BME PhD Candidate John L. Sperduto will be defending his dissertation:


A Microvessel-on-a-Chip for Studying how Tumor-Derived Factors Prime the Endothelium for Extravasation



Metastasis is a leading cause of disability and death from cancer. Each year, 50% of new cancer patients are diagnosed with metastasis and must undergo immediate, aggressive, and crippling treatment. Within 5 years, 60% of these patients will die.

These dire statistics translate to staggering mortality. In 2020 alone, 5.8 million patients died from metastasis. By 2040, this mortality will increase to an estimated 8.4 million deaths.

Yet few effective treatments for metastasis exist. One reason for this deficiency is poor understanding about how circulating tumor cells escape through the endothelium into the surrounding tissue of distant organs. This process, called extravasation, is critical. If it does not occur, metastasis cannot progress and 5-year survival increases from 25% to 56%. Better understanding extravasation could therefore be vital to improving treatments for metastasis and reducing its mortality.

However, obtaining new insight about extravasation is challenging. One major roadblock is studying extravasation and its underlying pathophysiology in vitro. Current culture models lack key mechanical cues crucial to producing an endothelial monolayer replicating the endothelium in vivo. Better modeling extravasation in vitro is thus pivotal to better understanding its pathophysiology in vivo. This dissertation therefore aimed to create a microvessel-on-a-chip model for studying extravasation and its underlying processes in vitro with improved physiological relevance and high spatiotemporal resolution.

The first objective was developing the model. This consisted of reviewing existing microvessel-on-a-chip models for their advantages and disadvantages, then using this information to design the model, and finally developing processes to fabricate the model and form endothelial microvessels inside it.

The second objective was developing tools to quantify key metrics of endothelial phenotype and function from the model. This consisted of developing a toolbox of image processing algorithms and corresponding ImageJ macros for quantifying permeability, patency, protein expression, and morphology. This toolbox provides a semi-automated method to obtain high-resolution data that is laborious, cumbersome, and often inaccurate to obtain via manual means.

The third objective was validating if the model produces endothelial microvessels that replicate key properties of the endothelium in vivo. This consisted of quantifying permeability, patency, protein expression, and morphology of microvessels cultured under static, flow, and inflamed conditions. Results show that the model produces microvessel replicating key properties from in vivo, including very low permeabilities to 70kDa (<1E-08 cm/s) and 10kDa (~1E-07 cm/s) dextrans, few-to-no focal leaks (<2 leak/mm), dense and continuous adherens junctions, cell elongation and orientation with flow, cytoskeletal alignment with flow, and an appropriate response to inflammatory stimuli.

The fourth and final objective was applying the model to study how tumor proteins and tumor extracellular vesicles can prime the endothelium to facilitate extravasation. Results show that tumor proteins, as expected, have a strong capacity to disrupt and inflame the endothelium: they increased permeability, decreased patency, and shifted endothelial cells to a more mesenchymal phenotype. In contrast, tumor extracellular vesicles showed limited capacity, if any, to disrupt or inflame the endothelium. While preliminary, these results question the current paradigm that tumor extracellular vesicles prime the endothelium for extravasation. They also highlight the utility of the microvessel-on-a-chip for studying how tumor factors can prime the endothelium to facilitate extravasation.

In sum, this dissertation presents a microvessel-on-a-chip model for studying extravasation and its underlying processes in vitro. This model is a promising addition to existing culture models and provides newfound physiological relevance while maintaining high spatiotemporal resolution. By doing so, it can advance understanding of extravasation and thereby help improve treatments for metastasis.