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Posts Tagged ‘EPA’


BioInformatic Resources at the Environmental Protection Agency: Tools and Webinars on Toxicity Prediction

Curator Stephen J. Williams Ph.D.

New GenRA Module in EPA’s CompTox Dashboard Will Help Predict Potential Chemical Toxicity

Published September 25, 2018

As part of its ongoing computational toxicology research, EPA is developing faster and improved approaches to evaluate chemicals for potential health effects.  One commonly applied approach is known as chemical read-across. Read-across uses information about how a chemical with known data behaves to make a prediction about the behavior of another chemical that is “similar” but does not have as much data. Current read-across, while cost-effective, relies on a subjective assessment, which leads to varying predictions and justifications depending on who undertakes and evaluates the assessment.

To reduce uncertainties and develop a more objective approach, EPA researchers have developed an automated read-across tool called Generalized Read-Across (GenRA), and added it to the newest version of the EPA Computational Toxicology Dashboard. The goal of GenRA is to encode as many expert considerations used within current read-across approaches as possible and combine these with data-driven approaches to transition read-across towards a more systematic and data-based method of making predictions.

EPA chemist Dr. Grace Patlewicz says it was this uncertainty that motivated the development of GenRA. “You don’t actually know if you’ve been successful at using read-across to help predict chemical toxicity because it’s a judgement call based on one person versus the next. That subjectivity is something we were trying to move away from.” Patlewicz says.

Since toxicologists and risk assessors are already familiar with read-across, EPA researchers saw value in creating a tool that that was aligned with the current read-across workflow but which addressed uncertainty using data analysis methods in what they call a “harmonized-hybrid workflow.”

In its current form, GenRA lets users find analogues, or chemicals that are similar to their target chemical, based on chemical structural similarity. The user can then select which analogues they want to carry forward into the GenRA prediction by exploring the consistency and concordance of the underlying experimental data for those analogues. Next, the tool predicts toxicity effects of specific repeated dose studies. Then, a plot with these outcomes is generated based on a similarity-weighted activity of the analogue chemicals the user selected. Finally, the user is presented with a data matrix view showing whether a chemical is predicted to be toxic (yes or no) for a chosen set of toxicity endpoints, with a quantitative measure of uncertainty.

The team is also comparing chemicals based on other similarity contexts, such as physicochemical characteristics or metabolic similarity, as well as extending the approach to make quantitative predictions of toxicity.

Patlewicz thinks incorporating other contexts and similarity measures will refine GenRA to make better toxicity predictions, fulfilling the goal of creating a read-across method capable of assessing thousands of chemicals that currently lack toxicity data.

“That’s the direction that we’re going in,” Patlewicz says. “Recognizing where we are and trying to move towards something a little bit more objective, showing how aspects of the current read-across workflow could be refined.”

Learn more at: https://comptox.epa.gov

 

A listing of EPA Tools for Air Quality Assessment

Tools

  • Atmospheric Model Evaluation Tool (AMET)
    AMET helps in the evaluation of meteorological and air quality simulations.
  • Benchmark Dose Software (BMDS)
    EPA developed the Benchmark Dose Software (BMDS) as a tool to help estimate dose or exposure of a chemical or chemical mixture associated with a given response level. The methodology is used by EPA risk assessors and is fast becoming the world’s standard for dose-response analysis for risk assessments, including air pollution risk assessments.
  • BenMAP
    BenMAP is a Windows-based computer program that uses a Geographic Information System (GIS)-based to estimate the health impacts and economic benefits occurring when populations experience changes in air quality.
  • Community-Focused Exposure and Risk Screening Tool (C-FERST)
    C-FERST is an online tool developed by EPA in collaboration with stakeholders to provide access to resources that can be used with communities to help identify and learn more about their environmental health issues and explore exposure and risk reduction options.
  • Community Health Vulnerability Index
    EPA scientists developed a Community Health Vulnerability Index that can be used to help identify communities at higher health risk from wildfire smoke. Breathing smoke from a nearby wildfire is a health threat, especially for people with lung or heart disease, diabetes and high blood pressure as well as older adults, and those living in communities with poverty, unemployment and other indicators of social stress. Health officials can use the tool, in combination with air quality models, to focus public health strategies on vulnerable populations living in areas where air quality is impaired, either by wildfire smoke or other sources of pollution. The work was published in Environmental Science & Technology.
  • Critical Loads Mapper Tool
    The Critical Loads Mapper Tool can be used to help protect terrestrial and aquatic ecosystems from atmospheric deposition of nitrogen and sulfur, two pollutants emitted from fossil fuel burning and agricultural emissions. The interactive tool provides easy access to information on deposition levels through time; critical loads, which identify thresholds when pollutants have reached harmful levels; and exceedances of these thresholds.
  • EnviroAtlas
    EnviroAtlas provides interactive tools and resources for exploring the benefits people receive from nature or “ecosystem goods and services”. Ecosystem goods and services are critically important to human health and well-being, but they are often overlooked due to lack of information. Using EnviroAtlas, many types of users can access, view, and analyze diverse information to better understand the potential impacts of various decisions.
  • EPA Air Sensor Toolbox for Citizen Scientists
    EPA’s Air Sensor Toolbox for Citizen Scientists provides information and guidance on new low-cost compact technologies for measuring air quality. Citizens are interested in learning more about local air quality where they live, work and play. EPA’s Toolbox includes information about: Sampling methodologies; Calibration and validation approaches; Measurement methods options; Data interpretation guidelines; Education and outreach; and Low cost sensor performance information.
  • ExpoFIRST
    The Exposure Factors Interactive Resource for Scenarios Tool (ExpoFIRST) brings data from EPA’s Exposure Factors Handbook: 2011 Edition (EFH) to an interactive tool that maximizes flexibility and transparency for exposure assessors. ExpoFIRST represents a significant advance for regional, state, and local scientists in performing and documenting calculations for community and site-specific exposure assessments, including air pollution exposure assessments.
  • EXPOsure toolbox (ExpoBox)
    This is a toolbox created to assist individuals from within government, industry, academia, and the general public with assessing exposure, including exposure to air contaminants, fate and transport processes of air pollutants and their potential exposure concentrations. It is a compendium of exposure assessment tools that links to guidance documents, databases, models, reference materials, and other related resources.
  • Federal Reference & Federal Equivalency Methods
    EPA scientists develop and evaluate Federal Reference Methods and Federal Equivalency Methods for accurately and reliably measuring six primary air pollutants in outdoor air. These methods are used by states and other organizations to assess implementation actions needed to attain National Ambient Air Quality Standards.
  • Fertilizer Emission Scenario Tool for CMAQ (FEST-C)
    FEST-C facilitates the definition and simulation of new cropland farm management system scenarios or editing of existing scenarios to drive Environmental Policy Integrated Climate model (EPIC) simulations.  For the standard 12km continental Community Multi-Scale Air Quality model (CMAQ) domain, this amounts to about 250,000 simulations for the U.S. alone. It also produces gridded daily EPIC weather input files from existing hourly Meteorology-Chemistry Interface Processor (MCIP) files, transforms EPIC output files to CMAQ-ready input files and links directly to Visual Environment for Rich Data Interpretation (VERDI) for spatial visualization of input and output files. The December 2012 release will perform all these functions for any CMAQ grid scale or domain.
  • Instruction Guide and Macro Analysis Tool for Community-led Air Monitoring 
    EPA has developed two tools for evaluating the performance of low-cost sensors and interpreting the data they collect to help citizen scientists, communities, and professionals learn about local air quality.
  • Integrated Climate and Land use Scenarios (ICLUS)
    Climate change and land-use change are global drivers of environmental change. Impact assessments frequently show that interactions between climate and land-use changes can create serious challenges for aquatic ecosystems, water quality, and air quality. Population projections to 2100 were used to model the distribution of new housing across the landscape. In addition, housing density was used to estimate changes in impervious surface cover.  A final report, datasets, the ICLUS+ Web Viewer and ArcGIS tools are available.
  • Indoor Semi-Volatile Organic Compound (i-SVOC)
    i-SVOC Version 1.0 is a general-purpose software application for dynamic modeling of the emission, transport, sorption, and distribution of semi-volatile organic compounds (SVOCs) in indoor environments. i-SVOC supports a variety of uses, including exposure assessment and the evaluation of mitigation options. SVOCs are a diverse group of organic chemicals that can be found in: Many are also present in indoor air, where they tend to bind to interior surfaces and particulate matter (dust).

