Translational oncology: bringing theory and clinic one step closer : Blackboard to bench, and back

In over two centuries of cancer research, we have gone from knowing its cellular origin to knowing that it can be viewed as a rogue organ that can recruit immune cells and other healthy cells. While laboratory and clinical observations accumulate rapidly, the theory that could connect all the observations requires catching up and validation. Consequently, we have seen one-off successes in hematological malignancies, but theoretical and quantitative support is necessary to treat solid tumors. In this thesis, I present my contribution to tools in accelerating research from conceptual to laboratory and clinical phases. Each chapter in this thesis focuses on a particular characteristic of cancer cells while working with tumors of different organs. I distill the critical processes within and surrounding the tumor cells to gain mechanistic underpinnings and quantify population-level dynamics. I use ordinary differential equations and agent-based models to capture tumor cell heterogeneity and Bayesian inference to perform model selection from experimental data. The thesis aims for mechanistic insights into carcinogenesis and cancer treatment with quantitative models highlighting their value for integrative cancer research. This work explores several cancer systems unified by questions in the ecology and treatment dynamics of heterogeneous tumors. The approaches used in this work show new ways to accelerate blackboard-to-bench translation in cancer research.



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