Blog
About

  • Record: found
  • Abstract: found
  • Article: found
Is Open Access

CLC-Pred: A freely available web-service for in silico prediction of human cell line cytotoxicity for drug-like compounds

Read this article at

Bookmark
      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

      Abstract

      In silico methods of phenotypic screening are necessary to reduce the time and cost of the experimental in vivo screening of anticancer agents through dozens of millions of natural and synthetic chemical compounds. We used the previously developed PASS (Prediction of Activity Spectra for Substances) algorithm to create and validate the classification SAR models for predicting the cytotoxicity of chemicals against different types of human cell lines using ChEMBL experimental data. A training set from 59,882 structures of compounds was created based on the experimental data (IG50, IC50, and % inhibition values) from ChEMBL. The average accuracy of prediction (AUC) calculated by leave-one-out and a 20-fold cross-validation procedure during the training was 0.930 and 0.927 for 278 cancer cell lines, respectively, and 0.948 and 0.947 for cytotoxicity prediction for 27 normal cell lines, respectively. Using the given SAR models, we developed a freely available web-service for cell-line cytotoxicity profile prediction (CLC-Pred: Cell-Line Cytotoxicity Predictor) based on the following structural formula: http://way2drug.com/Cell-line/.

      Related collections

      Most cited references 48

      • Record: found
      • Abstract: found
      • Article: not found

      Cancer statistics, 2015.

      Each year the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival. Incidence data were collected by the National Cancer Institute (Surveillance, Epidemiology, and End Results [SEER] Program), the Centers for Disease Control and Prevention (National Program of Cancer Registries), and the North American Association of Central Cancer Registries. Mortality data were collected by the National Center for Health Statistics. A total of 1,658,370 new cancer cases and 589,430 cancer deaths are projected to occur in the United States in 2015. During the most recent 5 years for which there are data (2007-2011), delay-adjusted cancer incidence rates (13 oldest SEER registries) declined by 1.8% per year in men and were stable in women, while cancer death rates nationwide decreased by 1.8% per year in men and by 1.4% per year in women. The overall cancer death rate decreased from 215.1 (per 100,000 population) in 1991 to 168.7 in 2011, a total relative decline of 22%. However, the magnitude of the decline varied by state, and was generally lowest in the South (∼15%) and highest in the Northeast (≥20%). For example, there were declines of 25% to 30% in Maryland, New Jersey, Massachusetts, New York, and Delaware, which collectively averted 29,000 cancer deaths in 2011 as a result of this progress. Further gains can be accelerated by applying existing cancer control knowledge across all segments of the population. © 2015 American Cancer Society.
        Bookmark
        • Record: found
        • Abstract: found
        • Article: not found

        The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease.

        To pursue a systematic approach to the discovery of functional connections among diseases, genetic perturbation, and drug action, we have created the first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules, together with pattern-matching software to mine these data. We demonstrate that this "Connectivity Map" resource can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs. These results indicate the feasibility of the approach and suggest the value of a large-scale community Connectivity Map project.
          Bookmark
          • Record: found
          • Abstract: found
          • Article: not found

          Systematic identification of genomic markers of drug sensitivity in cancer cells

          Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers of response to targeted agents. To uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines, which represent much of the tissue-type and genetic diversity of human cancers, with 130 drugs under clinical and preclinical investigation. In aggregate, we found mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing’s sarcoma cells harboring the EWS-FLI1 gene translocation to PARP inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.
            Bookmark

            Author and article information

            Affiliations
            [1 ] Department for Bioinformatics, Institute of Biomedical Chemistry, Moscow, Russia
            [2 ] Department for Bioinformatics, Medico-Biologic Faculty, Pirogov Russian National Research Medical University, Moscow, Russia
            [3 ] Centre for Molecular Modeling, CSIR-Indian Institute of Chemical Technology, Hyderabad, India
            Wayne State University, UNITED STATES
            Author notes

            Competing Interests: The authors have declared that no competing interests exist.