    • Pesticides;
    • Ingredients in cleaning agents and personal care products;
    • Additives to vinyl flooring, furniture, clothing, cookware, food packaging, and electronics.
  • Municipal Solid Waste Decision Support Tool (MSW DST)EXIT
    This tool is designed to aid solid waste planners in evaluating the cost and environmental aspects of integrated municipal solid waste management strategies. The tool is the result of collaboration between EPA and RTI International and its partners.
  • Optical Noise-Reduction Averaging (ONA) Program Improves Black Carbon Particle Measurements Using Aethalometers
    ONA is a program that reduces noise in real-time black carbon data obtained using Aethalometers. Aethalometers optically measure the concentration of light absorbing or “black” particles that accumulate on a filter as air flows through it. These particles are produced by incomplete fossil fuel, biofuel and biomass combustion. Under polluted conditions, they appear as smoke or haze.
  • RETIGO tool
    Real Time Geospatial Data Viewer (RETIGO) is a free, web-based tool that shows air quality data that are collected while in motion (walking, biking or in a vehicle). The tool helps users overcome technical barriers to exploring air quality data. After collecting measurements, citizen scientists and other users can import their own data and explore the data on a map.
  • Remote Sensing Information Gateway (RSIG)
    RSIG offers a new way for users to get the multi-terabyte, environmental datasets they want via an interactive, Web browser-based application. A file download and parsing process that now takes months will be reduced via RSIG to minutes.
  • Simulation Tool Kit for Indoor Air Quality and Inhalation Exposure (IAQX)
    IAQX version 1.1 is an indoor air quality (IAQ) simulation software package that complements and supplements existing indoor air quality simulation (IAQ) programs. IAQX is for advanced users who have experience with exposure estimation, pollution control, risk assessment, and risk management. There are many sources of indoor air pollution, such as building materials, furnishings, and chemical cleaners. Since most people spend a large portion of their time indoors, it is important to be able to estimate exposure to these pollutants. IAQX helps users analyze the impact of pollutant sources and sinks, ventilation, and air cleaners. It performs conventional IAQ simulations to calculate the pollutant concentration and/or personal exposure as a function of time. It can also estimate adequate ventilation rates based on user-provided air quality criteria. This is a unique feature useful for product stewardship and risk management.
  • Spatial Allocator
    The Spatial Allocator provides tools that could be used by the air quality modeling community to perform commonly needed spatial tasks without requiring the use of a commercial Geographic Information System (GIS).
  • Traceability Protocol for Assay and Certification of Gaseous Calibration Standards
    This is used to certify calibration gases for ambient and continuous emission monitors. It specifies methods for assaying gases and establishing traceability to National Institute of Standards and Technology (NIST) reference standards. Traceability is required under EPA ambient and continuous emission monitoring regulations.
  • Watershed Deposition Mapping Tool (WDT)
    WDT provides an easy to use tool for mapping the deposition estimates from CMAQ to watersheds to provide the linkage of air and water needed for TMDL (Total Maximum Daily Load) and related nonpoint-source watershed analyses.
  • Visual Environment for Rich Data Interpretation (VERDI)
    VERDI is a flexible, modular, Java-based program for visualizing multivariate gridded meteorology, emissions, and air quality modeling data created by environmental modeling systems such as CMAQ and the Weather Research and Forecasting (WRF) model.

 

Databases

  • Air Quality Data for the CDC National Environmental Public Health Tracking Network 
    EPA’s Exposure Research scientists are collaborating with the Centers for Disease Control and Prevention (CDC) on a CDC initiative to build a National Environmental Public Health Tracking (EPHT) network. Working with state, local and federal air pollution and health agencies, the EPHT program is facilitating the collection, integration, analysis, interpretation, and dissemination of data from environmental hazard monitoring, and from human exposure and health effects surveillance. These data provide scientific information to develop surveillance indicators, and to investigate possible relationships between environmental exposures, chronic disease, and other diseases, that can lead to interventions to reduce the burden of theses illnesses. An important part of the initiative is air quality modeling estimates and air quality monitoring data, combined through Bayesian modeling that can be linked with health outcome data.
  • EPAUS9R – An Energy Systems Database for use with the Market Allocation (MARKAL) Model
    The EPAUS9r is a regional database representation of the United States energy system. The database uses the MARKAL model. MARKAL is an energy system optimization model used by local and federal governments, national and international communities and academia. EPAUS9r represents energy supply, technology, and demand throughout the major sectors of the U.S. energy system.
  • Fused Air Quality Surfaces Using Downscaling
    This database provides access to the most recent O3 and PM2.5 surfaces datasets using downscaling.
  • Health & Environmental Research Online (HERO)
    HERO provides access to scientific literature used to support EPA’s integrated science assessments, including the  Integrated Science Assessments (ISA) that feed into the National Ambient Air Quality (NAAQS) reviews.
  • SPECIATE 4.5 Database
    SPECIATE is a repository of volatile organic gas and particulate matter (PM) speciation profiles of air pollution sources.

A listing of EPA Tools and Databases for Water Contaminant Exposure Assessment

Exposure and Toxicity

  • EPA ExpoBox (A Toolbox for Exposure Assessors)
    This toolbox assists individuals from within government, industry, academia, and the general public with assessing exposure from multiple media, including water and sediment. It is a compendium of exposure assessment tools that links to guidance documents, databases, models, reference materials, and other related resources.

Chemical and Product Categories (CPCat) Database
CPCat is a database containing information mapping more than 43,000 chemicals to a set of terms categorizing their usage or function. The comprehensive list of chemicals with associated categories of chemical and product use was compiled from publically available sources. Unique use category taxonomies from each source are mapped onto a single common set of approximately 800 terms. Users can search for chemicals by chemical name, Chemical Abstracts Registry Number, or by CPCat terms associated with chemicals.

A listing of EPA Tools and Databases for Chemical Toxicity Prediction & Assessment

  • Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS)
    SeqAPASS is a fast, online screening tool that allows researchers and regulators to extrapolate toxicity information across species. For some species, such as humans, mice, rats, and zebrafish, the EPA has a large amount of data regarding their toxicological susceptibility to various chemicals. However, the toxicity data for numerous other plants and animals is very limited. SeqAPASS extrapolates from these data rich model organisms to thousands of other non-target species to evaluate their specific potential chemical susceptibility.

 

A listing of EPA Webinar and Literature on Bioinformatic Tools and Projects

Comparative Bioinformatics Applications for Developmental Toxicology

Discuss how the US EPA/NCCT is trying to solve the problem of too many chemicals, too high cost, and too much biological uncertainty Discuss the solution the ToxCast Program is proposing; a data-rich system to screen, classify and rank chemicals for further evaluation

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=186844

CHEMOINFORMATIC AND BIOINFORMATIC CHALLENGES AT THE US ENVIRONMENTAL PROTECTION AGENCY.

This presentation will provide an overview of both the scientific program and the regulatory activities related to computational toxicology. This presentation will provide an overview of both the scientific program and the regulatory activities related to computational toxicology.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=154013

How Can We Use Bioinformatics to Predict Which Agents Will Cause Birth Defects?

The availability of genomic sequences from a growing number of human and model organisms has provided an explosion of data, information, and knowledge regarding biological systems and disease processes. High-throughput technologies such as DNA and protein microarray biochips are now standard tools for probing the cellular state and determining important cellular behaviors at the genomic/proteomic levels. While these newer technologies are beginning to provide important information on cellular reactions to toxicant exposure (toxicogenomics), a major challenge that remains is the formulation of a strategy to integrate transcript, protein, metabolite, and toxicity data. This integration will require new concepts and tools in bioinformatics. The U.S. National Library of Medicine’s Pubmed site includes 19 million citations and abstracts and continues to grow. The BDSM team is now working on assembling the literature’s unstructured data into a structured database and linking it to BDSM within a system that can then be used for testing and generating new hypotheses. This effort will generate data bases of entities (such as genes, proteins, metabolites, gene ontology processes) linked to PubMed identifiers/abstracts and providing information on the relationships between them. The end result will be an online/standalone tool that will help researchers to focus on the papers most relevant to their query and uncover hidden connections and obvious information gaps.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=227345

ADVANCED PROTEOMICS AND BIOINFORMATICS TOOLS IN TOXICOLOGY RESEARCH: OVERCOMING CHALLENGES TO PROVIDE SIGNIFICANT RESULTS

This presentation specifically addresses the advantages and limitations of state of the art gel, protein arrays and peptide-based labeling proteomic approaches to assess the effects of a suite of model T4 inhibitors on the thyroid axis of Xenopus laevis.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=152823

