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Genome-wide analysis of therapeutic response uncovers molecular pathways governing tamoxifen resistance in ER+ breast cancer
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Rahem, Sarra. Genome-wide analysis of therapeutic response uncovers molecular pathways governing tamoxifen resistance in ER+ breast cancer. Retrieved from https://doi.org/doi:10.7282/t3-pcsy-s506

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TitleGenome-wide analysis of therapeutic response uncovers molecular pathways governing tamoxifen resistance in ER+ breast cancer
NameRahem, Sarra (author); Mitrofanova, Antonina (chair); Srinivasan, Shankar (internal member); Coffman, Frederick (internal member); Rutgers University; School of Health Professions
Date Created2020
Other Date2020-08 (degree)
SubjectBiomedical Informatics
Extent1 online resource (ix, 54 pages)
DescriptionDespite recent advances in diagnosis, classification, and therapeutic management, breast cancer (BC) remains one of the leading causes of cancer-related death in women worldwide. Nearly 70% of all diagnosed cases of breast tumors are Estrogen Receptor positive (ER+) and thus anti-estrogen therapy, such as tamoxifen, has become the standard-of-care for patients with ER+ breast cancers. Yet, nearly 30% of patients treated with tamoxifen develop resistance, ultimately leading to metastasis and lethality. Prioritization of breast cancer patients based on the risk of resistance to tamoxifen plays a significant role in personalized therapeutic planning and improving disease course and outcomes. In this work, we demonstrate that a genome-wide pathway-centric computational framework elucidates molecular pathways as markers of tamoxifen resistance in ER+ breast cancer patients. Through the association of pathway activity and response to tamoxifen, we identified five biological pathways and demonstrated their ability to predict the risk of tamoxifen resistance in two independent patient cohorts (Test cohort1: log-rank p-value = 0.02, adjusted HR = 3.11; Test cohort2: log-rank p-value = 0.01, adjusted HR = 4.24). Importantly, as a negative control, we have demonstrated that the identified 5 candidate pathways did not classify patients simply based on the disease aggressiveness and that pathways of aggressiveness do not overlap with the 5 candidate pathways. Finally, we have compared our pathway signature to other known signatures of tamoxifen response and have shown superiority of our pathway-based approach (adjusted hazard ratio = 3.11, hazard p-value=0.0278). Thus, we propose that the identified pathways as well as their representative read-out-genes can be utilized to prioritize patients who would benefit from tamoxifen treatment and patients at risk of tamoxifen resistance that should be offered alternative regimens.
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/t3-pcsy-s506
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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