In a simplified world, tumours are a collection of phenotypically and genotypically identical cells, and grow like spheroids, degrading the surrounding tissue. If this were the case, cancer research would probably have reached its goal many years ago. Unfortunately, as we all know, cancer is a multifactorial disease where phenotypic variation within the cancer cell population and microenvironment heterogeneity determine a number of complex interactions, which we will struggle to characterise as a whole. In the stroma, the connective tissue in which tumours grow, a number of cellular components, soluble and non-soluble factors are found to play an active role in tumour progression and, most importantly, to facilitate therapeutic escape. Indeed, the tumour microenvironment can induce a transient type of drug resistance, known as EMDR (environment-mediated drug resistance), protecting cells from therapy-induced cell death. Eventually this mechanism leads to patient relapse, caused by a rapid tumour regrowth after the therapy has been halted. At the end of my first year as a graduate student at the SABS Industrial Doctorate Centre, one of the Doctoral Training Centre programmes, I had the opportunity to undertake two short projects in two different research groups, in collaboration with the programme’s industrial partners.
During my first 10-week project, based in the Integrated Mathematical Oncology group at the Moffitt Cancer Center in Florida, I looked specifically at the interactions between CAFs (cancer-associated fibroblasts, the main cellular component of the tumour stroma) and melanoma cancer cells. Experimental observations show that melanoma cells recruit fibroblasts from the host tissue, resulting in a population of CAFs, which in turn stimulate proliferation (via production of growth factors) and environment-mediated drug resistance (via cell adhesion and survival signalling) in the cancer cell population. We can describe this mechanism with a dynamical model of cancer cell and fibroblast interactions. In the mathematical model, adapted from Flach et al. (2011), we investigate the crosstalk between two types of cancer cells and CAFs. Fibroblasts, recruited by cancer cells, stabilise the tumour mass, creating a protective niche and allowing the transition from a “free” type of cancer cell (representing the treatment-sensitive and proliferating population at the leading edge of the mass) to a “blocked” type of cancer cell (corresponding to the non-proliferative core, where the infiltration of CAFs allows treatment resistance).
|Adapted from Flach et al. Molecular Pharmaceutics 8 (2011) 2039-2049.|
This model represents a starting point for describing tumour-stroma interactions. Despite its simplicity, it allows us to compare the effects of chemotherapy (non-specific killing of all cell types, including fibroblasts) and targeted therapy (affecting only the “free” cancer cell population). The surviving portion of “blocked” cancer cells, protected by host cells from drug-induced cell death programmes, allows post-treatment regrowth. In order to fully characterise spatial variations in the tumour-stroma crosstalk, and the effects of a heterogeneous stroma, this model needs to be expanded to a spatial one. Additional environment components such as extracellular matrix and growth factors can be included, in order to explicitly describe the processes that orchestrate the interactions between tumour and stromal cells. Finally, the tumour stroma not only plays a promoting role in tumour initiation and progression, but it has been traditionally known to have a normalising and limiting effect against tumourigenesis. An initial question that we need to address is: how does the tumour stroma balance its cooperative versus competitive action?
This briefly describes the main direction that my D.Phil. project, which I have just started here at the WCMB, will take. Understanding the complex crosstalk between tumour and host tissue will allow us to identify the main interactions that drive the dynamics of the system, leading eventually to the definition of more successful therapies targeting the stroma, as opposed to targeted therapies that leave behind a resistant cancer cell population and hasten tumour progression.