Research. Chromosomal instability (CIN) ? observed as the first cancer hallmark over 100 years ago ? is characterized by the persistent loss and gain of whole chromosomes through abnormal cell division. This process results in aneuploidy, the state of having an incorrect number of chromosomes, which is present in over 70% of solid tumors, some of which display recurring patterns of aneuploidy. Persistent ?missegregation? of chromosomes is associated with worse patient prognosis and advanced clinical features. This is attributed to the increased adaptability of a tumor having increased genomic diversity via a broad landscape of different aneuploid clones. At higher rates of missegregation it appears to cause cell death and tumor inhibition. The occurrence of CIN is also theorized to sensitize tumors to CIN-inducing chemotherapies like taxanes. Despite CIN?s long history, its clinical use as a prognostic marker and biomarker for taxane efficacy is inaccessible as current methods of quantifying rates of chromosome missegregation are either infeasible in tissue, insufficiently informative and/or labor intensive. A critical goal for this proposal to combine stochastic computational modeling of cell division with single cell sequencing of tumors in order to allow for the quantification of intratumoral rates of chromosome missegregation. Additionally, cellular processes after chromosome missegregation that underlie karyotypic selection have not been explored. We hypothesize that post- missegregation transcriptional processes either preclude or permit the propagation of clones with specific aneuploid chromosome combinations. We will stochastically generate many combinations of chromosome copy number alterations in transformed and non-transformed cell lines and analyze the acute transcriptional alterations and clonal composition at single cell resolution. Overall, the long-term goal for this proposal is to resolve the complex relationship between chromosome missegregation and breast cancer progression with respect to its incidence in human breast tumors and downstream transcriptional consequences that underlie tumor evolution. This work is innovative in its approach and will significantly improve our understanding of tumor evolution and how to evaluate CIN in patients. Training. Through completion of the proposed research, I will develop my skills in the design and implementation of high impact and rigorous scientific studies. Through coursework and interactions with lab members and collaborators, I will develop multi-disciplinary expertise in cell biological and genomics/transcriptomics experimental and analytical methods. I will hone professional skills in scientific communication, public engagement, and networking through the many opportunities afforded to me to interact with and present my research to collaborators, field-experts, legislators, and community members. The unique, multi-disciplinary training proposed here will position me well for a career as an independent investigator in the field of cancer genomics at an academic or federal research institution.
Chromosomal instability is a major driver of intratumoral heterogeneity and associated with worse patient prognosis, yet there is no clinically accessible assay to easily use CIN as a prognostic marker. Because over 70% of solid tumors are aneuploid, CIN is found in most human tumors. The proposed research will address major knowledge gaps in how breast tumors evolve aneuploid karyotypes to become more adaptive to challenge and will offer valuable, clinically significant insight into how to use CIN as a prognostic marker for breast cancer.
