For advanced stage breast cancer, poor prognosis is a reflection of both metastatic progression and inadequate treatment strategies of the disease. Low overall survival and limited efficacy during the management of metastatic breast cancer highlights the need for targeted therapies tailored to treating metastatic breast cancer. Though treatments specifically targeting metastatic disease have been elusive, high throughput drug screening guided by genomic changes tied to metastatic progression promises to bring new treatment strategies to breast cancer. In pursuit of this, I have begun to acquire an integrative toolset, which has focused largely on bioinformatic and mouse model techniques. I will continue expand my knowledge to include high-throughput drug screening and immunomodulatory techniques as I finish my pre-doctoral work and move to the post-doctoral stage of my career. I will pursue this through three specific aims highlighting each stage of my career. In my first aim, which highlights the work completed in my graduate studies is to annotate conserved SNPs, CNVs, and translocations in human and mouse tumors to identify driving genes of tumor progression. This was pursued using a combination of bioinformatic techniques to interrogate whole genome sequencing data and gene expression microarrays as well as leverage CRISPR-Cas9 technology to validate target gene through both in vitro and in vivo metastasis assays.
The second aim which I will complete in the remainder of my graduate studies focuses on determining the impact and therapeutic vulnerabilities associated with those differences identified in aim 1.
This aim will once again leverage a number of bioinformatic tools and CRISPR-Cas9 gene editing to identify potential therapeutic vulnerabilities. These will be confirmed through the use of high throughput drug screening and PDX mouse models.
The third aim which I will pursue in my post-doctoral studies will focus on identifying the interaction of the tumor and the normal host tissue and how this relates to treatment response. In particular I will focus on identifying mutations within the tumor and the normal cells that lead to differential treatment response. This will be completed with a focus on tumor immunotherapy. By completing this work I will identify key SNPs, CNVs, and translocation that drive tumor progression and therapeutic response.
The proposed research is relevant to public health because besides improving basic research on the E2F's function in genomic instability and how it relates to cancer progress; the research will have direct impacts on patient treatments. This research will contribute by identifying genomic markers of treatment response both within the tumor itself and in the immune system of the patient and subsequently provide new tailored therapeutic options for breast cancer patients. Furthermore, the proposed research is relevant to the NIH mission of understanding the cause and generating a cure for human disease because through understanding the scope and mechanism of metastasis and treatment response in breast cancer new therapeutic opportunities and improved outcomes for breast cancer patients can be realized.
| Rennhack, Jonathan; To, Briana; Wermuth, Harrison et al. (2017) Mouse Models of Breast Cancer Share Amplification and Deletion Events with Human Breast Cancer. J Mammary Gland Biol Neoplasia 22:71-84 |
| Turpin, J; Ling, C; Crosby, E J et al. (2016) The ErbB2?Ex16 splice variant is a major oncogenic driver in breast cancer that promotes a pro-metastatic tumor microenvironment. Oncogene 35:6053-6064 |
