Functional Module Connectivity Map (FMCM): A Framework for Searching Repurposed Drug Compounds for Systems Treatment of Cancer and an Application to Colorectal Adenocarcinoma

Drug repurposing has become an increasingly attractive approach to drug development owing to the ever-growing cost of new drug discovery and frequent withdrawal of successful drugs caused by side effect issues. Here, we devised Functional Module Connectivity Map (FMCM) for the discovery of repurposed drug compounds for systems treatment of complex diseases, and applied it to colorectal adenocarcinoma. FMCM used multiple functional gene modules to query the Connectivity Map (CMap). The functional modules were built around hub genes identified, through a gene selection by trend-of-disease-progression (GSToP) procedure, from condition-specific gene-gene interaction networks constructed from sets of cohort gene expression microarrays. The candidate drug compounds were restricted to drugs exhibiting predicted minimal intracellular harmful side effects. We tested FMCM against the common practice of selecting drugs using a genomic signature represented by a single set of individual genes to query CMap (IGCM), and found FMCM to have higher robustness, accuracy, specificity, and reproducibility in identifying known anti-cancer agents. Among the 46 drug candidates selected by FMCM for colorectal adenocarcinoma treatment, 65% had literature support for association with anti-cancer activities, and 60% of the drugs predicted to have harmful effects on cancer had been reported to be associated with carcinogens/immune suppressors. Compounds were formed from the selected drug candidates where in each compound the component drugs collectively were beneficial to all the functional modules while no single component drug was harmful to any of the modules. In cell viability tests, we identified four candidate drugs: GW-8510, etacrynic acid, ginkgolide A, and 6-azathymine, as having high inhibitory activities against cancer cells. Through microarray experiments we confirmed the novel functional links predicted for three candidate drugs: phenoxybenzamine (broad effects), GW-8510 (cell cycle), and imipenem (immune system). We believe FMCM can be usefully applied to repurposed drug discovery for systems treatment of other types of cancer and other complex diseases.

[1]  S. Vaidyanathan,et al.  Chronic lymphocytic leukaemia, synchronous small cell carcinoma and squamous neoplasia of the urinary bladder in a paraplegic man following long-term phenoxybenzamine therapy , 2006, Spinal Cord.

[2]  C. Shi,et al.  Ginkgo biloba Extract in Alzheimer’s Disease: From Action Mechanisms to Medical Practice , 2010, International journal of molecular sciences.

[3]  F. Bruggeman,et al.  Cancer: a Systems Biology disease. , 2006, Bio Systems.

[4]  D. Hanahan,et al.  Hallmarks of Cancer: The Next Generation , 2011, Cell.

[5]  Kathryn A Phillips,et al.  Drug withdrawals in the United States: a systematic review of the evidence and analysis of trends. , 2007, Current drug safety.

[6]  Michal A. Kurowski,et al.  Transcriptome Profile of Human Colorectal Adenomas , 2007, Molecular Cancer Research.

[7]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[8]  R. Rettig.  Strategies And Tactics In The War On Cancer: A Review , 2006 .

[9]  Pamela K. Kreeger,et al.  Cancer systems biology: a network modeling perspective , 2009, Carcinogenesis.

[10]  M. Hayakari,et al.  Characterization of cell death induced by ethacrynic acid in a human colon cancer cell line DLD‐1 and suppression by N‐acetyl‐l‐cysteine , 2003, Cancer science.

[11]  Elena Edelman,et al.  A genomic approach to colon cancer risk stratification yields biologic insights into therapeutic opportunities , 2008, Proceedings of the National Academy of Sciences.

[12]  Hiroshi Tanaka,et al.  Screening for epigenetically masked genes in colorectal cancer Using 5-Aza-2'-deoxycytidine, microarray and gene expression profile. , 2012, Cancer genomics & proteomics.

[13]  M. Manfait,et al.  Inhibitory effects of extracellular Mg2+ on intracellular Ca2+ dynamic changes and thapsigargin-induced apoptosis in human cancer MCF7 cells , 2004, Molecular and Cellular Biochemistry.