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=344452

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=03%2F26%2F2014&dateEndPublishedPresented=03%2F26%2F2019&dirEntryId=344452&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=04%2F02%2F2014&dateEndPublishedPresented=04%2F02%2F2019&dirEntryId=344452&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=04%2F02%2F2014&dateEndPublishedPresented=04%2F02%2F2019&dirEntryId=344452&fed_org_id=111&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=344452&fed_org_id=111&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

 

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=03%2F26%2F2014&dateEndPublishedPresented=03%2F26%2F2019&dirEntryId=344452&fed_org_id=111&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=344452&fed_org_id=111&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=04%2F11%2F2014&dateEndPublishedPresented=04%2F11%2F2019&dirEntryId=344452&fed_org_id=111&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

Bioinformatic Integration of in vivo Data and Literature-based Gene Associations for Prioritization of Adverse Outcome Pathway Development

Adverse outcome pathways (AOPs) describe a sequence of events, beginning with a molecular initiating event (MIE), proceeding via key events (KEs), and culminating in an adverse outcome (AO). A challenge for use of AOPs in a safety evaluation context has been identification of MIEs and KEs relevant for AOs observed in regulatory toxicity studies. In this work, we implemented a bioinformatic approach that leverages mechanistic information in the literature and the AOs measured in regulatory toxicity studies to prioritize putative MIEs and/or early KEs for AOP development relevant to chemical safety evaluation. The US Environmental Protection Agency Toxicity Reference Database (ToxRefDB, v2.0) contains effect information for >1000 chemicals curated from >5000 studies or summaries from sources including data evaluation records from the US EPA Office of Pesticide Programs, the National Toxicology Program (NTP), peer-reviewed literature, and pharmaceutical preclinical studies. To increase ToxRefDB interoperability, endpoint and effect information were cross-referenced with codes from the United Medical Language System, which enabled mapping of in vivo pathological effects from ToxRefDB to PubMed (via Medical Subject Headings or MeSH). This enabled linkage to any resource that is also connected to PubMed or indexed with MeSH. A publicly available bioinformatic tool, the Entity-MeSH Co-occurrence Network (EMCON), uses multiple data sources and a measure of mutual information to identify genes most related to a MeSH term. Using EMCON, gene sets were generated for endpoints of toxicological relevance in ToxRefDB linking putative KEs and/or MIEs. The Comparative Toxicogenomics Database was used to further filter important associations. As a proof of concept, thyroid-related effects and their highly associated genes were examined, and demonstrated relevant MIEs and early KEs for AOPs to describe thyroid-related AOs. The ToxRefDB to gene mapping for thyroid resulted in >50 unique gene to chemical relationships. Integrated use of EMCON and ToxRefDB data provides a basis for rapid and robust putative AOP development, as well as a novel means to generate mechanistic hypotheses for specific chemicals. This abstract does not necessarily reflect U.S. EPA policy. Abstract and Poster for 2019 Society of Toxicology annual meeting in March 2019

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dateBeginPublishedPresented=04%2F11%2F2014&dateEndPublishedPresented=04%2F11%2F2019&dirEntryId=344452&keyword=Chemical+Safety&showCriteria=2&sortBy=pubDateYear&subject=Chemical+Safety+Research

A Web-Hosted R Workflow to Simplify and Automate the Analysis of 16S NGS Data

Next-Generation Sequencing (NGS) produces large data sets that include tens-of-thousands of sequence reads per sample. For analysis of bacterial diversity, 16S NGS sequences are typically analyzed in a workflow that containing best-of-breed bioinformatics packages that may leverage multiple programming languages (e.g., Python, R, Java, etc.). The process totransform raw NGS data to usable operational taxonomic units (OTUs) can be tedious due tothe number of quality control (QC) steps used in QIIME and other software packages forsample processing. Therefore, the purpose of this work was to simplify the analysis of 16SNGS data from a large number of samples by integrating QC, demultiplexing, and QIIME(Quantitative Insights Into Microbial Ecology) analysis in an accessible R project. User command line operations for each of the pipeline steps were automated into a workflow. In addition, the R server allows multi-user access to the automated pipeline via separate useraccounts while providing access to the same large set of underlying data. We demonstratethe applicability of this pipeline automation using 16S NGS data from approximately 100 stormwater runoff samples collected in a mixed-land use watershed in northeast Georgia. OTU tables were generated for each sample and the relative taxonomic abundances were compared for different periods over storm hydrographs to determine how the microbial ecology of a stream changes with rise and fall of stream stage. Our approach simplifies the pipeline analysis of multiple 16S NGS samples by automating multiple preprocessing, QC, analysis and post-processing command line steps that are called by a sequence of R scripts. Presented at ASM 2015 Rapid NGS Bioinformatic Pipelines for Enhanced Molecular Epidemiologic Investigation of Pathogens

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NERL&dirEntryId=309890

DEVELOPING COMPUTATIONAL TOOLS NECESSARY FOR APPLYING TOXICOGENOMICS TO RISK ASSESSMENT AND REGULATORY DECISION MAKING.

GENOMICS, PROTEOMICS & METABOLOMICS CAN PROVIDE USEFUL WEIGHT-OF-EVIDENCE DATA ALONG THE SOURCE-TO-OUTCOME CONTINUUM, WHEN APPROPRIATE BIOINFORMATIC AND COMPUTATIONAL METHODS ARE APPLIED TOWARDS INTEGRATING MOLECULAR, CHEMICAL AND TOXICOGICAL INFORMATION. GENOMICS, PROTEOMICS & METABOLOMICS CAN PROVIDE USEFUL WEIGHT-OF-EVIDENCE DATA ALONG THE SOURCE-TO-OUTCOME CONTINUUM, WHEN APPROPRIATE BIOINFORMATIC AND COMPUTATIONAL METHODS ARE APPLIED TOWARDS INTEGRATING MOLECULAR, CHEMICAL AND TOXICOGICAL INFORMATION.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=156264

The Human Toxome Project

The Human Toxome project, funded as an NIH Transformative Research grant 2011–‐ 2016, is focused on developing the concepts and the means for deducing, validating, and sharing molecular Pathways of Toxicity (PoT). Using the test case of estrogenic endocrine disruption, the responses of MCF–‐7 human breast cancer cells are being phenotyped by transcriptomics and mass–‐spectroscopy–‐based metabolomics. The bioinformatics tools for PoT deduction represent a core deliverable. A number of challenges for quality and standardization of cell systems, omics technologies, and bioinformatics are being addressed. In parallel, concepts for annotation, validation, and sharing of PoT information, as well as their link to adverse outcomes, are being developed. A reasonably comprehensive public database of PoT, the Human Toxome Knowledge–‐base, could become a point of reference for toxicological research and regulatory tests strategies. A reasonably comprehensive public database of PoT, the Human Toxome Knowledge–‐base, could become a point of reference for toxicological research and regulatory tests strategies.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NCCT&dirEntryId=309453

High-Resolution Metabolomics for Environmental Chemical Surveillance and Bioeffect Monitoring

High-Resolution Metabolomics for Environmental Chemical Surveillance and Bioeffect Monitoring (Presented by: Dean Jones, PhD, Department of Medicine, Emory University) (2/28/2013)

https://www.epa.gov/chemical-research/high-resolution-metabolomics-environmental-chemical-surveillance-and-bioeffect

Identification of Absorption, Distribution, Metabolism, and Excretion (ADME) Genes Relevant to Steatosis Using a Gene Expression Approach

Absorption, distribution, metabolism, and excretion (ADME) impact chemical concentration and activation of molecular initiating events of Adverse Outcome Pathways (AOPs) in cellular, tissue, and organ level targets. In order to better describe ADME parameters and how they modulate potential hazards posed by chemical exposure, our goal is to investigate the relationship between AOPs and ADME related genes and functional information. Given the scope of this task, we began using hepatic steatosis as a case study. To identify ADME genes related to steatosis, we used the publicly available toxicogenomics database, Open TG-GATEsTM. This database contains standardized rodent chemical exposure data from 170 chemicals (mostly drugs), along with differential gene expression data and corresponding associated pathological changes. We examined the chemical exposure microarray data set gathered from 9 chemical exposure treatments resulting in pathologically confirmed (minimal, moderate and severe) incidences of hepatic steatosis. From this differential gene expression data set, we utilized differential expression analyses to identify gene changes resulting from the chemical exposures leading to hepatic steatosis. We then selected differentially expressed genes (DEGs) related to ADME by filtering all genes based on their ADME functional identities. These DEGs include enzymes such as cytochrome p450, UDP glucuronosyltransferase, flavin-containing monooxygenase and transporter genes such as solute carriers and ATP-binding cassette transporter families. The up and downregulated genes were identified across these treatments. Total of 61 genes were upregulated and 68 genes were down regulated in all treatments. Meanwhile, 25 genes were both up regulated and downregulated across all the treatments. This work highlights the application of bioinformatics in linking AOPs with gene modulations specifically in relationships to ADME and exposures to chemicals. This abstract does not necessarily reflect U.S. EPA policy. This work highlights the application of bioinformatics tools to identify genes that are modulated by adverse outcomes. Specifically, we delineate a method to identify genes that are related to ADME and can impact target tissue dose in response to chemical exposures. The computational method outlined in this work is applicable to any adverse outcome pathway, and provide a linkage between chemical exposure, target tissue dose, and adverse outcomes. Application of this method will allow for the rapid screening of chemicals for their impact on ADME-related genes using available gene data bases in literature.

