Biology subjects

Harrison, J. K.

Publications and source records attributed to Harrison, J. K..

7 recordsLinked to original sources

bioRxiv2024

Optimal control of combination immunotherapy in a glioblastoma-immune dynamics model

The immune checkpoint inhibitor anti-PD-1, commonly used in cancer immunotherapy, has not been successful as a monotherapy for the highly aggressive brain cancer glioblastoma. However, when used in conjunction with a CC-chemokine receptor-2 (CCR2) antagonist, anti-PD-1 has shown efficacy in preclinical studies. In this paper, we aim to optimize treatment regimens for this combination immunotherapy using optimal control theory. We extend a treatment-free glioblastoma-immune dynamics ODE model to include interventions with anti-PD-1 and the CCR2 antagonist. An optimized regimen increases the survival of an average mouse from 32 days post-tumor implantation without treatment to 111 days with treatment. We scale this approach to a virtual murine cohort to evaluate mortality and quality of life concerns during treatment, and predict survival, tumor recurrence, or death after treatment. A parameter identifiability analysis identifies five parameters suitable for personalizing treatment within the virtual cohort. Sampling from these five practically identifiable parameters for the virtual murine cohort reveals that personalized, optimized regimens enhance survival: 84% of the virtual mice survive to day 100, compared to 60% survival in a previously studied experimental regimen. Subjects with high tumor growth rates and low T cell kill rates are identified as more likely to die during and after treatment due to their compromised immune systems and more aggressive tumors. Notably, the MDSC death rate emerges as a long-term predictor of either disease-free survival or death. HighlightsO_LIA mathematical model of glioma-immune dynamics integrates combination immunotherapy. C_LIO_LIAn optimized regimen extends survival in an average virtual mouse by 79 days. C_LIO_LIQuality of life and survival outcomes were evaluated for a virtual murine cohort. C_LIO_LIA high death rate of myeloid-derived suppressor cells predicts long-term survival. C_LI

cancer biology↗

bioRxiv2024

DR5 disulfide bonding as a sensor and effector of protein folding stress

New agents are needed that selectively kill cancer cells without harming normal tissues. The TRAIL ligand and its receptors, DR5 and DR4, exhibit cancer-selective toxicity, but TRAIL analogs or agonistic antibodies targeting these receptors have not received FDA approval for cancer therapy. Small molecules for activating DR5 or DR4 independently of protein ligands may bypass some of the pharmacological limitations of these protein drugs. Previously described Disulfide bond Disrupting Agents (DDAs) activate DR5 by altering its disulfide bonding through inhibition of the Protein Disulfide Isomerases (PDIs) ERp44, AGR2, and PDIA1. Work presented here extends these findings by showing that disruption of single DR5 disulfide bonds causes high-level DR5 expression, disulfide-mediated clustering, and activation of Caspase 8-Caspase 3 mediated pro-apoptotic signaling. Recognition of the extracellular domain of DR5 by various antibodies is strongly influenced by the pattern of DR5 disulfide bonding, which has important implications for the use of agonistic DR5 antibodies for cancer therapy. Disulfide-defective DR5 mutants do not activate the ER stress response or stimulate autophagy, indicating that these DDA-mediated responses are separable from DR5 activation and pro-apoptotic signaling. Importantly, other ER stressors, including Thapsigargin and Tunicamycin also alter DR5 disulfide bonding in various cancer cell lines and in some instances, DR5 mis-disulfide bonding is potentiated by overriding the Integrated Stress Response (ISR) with inhibitors of the PERK kinase or the ISR inhibitor ISRIB. These observations indicate that the pattern of DR5 disulfide bonding functions as a sensor of ER stress and serves as an effector of proteotoxic stress by driving extrinsic apoptosis independently of extracellular ligands.

cancer biology↗

bioRxiv2024

Systemically targeting monocytic MDSCs using dendrimers and their cell-level biodistribution kinetics

The focus of nanoparticles in vivo trafficking has been mostly on their tissue-level biodistribution and clearance. Recent progress in the nanomedicine field suggests that the targeting of nanoparticles to immune cells can be used to modulate the immune response and enhance therapeutic delivery to the diseased tissue. In the presence of tumor lesions, monocytic-myeloid-derived suppressor cells (M-MDSCs) expand significantly in the bone marrow, egress into peripheral blood, and traffic to the solid tumor, where they help maintain an immuno-suppressive tumor microenvironment. In this study, we investigated the interaction between PAMAM dendrimers and M-MDSCs in two murine models of glioblastoma, by examining the cell-level biodistribution kinetics of the systemically injected dendrimers. We found that M-MDSCs in the tumor and lymphoid organs can efficiently endocytose hydroxyl dendrimers. Interestingly, the trafficking of M-MDSCs from the bone marrow to the tumor contributed to the deposition of hydroxyl dendrimers in the tumor. M-MDSCs showed different capacities of endocytosing dendrimers of different functionalities in vivo. This differential uptake was mediated by the unique serum proteins associated with each dendrimer surface functionality. The results of this study set up the framework for developing dendrimer-based immunotherapy to target M-MDSCs for cancer treatment.

bioengineering↗

bioRxiv2024

KR158 spheres harboring slow-cycling cells recapitulate GBM features in an immunocompetent system

