Abstract
Aim and Objective: The number of anticancer drugs available currently is limited, and some of them have low treatment response rates. Moreover, developing a new drug for cancer therapy is labor intensive and sometimes cost prohibitive. Therefore, “repositioning” of known cancer treatment compounds can speed up the development time and potentially increase the response rate of cancer therapy. This study proposes a systems biology method for identifying new compound candidates for cancer treatment in two separate procedures.
Materials and Methods: First, a “gene set–compound” network was constructed by conducting gene set enrichment analysis on the expression profile of responses to a compound. Second, survival analyses were applied to gene expression profiles derived from four breast cancer patient cohorts to identify gene sets that are associated with cancer survival. A “cancer–functional gene set– compound” network was constructed, and candidate anticancer compounds were identified. Through the use of breast cancer as an example, 162 breast cancer survival-associated gene sets and 172 putative compounds were obtained.
Results: We demonstrated how to utilize the clinical relevance of previous studies through gene sets and then connect it to candidate compounds by using gene expression data from the Connectivity Map. Specifically, we chose a gene set derived from a stem cell study to demonstrate its association with breast cancer prognosis and discussed six new compounds that can increase the expression of the gene set after the treatment.
Conclusion: Our method can effectively identify compounds with a potential to be “repositioned” for cancer treatment according to their active mechanisms and their association with patients’ survival time.
Keywords: Drug reposition, expression profiling, connectivity map, breast cancer, gene set analysis, anticancer drugs.
Combinatorial Chemistry & High Throughput Screening
Title:Utilizing Cancer - Functional Gene Set - Compound Networks to Identify Putative Drugs for Breast Cancer
Volume: 21 Issue: 2
Author(s): Tzu-Hung Hsiao, Yu-Chiao Chiu, Yu-Heng Chen, Yu-Ching Hsu, Hung-I Harry Chen, Eric Y. Chuang*Yidong Chen*
Affiliation:
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University,Taiwan
- Greehey Children's Cancer Research Institute, University of Texas Health Science Center, San Antonio, TX,United States
Keywords: Drug reposition, expression profiling, connectivity map, breast cancer, gene set analysis, anticancer drugs.
Abstract: Aim and Objective: The number of anticancer drugs available currently is limited, and some of them have low treatment response rates. Moreover, developing a new drug for cancer therapy is labor intensive and sometimes cost prohibitive. Therefore, “repositioning” of known cancer treatment compounds can speed up the development time and potentially increase the response rate of cancer therapy. This study proposes a systems biology method for identifying new compound candidates for cancer treatment in two separate procedures.
Materials and Methods: First, a “gene set–compound” network was constructed by conducting gene set enrichment analysis on the expression profile of responses to a compound. Second, survival analyses were applied to gene expression profiles derived from four breast cancer patient cohorts to identify gene sets that are associated with cancer survival. A “cancer–functional gene set– compound” network was constructed, and candidate anticancer compounds were identified. Through the use of breast cancer as an example, 162 breast cancer survival-associated gene sets and 172 putative compounds were obtained.
Results: We demonstrated how to utilize the clinical relevance of previous studies through gene sets and then connect it to candidate compounds by using gene expression data from the Connectivity Map. Specifically, we chose a gene set derived from a stem cell study to demonstrate its association with breast cancer prognosis and discussed six new compounds that can increase the expression of the gene set after the treatment.
Conclusion: Our method can effectively identify compounds with a potential to be “repositioned” for cancer treatment according to their active mechanisms and their association with patients’ survival time.
