Biology subjects

Carmona-Fontaine, C.

Publications and source records attributed to Carmona-Fontaine, C..

4 recordsLinked to original sources

bioRxiv2023

Direct visualization of emergent metastatic features within an ex vivo model of the tumor microenvironment

Metabolic conditions such as hypoxia, nutrient starvation, and media acidification, together with interactions with stromal cells are critical drivers of metastasis. Since these conditions arise deep within tumor tissues with poor access to the bloodstream, the observation of nascent metastases in vivo is exceedingly challenging. On the other hand, conventional cell culture studies cannot capture the complex nature of metastatic processes. We thus designed and implemented an ex vivo model of the tumor microenvironment to study the emergence of metastatic features in tumor cells in their native 3-dimensional (3D) context. In this system, named 3MIC, tumor cells spontaneously create ischemic-like conditions, and it allows the direct visualization of tumor-stroma interactions with high spatial and temporal resolution. We studied how 3D tumor spheroids evolve in the 3MIC when cultured under different metabolic environments and in the presence or absence of stromal cells. Consistent with previous experimental and clinical data, we show that ischemic environments increase cell migration and invasion. Importantly, the 3MIC allowed us to directly observe the emergence of these pro-metastatic features with single-cell resolution allowing us to track how changes in tumor motility were modulated by macrophages and endothelial cells. With these tools, we determined that the acidification of the extracellular media was more important than hypoxia in the induction of pro-metastatic tumor features. We also illustrate how the 3MIC can be used to test the effects of anti-metastatic drugs on cells experiencing different metabolic conditions. Overall, the 3MIC allows us to directly observe the emergence of metastatic tumor features in a physiologically relevant model of the tumor microenvironment. This simple and cost-effective system can dissect the complexity of the tumor microenvironment to test perturbations that may prevent tumors from becoming metastatic.

cancer biology↗

bioRxiv2022

Hypoxia potentiates the inflammatory fibroblast phenotype promoted by pancreatic cancer cell-derived cytokines

Cancer-associated fibroblasts (CAFs) are a major cell type in the stroma of solid tumors and can exert both tumor-promoting and tumor-restraining functions. This functional heterogeneity is correlated with the existence of transcriptionally distinct subpopulations of CAFs. CAF heterogeneity is observed in pancreatic ductal adenocarcinoma (PDAC), a tumor characterized by a remarkably dense and hypoxic stroma that features tumor-restraining myofibroblastic CAFs (myCAFs) and tumor-supporting inflammatory CAFs (iCAFs). While CAF heterogeneity can be driven in part by tumor cell-produced cytokines, other determinants shaping CAF identity and function are largely unknown. In vivo, we found that iCAFs display a hypoxic gene expression and biochemical profile and are enriched in hypoxic regions of PDAC tumors. Hypoxia leads fibroblasts to acquire an inflammatory gene expression signature and synergizes with cancer cell-derived cytokines to promote an iCAF phenotype in a HIF-1 dependent fashion. Furthermore, we show that HIF-1 stabilization is sufficient to induce an iCAF phenotype in stromal cells introduced into PDAC organoid co-cultures and to promote PDAC tumor growth. These findings indicate hypoxia-induced HIF-1 as a regulator of CAF heterogeneity and promoter of tumor progression in PDAC.

cell biology↗

bioRxiv2021

The MEMIC: An ex vivo system to model the complexity of the tumor microenvironment

There is an urgent need for accurate, scalable, and cost-efficient models of the complexity and heterogeneity of the tumor microenvironment. Here, we detail how to fabricate and use the Metabolic Microenvironment Chamber (MEMIC) - a 3D-printed ex vivo model of intratumoral heterogeneity. A major driver of the cellular and molecular diversity in tumors is the accessibility to the blood stream that provides key resources such as oxygen and nutrients. While some tumor cells have direct access to these resources, many others must survive under progressively more ischemic environments as they reside further from the vasculature. The MEMIC is designed to simulate the differential access to nutrients and allows co-culturing different cell types, such as tumor and immune cells. This system is optimized for live imaging and other microscopy-based approaches and it is a powerful tool to study tumor features such as the effect of nutrient scarcity on tumor-stroma interactions. Due to its adaptable design and full experimental control, the MEMIC can provide novel insights into the tumor microenvironment that would be difficult to obtain via other methods. As a proof of principle, we show that cells can sense gradual changes in metabolite concentration, and tune intracellular cell signaling to form multicellular spatial patterns of cell proliferation. We also show that ischemic macrophages reduce epithelial features in neighboring tumor cells highlighting the power of this system to study cell-cell interactions and non-cell autonomous effects of the metabolic microenvironment. We propose that the MEMIC can be easily adapted to study early development, ischemic stroke, and other systems where multiple cell types interact within heterogeneous environments.

cancer biology↗

bioRxiv2017

A simple rule for the evolution of fast dispersal at the edge of expanding populations

Predicting evolution of expanding populations is critical to control biological threats such as invasive species and cancer metastasis. Expansion is primarily driven by reproduction and dispersal, but nature abounds with examples of evolution where organisms pay a reproductive cost to disperse faster. When does selection favor this survival of the fastest? We searched for a simple rule, motivated by evolution experiments where swarming bacteria evolved into an hy-perswarmer mutant which disperses[~] 100% faster but pays a growth cost of [~] 10% to make many copies of its flagellum. We analyzed a two-species model based on the Fisher equation to explain this observation: the population expansion rate (v) results from an interplay of growth (r) and dispersal (D) and is independent of the carrying capacity: [Formula]. A mutant can take over the edge only if its expansion rate (v2) exceeds the expansion rate of the established species (v1); this simple condition (v2 > v1) determines the maximum cost in slower growth that a faster mutant can pay and still be able to take over. Numerical simulations and time-course experiments where we tracked evolution by imaging bacteria suggest that our findings are general: less favorable conditions delay but do not entirely prevent the success of the fastest. Thus, the expansion rate defines a traveling wave fitness, which could be combined with trade-offs to predict evolution of expanding populations.

evolutionary biology↗