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Novel multi-omic algorithms to predict treatment response in prostate cancer
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Panja, Sukanya. Novel multi-omic algorithms to predict treatment response in prostate cancer. Retrieved from https://doi.org/doi:10.7282/t3-19s6-4x43

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TitleNovel multi-omic algorithms to predict treatment response in prostate cancer
NamePanja, Sukanya (author); Mitrofanova, Antonina (chair); Rutgers University; School of Health Professions
Date Created2022
Other Date2022-12 (degree)
SubjectBioinformatics, Prostate -- Cancer -- Treatment
Extent138 pages : illustrations
DescriptionTherapeutic resistance is a critical challenge in prostate cancer management. The lack of genome-wide computational tools to identify patients at risk of treatment resistance hampers personalized therapeutic planning, which could potentially delay disease progression, eliminate harmful side effects. and improve outcomes. To address this problem, I have developed two novel computational algorithms: (i) Epi2GenR, that integrates DNA methylation and mRNA gene expression patient profiles to identify markers associated with response to first-generation androgen deprivation therapy in prostate cancer; and (ii) TR-2-PATH, that integrates transcriptional regulatory programs and molecular pathways to identify markers associated with response to second generation androgen-deprivation (Enzalutamide) in castration resistant prostate cancer (CRPC) patients. Epi2GenR uncovered a panel of 5 differentially expressed and methylated sites, which could accurately predict primary resistance to first-generation androgen-deprivation therapy (log-rank p = 0.019), while TR-2-PATH uncovered MYC pathway and its upstream transcriptional regulatory program, NME2, to be significantly associated with response to Enzalutamide in CRPC patients (log-rank p = 0.0035). We anticipate that these discoveries can be utilized in the clinic to identify patients at risk of treatment resistance, which paves the road to personalized therapeutic advice and improved outcomes for patients with prostate cancer.
NotePh.D.
NoteIncludes bibliographical references
Genretheses
Persistent URLhttps://doi.org/doi:10.7282/t3-19s6-4x43
LanguageEnglish
CollectionSchool of Health Professions ETD Collection
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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