Abstract
We are interested in understanding how cancer cells adopt different shapes in response to informational and mechanical cues. Because different cell forms are absolutely necessary for tumorigenesis and metastasis, gaining insight into the mechanisms of cell morphogenesis will open up therapeutic avenues. At the molecular level, morphogenesis is an emergent property of dynamical interactions amongst numerous proteins across different time and space scales. These interactions act to control adhesion, protrusion, and contraction. Cell shape is also a function of cell level properties such as size, proliferation rates, and differentiation state. Finally, the shape of an individual cell is a reflection of cell-cell interactions and tissue organization. Because of the complex, and multi-scale nature of cell morphogenesis, using systems-level approaches to study cell shape determination is warranted.
To gain systems-level insights into cell morphogenesis, we have developed new “image-omic” approaches; where we integrate datasets derived from high-throughput imaging, proteomic/phosphoproteomic, and genomic analyses. These approaches have two advantages over classical “bottom-up” methods that have been typically used to study cell shape determination: (1) We can use image-omics to gain a comprehensive description of the biochemical networks that couple the control of different cellular processes to environmental flux. Thus we can gain unbiased mechanistic understanding into how cell shape is controlled. (2) We can also use our image-omic models to predict genotypes, mRNA/protein levels, or enzymatic activity based on cell shape. Meaning, we can use quantification of cell shape as a diagnostic tool to predict different clinically relevant aspects of cancer cells, such as their mutation status, or the activation of key signaling pathways.
I will discuss recent studies where we have used image-omics to understand how common mutations that drive melanoma, such as activating mutations in BRAF or NRAS, affect cell morphogenesis. We have found that in melanoma cells, different mutations alter the wiring of signaling networks that control cell cycle progression, cell growth (accumulation of mass), and adhesion – leading to diverse shapes. This work suggests that balancing proliferation rates, volume, and adhesiveness is an important design principle in cell shape determination.
I will also discuss how we are using image-omic models to develop rapid, cost-efficient, single-cell diagnostics for clinical use.