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=341273

Development of Environmental Fate and Metabolic Simulators

Presented at Bioinformatics Open Source Conference (BOSC), Detroit, MI, June 23-24, 2005. see description

https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NERL&dirEntryId=257172

 

Useful Webinars on EPA Computational Tools and Informatics

 

Computational Toxicology Communities of Practice

Computational Toxicology Research

EPA’s Computational Toxicology Communities of Practice is composed of hundreds of stakeholders from over 50 public and private sector organizations (ranging from EPA, other federal agencies, industry, academic institutions, professional societies, nongovernmental organizations, environmental non-profit groups, state environmental agencies and more) who have an interest in using advances in computational toxicology and exposure science to evaluate the safety of chemicals.

The Communities of Practice is open to the public. Monthly webinars are held at EPA’s RTP campus, on the fourth Thursday of the month (occasionally rescheduled in November and December to accommodate holiday schedules), from 11am-Noon EST/EDT. Remote participation is available. For more information or to be added to the meeting email list, contact: Monica Linnenbrink (linnenbrink.monica@epa.gov).

Related Links

Past Webinar Presentations

Presentation File Presented By Date
OPEn structure-activity Relationship App (OPERA) Powerpoint(VideoEXIT) Dr. Kamel Mansouri, Lead Computational Chemist contractor for Integrated Laboratory Systems in the National Institute of Environmental Health Sciences 2019/4/25
CompTox Chemicals Dashboard and InVitroDB V3 (VideoEXIT) Dr. Antony Williams, Chemist in EPA’s National Center for Computational Toxicology and Dr. Katie Paul-Friedman, Toxicologist in EPA’s National Center for Computational Toxicology 2019/3/28
The Systematic Empirical Evaluation of Models (SEEM) framework (VideoEXIT) Dr. John Wambaugh, Physical Scientist in EPA’s National Center for Computational Toxicology 2019/2/28
ToxValDB: A comprehensive database of quantitative in vivo study results from over 25,000 chemicals (VideoEXIT) Dr. Richard Judson, Research Chemist in EPA’s National Center for Computational Toxicology 2018/12/20
Sequence Alignment to Predict Across Species Susceptibility (seqAPASS) (VideoEXIT) Dr. Carlie LaLone, Bioinformaticist, EPA’s National Health and Environmental Effects Research Laboratory 2018/11/29
Chemicals and Products Database (VideoEXIT) Dr. Kathie Dionisio, Environmental Health Scientist, EPA’s National Exposure Research Laboratory 2018/10/25
CompTox Chemicals Dashboard V3 (VideoEXIT) Dr. Antony Williams, Chemist, EPA National Center for Computational Toxicology (NCCT). 2018/09/27
Generalised Read-Across (GenRA) (VideoEXIT) Dr. Grace Patlewicz, Chemist, EPA National Center for Computational Toxicology (NCCT). 2018/08/23
EPA’S ToxCast Owner’s Manual  (VideoEXIT) Monica Linnenbrink, Strategic Outreach and Communication lead, EPA National Center for Computational Toxicology (NCCT). 2018/07/26
EPA’s Non-Targeted Analysis Collaborative Trial (ENTACT)      (VideoEXIT) Elin Ulrich, Research Chemist in the Public Health Chemistry Branch, EPA National Exposure Research Laboratory (NERL). 2018/06/28
ECOTOX Knowledgebase: New Tools and Data Visualizations(VideoEXIT) Colleen Elonen, Translational Toxicology Branch, and Dr. Jennifer Olker, Systems Toxicology Branch, in the Mid-Continent Ecology Division of EPA’s National Health & Environmental Effects Research Laboratory (NHEERL) 2018/05/24
Investigating Chemical-Microbiota Interactions in Zebrafish (VideoEXIT) Tamara Tal, Biologist in the Systems Biology Branch, Integrated Systems Toxicology Division, EPA’s National Health & Environmental Effects Research Laboratory (NHEERL) 2018/04/26
The CompTox Chemistry Dashboard v2.6: Delivering Improved Access to Data and Real Time Predictions (VideoEXIT) Tony Williams, Computational Chemist, EPA’s National Center for Computational Toxicology (NCCT) 2018/03/29
mRNA Transfection Retrofits Cell-Based Assays with Xenobiotic Metabolism (VideoEXIT* Audio starts at 10:17) Steve Simmons, Research Toxicologist, EPA’s National Center for Computational Toxicology (NCCT) 2018/02/22
Development and Distribution of ToxCast and Tox21 High-Throughput Chemical Screening Assay Method Description(VideoEXIT) Stacie Flood, National Student Services Contractor, EPA’s National Center for Computational Toxicology (NCCT) 2018/01/25
High-throughput H295R steroidogenesis assay: utility as an alternative and a statistical approach to characterize effects on steroidogenesis (VideoEXIT) Derik Haggard, ORISE Postdoctoral Fellow, EPA’s National Center for Computational Toxicology (NCCT) 2017/12/14
Systematic Review for Chemical Assessments: Core Elements and Considerations for Rapid Response (VideoEXIT) Kris Thayer, Director, Integrated Risk Information System (IRIS) Division of EPA’s National Center for Environmental Assessment (NCEA) 2017/11/16
High Throughput Transcriptomics (HTTr) Concentration-Response Screening in MCF7 Cells (VideoEXIT) Joshua Harrill, Toxicologist, EPA’s National Center for Computational Toxicology (NCCT) 2017/10/26
Learning Boolean Networks from ToxCast High-Content Imaging Data Todor Antonijevic, ORISE Postdoc, EPA’s National Center for Computational Toxicology (NCCT) 2017/09/28
Suspect Screening of Chemicals in Consumer Products Katherine Phillips, Research Chemist, Human Exposure and Dose Modeling Branch, Computational Exposure Division, EPA’s National Exposure Research Laboratory (NERHL) 2017/08/31
The EPA CompTox Chemistry Dashboard: A Centralized Hub for Integrating Data for the Environmental Sciences (VideoEXIT) Antony Williams, Chemist, EPA’s National Center for Computational Toxicology (NCCT) 2017/07/27
Navigating Through the Minefield of Read-Across Tools and Frameworks: An Update on Generalized Read-Across (GenRA)(VideoEXIT)

 

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Gamma Linolenic Acid (GLA) as a Therapeutic tool in the Management of Glioblastoma

Eric Fine* (1), Mike Briggs* (1,2), Raphael Nir# (1,2,3)

Sefacor, LLC (1); Woodland Pharmaceuticals, LLC (2); SBH Sciences, Inc (3). 

* These authors contributed equally; # Corresponding author (rnir@sbhsciences.com).

 

I. Introduction

 

Glioblastoma multiform is a fast-growing, invasive central nervous system tumor that forms from glial (supportive) tissue of the brain and spinal cord. Glioblastoma multiform also called glioblastoma or glioma along with grade III/IV astrocytoma and abbreviated herein and elsewhere as GBM. It usually occurs in adults and affects the brain more often than the spinal cord.  Brain tumor patients with GBM have a severely major unmet medical need. Current treatment for stage IV glioblastoma provides only 16-month median survival from time of diagnosis.