            Contributors
            ORCID: http://orcid.org/0000-0003-1757-8004, Role: Conceptualization, Role: Funding acquisition, Role: Methodology, Role: Project administration, Role: Supervision, Role: Validation, Role: Writing – original draft, Role: Writing – review & editing
            Role: Data curation, Role: Investigation, Role: Validation, Role: Writing – original draft
            Role: Investigation, Role: Software, Role: Visualization
            Role: Data curation, Role: Formal analysis, Role: Investigation, Role: Methodology, Role: Resources, Role: Validation, Role: Visualization, Role: Writing – original draft
            Role: Formal analysis, Role: Resources, Role: Software, Role: Visualization
            Role: Data curation, Role: Formal analysis, Role: Investigation
            Role: Formal analysis, Role: Funding acquisition, Role: Investigation, Role: Software, Role: Validation
            Role: Formal analysis, Role: Methodology, Role: Writing – review & editing
            Role: Conceptualization, Role: Formal analysis, Role: Investigation, Role: Project administration, Role: Resources, Role: Supervision, Role: Writing – original draft, Role: Writing – review & editing
            Role: Editor
            Journal
            PLoS One
            PLoS ONE
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, CA USA )
            1932-6203
            25 January 2018
            2018
            : 13
            : 1
            29370280
            5784992
            10.1371/journal.pone.0191838
            PONE-D-17-36975
            (Editor)
            © 2018 Lagunin et al

            This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

            Counts
            Figures: 1, Tables: 3, Pages: 13
            Product
            Funding
            Funded by: funder-id http://dx.doi.org/10.13039/501100006769, Russian Science Foundation;
            Award ID: 16-45-02012
            Award Recipient : ORCID: http://orcid.org/0000-0003-1757-8004
            Funded by: funder-id http://dx.doi.org/10.13039/501100006769, Russian Science Foundation;
            Award ID: 16-45-02012
            Award Recipient :
            Funded by: funder-id http://dx.doi.org/10.13039/501100006769, Russian Science Foundation;
            Award ID: 16-45-02012
            Award Recipient :
            Funded by: funder-id http://dx.doi.org/10.13039/501100006769, Russian Science Foundation;
            Award ID: 16-45-02012
            Award Recipient :
            Funded by: funder-id http://dx.doi.org/10.13039/501100006769, Russian Science Foundation;
            Award ID: 16-45-02012
            Award Recipient :
            Funded by: funder-id http://dx.doi.org/10.13039/501100006769, Russian Science Foundation;
            Award ID: 16-45-02012
            Award Recipient :
            Funded by: Department of Science & Technology (IN)
            Award ID: INT/RUS/RSF/12
            Award Recipient :
            Funded by: funder-id http://dx.doi.org/10.13039/501100006769, Russian Science Foundation;
            Award ID: 16-45-02012
            Award Recipient :
            This work was supported by Russian Science Foundation ( http://rscf.ru/en) - Department of Science & Technology (India, http://www.dst.gov.in/) grant № 16-45-02012 - INT/RUS/RSF/12. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
            Categories
            Research Article
            Biology and Life Sciences
            Toxicology
            Cytotoxicity
            Medicine and Health Sciences
            Pathology and Laboratory Medicine
            Toxicology
            Cytotoxicity
            Biology and Life Sciences
            Cell Biology
            Cellular Types
            Animal Cells
            Connective Tissue Cells
            Fibroblasts
            Biology and Life Sciences
            Anatomy
            Biological Tissue
            Connective Tissue
            Connective Tissue Cells
            Fibroblasts
            Medicine and Health Sciences
            Anatomy
            Biological Tissue
            Connective Tissue
            Connective Tissue Cells
            Fibroblasts
            Biology and Life Sciences
            Developmental Biology
            Organism Development
            Organogenesis
            Lung Development
            Medicine and Health Sciences
            Oncology
            Cancers and Neoplasms
            Lung and Intrathoracic Tumors
            Medicine and Health Sciences
            Oncology
            Cancer Treatment
            Medicine and Health Sciences
            Oncology
            Cancers and Neoplasms
            Lung and Intrathoracic Tumors
            Secondary Lung Tumors
            Medicine and Health Sciences
            Oncology
            Cancers and Neoplasms
            Carcinomas
            Adenocarcinomas
            Adenocarcinoma of the Lung
            Medicine and Health Sciences
            Oncology
            Cancers and Neoplasms
            Lung and Intrathoracic Tumors
            Adenocarcinoma of the Lung
            Medicine and Health Sciences
            Oncology
            Cancers and Neoplasms
            Lung and Intrathoracic Tumors
            Non-Small Cell Lung Cancer
            Custom metadata
            All relevant data are within the paper and its Supporting Information files and also from http://www.way2drug.com/cell-line/.

            Uncategorized

            Comments

            Comment on this article