Glioblastoma (GBM) poses a significant challenge in clinical oncology due to its aggressive nature, heterogeneity, and resistance to therapies. Cancer stem cells (CSCs) play a critical role in GBM, particularly in treatment-resistance and tumor relapse, emphasizing the need to comprehend the mechanisms regulating these cells. Also, their multifaceted contributions to the tumor-microenvironment (TME) underline their significance, driven by their unique properties. This study aimed to characterize glioblastoma stem cells (GSCs), specifically slow-cycling cells (SCCs), in an immunocompetent murine GBM model to explore their similarities with their human counterparts. Using the KR158 mouse model, we confirmed that SCCs isolated from this model exhibited key traits and functional properties akin to human SCCs. KR158 murine SCCs, expanded in the gliomasphere assay, demonstrated sphere forming ability, self-renewing capacity, positive tumorigenicity, enhanced stemness and resistance to chemotherapy. Together, our findings validate the KR158 murine model as a framework to investigate GSCs and SCCs in GBM-pathology, and explore specifically the SCC-immune system communications, understand their role in disease progression, and evaluate the effect of therapeutic strategies targeting these specific connections.

cancer biology↗

bioRxiv2023

Global stability and parameter analysis reinforce therapeutic targets of PD-L1-PD-1 and MDSCs for glioblastoma

Glioblastoma (GBM) is an aggressive primary brain cancer that currently has minimally effective treatments. Like other cancers, immunosuppression by the PD-L1-PD-1 immune checkpoint complex is a prominent axis by which glioma cells evade the immune system. Myeloid-derived suppressor cells (MDSCs), which are recruited to the glioma microenviroment, also contribute to the immunosuppressed GBM microenvironment by suppressing T cell functions. In this paper, we propose a GBM-specific tumor-immune ordinary differential equations model of glioma cells, T cells, and MDSCs to provide theoretical insights into the interactions between these cells. Equilibrium and stability analysis indicates that there are unique tumorous and tumor-free equilibria which are locally stable under certain conditions. Further, the tumor-free equilibrium is globally stable when T cell activation and the tumor kill rate by T cells overcome tumor growth, T cell inhibition by PD-L1-PD-1 and MDSCs, and the T cell death rate. Bifurcation analysis suggests that a treatment plan that includes surgical resection and therapeutics targeting immune suppression caused by the PD-L1-PD1 complex and MDSCs results in the system tending to the tumor-free equilibrium. Using a set of preclinical experimental data, we implement the Approximate Bayesian Computation (ABC) rejection method to construct probability density distributions that estimate model parameters. These distributions inform an appropriate search curve for global sensitivity analysis using the extended Fourier Amplitude Sensitivity Test (eFAST). Sensitivity results combined with the ABC method suggest that parameter interaction is occurring between the drivers of tumor burden, which are the tumor growth rate and carrying capacity as well as the tumor kill rate by T cells, and the two modeled forms of immunosuppression, PD-L1-PD-1 immune checkpoint and MDSC suppression of T cells. Thus, treatment with an immune checkpoint inhibitor in combination with a therapeutic targeting the inhibitory mechanisms of MDSCs should be explored.

cancer biology↗

bioRxiv2022

Glioma-derived CCL2 and CCL7 mediate migration of immune suppressive CCR2+ myeloid cells into the tumor microenvironment in a redundant manner

Glioblastoma (GBM) is the most common and malignant primary brain tumor, resulting in poor survival despite aggressive therapies. GBM is characterized in part by a highly heterogeneous and immunosuppressive tumor microenvironment (TME) made up predominantly of infiltrating peripheral immune cells. One significant immune cell type that contributes to glioma immune evasion is a population of immunosuppressive, hematopoietic cells, termed myeloid-derived suppressor cells (MDSCs). Previous studies suggest that a potent subset of myeloid cells, expressing monocytic (M)-MDSC markers, distinguished by dual expression of chemokine receptors CCR2 and CX3CR1, utilize CCR2 to infiltrate into the TME. This study evaluated the T cell suppressive function and migratory properties of CCR2+/CX3CR1+ MDSCs. Bone marrow-derived CCR2+/CX3CR1+ cells adopt an immune suppressive cell phenotype when cultured with glioma-derived factors. Recombinant and glioma-derived CCL2 and CCL7 induce the migration of CCR2+/CX3CR1+ MDSCs with similar efficacy. KR158B-CCL2 and -CCL7 knockdown murine gliomas contain equivalent percentages of CCR2+/CX3CR1+ MDSCs compared to KR158B gliomas. Combined neutralization of CCL2 and CCL7 completely blocks CCR2-expressing cell migration to KR158B cell conditioned media. High levels of CCL2 and CCL7 are also associated with negative prognostic outcomes in GBM patients. These data provide a more comprehensive understanding of the function of CCR2+/CX3CR1+ MDSCs and the role of CCL2 and CCL7 in the recruitment of these immune suppressive cells and further support the significance of targeting this chemokine axis in GBM.

cancer biology↗

bioRxiv2022

Exploring genomic data coupled with 3D chromatin structures using the WashU Epigenome Browser

Biological functions are not only encoded by the genomes sequence but also regulated by its three-dimensional (3D) structure. More and more studies have revealed the importance of 3D chromatin structures in development and diseases; therefore, visualizing the connections between genome sequence, epigenomic dynamics (1D) and the 3D genome becomes a pressing need. The WashU Epigenome Browser introduces a new 3D visualization module to integrate visualization of 1D (such as sequence features, epigenomic data) and 2D data (such as chromosome conformation capture data) with 3D genome structure. Genomic coordinates are encoded in 3D models of the chromosomes; thus, all genomic information displayed on a 1D genome browser can be visualized on a 3D model, supported by genome browser utilities and facilitating interpretation of genomic data. Biological information that is difficult to illustrate in 1D becomes more intuitive when displayed in 3D, providing novel and powerful tools for investigators to hypothesize and understand the connections between biological functions and 3D genome structures.

bioinformatics↗