ANTICANCER DRUG EXPULSION IN SHED VESICLES
Gus R Rosania
University Of Michigan At Ann Arbor 3003 South State Street, Room 1040 Ann Arbor, Mi 481091274
Grant 1R21CA104686-01A2 from National Cancer Institute IRG: ZRG1
Abstract: In the course of cancer chemotherapy, an initial remission may be followed by drug-resistant relapse. Drug resistant cell populations can arise from selective pressure of chemotherapy, combined with mutations or epigenetic changes that confer a selective growth advantage to drug-resistant tumor cells. Recently, it has been found that cancer cells shed large numbers of nanometer-sized, cell surface-derived particles both in vivo and in vitro. We hypothesize that these particles represent an anticancer drug efflux mechanism, involved in drug resistance. If confirmed, understanding this mechanism would help design anticancer drugs with increased efficacy, and would facilitate development of novel pharmacological agents for blocking drug resistance. In support of this hypothesis, preliminary evidence obtained in my laboratory indicates that expression of vesicle shedding-associated genes correlates with multidrug resistance. Statistical analyses of gene expression profiles in relation to chemosensitivity profiles spanning human derived cancer cell lines from different tissues indicate that vesicle shedding associated genes predict drug resistance profiles. Pulse-chase experiments with doxorubicin and other small, fluorescent molecules confirm that vesicles shed from the surface of cancer cells can mediate drug expulsion. Here, we propose to perform a pilot study of the contribution of vesicle-mediated drug expulsion to total anticancer drug efflux and resistance. The first aim of this study will be to measure expulsion of drug in shed vesicles, using several different radiolabeled drugs as tracers, and relate drug expulsion to multidrug resistance across various breast tumor-derived cell lines. A second objective is to detect the presence of shed vesicles -or shed vesicle-associated antigens- in nipple aspirates and ductal lavage fluid obtained from breast cancer patients. Bilateral nipple aspirates and ductal lavage samples obtained prior to mastectomy will be analyzed for the presence of shed vesicles or shed vesicle-associated antigens using microscopic, biochemical and biophysical techniques. Establishing the presence of shed vesicles specifically in cancerous breast fluids would enable future studies of the role of vesicle shedding as a prognostic marker of drug resistance and cancer progression, and would constitute evidence for the physiological relevance of the shedding mechanism.
Project start date: 2005-06-30
Project end date: 2007-05-31
1R21CA104686-01A2 (2005): $128036
Sponsored Links Excellgen http://Excellgen.com
Grants awarded to Gus R Rosania
ANTICANCER DRUG EXPULSION IN SHED VESICLES
Gus R Rosania
University Of Michigan At Ann Arbor 3003 South State Street, Room 1040 Ann Arbor, Mi 481091274
Grant 5R21CA104686-02 from National Cancer Institute IRG: ZRG1
Abstract: In the course of cancer chemotherapy, an initial remission may be followed by drug-resistant relapse. Drug resistant cell populations can arise from selective pressure of chemotherapy, combined with mutations or epigenetic changes that confer a selective growth advantage to drug-resistant tumor cells. Recently, it has been found that cancer cells shed large numbers of nanometer-sized, cell surface-derived particles both in vivo and in vitro. We hypothesize that these particles represent an anticancer drug efflux mechanism, involved in drug resistance. If confirmed, understanding this mechanism would help design anticancer drugs with increased efficacy, and would facilitate development of novel pharmacological agents for blocking drug resistance. In support of this hypothesis, preliminary evidence obtained in my laboratory indicates that expression of vesicle shedding-associated genes correlates with multidrug resistance. Statistical analyses of gene expression profiles in relation to chemosensitivity profiles spanning human derived cancer cell lines from different tissues indicate that vesicle shedding associated genes predict drug resistance profiles. Pulse-chase experiments with doxorubicin and other small, fluorescent molecules confirm that vesicles shed from the surface of cancer cells can mediate drug expulsion. Here, we propose to perform a pilot study of the contribution of vesicle-mediated drug expulsion to total anticancer drug efflux and resistance. The first aim of this study will be to measure expulsion of drug in shed vesicles, using several different radiolabeled drugs as tracers, and relate drug expulsion to multidrug resistance across various breast tumor-derived cell lines. A second objective is to detect the presence of shed vesicles -or shed vesicle-associated antigens- in nipple aspirates and ductal lavage fluid obtained from breast cancer patients. Bilateral nipple aspirates and ductal lavage samples obtained prior to mastectomy will be analyzed for the presence of shed vesicles or shed vesicle-associated antigens using microscopic, biochemical and biophysical techniques. Establishing the presence of shed vesicles specifically in cancerous breast fluids would enable future studies of the role of vesicle shedding as a prognostic marker of drug resistance and cancer progression, and would constitute evidence for the physiological relevance of the shedding mechanism.
