Person:

Tabassum, Doris P.

SUMMARY Cancers arise through a process of somatic evolution that can result in substantial sub-clonal heterogeneity within tumors. The mechanisms responsible for the coexistence of distinct sub-clones and the biological consequences of this coexistence remain poorly understood. Here we used a mouse xenograft model to investigate the impact of sub-clonal heterogeneity on tumor phenotypes and the competitive expansion of individual clones. We found that tumor growth can be driven by a minor cell subpopulation, which enhances the proliferation of all cells within a tumor by overcoming environmental constraints and yet can be outcompeted by faster proliferating competitors, resulting in tumor collapse. We then developed a mathematical modeling framework to identify the rules underlying the generation of intratumor clonal heterogeneity. We found that non-cell autonomous driving, together with clonal interference, stabilizes sub-clonal heterogeneity, thereby enabling inter-clonal interactions that can lead to new phenotypic traits.

Breast cancer is a highly heterogeneous disease, having not only several intrinsic sub-types but also significant sub-clonal heterogeneity within tumors. Intra-tumor heterogeneity can have profound impact on tumor evolution, disease progression and response to therapy. Furthermore, these phenomena can also be influenced by interactions of cancer cells with those of the microenvironment, thereby adding an extra layer of complexity to the study of tumor biology.

To investigate the impact of sub-clonal heterogeneity on tumor phenotypes, we developed a heterogeneous mouse xenograft model of breast cancer. Our model revealed that tumor growth can be driven by a minor clone, expressing IL11, in a non-cell autonomous fashion mediated through the microenvironment. We also found that non-cell autonomous driving and clonal interference stabilizes sub-clonal heterogeneity, thereby enabling inter-clonal interactions leading to new phenotypic traits.

Utilizing the same model, we identified cooperative interactions between IL11- and FIGF- expressing sub-clones that enhance the metastatic behavior of the tumor as a whole. We found that metastatic cooperation between these two populations result in larger and heterogeneous lung metastasis. Using expression profiles from primary tumors and corresponding metastatic lesions, we identified several key immune-regulatory and extracellular matrix (ECM) remodeling pathways that promote metastasis in our model system.

Lastly, we examined heterotypic interactions between tumor cells and cancer associated fibroblasts (CAFs) to understand the mechanism of resistance to lapatinib. Using a 3D co-culture model, we identified significant sub-type-specific changes in gene expression, metabolic, and therapeutic sensitivity profiles of breast cancer cells induced by CAFs. We identified JAK2/STAT3 pathway and CAF-secreted hyaluronan as major factors contributing to CAF-mediated protection. We also found that close spatial proximity to CAFs impacts therapeutic responses by affecting proliferation rates of cancer cells.

In summary, we have used in vitro and in vivo models systems to identify key interactions within populations of tumors cells, as well as between tumor microenvironmental components and cancer cells, to identify mechanisms that influence tumorigenesis, metastasis and drug response. We believe that these findings will increase our understanding of breast cancer heterogeneity and enable us to design better therapeutic regimens to eradicate the disease.