Overcoming the Tumor Microenvironment and Heterogeneity to Improve Preclinical Response
It is well known that the tumor microenvironment is quite complex to model preclinically. A major challenge we face is that there are numerous different cancer types along with many different mutations that make up the diversity of cancers. Therefore, the path each malignancy evolves proves to be very different.
One of the key mechanisms that drives cancer is heterogeneity. Tumor heterogeneity changes with treatment and eventually leads to therapy failure. Understanding how treatment can change the make-up of tumors is crucial and we don’t tend to look at this very carefully.
Do the Models we have Embrace Heterogeneity?
It is critical to ensure we are capturing diversity and different mutations at all different stages of cancer. Patient-derived xenograft (PDX) models are proven to be both relevant and essential. The genomic integrity and heterogeneity are preserved and that is what leads to the popularity of these models. Furthermore, PDX models have been shown to be quite a predictive indicator of tumor sensitivity and resistance. Currently there exists a growing body of literature (including Gao H et al Nat Med 2015, Malaney et al Cancer Letters 2014) containing retrospective analysis, in addition to both co-clinical and personalized medicine approaches currently being utilized.
Although PDX models are great for heterogeneity they do lack the tumor microenvironment, being that they are subcutaneous tumors with no immune compartment association. Although blood supply, vascularization, hypoxia, and apoptosis are all occurring among other biological processes, the tumor in cancer patients is extremely self-sufficient, ever evolving and growing. Therefore, there exists an abundance of oncogenic drivers as well as by-standing mutations that we currently don’t understand.
There are also non-transformed cells that co-evolve with the tumor aiding in tumor progression, metastasis, and resistance. Both stromal interactions and the immune microenvironment are central to cancer and how all these changes are influenced by treatments are needed to be mimicked in our preclinical models. As one can surmise, heterogeneity and the tumor microenvironment are very closely aligned.
With the ever changing landscape in immuno-oncology there are more emerging targets, therapies, and combinatorial strategies that need to be evaluated. This is a challenge since all cannot be accomplished in the clinic, and there are only so many models that can effectively answer our scientific questions. As with all preclinical models there are limitations, so we have to try and understand what questions we are asking in order to identify what models are best suited.
We do need to be able to modulate the tumor microenvironment and that requires relevant preclinical models being at our disposal.
One such group of models that have been around for a long time are syngeneics. These models are both widely used and have been extensively characterized, thus enabling movement away from subcutaneous sites into orthotopic models. These models can then provide for better stromal interactions and allow us to look at what the immune system is doing in the relevant microenvironment rather than at subcutaneous sites.
Although there is a wide diversity in PDX models, covering both pretreated and naïve patients, collections can always be expanded to fill in the gaps where there are limitations, especially at different stages of disease and for rare mutations. One area where these new models can be developed from is co-clinical studies.
One way to do this is rapid autopsy, where patients on clinical trials have been treated and then PDX models are derived from relapsed patient tissue, allowing researchers to look at both late stage disease and also resistance. This strategy allows a better representation of the heterogeneity of later stage disease.
An alternative ex vivo system to mimic the microenvironment is also the 3D TGA assay. This assay stems from the fact that 2D cultures are not reflective of patients in many aspects such as hypoxic levels, oxygen tension, pH, stiffness, and glucose levels. 2D assays conducted on plastic are quite artificial compared to patients, whereas in a humanized 3D culture the disconnects have been repaired.
The cells are in the right environment, the right structures, getting the right interactions, and therefore are more relevant to their origin. Cells have memory and when put in the right environment they behave the same way and can remember where they came from and how to function, thus allowing response predictions to become much improved. As assays improve and more human components are added both the complexity and relevance will continually evolve.
Understanding Interplays to Progress Oncology Research
With a deeper understanding of the interplays between the tumor microenvironment, heterogeneity, and resistance more questions will continue to be raised and need to be answered utilizing the above capabilities we currently have in our preclinical oncology tool box.