 

There has been and continues to be a tremendous amount of research with the goal of finding a cure for brain tumors, yet there are only 3 FDA approved drugs for this indication, BCNU in the form of Gliadel® wafers, temozolomide (Temodar®), since 2005 and most recently, 2009 bevacizumab (Avastin®; 10 mg/Kg intra venous) for recurrent GBM. Patients with grade IV glioma undergoing surgical resection of the tumor combined with radiation therapy (RT) to prevent any remaining cancer cells from regrowing have shown historical median survival of 11.5 to 12 months. The first FDA approved glioma treatment was the Gliadel wafer that is placed in the brain tumor bed after surgery, where it degrades, releasing the drug carmustine. This treatment that included surgery and radiation has been shown to extend the median survival of these patients to about 14 months approximately 2 months longer than the group that received placebo wafers (Westphal M, 2003, 2006), (Attenello FJ, 2008). However, the rate of complications, including an increase in cerebrospinal fluid leaks and intracranial hypertension, has limited their use (Nagpal S., 2012).  The current ‘gold standard’ treatment to which all new experimental treatments are compared is temozolomide. Patients with high grade glioma receiving surgery, temozolomide and radiation therapy have a mean survival of 14.5 to 16 months (Stupp R, 2005), (Grossman SA, 2010). Avastin (bevacizumab), is a humanized monoclonal antibody that inhibits vascular endothelial growth factor A (VEGF-A) administered by intravenous infusion and has been approved for treating the recurrence of glioma only after the cancer has become refractory to temozolomide (Cohen MH, 2009), (Chamberlain MC, 2010). Still, GBM remains one of the two worst-case scenarios in the spectrum of cancer, sharing with pancreatic cancer a less than 5% five-year survival rate.

 

Due to the current success of polyunsaturated fatty acid (PUFA) based therapeutics including Lovasa (GlaxoSmithKline/ Reliant Pharmaceuticals) and Vascepa (Amarin) for high triglycerides with mixed dyslipidemia, there seems to be a renewed interest in PUFA’s therapeutic effects in different disease indications, especially cancer.

 

The scientific literature reports various results for the many different PUFA forms and their affects in a wide variety of cancer cell line tests.  The use of PUFA in the clinical setting has shown a slight enhancement of tamoxifen treatment in breast cancer patients when taken as an oral supplement (Kenny FS, 2000). But the lack of clear clinical improvement predominates in most trials such as those for bladder cancer (Harris NM, 2002) and pancreatic cancer (Johnson CD, 2001). Intravenous infusion of the polyunsaturated fatty acid gamma linolenic acid (GLA) for pancreatic cancer patients had met with little success in extending these patients’ lives (Johnson CD, 2001).

We hypothesize that the systemic administration of PUFAs has had limited success in cancer treatment mainly due to their being highly protein bound in the blood upon infusion and the need for an apparently high local concentration in the vicinity of the cancer tissue. In the face of the confounding data for the utility of PUFAs in cancer treatment, our hypothesis has been supported by the promising results found in a small, but uncontrolled pilot clinical trial using a protocol entailing local application of GLA directly into the resected tumor bed of High Grade GBM patients (Das UN, 1995).

 

 

II.  Polyunsaturated fatty acids in Glioblastoma

 

Fatty acids are key nutrients that affect early growth and development, as well as chronic and other diseases. A fatty acid containing more than one carbon double bond is termed polyunsaturated fatty acid (PUFA). PUFA affect the prevalence and severity of cardiovascular disease, diabetes, inflammation, cancer, and age-related functional decline. PUFA are components of the structural phospholipids in cell membranes; they modulate cellular signaling, cellular interaction, and membrane fluidity. The two most important groups of PUFA are the Omega 3 and Omega 6 fatty acids. Alpha-linolenic acid (ALA or 18 : 3n-3) is the parent of Omega 3 fatty acids, and linoleic acid (LA or 18 : 2n-6), the parent of the n-6 PUFA family. The human body is unable to readily synthesize ALA, and LA, classifying them both as essential fatty acids that one must ingest in the diet.    LA and ALA are converted to their respective n-6 and n-3 PUFA families by a series of independent reactions of which both pathways require the same enzymes, Δ6 Desaturase and Δ5 Desaturase, for desaturation and elongation (Sprecher H, 2002).

 

Common polyunsaturated fatty acid forms tested for their anti-tumor effect include gamma linolenic acid (GLA), arachidonic acid (AA) from the n-6 series and eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) from the n-3 series. One of the most promising PUFA in the development of cancer therapeutics is the GLA.  GLA is a carboxylic acid with an 18-carbon chain and three cis double bonds. Although the cytotoxicity of GLA, AA, EA and DHA is very high in cancer cell-lines, GLA shows the greatest specificity of destroying only cancerous cells and leaving non-cancerous cells intact (Bégin ME, 1986) (Das UN, 1991). For this reason we will narrow the focus of this review to GLA.

 

In-Vitro analysis of GLA on various cancer cell lines

GLA has shown cytotoxicity to a number of cancer cell lines including breast (ZR-75-11), lung (A-549), prostate (PC-3) (Begin ME, 1986), pancreas (Ravichandran D, 2000), liver (Itoh S, 2010).   GLA was the most effective in selectively killing the tumor cells. In a co-culture experiment wherein normal human skin fibroblasts (CCD-41-SK) and human breast cancer cells (ZR-75-1) were grown together in a Petri dish and supplemented with GLA, only human breast cancer cells were eliminated without any effect on normal skin fibroblasts  (Bégin ME, 1986).

The studies outlined below focus on GBM:

Bell et al, (1999) examined the invasion and growth of cell spheroids of human GBM cell lines U87, U373 and MOG-G-CCM.  The spheroids were grown on collagen with up to 1 mM GLA for 5 days. Measurements showed that low concentrations of GLA (< 100uM) increased both apoptosis and proliferation while higher concentrations (>250 uM) significantly impaired spheroid growth. All spheroid preparations showed 100% growth inhibition after 5 days of culture with 500–1000 uM GLA. Similar experiments by Leaver HA et al, [2002a] found that the Lithium  (Li+) salt of GLA was more potent than GLA, most likely due to its increased solubility. Li+GLA showed statistically significant pro-apoptotic and anti-proliferative effects in C6 rat glioma cell line culture at 40 uM PUFA as observed using the MTT assay compared to nontreated controls.  Meglumine gammalinolenate (MeGLA) was also developed for enhancing the water solubility of the PUFA and it showed greater activity than Li+GLA (Ilc K, 1999). Work reported by Scheim (Scheim DE, 2009) on human cell cultures derived from human GBM biopsy treated with 500 uM GLA showed complete cytotoxicity to the cancerous cells, while maintaining complete viability in noncancerous cell organ cultures from human biopsy.

 

 

III. Mechanism of Action for GLA against cancer cells

The mechanisms by which PUFA act on normal and cancerous cells are complex and not well understood. In tumor cells, addition of PUFAs results in the generation of free radicals, enhancement of lipid peroxidation and the suppression of cell rescue proteins and pathways thereby leading to cell apoptosis.  However, in normal cells, supplementation of PUFAs produce adequate amounts of lipoxins, resolvins and protectins that protect the cells from free radicals and reactive oxygen species, suppress inflammation and prevent actions of mutagens and carcinogens (Das UN and Madhavi N, 2011).

 

  1. A.    Free radical generation:

In vitro experiments testing the cytotoxic effects of  PUFA has shown that GLA application induced lipid peroxidation products may have a high affinity to Bcl-2, an integral membrane oncoprotein that is unique in its ability to suppress apoptosis. This interaction prevents Bcl-2 from suppressing apoptosis even in cancer cells. Haldar et al (1995) concluded that Bcl-2 is deactivated upon phosphorylation and Bodur et al (2012), have shown that the exposure to 4-hydroxynonenal (HNE) the main aldehydic product of plasma LDL peroxidation induces Bcl-2 phosphorylation (Haldar S, 1995), (Bodur C, 2012).

To decipher the mechanism of the cytotoxic action of GLA and other fatty acids, cyclo-oxygenase, lipoxygenase inhibitors, and anti-oxidants and free radical quenchers have been added to cancer cell line cultures.  The GLA may induce different cell death pathways in different cell lines. In HeLa cells, indomethacin, a cyclo-oxygenase and inhibitor, and NDGA, a lipoxygenase inhibitor, that were added to cell cultures were ineffective in blocking the cytotoxic action of GLA and DHA (Das UN and Madhavi N, 2011).  However, SOD and Vitamin E, both free radical scavengers blocked the tumoricidal action of GLA on human cervical carcinoma, (HeLa) cells, human leukemia, HL-60 cells, breast cancer, ZR-75-1, cells (Das UN, 1991, 2007), (Sagar PS, 1995).   The increased production of free radicals by GLA treated cancer cells may be one of the reasons for enhanced cytotoxicity of glioma tumors seen in the pilot human clinical trials.

