Biology subjects

Munson, J. M.

Publications and source records attributed to Munson, J. M..

10 recordsLinked to original sources

bioRxiv2025

Interstitial fluid transport dynamics predict glioblastoma invasion and progression

Glioblastoma is characterized by aggressive infiltration into surrounding brain tissue, hindering complete surgical resection and contributing to poor patient outcomes. Identifying tumor-specific invasion patterns is essential for advancing our understanding of glioblastoma progression and improving surgical and radiotherapeutic strategies. Here, we leverage in vivo dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to noninvasively quantify interstitial fluid velocity, direction, and diffusion within and around glioblastomas. We introduce a novel vector-based pathline analysis to trace downstream accumulation of fluid flow originating from the tumor core, providing a spatially explicit perspective on local flow patterns. We find that localized fluid transport metrics predict glioblastoma invasion and progression, offering a new framework to non-invasively identify high-risk regions and guide targeted treatment approaches. One sentence summaryInvasion and progression of glioblastoma can be predicted with interstitial fluid flow patterns via magnetic resonance imaging.

bioengineering↗

bioRxiv2024

Engineered human lymph node stroma model for examining interstitial fluid flow and T cell egress

The lymph node (LN) performs essential roles in immunosurveillance throughout the body. Developing in vitro models of this key tissue is of great importance to enhancing physiological relevance in immunoengineering. The LN consists of stromal populations and immune cells, which are highly organized and bathed in constant interstitial flow. The stroma, notably the fibroblastic reticular cells (FRCs) and the lymphatic endothelial cells (LECs), play crucial roles in guiding T cell migration and are known to be sensitive to fluid flow. During inflammation, interstitial fluid flow rates drastically increase in the LN. It is unknown how these altered flow rates impact crosstalk and cell behavior in the LN, and most existing in vitro models focus on the interactions between T cells, B cells, and dendritic cells rather than with the stroma. To address this gap, we developed a human engineered model of the LN stroma consisting of FRC-laden hydrogel above a monolayer of LECs in a tissue culture insert with gravity-driven interstitial flow. We found that FRCs had enhanced coverage and proliferation in response to high flow rates, while LECs experienced decreased barrier integrity. We added CD4+ and CD8+ T cells and found that their egress was significantly decreased in the presence of interstitial flow, regardless of magnitude. Interestingly, 3.0 {micro}m/s flow, but not 0.8 {micro}m/s flow, correlated with enhanced inflammatory cytokine secretion in the LN stroma. Overall, we demonstrate that interstitial flow is an essential consideration in the lymph node for modulating LN stroma morphology, T cell migration, and inflammation.

bioengineering↗

bioRxiv2024

Ex vivo model of breast cancer cell invasion in live lymph node tissue

Lymph nodes (LNs) are common sites of metastatic invasion in breast cancer, often preceding spread to distant organs and serving as key indicators of clinical disease progression. However, the mechanisms of cancer cell invasion into LNs are not well understood. Existing in vivo models struggle to isolate the specific impacts of the tumor-draining lymph node (TDLN) milieu on cancer cell invasion due to the co-evolving relationship between TDLNs and the upstream tumor. To address these limitations, we used live ex vivo LN tissue slices with intact chemotactic function to model cancer cell spread within a spatially organized microenvironment. After showing that BRPKp110 breast cancer cells were chemoattracted to factors secreted by naive LN tissue in a 3D migration assay, we demonstrated that ex vivo LN slices could support cancer cell seeding, invasion, and spread. This novel approach revealed dynamic, preferential cancer cell invasion within specific anatomical regions of LNs, particularly the subcapsular sinus (SCS) and cortex, as well as chemokine-rich domains of immobilized CXCL13 and CCL1. While CXCR5 was necessary for a portion of BRPKp110 invasion into naive LNs, disruption of CXCR5/CXCL13 signaling alone was insufficient to prevent invasion towards CXCL13-rich domains. Finally, we extended this system to pre-metastatic TDLNs, where the ex vivo model predicted a lower invasion of cancer cells. The reduced invasion was not due to diminished chemokine secretion, but it correlated with elevated intranodal IL-21. In summary, this innovative ex vivo model of cancer cell spread in live LN slices provides a platform to investigate cancer invasion within the intricate tissue microenvironment, supporting time-course analysis and parallel read-outs. We anticipate that this system will enable further research into cancer-immune interactions and allow isolation of specific factors that make TDLNs resistant to cancer cell invasion, which are challenging to dissect in vivo.