Project start date: 2005-06-30
Project end date: 2007-05-31
5R21CA104686-02 (2006): $124317
CHEMICAL ADDRESS TAGS: A CHEMINFORMATIC & IMAGE DATA MANAGEMENT AND ANALYSIS PLAN
Gus R Rosania, Associate Professor Of Pharm. Sciences
University Of Michigan At Ann Arbor, 1040 Wolverine Tower, Ann Arbor, Mi 48109-1274
Grant 5R01GM078200-05 from National Institute Of General Medical Sciences
Abstract: Adverse drug reactions (ADRs) are one of the leading causes of hospitalization and death in the United States. ADRs are often associated with unfavorable drug bioavailability or biodistribution profiles. Thus, ADRs could be prevented by optimizing drug transport properties -from the systemic, organ level down to the microscopic, cellular level. To improve the quality of drugs entering clinical trials, a new generation of microscopic imaging instruments -known as "high content screening" or "HCS" systems has been developed. HCS instruments can provide preclinical, human cell-based data to complement animal studies in predictive toxicology testing. As a high-throughput platform, HCS systems can be used to screen large collections of small molecules in physiologically-relevant assays. Now the challenge is to incorporate HCS technology into standard biomedical research practice, to facilitate discovery of less toxic drug candidates with improved clinical success rates. To meet this challenge, we propose to develop a cheminformatic and image data management and analysis plan to study the subcellular localization of fluorescent, small molecules -in living cells. Inspired by machine vision approaches currently being used as a tool to analyze the subcellular distribution of proteins on a genome-wide scale ("location proteomics"), we propose that machine vision could also be adopted as a tool to analyze the distribution of small molecule fluorescent drug candidates. In analogy to how protein location is encoded by signal peptides, we hypothesize that subcellular small molecule localization is encoded by "Chemical Address Tags" to be discovered within the chemical structure of small molecules. To test this hypothesis, we plan to 1) Develop automated, image analysis and cheminformatic tools to reverse- engineer Chemical Address Tags in an objective, quantitative and high-throughput manner; 2) Develop and compare two quantitative, machine vision approaches to assay the transport properties of mitochondria- targeting molecules; 3) Demonstrate how a cheminformatics-driven, image data management and analysis plan can impact an anticancer drug lead optimization effort
Keywords: ABCB1; ATP-Binding Cassette, Sub-Family B Proteins; ATP-Binding Cassette, Sub-Family B, Member 1; Address; Adopted; Adverse reactions; Animals; Anti-Cancer Agents; Anti-Tumor Agents; Anti-Tumor Drugs; Antineoplastic Agents; Antineoplastic Drugs; Antineoplastics; Antiproliferative Agents; Antiproliferative Drugs; Assay; Behavior; Bioassay; Bioavailability; Biodistribution; Biologic Assays; Biologic Availability; Biological Assay; Biological Availability; Biomedical Research; Cancer Drug; Cells; Cessation of life; Chemical Engineering; Chemical Structure; Chemicals; Chemotherapeutic Agents, Neoplastic Disease; Clinical; Clinical Trials; Clinical Trials, Unspecified; Collection; Complement; Complement Proteins; Data Banks; Data Bases; Data Set; Databank, Electronic; Databanks; Database, Electronic; Databases; Dataset; Death; Dose; Drug Resistance, Multiple; Drug Resistant, Multiple; Drug Transport; Drug toxicity; Drugs; Engineering; Engineerings; Generations; HOSP; Half-Life; Half-Lifes; Hospitalization; Human; Human, General; Image; Image Analyses; Image Analysis; Imaging Procedures; Imaging Techniques; Investigators; Killings; Kinetic; Kinetics; Lead; Libraries; Life; Location; MDR1 Protein; Malignant Cell; Man (Taxonomy); Man, Modern; Mediating; Medication; Microscopic; Mitochondria; Modeling; Monitor; Multi-Drug Resistance; Multidrug Resistance; Multidrug Resistance 1; Multidrug Resistance Protein 1; Multidrug Resistance Proteins; Multidrug Resistant Proteins; Normal Cell; Optics; Organ; P-GP; P-Glycoprotein; P-Glycoprotein 1; P-Glycoprotein Transporter; P-Glycoproteins; PGY-1 Protein; Pb element; Peptide