We develop an experimental-computational approach that will accurately classify tumors, such that every single tumor can be mapped precisely and unambiguously according to its characteristics, namely the changes in gene structure (mutations) that it harbors. These mutations cause an imbalance in the activity network of the cancer cell. This network, which determines how how cancer cell behaves, represents a web of interactions between molecules in the cell that can turn each other off or on. Those interactions together generate a flow of information by which a tumor cell will make “decisions”, for example whether to die or to live.

Our algorithms allow us to identify unbalanced networks in tumor cells, for each particular patient.They also allow us to propose drugs that will target particular components of the network, in order to restore balance, and correct the processes, preferentially by killing the tumor cell.

We develop a computational-experimental strategy, based on information theory that resolves the intra-tumor molecular heterogeneity on the single cell level and allows to rationally design patient-specific treatments. The approach breaks down tumors into the subpopulations that they possess, and altered protein networks associated with each subpopulation. The resolved patient-specific intra-tumor heterogeneity is used to predict and test the optimal treatment. Moreover, these networks can be used to rationally plan personalized sensitization of TNBC tumors to RT/ CT. 

The architecture of tumors plays an important role in tumor development. The understanding of these structures and the forces that drive their formation is of high importance in cancer research and therapy. We develop quantitative experimental-theoretical methods to provide an in-depth understanding of the influence of the cell-cell and cell-environment interactions on directed cell-cell movement, cellular signaling and cancer tissues architectures.

Our studies encompass analytical approaches from physics and chemistry, molecular profiling and analysis of tumor tissues, single cell measurements and live cell imaging of 2D and 3D cell cultures.