bioengineering↗

bioRxiv2024

Mitigating reactive oxygen species production and increasing gel porosity improves lymphocyte motility and fibroblast spreading in photocrosslinked gelatin-thiol hydrogels

On-chip 3D culture systems that incorporate immune cells such as lymphocytes and stromal cells are needed to model immune organs in engineered systems such as organs-on-chip. Photocrosslinking is a useful tool for creating such immune-competent hydrogel cultures with spatial cell organization. However, loss of viability and motility in photocrosslinked gels can limit its utility, especially when working with fragile primary cells. We hypothesized that optimizing photoexposure-induced ROS production, hydrogel porosity or a combination of both factors was necessary to sustain cell viability and motility during culture in photocrosslinked gelatin-thiol (GelSH) hydrogels. Jurkat T cells, primary human CD4+ T cells and human lymphatic fibroblasts were selected as representative lymphoid immune cells to test this hypothesis. Direct exposure of these cells to 385 nm light and LAP photoinitiator dramatically increased ROS levels. Pretreatment with an antioxidant, ascorbic acid (AA), protected the cells from light + LAP-induced ROS and was non-toxic at optimized doses. Furthermore, scanning electron microscopy showed that native GelSH hydrogels had limited porosity, and that adding collagen to GelSH precursor before crosslinking markedly increased gel porosity. Next, we tested the impact of AA pretreatment and increasing gel porosity, alone or in combination, on cell viability and function in 3D GelSH hydrogel cultures. Increasing gel porosity, rather than AA pretreatment, was more critical for rescuing viability of Jurkat T cells and spreading of human lymphatic fibroblasts in GelSH-based gels, but both factors improved the motility of primary human CD4+ T cells. Increased porosity enabled formation of spatially organized co-cultures of primary human CD4+ T cells and human lymphatic fibroblasts in photo-crosslinked gels in a multi-lane microfluidic chip, towards modeling the lymphoid organ microenvironment. Some optimization is still needed to improve homogeneity between regions on the chip. These findings will enable researchers utilizing photocrosslinking methods to develop immunocompetent 3D culture models that support viability and function of sensitive lymphoid cells.

bioengineering↗

bioRxiv2023

Structural and practical identifiability of contrast transport models for DCE-MRI

Compartment models are widely used to quantify blood flow and transport in dynamic contrast-enhanced magnetic resonance imaging. These models analyze the time course of the contrast agent concentration, providing diagnostic and prognostic value for many biological systems. Thus, ensuring accuracy and repeatability of the model parameter estimation is a fundamental concern. In this work, we analyze the structural and practical identifiability of a class of nested compartment models pervasively used in analysis of MRI data. We combine artificial and real data to study the role of noise in model parameter estimation. We observe that although all the models are structurally identifiable, practical identifiability strongly depends on the data characteristics. We analyze the impact of increasing data noise on parameter identifiability and show how the latter can be recovered with increased data quality. To complete the analysis, we show that the results do not depend on specific tissue characteristics or the type of enhancement patterns of contrast agent signal.

systems biology↗

bioRxiv2023

Non-invasive measurement of intra-tumoral fluid dynamics with localized convolutional function regression

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to non-invasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that it will contribute to the better understanding of cancer progression and therapeutic response. One-Sentence SummaryA physics-informed computational method enables accurate and efficient measurement of fluid dynamics in individual patient tumors and demonstrates differences between tissues.

bioengineering↗

bioRxiv2021

Fusobacterium nucleatum infection induces pancreatic cancer cell proliferation and migration through regulation of host cytokine signaling

Pancreatic ductal adenocarcinoma (PDAC) harbors a complex tumor microbiome that has been implicated in cancer progression and resistance to chemotherapy. Recent clinical investigations uncovered a correlation between high loads of intratumor Fusobacterium nucleatum and decreased patient survival. Here we show that healthy and cancerous pancreatic cell lines harboring intracellular F. nucleatum secrete increased levels of cancer-associated cytokines including GM-CSF, CXCL1, IL-8, and MIP-3. We report that GM-CSF (granulocyte-macrophage colony stimulating factor) secretion directly increases the proliferation and migration of pancreatic cancer cells via an autocrine mechanism, notably in the absence of immune cell participation. Furthermore, we show that non-cancerous pancreatic epithelial cells do not exhibit increased proliferation or migration in response to these cytokines, but nevertheless, their secreted cytokines stimulate these responses in cancerous cell lines through paracrine signaling. Our results provide evidence that intratumor F. nucleatum in the pancreas elicits an infection-specific cytokine secretion profile from both normal and cancerous cells that adversely contributes to cancer progression through autocrine and paracrine mechanisms. Therefore, these results support the importance of investigating the contributions of both microbiome and host driven processes in pancreatic cancer to guide future therapeutic interventions.

