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DC Field | Value | Language |
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dc.contributor.advisor | Zhang, Boyang | - |
dc.contributor.advisor | Wylie, Ryan | - |
dc.contributor.author | Marway, Mandeep | - |
dc.date.accessioned | 2025-10-15T18:29:34Z | - |
dc.date.available | 2025-10-15T18:29:34Z | - |
dc.date.issued | 2025 | - |
dc.identifier.uri | http://hdl.handle.net/11375/32518 | - |
dc.description.abstract | Modeling cancer in vitro remains a significant challenge due to the complexity of the tumor microenvironment (TME), including its immune microenvironment, cellular crosstalk, and drug transport processes. Additionally, effective cancer treatment remains a major clinical challenge, in part due to the limited ability of current preclinical models to replicate the complexity of the TME. Tumor-associated macrophages (TAMs) are key immune regulators that can either suppress or promote tumor progression depending on their phenotype. Immunotherapies that promote TAMs toward a pro-inflammatory state, such as cytokine-based treatments, have shown clinical promise, yet their translation is often hindered by rapid clearance and toxicity. Furthermore, conventional in vitro models rarely account for drug clearance, a crucial component of pharmacokinetics that influences both therapeutic efficacy and safety. These gaps highlight the need for more physiologically relevant models to better predict clinical outcomes and guide treatment strategies. To address these gaps, the IFlowPlate-T was developed as a high-throughput microfluidic platform that replicates key aspects of in vivo tissue physiology, including continuous clearance via tunable pressure gradients to study therapeutic efficacy under physiologically relevant conditions. This platform enables investigation of drug behavior under conditions that more closely reflect human tissue environments. The IFlowPlate-T was employed to evaluate how continuous clearance impacts local drug delivery in two cancer models: HER2-positive breast cancer (SKBR3; Chapter 2) and patient-derived glioblastoma (BT935; Chapter 4). Clearance studies using fluorescently labeled 4 and 65 kDa dextran demonstrated that high-pressure gradients effectively promoted high clearance into a designated clearance well. In the SKBR3 model (Chapter 2), spheroids and THP-1-derived macrophages embedded in fibrin gel were treated with IFN-γ, delivered via agarose with or without anti-HER2. Clearance diminished drug residence time and therapeutic efficacy, as evidenced by increased cancer cell viability, emphasizing the importance of clearance when conducting in vitro testing. Furthermore, pro-inflammatory cytokines like IL-6, MCP-1, and IL-8 showed higher clearance in the presence of the pressure gradient, suggesting that that rapid cytokine clearance may affect immune cell signaling and therapeutic outcomes, reinforcing the need to account for cytokine pharmacokinetics in preclinical models. In vivo, monocytes adhere loosely to the vascular lumen, get activated, and migrate between (paracellular migration) or through (transcellular migration) the endothelial cells (ECs) to the TME, activating the differentiation and polarization processes, a process not captured by chemically induced differentiation. Further investigation into the mechanisms regulating transendothelial monocyte migration was conducted using the IFlowPlate platform by incorporating a human umbilical vein endothelial cell (HUVEC) barrier, enabling the study of THP-1 monocyte transendothelial migration in response to BT935 spheroids (Chapter 3). In the presence of the EC barrier, THP-1 monocytes exhibited delayed and reduced migration, confirming its regulatory role in transendothelial migration. In the presence of the EC barrier, monocytes, and cancer spheroids, levels of GM-CSF, IL-6, IL-10, and IL-1β increased, TNF-α and IL-12p40 decreased, while MCP-1 and IL-8 remained unchanged, highlighting the EC barrier’s role in regulating monocyte activation and migration. In the BT935 model (Chapter 4), continuous clearance reduced the efficacy of IFN-γ treatment, while co-treatment with anti-CD133 was less affected. Notably, transendothelial migration of THP-1 monocytes across an endothelial barrier combined with IFN-γ and anti-CD133 resulted in significantly greater cancer cell death compared to PMA-differentiated macrophages, although clearance still diminished this effect. This highlights that modeling monocyte migration and differentiation in situ more closely mimics in vivo immune responses and enhances therapeutic efficacy compared to chemically induced macrophages. Collectively, these studies highlight the importance of modeling interstitial clearance and vascular interfaces in vitro to capture drug responses and immune-tumor dynamics. Unlike prior organ-on-a-chip models, our platforms uniquely integrate physiologically relevant interstitial clearance with transendothelial monocyte migration, capturing both drug clearance dynamics and immune cell recruitment within a high-throughput format. The IFlowPlate-T and IFlowPlate platforms offer versatile and physiologically relevant systems for preclinical evaluation of immunotherapies and localized drug delivery strategies in cancer. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Organ-on-a-chip | en_US |
dc.subject | Macrophages | en_US |
dc.subject | Monocytes | en_US |
dc.subject | Clearance | en_US |
dc.title | Microfluidics Meet Immunotherapy: Improving Preclinical Cancer Models | en_US |
dc.title.alternative | In Vitro 3D Cancer-on-a-chip Models for Immunotherapy Testing | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Biomedical Engineering | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Doctor of Philosophy (PhD) | en_US |
dc.description.layabstract | Organ-on-a-chip technology is a powerful tool that lets scientists grow human cells in tiny devices designed to replicate key organ functions. These chips create mini versions of tissues like the brain, liver, or lungs to study how they work, test new drugs, and understand diseases better without needing large-scale experiments or animals. Treating cancer is difficult because it is hard to recreate what happens inside the human body in the lab. Tumors are surrounded by a complex environment made up of different cells, immune responses, and constantly moving fluids. This environment plays a big role in how cancer grows and how treatments work. Unfortunately, many current lab models do not fully capture this complexity, especially when it comes to how drugs move through tissues and get cleared from the body. These limitations make it hard to predict how well a new therapy will work in real patients. To address this problem, we developed a lab tool called the IFlowPlate-T, which mimics some of the body’s natural processes, including how fluids are drained (similar to lymphatic clearance). This platform allows researchers to test cancer treatments under more realistic conditions, which could lead to more effective therapies in the future. Using this tool, we studied how immune-based treatments work in two types of cancer: HER2-positive breast cancer and glioblastoma, a type of aggressive brain tumor. In both cases, we found that when fluids are cleared quickly, similar to what happens in the body, drugs did not stay around long enough to be fully effective. However, combining therapies or adjusting the delivery method helped overcome this issue. We also looked at how immune cells, specifically monocytes and macrophages, interact with cancer cells using another platform known as the IFlowPlate. In the body, monocytes must pass through blood vessel walls to become macrophages and fight disease. To replicate this, we added a layer of human blood vessel cells to the model. This made it harder for immune cells to reach the tumor, just like in real tissues, and changed how they behaved. We observed shifts in immune signaling molecules (cytokines), suggesting that the blood vessel layer plays a big role in shaping the immune response. Altogether, this work shows that capturing how fluids move and how immune cells interact with tumors is essential for building more accurate cancer models. The IFlowPlate-T and the IFlowPlate represent a step forward in designing lab tools that better reflect what happens in patients, helping scientists test treatments more effectively before they reach clinical trials. | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Marway_Mandeep_K_Final Submission_202509_PhD.pdf | 4.63 MB | Adobe PDF | View/Open |
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