Signal Sequences; Pharmaceutic Preparations; Pharmaceutical Preparations; Physiologic Availability; Programs (PT); Programs [Publication Type]; Property; Property, LOINC Axis 2; Proteins; Proteomics; ROC Analysis; Reaction; Reaction Time; Research Personnel; Researchers; Resistance to Multi-drug; Resistance to Multidrug; Resistance to Multiple Drug; Resistant to Multiple Drug; Resistant to multi-drug; Resistant to multidrug; Response RT; Response Time; Screening procedure; Sight; Signal Peptide; Signal Sequences; Signal Sequences, Peptide; System; System, LOINC Axis 4; Technics, Imaging; Technology; Testing; Toxicology; Tumor-Specific Treatment Agents; United States; Vision; Work; analog; anticancer agent; anticancer drug; base; bioavailability of drug; cancer cell; cell killing; chemical informatics; cheminformatics; clinical data repository; clinical data warehouse; clinical investigation; data management; data repository; design; designing; drug candidate; drug quality; drug/agent; experiment; experimental research; experimental study; extracellular; gene product; genome-wide; heavy metal Pb; heavy metal lead; image evaluation; imaging; improved; instrument; meetings; mitochondrial; multi-drug resistant; multidrug resistant; pre-clinical; preclinical; prevent; preventing; programs; protein distribution; protein signal sequence; psychomotor reaction time; relational database; research study; screening; screenings; small molecule; spatiotemporal; success; tool; uptake
Project start date: 2006-07-01
Project end date: 2012-10-31
Budget start date: 1-JUL-2010
Budget end date: 30-JUN-2011
5R01GM078200-05 (2010): $281966
3R01GM078200-05S1 (2010): $202308
5R01GM078200-04 (2009): $286235
5R01GM078200-03 (2008): $273030
CHEMICAL ADDRESS TAGS: A Cheminformatic And Image Data Management And Analysis Plan
Gus R Rosania
University Of Michigan At Ann Arbor 3003 South State Street, Room 1040 Ann Arbor, Mi 481091274
Grant 5R01GM078200-02 from National Institute Of General Medical Sciences IRG: BDMA
Abstract: Adverse drug reactions (ADRs) are one of the leading causes of hospitalization and death in the United States. ADRs are often associated with unfavorable drug bioavailability or biodistribution profiles. Thus, ADRs could be prevented by optimizing drug transport properties -from the systemic, organ level down to the microscopic, cellular level. To improve the quality of drugs entering clinical trials, a new generation of microscopic imaging instruments -known as "high content screening" or "HCS" systems has been developed. HCS instruments can provide preclinical, human cell-based data to complement animal studies in predictive toxicology testing. As a high-throughput platform, HCS systems can be used to screen large collections of small molecules in physiologically-relevant assays. Now the challenge is to incorporate HCS technology into standard biomedical research practice, to facilitate discovery of less toxic drug candidates with improved clinical success rates. To meet this challenge, we propose to develop a cheminformatic and image data management and analysis plan to study the subcellular localization of fluorescent, small molecules -in living cells. Inspired by machine vision approaches currently being used as a tool to analyze the subcellular distribution of proteins on a genome-wide scale ("location proteomics"), we propose that machine vision could also be adopted as a tool to analyze the distribution of small molecule fluorescent drug candidates. In analogy to how protein location is encoded by signal peptides, we hypothesize that subcellular small molecule localization is encoded by "Chemical Address Tags" to be discovered within the chemical structure of small molecules. To test this hypothesis, we plan to 1) Develop automated, image analysis and cheminformatic tools to reverse- engineer Chemical Address Tags in an objective, quantitative and high-throughput manner; 2) Develop and compare two quantitative, machine vision approaches to assay the transport properties of mitochondria- targeting molecules; 3) Demonstrate how a cheminformatics-driven, image data management and analysis plan can impact an anticancer drug lead optimization effort.