Export Options
About this article
Cite this article as:
Hsiao Tzu-Hung , Chiu Yu-Chiao , Chen Yu-Heng, Hsu Yu-Ching , Chen Harry Hung-I , Chuang Y. Eric*, Chen Yidong *, Utilizing Cancer - Functional Gene Set - Compound Networks to Identify Putative Drugs for Breast Cancer, Combinatorial Chemistry & High Throughput Screening 2018; 21 (2) . https://dx.doi.org/10.2174/1574888X13666180105125347
DOI https://dx.doi.org/10.2174/1574888X13666180105125347 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
Call for Papers in Thematic Issues
Artificial Intelligence Methods for Biomedical, Biochemical and Bioinformatics Problems
Recently, a large number of technologies based on artificial intelligence have been developed and applied to solve a diverse range of problems in the areas of biomedical, biochemical and bioinformatics problems. By utilizing powerful computing resources and massive amounts of data, methods based on artificial intelligence can significantly improve the ...read more
Eco-friendly Agents for Biological Control of Pathogenic Diseases
The discovery of an alternative biological approach to disease management includes work on medicinal products derived from natural sources as a starting point for the development of eco-friendly agents for these diseases and the injuries they cause, as well as reducing human contact with hazardous chemicals and their residues. We ...read more
Emerging trends in diseases mechanisms, noble drug targets and therapeutic strategies: focus on immunological and inflammatory disorders
Recently infectious and inflammatory diseases have been a key concern worldwide due to tremendous morbidity and mortality world Wide. Recent, nCOVID-9 pandemic is a good example for the emerging infectious disease outbreak. The world is facing many emerging and re-emerging diseases out breaks at present however, there is huge lack ...read more
Exploring Spectral Graph Theory in Combinatorial Chemistry
Scope of the Thematic Issue: Combinatorial chemistry involves the synthesis and analysis of a large number of diverse compounds simultaneously. Traditional methods rely on brute force experimentation, which can be time-consuming and resource-intensive. Spectral Graph Theory, a branch of mathematics dealing with the properties of graphs in relation to the ...read more
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Snake Venom Metalloproteinases: Structure, Mechanism and Induced Diseases
Current Chemical Biology Modification of Taxane A Ring via Manoeuvering of the C-11 Double Bond of 10-Deacetylbaccatin III to Get Novel Rearranged Taxoids
Letters in Organic Chemistry The Role of Oxidative Stress Modulators in Breast Cancer
Current Medicinal Chemistry Brain Targeting of siRNA via Intranasal Pathway
Current Pharmaceutical Design Rheb/mTOR Activation and Regulation in Cancer: Novel Treatment Strategies beyond Rapamycin
Current Drug Targets Taxotere Chemosensitivity Evaluation in Rat Breast Tumor by Multimodal Imaging: Quantitative Measurement by Fusion of MRI, PET Imaging with MALDI and Histology
Recent Patents on Medical Imaging Clinical Pharmacogenetics and Potential Application in Personalized Medicine
Current Drug Metabolism Computational Models for 5αR Inhibitors for Treatment of Prostate Cancer: Review of Previous Works and Screening of Natural Inhibitors of 5αR2
Current Computer-Aided Drug Design Cause and Consequences of Genetic and Epigenetic Alterations in Human Cancer
Current Genomics Approaches to Gastrointestinal Cytoprotection: From Isolated Cells, Via Animal Experiments to Healthy Human Subjects and Patients with Different Gastrointestinal Disorders
Current Pharmaceutical Design Update to: The Aryl Hydrocarbon Receptor in Anticancer Drug Discovery: Friend or Foe?
Medicinal Chemistry Reviews - Online (Discontinued) Ellagic Acid Enhances the Efficacy of PI3K Inhibitor GDC-0941 in Breast Cancer Cells
Current Molecular Medicine Aptamers: Molecular Tools for Medical Diagnosis
Current Topics in Medicinal Chemistry Design, Synthesis and Anticancer Evaluation of Acetamides Comprising 1,2,3-triazole, 1,3,4-thiadiazole and Isothiazolo[4,3-b]pyridine Rings
Letters in Organic Chemistry Matrix Metalloproteinase Knockout Studies and the Potential Use of Matrix Metalloproteinase Inhibitors in the Rheumatic Diseases
Current Drug Targets - Inflammation & Allergy Overcoming Cell Death and Tau Phosphorylation Mediated by PI3KInhibition: A Cell Assay to Measure Neuroprotection
CNS & Neurological Disorders - Drug Targets 4-Anilinoquinazoline Derivatives with Epidermal Growth Factor Receptor Inhibitor Activity
Anti-Cancer Agents in Medicinal Chemistry Subject Index To Volume 6
Anti-Cancer Agents in Medicinal Chemistry Human 5-HT4 and 5-HT7 Receptor Splice Variants: Are they Important?
Current Neuropharmacology Neuropeptides as Therapeutic Targets in Anxiety Disorders
Current Pharmaceutical Design