Grant: Doctoral Research Award - PA - Bioinformatics and Computational Biology

Cancer is driven by mutations that result in genetically distinct subpopulations of cells called clones. Clones may respond differentially to treatment, leading to a partial remission and proliferation of treatment-resistant cell populations. Therefore, the identification of these clones and their evolutionary history has become essential for effective treatment. This proposal aims to develop probabilistic methods that characterize cancer evolution leveraging different sequencing technologies and strategies. Cancer evolution has largely been investigated through bulk whole-genome sequencing. However, the bulk mixture of different cells requires methods to identify clones. PhyClone is a method for characterizing cancer clonal evolution from bulk data, which probabilistically defines clonal groups and reconstructs their evolutionary relationships. PhyClone's models capture uncertainty and allow for the inference of complex evolutionary histories. However, nearly all current methods rely on genomic instability, which leaves genomically stable cancers under-served, calling for alternative approaches. MiClone is a probabilistic method for inferring cell phylogenies, leveraging the hundreds to thousands of mitochondria per cell, capturing the signal present from the entirety of the mitochondrial variant set. MiClone expands upon PhyClone, using the mitochondrial genome alone. Finally, I propose a project with therapeutic implications. To investigate two cancer therapeutics, cisplatin and PARP inhibitors (PARPi), a series of mouse patient-derived xenograft lines have been established from patients with high-grade serous ovarian cancer. By applying one or both therapeutics in different orders, we hope to better understand treatment strategies and uncover new opportunities for methodological advancement. With their focus on scalability and accuracy, these innovative methods are poised to become powerful tools for future cancer research and subsequent treatment.