Our goal is to identify mechanisms behind cellular diversity in highly heterogeneous brain tumors and use our knowledge to develop new ways to target these malignancies.
Therapies aiming at molecular targets significantly increased the efficacy of cancer treatment. However, in many instances, resistance develops and leads to progression of the disease. Development of resistance and recurrence is often due to intratumor heterogeneity, that drives evolution of the tumor during treatment. Genetically, epigenetically or phenotypically distinct subpopulations of cancer cells within a tumor can respond differently to therapy due to variable expression of the treatment target or presence of resistance-conferring mutations. Treatment-associated changes arising within the microenvironment of a growing tumor mass, such as nutrient and oxygen supply, often select for more opportunistic cells. Therefore, designing better methods of detection of rare resistant cells in treatment-naïve tumor samples and understanding of the cellular selection processes would help predict patient outcomes and guide future therapies. We aim to uncover the functional relevance of genetic intratumor heterogeneity in development of treatment resistance, which will allow us to design methods for early detection of resistance-conferring clones in heterogeneous tumors.
In normal tissues genetically identical cells can assume different functions due differentiation programs controlled by chromatin organization. This epigenetic control of gene expression is often deregulated in cancer and may also contribute to intratumor heterogeneity. We aim to dissect the mechanisms of interactions between genetically and epigenetically heterogeneous cells in diverse microenvironments. These efforts will improve our understanding of the impact of treatment on tumor evolution, leading to development of drugs targeting inter-clonal interactions early in tumor progression and lead to recurrence prevention.
Human tumors are very complex, thus standard cell cultures and transgenic models are not faithfully recapitulating full heterogeneity of cancer. However, to be able to perturb particular cellular interactions and test our hypotheses, model systems will be required. We will generate in vitro and in vivo systems, to mimic interactions between different subpopulations of cancer cells and their microenvironment.
Glioblastoma, the most aggressive form of brain tumor, remains an unmet medical need, as despite chemotherapy and radiation the median survival with this tumor is only 16 months. We aim to identify novel therapeutic targets and develop more effective treatment for this tumor. Our interdisciplinary approach bridges cancer biology, computational chemistry and structure biology to drive innovative therapies targeting intratumor heterogeneity.