Keywords: automated data processing, cheminformatics, data management, evaluation /testing, high throughput technology, imaging /visualization /scanning, method development, analog, chemical kinetics, computer program /software, drug discovery /isolation, fluorescence, glycoprotein, membrane transport protein, microscopy, mitochondria, protein localization, cell line, chemical registry /resource
Project start date: 2006-07-01
Project end date: 2012-10-31
5R01GM078200-02 (2007): $211897
CHEMICAL ADDRESS TAGS: A Cheminformatic & Image Data Management And Analysis Plan
Gus R Rosania
University Of Michigan At Ann Arbor 3003 South State Street, Room 1040 Ann Arbor, Mi 481091274
Grant 1R01GM078200-01 from National Institute Of General Medical Sciences IRG: BDMA
Abstract: Adverse drug reactions (ADRs) are one of the leading causes of hospitalization and death in the United States. ADRs are often associated with unfavorable drug bioavailability or biodistribution profiles. Thus, ADRs could be prevented by optimizing drug transport properties -from the systemic, organ level down to the microscopic, cellular level. To improve the quality of drugs entering clinical trials, a new generation of microscopic imaging instruments -known as "high content screening" or "HCS" systems has been developed. HCS instruments can provide preclinical, human cell-based data to complement animal studies in predictive toxicology testing. As a high-throughput platform, HCS systems can be used to screen large collections of small molecules in physiologically-relevant assays. Now the challenge is to incorporate HCS technology into standard biomedical research practice, to facilitate discovery of less toxic drug candidates with improved clinical success rates. To meet this challenge, we propose to develop a cheminformatic and image data management and analysis plan to study the subcellular localization of fluorescent, small molecules -in living cells. Inspired by machine vision approaches currently being used as a tool to analyze the subcellular distribution of proteins on a genome-wide scale ("location proteomics"), we propose that machine vision could also be adopted as a tool to analyze the distribution of small molecule fluorescent drug candidates. In analogy to how protein location is encoded by signal peptides, we hypothesize that subcellular small molecule localization is encoded by "Chemical Address Tags" to be discovered within the chemical structure of small molecules. To test this hypothesis, we plan to 1) Develop automated, image analysis and cheminformatic tools to reverse- engineer Chemical Address Tags in an objective, quantitative and high-throughput manner; 2) Develop and compare two quantitative, machine vision approaches to assay the transport properties of mitochondria- targeting molecules; 3) Demonstrate how a cheminformatics-driven, image data management and analysis plan can impact an anticancer drug lead optimization effort.
Keywords: automated data processing, cheminformatics, data management, evaluation /testing, high throughput technology, imaging /visualization /scanning, method development, analog, chemical kinetics, computer program /software, drug discovery /isolation, fluorescence, glycoprotein, membrane transport protein, microscopy, mitochondria, protein localization, cell line, chemical registry /resource
Project start date: 2006-07-01
Project end date: 2011-06-30
1R01GM078200-01 (2006): $218511