Author ORCID Identifier
0000-0003-3131-7679
Date of Graduation
5-2023
Document Type
Dissertation (PhD)
Program Affiliation
Genetics and Epigenetics
Degree Name
Doctor of Philosophy (PhD)
Advisor/Committee Chair
Guillermina Lozano
Committee Member
Patrick Lin
Committee Member
Michael Andreeff
Committee Member
Nicholas Navin
Committee Member
Richard Behringer
Abstract
Missense mutations in the DNA binding domain of the Trp53 gene are characterized as structural (p53R172H) or contact (p53R245W) mutations based on their effect on the conformation of the protein. These mutations show gain-of-function activities such as increased metastatic incidence as compared to p53 loss, often mediated by their interaction with a repertoire of transcription factors. These interactions are largely context specific. In order to understand the mechanisms by which these mutations drive osteosarcoma progression, we created a mouse model, wherein either the p53 structural mutant p53R172H, or the contact mutant, p53R245W, are expressed specifically in osteoblasts, yielding osteosarcoma tumor development. We observed a significant decrease in survival and increased metastatic incidence in mice expressing p53 mutants as compared to p53-null mice, suggesting gain of function. RNA-sequencing of primary osteosarcomas revealed that tumors expressing these missense mutants had vastly different gene expression profiles as compared to p53-null tumors. Further, p53R172H and p53R245W regulated unique transcriptomes, that affected distinct pathways, through interactions with a unique repertoire of transcription factors. Validation assays showed that p53R245W, but not p53R172H, interacts with KLF15 to drive migration and invasion in osteosarcoma cell lines, and metastases in allo-transplantation models. Additionally, analyses of p53R248W ChIP peaks showed enrichment of KLF15 motifs in human osteoblasts. Taken together, these data suggest that the structural and contact mutants of p53 have unique mechanisms of action.
Keywords
p53, osteosarcoma, KLF15, GEMMs
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Cancer Biology Commons, Computational Biology Commons, Genomics Commons, Molecular Genetics Commons