Document Type



Doctor of Philosophy (PhD)


Public Health

First Advisor's Name

Deodutta Roy

First Advisor's Committee Title

Committee chair

Second Advisor's Name

Changwon Yoo

Second Advisor's Committee Title

Committee co-chair

Third Advisor's Name

Quentin Felty

Third Advisor's Committee Title

Committee member

Fourth Advisor's Name

Alok Deoraj

Fourth Advisor's Committee Title

Committee member

Fifth Advisor's Name

Juan Luizzi

Fifth Advisor's Committee Title

Committee member


Breast cancer, NRF1, Nuclear respiratory factor 1, Bayesian networks, signal pathway analysis.

Date of Defense



Despite tremendous progress in the understanding of breast cancer (BC), gaps remain in our knowledge of the molecular basis underlying the aggressiveness of BC and BC disparities. Nuclear respiratory factor 1 (NRF1) is a transcription factor (TF) known to control breast cancer cell cycle progression. DNA response elements bound by NRF1 positively correlate with the progression of malignant breast cancer. Mechanistic aspects by which NRF1 contributes to susceptibility to different breast tumor subtypes are still not fully understood. Therefore, the primary objective of this dissertation was to decipher mechanisms by which NRF1 coordinates changes in the transcriptional and chromatin landscape affecting development and progression of invasive breast cancer. Our hypothesis was that NRF1 reprogramming the transcription of tumor initiating gene(s) and tumor suppressor gene(s) contribute in the development and progression of invasive breast cancer. To test this hypothesis, we proposed three specific aims: (a) Decipher regulatory landscape of NRF1 networks in breast cancer. (b) Determine the role of NRF1 gene networks in different subtypes of breast cancer. (c) Determine differential NRF1 gene network sensitivity contributing to breast cancer disparities. Our approach to test these aims consisted of a systematic integration of ChIP DNA-seq, RNA-Seq, NRF1 protein-DNA motif binding, signal pathway analysis, and Bayesian machine learning. We uncovered a novel oncogenic role for NRF1. This discovery strongly supported the supposition that NRF1 overexpression is sufficient to derive breast tumorigenesis. We also observed new roles for NRF1 in the acquisition of breast tumor initiating cells, regulation of epithelial to mesenchymal transition (EMT), and invasiveness of BC stem cells. Furthermore, through the use of Bayesian network structure learning we found that the NRF1 motif was enriched in 14 associated with HER2 amplified breast cancer. Three genes—GSK3B, E2F3, and PIK3CA—were able to predict HER2 breast tumor status with 96% to100% confidence. The findings of this study also showed the roles of NRF1 sensitivity to development of lobular A, Her2+, and TNBC in different racial/ethnic groups of breast cancer patients. In summary, our study revealed for the first time the role of NRF1 in the pathogenesis of invasive BC and BC disparities.







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