tool for gaining insight into biology. Novel strategies are required to analyze the growing archives of microarray data and extract useful information from them. One area of interest is in the construction of gene association networks from collections of profiling data. Various approaches have been proposed to construct gene networks using profiling data, and these networks have been used in functional inference as well as in data visualization. Here, we investigated a non-parametric approach to translate profiling data into a gene network. We explored the characteristics and utility of the resulting network and investigated the use of network information in analysis of variance models and hypothesis testing. RESULTS: Our work is composed of two parts: gene network construction and partitioning and hypothesis testing using sub-networks as groups. In the first part, multiple independently collected microarray datasets from the Gene Expression Omnibus data repository were analyzed to identify probe pairs that are positively co-regulated across the samples. A co-expression network was constructed based on a reciprocal ranking criteria and a false discovery rate analysis. We named this network Reference Gene Association (RGA) network. Then, the network was partitioned into densely connected sub-networks of probes using a multilevel graph partitioning algorithm. In the second part, we proposed a new, MANOVA-based approach that can take individual probe expression values as input and perform hypothesis testing at the sub-network level. We applied this MANOVA methodology to two published studies and our analysis indicated that the methodology is both effective and sensitive for identifying transcriptional sub-networks or pathways that are perturbed across treatments.
    Full-text · Article · Nov 2007 · Bioinformatics
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    Petra Ross-Macdonald

    Preview · Article · Feb 2007 · Expert Review of Molecular Diagnostics
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    ABSTRACT: We report here on a chemical genetic screen designed to address the mechanism of action of a small molecule. Small molecules that were active in models of urinary incontinence were tested on the nematode Caenorhabditis elegans, and the resulting phenotypes were used as readouts in a genetic screen to identify possible molecular targets. The mutations giving resistance to compound were found to affect members of the RGS protein/G-protein complex. Studies in mammalian systems confirmed that the small molecules inhibit muscarinic G-protein coupled receptor (GPCR) signaling involving G-alphaq (G-protein alpha subunit). Our studies suggest that the small molecules act at the level of the RGS/G-alphaq signaling complex, and define new mutations in both RGS and G-alphaq, including a unique hypo-adapation allele of G-alphaq. These findings suggest that therapeutics targeted to downstream components of GPCR signaling may be effective for treatment of diseases involving inappropriate receptor activation.
    Full-text · Article · May 2006 · PLoS Genetics
  • Petra Ross-Macdonald
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    ABSTRACT: Pharmaceutical discovery has a renewed interest in physiological screening, while chemical genomics initiatives will soon provide a large amount of cellular assay data. However, there is no single robust approach to connect active compounds with their targets, limiting their experimental and therapeutic use. Systematic matching of chemical genetic phenotypes with reverse genetic phenotypes would provide a valuable starting point for many investigations.
    No preview · Article · Jul 2005 · Pharmacogenomics
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    ABSTRACT: A chemical genetics approach identified a cellular target of several proapoptotic farnesyl transferase inhibitors (FTIs). Treatment with these FTIs caused p53-independent apoptosis in Caenorhabditis elegans, which was mimicked by knockdown of endosomal trafficking proteins, including Rab5, Rab7, the HOPS complex, and notably the enzyme Rab geranylgeranyl transferase (RabGGT). These FTIs were found to inhibit mammalian RabGGT with potencies that correlated with their proapoptotic activity. Knockdown of RabGGT induced apoptosis in mammalian cancer cell lines, and both RabGGT subunits were overexpressed in several tumor tissues. These findings validate RabGGT, and by extension endosomal function, as a therapeutically relevant target for modulation of apoptosis, and enhance our understanding of the mechanism of action of FTIs.
    Full-text · Article · May 2005 · Cancer Cell
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    ABSTRACT: Animal model systems are an intricate part of the discovery and development of new medicines. The sequencing of not only the human genome but also those of the various pathogenic bacteria, the nematode Caenorhabditis elegans, the fruitfly Drosophila, and the mouse has enabled the discovery of new drug targets to push forward at an unprecedented pace. The knowledge and tools in these "model" systems are allowing researchers to carry out experiments more efficiently and are uncovering previously hidden biological connections. While the history of bacteria, yeast, and mice in drug discovery are long, their roles are ever evolving. In contrast, the history of Drosophila and C. elegans at pharmaceutical companies is short. We will briefly review the historic role of each model organism in drug discovery and then update the readers as to the abilities and liabilities of each model within the context of drug development.
    No preview · Article · Sep 2003 · Pharmacology [?] Therapeutics
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    ABSTRACT: Determining the effect of gene deletion is a fundamental approach to understanding gene function. Conventional genetic screens exhibit biases, and genes contributing to a phenotype are often missed. We systematically constructed a nearly complete collection of gene-deletion mutants (96% of annotated open reading frames, or ORFs) of the yeast Saccharomyces cerevisiae. DNA sequences dubbed 'molecular bar codes' uniquely identify each strain, enabling their growth to be analysed in parallel and the fitness contribution of each gene to be quantitatively assessed by hybridization to high-density oligonucleotide arrays. We show that previously known and new genes are necessary for optimal growth under six well-studied conditions: high salt, sorbitol, galactose, pH 8, minimal medium and nystatin treatment. Less than 7% of genes that exhibit a significant increase in messenger RNA expression are also required for optimal growth in four of the tested conditions. Our results validate the yeast gene-deletion collection as a valuable resource for functional genomics.
    Full-text · Article · Aug 2002 · Nature
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    J E Novak · P B Ross-Macdonald · G. Shirleen Roeder
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    ABSTRACT: The budding yeast MSH4 gene encodes a MutS homolog produced specifically in meiotic cells. Msh4 is not required for meiotic mismatch repair or gene conversion, but it is required for wild-type levels of crossing over. Here, we show that a msh4 null mutation substantially decreases crossover interference. With respect to the defect in interference and the level of crossing over, msh4 is similar to the zip1 mutant, which lacks a structural component of the synaptonemal complex (SC). Furthermore, epistasis tests indicate that msh4 and zip1 affect the same subset of meiotic crossovers. In the msh4 mutant, SC formation is delayed compared to wild type, and full synapsis is achieved in only about half of all nuclei. The simultaneous defects in synapsis and interference observed in msh4 (and also zip1 and ndj1/tam1) suggest a role for the SC in mediating interference. The Msh4 protein localizes to discrete foci on meiotic chromosomes and colocalizes with Zip2, a protein involved in the initiation of chromosome synapsis. Both Zip2 and Zip1 are required for the normal localization of Msh4 to chromosomes, raising the possibility that the zip1 and zip2 defects in crossing over are indirect, resulting from the failure to localize Msh4 properly.
    Full-text · Article · Aug 2001 · Genetics

Publication Stats

7k Citations
317.00 Total Impact Points

Institutions

  • 2000-2015
    • Bristol-Myers Squibb
      • • Department of Applied Genomics
      • • Pharmaceutical Research Institute
      New York, New York, United States
  • 1998-2001
    • Yale University
      • Department of Molecular, Cellular and Developmental Biology
      New Haven, Connecticut, United States
    • The National Institute for Medical Research, Yaba
      Eko, Lagos, Nigeria
  • 1994
    • MRC National Institute for Medical Research
      Londinium, England, United Kingdom