Image-based Systems Biology

Our growing understanding of cancer pathways has been the result of pioneering studies spanning the cellular, microvascular and tissue levels. However, visualizing these pathways remains a challenge due to the lack of integration between micro- and macroscopic cancer imaging data, which also presents a major hurdle for developing computational models of tumor biology. Therefore, we have initiated the development of ‘multiscale imaging’ for cancer systems biology (Kim et al. 2012). This approach employs imaging methods such as ‘mesoscopic’ scale magnetic resonance microscopy, to bridge the resolution gap between micro- and macroscopic imaging data (Cebulla et al. 2014). Such ‘multiscale’ datasets help correlate the underlying genotype with the emergent tumor phenotype (Kim et al. 2011) and facilitate development of ‘image-based’ models of cancer pathways (Kim et al. 2012). Currently, in collaboration with Dr. Popel’s Systems Biology Laboratory we are using this approach to gain new insight into the role of angiogenesis in breast cancer progression (Stamatelos et al. 2014).

 Multiscale imaging for image-based systems biology and phenotyping [ Link to paper ].

Multiscale imaging for image-based systems biology and phenotyping [Link to paper].

 Image-based modeling of tumor blood flow in a breast cancer xenograft model [ Link to paper ].

Image-based modeling of tumor blood flow in a breast cancer xenograft model [Link to paper].