[14]  Sandhya Rani,et al.  Human Protein Reference Database—2009 update , 2008, Nucleic Acids Res..

[15]  Alexander Kamb,et al.  Why is cancer drug discovery so difficult? , 2007, Nature Reviews Drug Discovery.

[16]  K. Tew,et al.  Ethacrynic acid and piriprost as enhancers of cytotoxicity in drug resistant and sensitive cell lines. , 1988, Cancer research.

[17]  Yang Song,et al.  Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery , 2011, Nucleic Acids Res..

[18]  Robert N. Hughes,et al.  The War on Cancer: An Anatomy of Failure, a Blueprint for the Future , 2006 .

[19]  Hoong-Chien Lee,et al.  ToP: A Trend-of-Disease-Progression Procedure Works Well for Identifying Cancer Genes from Multi-State Cohort Gene Expression Data for Human Colorectal Cancer , 2013, PloS one.

[20]  J. Wu,et al.  Characterization of novel inhibitors of cyclin-dependent kinases. , 1999, Biochemical and biophysical research communications.

[21]  S. Friend,et al.  A network view of disease and compound screening , 2009, Nature Reviews Drug Discovery.

[22]  C. Chong,et al.  New uses for old drugs , 2007, Nature.

[23]  W. Prusoff,et al.  Biological investigations of 6-azathymine, a thymine analog. , 1954, Cancer research.

[24]  Alexander A. Morgan,et al.  Discovery and Preclinical Validation of Drug Indications Using Compendia of Public Gene Expression Data , 2011, Science Translational Medicine.

[25]  Dong I. Lee,et al.  Mechanisms of resistance and adaptation to thapsigargin in androgen-independent prostate cancer PC3 and DU145 cells. , 2007, Archives of biochemistry and biophysics.

[26]  L. Laine,et al.  A systematic review of NSAIDs withdrawn from the market due to hepatotoxicity: lessons learned from the bromfenac experience , 2006, Pharmacoepidemiology and drug safety.

[27]  P. Imming,et al.  Drugs, their targets and the nature and number of drug targets , 2006, Nature Reviews Drug Discovery.

[28]  Paul A Clemons,et al.  The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease , 2006, Science.

[29]  Tudor I. Oprea,et al.  Drug Repurposing: Far Beyond New Targets for Old Drugs , 2012, The AAPS Journal.

[30]  Thomas Lengauer,et al.  Improved scoring of functional groups from gene expression data by decorrelating GO graph structure , 2006, Bioinform..

[31]  Shi-hai Xia,et al.  Pharmacological action and mechanisms of ginkgolide B. , 2007, Chinese medical journal.

[32]  Rafael A Irizarry,et al.  Exploration, normalization, and summaries of high density oligonucleotide array probe level data. , 2003, Biostatistics.

[33]  V. Grantcharova,et al.  Therapeutically Targeting ErbB3: A Key Node in Ligand-Induced Activation of the ErbB Receptor–PI3K Axis , 2009, Science Signaling.

[34]  Canguo Zhao,et al.  Expression-Based In Silico Screening of Candidate Therapeutic Compounds for Lung Adenocarcinoma , 2011, PloS one.

[35]  Alexander A. Morgan,et al.  Computational Repositioning of the Anticonvulsant Topiramate for Inflammatory Bowel Disease , 2011, Science Translational Medicine.

[36]  A. Weeraratna,et al.  Thapsigargin induces a calmodulin/calcineurin‐dependent apoptotic cascade responsible for the death of prostatic cancer cells , 2000, The Prostate.

[37]  R. Tibshirani,et al.  Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[38]  Gordon K Smyth,et al.  Statistical Applications in Genetics and Molecular Biology Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments , 2011 .

[39]  V. Papadopoulos,et al.  Ginkgo biloba extracts and cancer: a research area in its infancy , 2003, Fundamental & clinical pharmacology.

[40]  S. Christensen,et al.  Thapsigargin, a histamine secretagogue, is a non-12-O-tetradecanolphorbol-13-acetate (TPA) type tumor promoter in two-stage mouse skin carcinogenesis , 2004, Journal of Cancer Research and Clinical Oncology.