cancer biology↗

bioRxiv2019

2D or 3D? How in vitro cell motility is conserved across dimensions, and predicts in vivo invasion

Cell motility is a critical aspect of wound healing, the immune response, and is deregulated in cancer. Current limitations in imaging tools make it difficult to study cell migration in vivo. To overcome this, and to identify drivers from the microenvironment that regulate cell migration, bioengineers have developed 2D and 3D tissue model systems in which to study cell motility in vitro, with the aim of mimicking the environments in which cells move in vivo. However, there has been no systematic study to explicitly relate and compare cell motility measurements between these geometries/systems. Here, we provide such analysis on our own data, as well as across data in existing literature to understand whether, and which, in vitro models are predictive of in vivo cell motility. To our surprise, many metrics of cell movement on 2D surfaces significantly and positively correlate with cell migration in 3D environments, and cell invasion in 3D is negatively correlated with glioblastoma invasion in vivo. Finally, to best compare across complex model systems, in vivo data, and data from different labs, we suggest that groups report an effect size, a statistical tool that is most translatable across experiments and labs, when conducting experiments that affect cellular motility.

bioengineering↗

bioRxiv2018

Convective forces increase CXCR4-dependent glioblastoma cell invasion in GL261 murine model

Glioblastoma is the most common and malignant form of brain cancer. Its invasive nature limits treatment efficacy and promotes inevitable recurrence. Previous in vitro studies have shown that interstitial fluid flow, a factor characteristically increased in cancer, increases glioma cell invasion via CXCR4-CXCL12. It is currently unknown if these effects translate in vivo. Using the therapeutic technique of convection enhanced delivery (CED), we tested if convective flow alters glioma invasion in vivo using the syngeneic GL261 mouse model of glioblastoma. We first confirmed that GL261 invasion in vitro increased under flow in a CXCR4-CXCL12 dependent manner. Additionally, approximately 65.4% and 6.59% of GL261 express CXCR4 and CXCL12 in vivo, respectively, with 3.38% expressing both. Inducing convective flow within implanted tumors indeed increased glioma cell invasion over untreated controls, and administering CXCR4 antagonist AMD3100 (5 mg/kg) effectively eliminated this response. Therefore, glioma invasion is in fact stimulated by convective flow in vivo through CXCR4. We also analyzed patient samples to show that expression of CXCR4 and CXCL12 increase in patients following therapy. These results suggesting that targeting flow-stimulated invasion may prove beneficial as a second line of therapy, particularly in patients chosen to receive convection enhanced drug delivery.

cancer biology↗

bioRxiv2018

Applicability of Drug Response Metrics for Cancer Studies using Biomaterials

Bioengineers have built increasingly sophisticated models of the tumor microenvironment in which to study cell-cell interactions, mechanisms of cancer growth and metastasis, and to test new potential therapies. These models allow researchers to culture cells in conditions that include features of the in vivo tumor microenvironment (TME) implicated in regulating cancer progression, such as ECM stiffness, integrin binding to the ECM, immune and stromal cells, growth factor and cytokine depots, and a 3D geometry more representative of the TME than tissue culture polystyrene (TCPS). These biomaterials could be particularly useful for drug screening applications to make better predictions of efficacy, offering better translation to preclinical in vivo models and clinical trials. However, it can be challenging to compare drug response reports across different platforms and conditions in the current literature. This is, in part, as a result of inconsistent reporting and use of drug response metrics, and vast differences in cell growth rates across a large variety of biomaterial design. This perspective paper attempts to clarify the definitions of drug response measurements used in the field, and presents examples in which these measurements can and cannot be applied. We suggest as best practice to include appropriate controls, always measure the growth rate of cells in the absence of drug, and follow our provided \"decision tree\" matrix when reporting drug response metrics.

bioengineering↗