 

  1. B.    GLA influence on Angiogenesis:

Inclusion of GLA in a 3D matrix culture system of the rat aortic ring assay, significantly inhibited angiogenesis in a concentration-dependent manner and a significant reduction of vascular endothelial cell motility was observed (Cai J, 1999).  Localized administration of GLA to orthotopically implanted C6 glioma cell line in the rat brain decreased the tumor cell’s protein expression of the pro-angiogenic factor vascular endothelial growth factor (VEGF) by 71% (± 16%) and the VEGF receptor Flt1 by 57% (± 5.8%) (Miyake JA, 2009). The GLA treatment reduced the micro vessel density of the tumors by 41% compared to control tumors.  In addition, the GLA treatment caused a significant decrease in ERK1 and ERK2 protein expression of (27 ± 7.7%) and (31±8.7%), respectively. More recently, Miyake et al report that neoangiogenesis is regulated through the ERK1/2 pathway (Miyake M, 2013).

 

  1. C.    GLA influence on cancer related genes:

Miyake et al, [2009] examined the changes in cancer related gene expression in C6 glioma cells growing in rat brains when treated with local GLA brain infusion as compared to vehicle controls. The GLA treatment shows evidence for the upregulation of proteins that would inhibit cell cycle growth and division and induce apoptosis. The expression of p53 was increased (44 ±16%) by GLA as compared to control.

The tumor suppressor protein p53 has many mechanisms of anticancer function, playing a role in apoptosis, genomic stability, and inhibition of angiogenesis. The mechanisms by which p53 works include: activating DNA repair proteins when DNA has sustained damage; arresting growth by holding the cell cycle at the G1/S regulation point if DNA damage is recognized allowing for repair or it can initiate apoptosis, or it can initiate programmed cell death, if DNA damage proves to be irreparable (Liang Y, 2013).  Similarly, the expression of p27 (another tumor suppressor protein) was also increased (27 ± 7.3%) in GLA treated animals (Miyake JA, 2009).

 

  1. D.    Caspase:

Apoptosis is induced by caspase signaling pathways in many cells (Kim R, 2002) (Philchenkov A, 2004). One of the mechanisms of apoptosis involves a mitochondrial signaling pathway, which entails the efflux of cytochrome c from mitochondria to the cytosol (Ge H, 2009). Cytosolic cytochrome c together with Apaf-1 activates caspase-9, which then activates caspase-3 (Cain K, 2002), (Wang X, 2001). Caspase-3 play an important role in apoptosis and degrades proteins such as PARP, which is a nuclear enzyme implicated in many cellular process including apoptosis and DNA repair. Studies by Ge et al, (2009) suggest that GLA treatment induces a dose-dependent increase in cytochrome c and activation of caspase-3 that correlates with the apoptosis of human chronic myelogenous leukemia K562 cells (Kong X, 2006). Further, the apoptosis could be inhibited by a pan-caspase inhibitor (z-VAD-fmk) (Ge H, 2009).

 

  1. E.    Ku Proteins:

The heterodimeric Ku70/Ku80 protein complex is important for DNA repair and plays an important role in double strand breaks especially in gamma irradiation resistant tumor cells where high levels of these proteins are related to hyper proliferation and carcinogenesis (Gullo, 2006). Ku proteins have shown that loss or reduction in their expression causes increased DNA damage and micronucleus formation in the presence of radiation (Yang QS, 2008). GLA treatment of C6 rat glioma cells was accompanied by a 71% reduction in Ku80 protein expression and a 39% increase in the number of micronuclei detected by Hoechst fluorescence, as well as a 49% reduction of cells in S-phase even at concentrations that do not produce significant increases in apoptosis when measured within only a 24 hour exposure (Benadiba M, 2009).

 

 

  1. IV.  In Vivo effect of GLA

As previously discussed, GLA has been reported to have effects in many cancers in vivo with treatments ranging from direct anti-tumor activity in clinical studies with injected GLA to dietary supplementation as an adjuvant to more traditional chemotherapy (Fetrow CW, 1999) (Kleijnen J, 1994). There are a number of anecdotal reports of increased response and duration, but none of these studies have shown convincing evidence to support the continued use of GLA against any specific cancer subtype. In one small clinical pancreatic cancer study using an injectable form of GLA there was some apparent benefit (Fearon KC, 1996), which failed to be reproduced in a larger study (Johnson CD, 2001). Other tumor types for which there have been reports regarding use of GLA in cancer include breast cancer (Kenny FS, 2000, 2001), (Menendez JA, 2004, 2005) bladder cancer (Harris NM, 2002) and even leukemia (Kong X, 2009). In even earlier studies, PUFAs including GLA were shown to have some efficacy against both chemically induced skin carcinogenesis in mice (Ramesh G, 1998) and hepatocarcinoma models in rats (Ramesh G, 1995) although again, these studies were not definitive.  A recurring theme seems to be that for utility, the GLA needs to be present at reasonably high doses in the vicinity of the tumor, indicating the some form of local delivery must be considered, or perhaps some kind of targeted therapy.

 

A. GLA tumorcidal effect on rat glioma:

The Leaver group (Leaver HA, 2002 b) continued their work examining the effects of GLA treatment.  Rats with orthotopically placed C6 glioma tumor in their brains were locally infused with PBS vehicle or GLA solution from 200 uM to 2 mM. The most active was 2 mM, infused at 1 ul/hr over 7 days. In contrast 1mM total dose had no significant difference from the controls.  In the positive response group, tumor regression, increased apoptosis and decreased proliferation were observed. Minimal effects on normal neuronal tissue was detected, with the caveat that their methods were not comprehensive (see discussion on safety, section IV.B. and Conclusion discussion, section VI). Tumor volume was less than 50% of controls in the 2 mM infused rats. However, histology and TUNEL reactivity of the remaining tumor indicated that this may be an under-estimate of residual viable tumor as substantial areas of treated tumors showed characteristics of necrotic tissue and apoptotic cell death. Supporting this hypothesis, tumor tissue sections evaluated by IHC with the proliferative marker Ki67 in the 2mM GLA treated animals showed < 20% of PBS control expression. Note: in these experiments there was no initial debulking surgery of the tumor mass.

Further studies by Miyake JA et al, (2009) showed that increasing the concentration of GLA delivered to the implanted C6 cell glioma in rat brains by treating them with 5 mM GLA/d in cerebrospinal fluid (CSF) caused an even greater decrease in C6 tumor growth in vivo. The average tumor area was reduced by 75 ± 8.8% in comparison with CSF alone.  VEGF protein expression was reduced 77 ± 16%. GLA had an inhibitory effect on vessel number causing a 44 ± 5.4% reduction in tumor micro vessel density.

While the in vivo data have a mixed response when looking at different tumor types and delivery methods, it appears that there may be some utility in GBM, particularly when the drug is delivered locally.  Further exploration of delivery methods for GBM and other tumor types need to be explored including the use of more targeted therapies such as targeted nano-particle delivery and even antibody-drug conjugates (ADC).  The research models also need to reinforce and support if possible the clinical observation of efficacy seen with direct intratumoral (or resected cavity) delivery noted in previous studies carried out in India.

 

B. Safety Studies in the Canine Model:

A safety study in 3 healthy dogs showed that daily injection of 0.25 mg in 1ml of saline for six days into the brain parenchyma under aseptic conditions was found to be safe (Das U N, 1995). CT scan and gross examination of the meninges and subarachnoid space as well as histopathological exams showed no abnormality and no difference between injected side and non-injected side. None of the animals developed any side effects or complications due to the procedure or GLA injection. Note that humans were given 1 mg GLA per day (see next section).  These are at best preliminary findings and further evaluation of safety in normal brain tissues and CSF need to be considered.

 

  1. V.            Clinical application of GLA for Glioma Patients

The most compelling argument for the usefulness of GLA in the treatment of glioblastoma comes from a series of open label, non-randomized trials that were run in India by Drs. Das and Reddy nearly 2 decades ago.  In these studies, summarized below, they found that direct administration of the GLA to the tumor site via infusion over several days provided no observable toxicities or side effects although there were not complete cognitive or behavioral studies done on the patients.  It remains to be shown that there are no significant liabilities to the administration of GLA to brain cancer patients to provide both an extension of life (overall survival benefit) as well as not impinging on the quality of life for the patient.