[41]  J. Schulz,et al.  Differential effects of l-buthionine sulfoximine and ethacrynic acid on glutathione levels and mitochondrial function in PC12 cells , 1999, Neuroscience Letters.

[42]  Ravi Iyengar,et al.  Network analyses in systems pharmacology , 2009, Bioinform..

[43]  B. Ye,et al.  Ginkgo May Sensitize Ovarian Cancer Cells to Cisplatin , 2014, Integrative cancer therapies.

[44]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[45]  R. James,et al.  Irinotecan combined with fluorouracil compared with fluorouracil alone as first-line treatment for metastatic colorectal cancer: a multicentre randomised trial , 2000, The Lancet.

[46]  A. Martelli,et al.  Genotoxicity and carcinogenicity studies of antihypertensive agents. , 2006, Mutation research.

[47]  B. Ahlemeyer,et al.  Pharmacological Studies Supporting the Therapeutic Use of Ginkgo biloba Extract for Alzheimer’s Disease , 2003, Pharmacopsychiatry.

[48]  D. Lauffenburger,et al.  Multipathway Model Enables Prediction of Kinase Inhibitor Cross-Talk Effects on Migration of Her2-Overexpressing Mammary Epithelial Cells , 2008, Molecular Pharmacology.

[49]  Shuangping Zhao,et al.  An Integrated Bioinformatics Approach Identifies Elevated Cyclin E2 Expression and E2F Activity as Distinct Features of Tamoxifen Resistant Breast Tumors , 2011, PloS one.

[50]  J. Isaacs,et al.  Mechanism and role of growth arrest in programmed (apoptotic) death of prostatic cancer cells induced by thapsigargin , 1997, The Prostate.

[51]  Yajie Wang,et al.  Using Functional Signatures to Identify Repositioned Drugs for Breast, Myelogenous Leukemia and Prostate Cancer , 2012, PLoS Comput. Biol..

[52]  T. Kipps,et al.  Ethacrynic Acid Exhibits Selective Toxicity to Chronic Lymphocytic Leukemia Cells by Inhibition of the Wnt/β-Catenin Pathway , 2009, PloS one.

[53]  C. Tan,et al.  [Clinical investigations of 6-azathymine: a thymine analog]. , 1960, Cancer research.

[54]  Keith D. Hill,et al.  Psychotropic Drug-Induced Falls in Older People , 2012, Drugs & Aging.

[55]  S. Sleigh,et al.  Repurposing Strategies for Therapeutics , 2010, Pharmaceutical Medicine.

[56]  W. Qiu,et al.  Ginkgo may prevent genetic-associated ovarian cancer risk: multiple biomarkers and anticancer pathways induced by ginkgolide B in BRCA1-mutant ovarian epithelial cells , 2011, European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation.

[57]  P. Twentyman,et al.  A study of ethacrynic acid as a potential modifier of melphalan and cisplatin sensitivity in human lung cancer parental and drug-resistant cell lines. , 1992, British Journal of Cancer.

[58]  A. Hopkins.  Network pharmacology: the next paradigm in drug discovery. , 2008, Nature chemical biology.

[59]  K. Tew,et al.  Pharmakokinetics and bioavailability study of ethacrynic acid as a modulator of drug resistance in patients with cancer. , 1994, The Journal of pharmacology and experimental therapeutics.

[60]  C. Harmon,et al.  Thapsigargin induces rapid, transient growth inhibition and c-fos expression followed by sustained growth stimulation in mouse keratinocyte cultures. , 1996, The Journal of investigative dermatology.

[61]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[62]  E. Freireich,et al.  A comparative study of two regimens of combination chemotherapy in acute leukemia. , 1958, Blood.

[63]  G Inesi,et al.  Use of thapsigargin to study Ca2+ homeostasis in cardiac cells , 1995, Bioscience reports.

[64]  R. Bauer,et al.  Pharmacokinetics of bilobalide, ginkgolide A and B after administration of three different Ginkgo biloba L. preparations in humans , 2010, Phytotherapy research : PTR.

[65]  David B Jackson,et al.  Drug profiling: knowing where it hits. , 2010, Drug discovery today.