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Nanotechnology approach for precision targeted therapy of ovarian cancer
Descriptive
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Title
Nanotechnology approach for precision targeted therapy of ovarian cancer
Name
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Sapiezynski
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Justin E.
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Justin E. Sapiezynski
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author
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Minko
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Tamara
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Tamara Minko
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Advisory Committee
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chair
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Colaizzi
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John L
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John L Colaizzi
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Advisory Committee
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internal member
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You
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Guofeng
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Guofeng You
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Advisory Committee
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internal member
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Garbuzenko
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Olga
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Olga Garbuzenko
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Advisory Committee
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Rutgers University
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School of Graduate Studies
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school
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Text
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theses
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2019
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2019-10
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2019
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English
Abstract
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One of the most pressing health concerns in recent history is cancer. The World Health Organization reports that more than 10 million cases of cancer are diagnosed each year [1]. In the United States, it is the second leading cause of death and is responsible for approximately one in four deaths in the general population [2]. Currently, only about 25% of patients treated with a certain treatment will show a response in the clinic [3]. Therefore, it is necessary to design methods for improvement patient outcomes once being diagnosed with the disease. Precision medicine is a newly found trend in the field of pharmacology to treat patients with more specified treatment regiments for increased efficacy. Patients are further categorized into subtypes based on histology of the disease and new methods are being investigated to further stratify patients based on molecular biology and on the genetic level of the disease in individual patients.
The purpose of the current proposal is to help design precision treatment of ovarian cancer patients. First, we obtained patient biopsy samples from the Cancer Institute of New Jersey and constructed gene expression profiles to help identify key dysregularities in patients and design an efficient way to screen further patients for these biomarkers. Once gene expression profiles were obtained, we targeted certain overexpressed genes through RNA interference (RNAi) therapy to downregulate their expression in the cancer cells. RNAi therapy was combined with traditional small molecule chemotherapeutics to improve their efficacy compared to being used alone to treat the patients. We categorized and optimized liposomal and dendrimer drug delivery systems (DDSs) to help delivery our proposed combinational therapies. Several small molecule chemotherapeutics were formulated separately with RNAi therapy and evaluated against monotherapies of the corresponding drug. We successfully demonstrated these DDSs efficiently delivered our combinational therapies to tumors, reduced off-site accumulation of the therapeutics, and raised the efficacy of the treatment compared to monotherapies of the corresponding drug.
The purpose of the current proposal is to help design precision treatment of ovarian cancer patients. First, we obtained patient biopsy samples from the Cancer Institute of New Jersey and constructed gene expression profiles to help identify key dysregularities in patients and design an efficient way to screen further patients for these biomarkers. Once gene expression profiles were obtained, we targeted certain overexpressed genes through RNA interference (RNAi) therapy to downregulate their expression in the cancer cells. RNAi therapy was combined with traditional small molecule chemotherapeutics to improve their efficacy compared to being used alone to treat the patients. We categorized and optimized liposomal and dendrimer drug delivery systems (DDSs) to help delivery our proposed combinational therapies. Several small molecule chemotherapeutics were formulated separately with RNAi therapy and evaluated against monotherapies of the corresponding drug. We successfully demonstrated these DDSs efficiently delivered our combinational therapies to tumors, reduced off-site accumulation of the therapeutics, and raised the efficacy of the treatment compared to monotherapies of the corresponding drug.
Subject
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Topic
Pharmaceutical Science
Subject
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Topic
Precision
Subject
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Topic
Ovaries -- Cancer -- Treatment
Subject
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Topic
Nanomedicine
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Rutgers University Electronic Theses and Dissertations
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ETD_10105
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1 online resource (xi, 111 pages) : illustrations
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Ph.D.
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Includes bibliographical references
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School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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doi:10.7282/t3-7asj-hn94
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ETD doctoral
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Rights
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The author owns the copyright to this work.
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Sapiezynski
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Justin
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Permission or license
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2019-07-01 10:42:52
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Justin Sapiezynski
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Rutgers University. School of Graduate Studies
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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2019-08-08T18:05:28
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2019-08-08T18:05:28
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