 

  1. A.    Recurrent glioma patients:

The initial study treating patients with local administration of GLA was performed on patients with recurrent GBM. GLA was injected directly into the tumor and/or an Ommaya reservoir was used to deliver the GLA to the tumor bed after surgical tumor resection followed by standard RT (see Naidu MR , 1992).  This procedure not only showed substantial efficacy but also there were no drug related side effects. Although only a small group of 6 patients, 3 of the 6 were alive at their last follow-up check-in 2 yrs 4 months to 2 yrs 8 months. These patients with recurrent glioma when administered the GLA therapy were in critical condition with life expectancy of 9 months or less. A 50 % survival at ~ 2.5 yrs is much better than historic average of 27% survival at 2 years in primary glioma patients with what is now the “gold standard” treatment of radiation and temozolomide and thus warranted further study.

 

  1. B.    GLA treatment of primary tumor patients:

The next study performed was on patients with grade III Astrocytoma and Grade IV glioblastoma receiving their first intervention. Patients underwent neurosurgery to remove as much of tumor as possible. Before closure of the dura, 1 mg GLA was instilled into the tumor bed and cerebral catheter and reservoir were positioned for subsequent injections. On day 7 post operation, a baseline CT brain scan was taken. One mg daily of GLA in 2-3 ml of sterile saline was instilled for 10 days before a repeat CT scan was taken for comparison  This procedure not only showed substantial efficacy but also there were no drug related side effects. Surgery plus RT supplemented with GLA treatment extended patient survival for 80% of treated patients (12/15) to 34 months with very limited drug-related side effects (Das U N, 1995).

 

  1. VI.           Conclusion

As some of the patients (Trial B, above) were alive and apparently well more than 2 years after receiving treatment, it is rather incredible that this treatment has not been more widely tested in the west in the last 18 years.  It is likely due to the fact that no robust and reproducible preclinical studies have come forward and that more standard GLP toxicology studies were not done.  Safety needs to be the first concern and whether in rats, dogs or monkeys, if direct delivery of GLA to the brain cavity is the best treatment, then it is imperative to have these studies carried out with a full analysis of both histopathological findings as well as the more indirect cognitive and behavioral studies that will be very important in human therapy.  As direct delivery to the brain is not a typical therapeutic approach, it remains to be seen what the regulatory agencies will demand for this kind of novel treatment.  The most pressing need is to have a thorough assessment of normal brain tissue exposure at the doses that are likely to be administered to a human and to include some surgical intervention (slicing through the brain) to mimic the surgical resection of the glioma.  Thus just delivering to the cerebrospinal fluid, while an intermediate assessment tool, may not have full predictive value for the adjuvant application of GLA in the treatment of glioblastoma.  For true safety studies, multiples of the minimum efficacious dose would ideally be done to ensure that there is a safety margin for dose administration errors.  These studies are enabled by Alzet mini-pump technologies as well as direct cannulation and a sterile port for the daily administration of drugs to the test subject.

As systemic exposures will be minimized from direct brain delivery of small amounts such as the 1-2 mg per day in the referenced trials, there would be almost no way to evaluate for typical toxicology organ effects, coupled with the fact that GLA is an endogenous component of fatty acid metabolism.  With drugs such as Gliadel® having been used, with its poor safety profile (Based on Pharmacy Codes: The oral LD50 in rat and mouse are 20 mg/kg and 45 mg/kg, respectively. Side effects include leukopenia, thrombocytopenia, and nausea.) Toxic effects include pulmonary fibrosis and bone marrow toxicity). Moreover, recent studies showing combining carmustine with temozolomide reduces survival time compared to temozolomide alone (Prados MD, 2004). The safety hurdle is fairly low for this devastating and fast growing tumor, however, that is not an excuse to forgo the safety studies that apparently were casually done previously and have kept this potential therapy out of the mainstream medicine for the past 18 years.

Taken together, these reports from the intriguing conundrum provided by the various outcomes of the animal efficacy studies to the patient feeding studies and the various delivery routes tested suggest that there is some rationale for utility of GLA in the treatment of cancer. Disciplined and well-controlled studies need to be undertaken with GLA / GLA salt or derivative forms of GLA that may have better pharmaceutical properties coupled with optimal delivery of the agent to the tumor with or without another therapy (chemotherapy or electrical field therapy ).

REFERENCES

Attenello FJ, Mukherjee D, Datoo G, McGirt MJ, Bohan E, Weingart JD, Olivi A, Quinones-Hinojosa A, Brem H. “Use of Gliadel (BCNU) wafer in the surgical treatment of malignant glioma: a 10-year institutional experience.” Ann Surg Oncol. 15.10 (2008): 2887-93.

Bégin ME, Ells G, Das UN, Horrobin DF. “Differential killing of human carcinoma cells supplemented with n-3 and n-6 polyunsaturated fatty acids.” J Natl Cancer Inst. 77.5 (1986): 1053-62.

Bell HS, Wharton SB, Leaver HA, Whittle IR. “Effects of N-6 essential fatty acids on glioma invasion and growth: experimental studies with glioma spheroids in collagen gels.” J Neurosurg. 91.6 (1999): 989-96.

Benadiba M, Miyake JA, Colquhoun A. “Gamma-linolenic acid alters Ku80, E2F1, and bax expression and induces micronucleus formation in C6 glioma cells in vitro.” IUBMB Life. 61.3 (2009): 244-51.

Bodur C, Kutuk O, Tezil T, Basaga H. “Inactivation of Bcl-2 through IκB kinase (IKK)-dependent phosphorylation mediates apoptosis upon exposure to 4-hydroxynonenal (HNE).” J Cell Physiol. 227.11 (2012): 3556-65.

Cai J, Jiang WG, Mansel RE. “Inhibition of angiogenic factor- and tumour-induced angiogenesis by gamma linolenic acid.” Prostaglandins Leukot Essent Fatty Acids. 60.1 (1999): 21-9.

Cain K, Bratton SB, Cohen GM. “The Apaf-1 apoptosome: a large caspase-activating complex.” Biochimie. 84.2-3 (2002): 203-14.

Chamberlain MC, Johnston SK. “Salvage therapy with single agent bevacizumab for recurrent glioblastoma.” J Neurooncol. 96.2 (2010): 259-69.

Cohen MH, Shen YL, Keegan P, Pazdur R. “FDA drug approval summary: bevacizumab (Avastin) as treatment of recurrent glioblastoma multiforme.” Oncologist. 14.11 (2009): 1131-8.

Das UN. “Tumoricidal action of cis-unsaturated fatty acids and their relationship to free radicals and lipid peroxidation.” Cancer Lett. 56.3 (1991): 235-43.

Das UN, Prasad V, Reddy D R. “Local application of gamma-linolenic acid in the treatment of human gliomas.” Cancer Lett 94 (1995): 147-155.

Das UN. “Gamma-linolenic acid therapy of human glioma-a review of in vitro, in vivo, and clinical studies.” Med Sci Monit. 13.7 (2007): RA119-31.

Das UN and Madhavi N. “Effect of polyunsaturated fatty acids on drug sensitive and resistant tumor cells in vitro.” Lipids in Health and Disease 10.1 (2011): 159.

Fearon KC, Falconer JS, Ross JA, Carter DC, Hunter JO, Reynolds PD, Tuffnell Q. “An open-label phase I/II dose escalation study of the treatment of pancreatic cancer using lithium gammalinolenate.” Anticancer Res. 16.2 (1996): 867-74.

Fetrow CW, Avila JR. Professional’s Handbook of Complementary and Alternative Medicines. Springhouse, PA: Springhouse Corp, 1999.

Ge H, Kong X, Shi L, Hou L, Liu Z, Li P. “Gamma-linolenic acid induces apoptosis and lipid peroxidation in human chronic myelogenous leukemia K562 cells.” Cell Biol Int 33.3 (2009): 402-10.

Grossman SA, Ye X, Piantadosi S, Desideri S, Nabors LB, Rosenfeld M, Fisher J and NABTT CNS Consortium. “Survival of patients with newly diagnosed glioblastoma treated with radiation and temozolomide in research studies in the United States.” Clin Cancer Res. 16.8 (2010): 2443-9.

Gullo, C., Au, M., Feng, G., and Teoh, G. “The biology of Ku and its potential oncogenic role in cancer.” Biochim. Biophys. Acta 1765.2 (2006): 223-34.

Haldar S, Jena N, Croce CM. “Inactivation of Bcl-2 by phosphorylation.” Proc Natl Acad Sci U S A. 92.10 (1995): 4507-11.

Harris NM, Crook TJ, Dyer JP, Solomon LZ, Bass P, Cooper AJ, Birch BR. “Intravesical meglumine gamma-linolenic acid in superficial bladder cancer: An efficacy study.” Eur Urol. 42.1 (2002): 39-42.

