Emerging Tumor Development by Simulating Single-cell Events

Despite decades of substantial research, cancer remains a ubiquitous scourge in the industrialized world. Effective treatments require a thorough understanding of macroscopic cancerous tumor growth out of individual cells. Clinical imaging methods, however, only detect late-stage macroscopic tumors, while many quantitative experiments focus on small clusters of cancerous cells in microscopic detail but struggle to grow full tumors in-vitro. Here, we introduce the critical scale-bridging link between both these scopes. We are able to simulate the growth of mm-sized tumors composed of 1.5 million m-resolved individual cells by employing highly parallelized code on a supercomputer. We observe the competition for resources and space, which can lead to hypoxic or necrotic tissue regions. Cellular mutations and tumor stem cells can lead to tissue heterogeneity and change tumor properties. We probe the effects of different chemotherapy and radiotherapy treatments and observe selective pressure. This improved theoretical understanding of cancer growth as emerging behavior from single-cells opens new avenues for various scientific fields, ranging from developing better early-stage cancer detection devices to testing treatment regimes in-silico for personalized medicine. Author summaryExperimental and microscopy techniques are rapidly advancing biology and the observability of tissue. The theoretical understanding of tissue either focuses on a few cells or continuous tissue. Here we introduce the scale-bridging theoretical link that is able to model single cells as well as tissue consisting of millions of those cells, harvesting the power of modern supercomputers. We close the gap between single-cells and tissue through access to the full time-resolved trajectories of each cell and the emerging behavior of the tissue. We apply our framework on a generalized model for tumor growth. Tumor heterogeneity, as well as tumor stem cells are introduced, and the changes of behavior in response to cancer treatments is observed and validated.