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Mathematical modeling of tumor progression and chemotherapy regimens
Descriptive
TitleInfo
Title
Mathematical modeling of tumor progression and chemotherapy regimens
Name
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NamePart
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Miranda Santana
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Leonardo
NamePart
(type = date)
1988-
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Leonardo Miranda Santana
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author
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Bhanot
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Gyan
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Gyan Bhanot
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Advisory Committee
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chair
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Coleman
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Piers
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Piers Coleman
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Advisory Committee
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internal member
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NamePart
(type = family)
Khiabanian
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Hossein
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Hossein Khiabanian
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Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Morozov
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(type = given)
Alexandre
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Alexandre Morozov
Affiliation
Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Ganesan
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Shridar
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Shridar Ganesan
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Advisory Committee
Role
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(authority = RULIB)
outside member
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Rutgers University
Role
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degree grantor
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School of Graduate Studies
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theses
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ETD doctoral
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2020
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2020-10
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2020
Language
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English
Abstract
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Despite all important advances in the treatment of cancer over the last decades, preventing disease recurrence remains a challenge. Resistance of tumors to chemotherapy can be caused not only by selection of drug-resistant clones over the course of treatment, but also by the presence of tumor foci that are in a dormant state and are not targeted/killed by DNA-damaging agents. Such dormant tumor foci can eventually transition to a state of active growth, causing disease recurrence. In this thesis, we propose a stochastic model to describe recurrence of generic tumors, in which tumor foci can transition between a chemoresistant dormant state and a chemosensitive state of active growth. We develop a framework to determine the time-dependent probability that an undetectable residual tumor will become large enough to be detectable, and model the effect of chemotherapy on recurrence by switching the death rate of active tumor foci at the treatment time cap. We fit our model to data from a clinical trial for maintenance chemotherapy with the poly(ADP-ribose) polymerase (PARP) inhibitor olaparib in ovarian cancer, and use parameters from the fits to predict recurrence-free survival when chemotherapy dosage or duration are increased. In this context, we also investigate how recurrence and cure are affected by transition rates between dormant and active states within the tumor, and predict how the effectiveness of increasing chemotherapy dosage or duration for improving long-term recurrence-free survival depends on these rates. Our results should be useful in planning optimized chemotherapy dosage and duration for cancer treatment, especially in cancer types for which no targeted therapy is available.
Subject
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Topic
Chemotherapy
Subject
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Topic
Physics and Astronomy
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Title
Rutgers University Electronic Theses and Dissertations
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ETD_11235
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application/pdf
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Extent
1 online resource (ix, 119 pages) : illustrations
Note
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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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NjNbRU
Identifier
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doi:10.7282/t3-ey4r-q552
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Rights
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The author owns the copyright to this work.
RightsHolder
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Name
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Miranda Santana
GivenName
Leonardo
Role
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Permission or license
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2020-09-29 02:43:18
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Leonardo Miranda Santana
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Affiliation
Rutgers University. School of Graduate Studies
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Author Agreement License
Detail
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.
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Embargo
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2020-10-31
DateTime
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2021-10-31
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after October 31st, 2021.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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2020-09-29T01:58:42
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2020-09-29T01:58:42
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