Ilc K, Ferrero JM, Fischel JL, Formento P, Bryce R, Etienne MC, Milano G. “Cytotoxic effects of two gamma linoleic salts (lithium gammalinolenate or meglumine gammalinolenate) alone or associated with a nitrosourea: an experimental study on human glioblastoma cell lines.” Anticancer Drugs. 10.4 (1999): 413-17.

Itoh S, Taketomi A, Harimoto N, Tsujita E, Rikimaru T, Shirabe K, Shimada M, Maehara Y. “Antineoplastic effects of gamma linolenic Acid on hepatocellular carcinoma cell lines.” J Clin Biochem Nutr. 47.1 (2010): 81-90.

Johnson CD, Puntis M, Davidson N, Todd S, Bryce R. “Randomized, dose-finding phase III study of lithium gamolenate in patients with advanced pancreatic adenocarcinoma.” Br J Surg. 88.5 (2001): 662-8.

Kenny FS, Pinder SE, Ellis IO, Gee JM, Nicholson R and Bryce RP, Robertson JF. “Gamma linolenic acid with tamoxifen as primary therapy in breast cancer.” Int J Cancer. 85.5 (2000): 643-8.

Kenny FS, Gee JM, Nicholson RI, Ellis IO, Morris TM, Watson SA, Bryce RP, Robertson JF. “Effect of dietary GLA+/-tamoxifen on the growth, ER expression and fatty acid profile of ER positive human breast cancer xenografts.” Int J Cancer 92.3 (2001): 342-7.

Kim R, Tanabe K, Uchida Y, Emi M, Inoue H, Toge T. “Current status of the molecular mechanisms of anticancer drug-induced apoptosis. The contribution of molecular-level analysis to cancer chemotherapy.” Cancer Chemother Pharmacol. 50.5 (2002): 343-52.

Kleijnen J. “Evening primrose oil.” BMJ 309 (1994): 824-5.

Kong X, Ge H, Hou L, Shi L, Liu Z. “Induction of apoptosis in K562/ ADM cells by gamma-linolenic acid involves lipid peroxidation and activation of caspase-3.” Chem Biol Interact. 162 (2006): 140-48.

Kong X, Ge H, Chen L, Liu Z, Yin Z, Li P, Li M. “Gamma-linolenic acid modulates the response of multidrug-resistant K562 leukemic cells to anticancer drugs.” Toxicology in Vitro 23.4 (2009): 634-9.

Leaver HA, Bell HS, Rizzo MT, Ironside JW, Gregor A,Wharton SB, Whittle IRl. “Antitumour and pro-apoptotic actions of highly unsaturated fatty acids in glioma.” Prostaglandins, Leukotr. Ess. Fatty Acids 66.1 (2002): 19-29.

Leaver HA, Wharton SB, Bell HS, Leaver-Yap IM, Whittie IR. “Highly unsaturated fatty acid induced tumour regression in glioma pharmacodynamics and bio-availability of gamma linolenic acid in an implantation glioma model: effects on tumour biomass, apoptosis and neuronal tissue histology.” Prostaglandins Leukot Ess. Fatty Acids 67.5 (2002 b): 283-92.

Liang Y, Liu J, Feng Z. “The regulation of cellular metabolism by tumor suppressor p53.” Cell Biosci. 3.1 (2013): 9.

Menendez JA, Ropero S, Lupo R, Colmer R. “Omega-6 polyunsaturated fatty acid gamma-linolenic acid (18:3n-6) enhances docetaxel (Taxotere) cytotoxicity in human breast carcinoma cells: Relationship to lipid peroxidation and HER-2/neu expression.” Oncology Reports. 2004;11:1241-1252., 11.6 (2004): 1241-52.

Menendez JA, Vellon L, Colomer R, Lupu R. “Effect of gamma-linolenic acid on the transcriptional activity of the Her-2/neu (erbB-2) oncogene.” J Natl Cancer Inst. (2005): 1611-15.

Miyake JA, Benadiba M, Colquhoun A. “Gamma-linolenic acid inhibits both tumour cell cycle progression and angiogenesis in the orthotopic C6 glioma model through changes in VEGF, Flt1, ERK1/2, MMP2, cyclin D1, pRb, p53 and p27 protein expression.” Lipids Health Dis. 8 (2009): 8.

Miyake M, Goodison S, Urquidi V, Gomes Giacoia E, Rosser CJ. “Expression of CXCL1 in human endothelial cells induces angiogenesis through the CXCR2 receptor and the ERK1/2 and EGF pathways.” Lab Invest. 93.7 (2013): 768-78.

Nagpal S. “The role of BCNU polymer wafers (Gliadel) in the treatment of malignant glioma.” Neurosurg Clin N Am 23.2 (2012): 289-95.

Naidu MR,  Das UN, Kishan A. Intratumoral gamma-linolenic acid therapy of human gliomas.

Prostglandins Leukotrienes and Essential Fatty Acids (1992): Vol. 45, 181-184

Philchenkov A. “Caspases: potential targets for regulating cell death.” J Cell Mol Med. 8.4 (2004): 432-44.

Prados MD, Yung WK, Fine HA, Greenberg HS, Junck L, Chang SM, Nicholas MK, Robins HI, Mehta MP, Fink KL, Jaeckle KA, Kuhn J, Hess KR, Schold SC Jr; study, North American Brain Tumor Consortium. “Phase 2 study of BCNU and temozolomide for recurrent glioblastoma multiforme: North American Brain Tumor Consortium study.” Neuro Oncol. 6.1 (2004):33-7.

Ramesh G, Das UN. “Effect of dietary fat on diethylnitrosamine induced hepatocarcinogenesis in Wistar rats.” Cancer Lett. 95.1-2 (1995): 237-45.

Ramesh G, Das UN. “Effect of evening primrose and fish oils on two-stage skin carcinogenesis in mice.” Prostaglandins Leukot Essent Fatty Acids. 59.3 (1998): 155-61.

Ravichandran D, Cooper A, Johnson CD. “Effect of lithium gamma-linolenate on the growth of experimental human pancreatic carcinoma.” Eur J Cancer. 36.3 (2000): 423-7.

Scheim DE. “Cytotoxicity of unsaturated fatty acids in fresh human tumor explants: concentration thresholds and implications for clinical efficacy.” Lipids in Health and Disease 8:54 (2009).

Sagar PS, Das UN. “Cytotoxic action of cis-unsaturated fatty acids on human cervical carcinoma (HeLa) cells in vitro.” Prostaglandins Leukot Ess. Fatty Acids 53.4 (1995): 287-99

Sprecher H. “The roles of anabolic and catabolic reactions in the synthesis and recycling of polyunsaturated fatty acids.” Prostaglandins Leukot Essent Fatty Acids 67.2-3 (2002): 79-83.

Stupp R, Mason WP, van den Bent MJ, Weller M, Fisher B, Taphoorn MJ, Belanger K, Brandes AA, Marosi C, Bogdahn U, Curschmann J, Janzer RC, Ludwin SK, Gorlia T, Allgeier A, Lacombe D, Cairncross JG, Eisenhauer E, Mirimanoff RO and European Organisation for Re for Research and Treatment of Cancer Brain Tumor and Radiotherapy Groups and the National Cancer Institute of Canada Clinical Trials Group. “Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma.” N Engl J Med 352.10 (2005): 987-96.

Wang, X. “The expanding role of mitochondria in apoptosis.” Genes Dev 15.22 (2001): 2922-33.

Westphal M, Hilt DC, Bortey E, Delavault P, Olivares R, Warnke PC, Whittle IR, Jääskeläinen J, Ram Z. “A phase 3 trial of local chemotherapy with biodegradable carmustine (BCNU) wafers (Gliadel wafers) in patients with primary malignant glioma.” Neuro Oncol. 5.2 (2003): 79-88.

Westphal M, Ram Z, Riddle V, Hilt D, Bortey E and Executive Committee of the Gliadel Study Group. “Gliadel wafer in initial surgery for malignant glioma: long-term follow-up of a multicenter controlled trial.” Acta Neurochir (Wien). 48.3 (2006): 269-75.

Yang QS, Gu JL, Du LQ, Jia LL, Qin LL, Wang Y, Fan FY. “ShRNA-mediated Ku80 gene silencing inhibits cell proliferation and sensitizes to gamma-radiation and mitomycin C induced apoptosis in esophageal squamous cell carcinoma lines.” J Radiat Res. 49.4 (2008): 399-407.

 

 

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