Immuno Oncology treatments, including checkpoint inhibitors like the programmed cell death protein-1 (PD-1), have been shown to be effective at harnessing the body’s own ability to recognize and destroy cancerous cells whilst preserving normal healthy cells. However, these therapies are successful in only a small subset of patients, and it is challenging to accurately predict or monitor how an individual patient will respond to treatment. As the efficacy of these treatments is dependent on its ability to successfully activate and stimulate proliferation of T-cells, there is a need for clinical assays that can measure T-cell presence, activity, and proliferation in living subjects. To address this, we propose to develop radiolabeled antibody and fragments that specifically bind the CD3ε antigen expressed on T cells for longitudinal in vivo imaging. The CD3ε full length antibodies and fragments will be modified with chelator deferoxamine (DFO) or 1,4,7-triazacyclononane-N,N',N''-triacetic acid (NOTA) respectively. We will describe here the synthesis of our imaging probe and demonstrate the in vitro specificity and binding affinity is preserved following chelation. Furthermore, we will measure immunoreactive fraction and evaluate the in vivo specificity of the CD3ε radiolabeled probes in immunocompetent (C57Bl6 and Balb/c) and immunocompromised (NSG) mouse models. Our goal is to demonstrate the feasibility and translatability of our approach and ultimately employ these tools to further our understanding of the mechanism of action of current and future immunotherapies.

A significant amount of energy is required for T cells to activate and carry out effector functions against cancer. However, tumor-infiltrating T cells lack the energy resources to maintain an anticancer immune response in the tumor microenvironment. The ability of creatine to regulate cellular metabolism has made it a promising supplement to enhance T cell antitumor activity in the nutrient-starved tumor microenvironment. In this study, we developed a syngeneic ovarian cancer mouse model to investigate the effect of creatine supplementation as a method of powering antitumor T cell function and suppressing tumor growth. We found creatine supplementation does not significantly suppress tumor growth in the ovarian cancer model. These results suggest creatine supplementation is ineffective as a monotherapy to enhance effector T cell activity against ovarian cancer, but creatine will continue to be tested in combination with existing treatment methods to investigate its ability to increase their effectiveness.

Glioblastoma (GBM) is both a highly invasive and lethal cancer of the central nervous system. Its lethality is attributed to its robust resistance against treatment and ability to infiltrate healthy tissue. GBM rarely metastasizes beyond the brain, indicating its preference for the brain’s microenvironment and the importance of the extracellular matrix in promoting GBM survival. Along with the extracellular matrix, Src protein-tyrosine kinase (Src) activation has been identified as a key signaling event mediating both chemotherapy resistance and invasive morphology by inhibiting downstream expression of BCL-2 family pro-apoptotic factors. Studies have shown that dasatinib, a Src inhibitor, is effectively able to abolish the invasive morphology of GBM cells but is not able to induce apoptosis, making it an ineffective monotherapy. Here, we employed a biomaterial-based, 3D culture platform to investigate the effectiveness of dual treatment using temozolomide, an alkylating chemotherapy, and dasatinib to inhibit Src activation and promote GBM apoptosis. We found that both drugs used in conjunction resulted in a greater GBM cell death. However, the effect could not be fully attributed to the use of both drugs, as dasatinib only conditions produced similar changes. We attribute this similarity to missed cell count from our imaging methodology and the timing of when the drugs were given. In conclusion, simultaneous treatment with dasatinib and temozolomide showed promise as an effective treatment method, but further studies will need to be performed to elucidate the efficacy of the treatment.

Cancer, being a leading cause of death, is a highly researched topic, yet researchers have struggled to understand the relationship between metabolism and cancer cell growth. Glycolysis and gluconeogenesis are the two most important pathways in cancer metabolism. In a low glucose environment, only gluconeogenesis can be performed. A challenge in analyzing cancer’s metabolic pathways is measuring what happens inside cells. Cells are dynamic beings which reside in dynamic environments. Traditional measurement techniques are limiting because they rely on a snapshot of the cell and environment, which is a crude representation of the dynamic processes. In order to understand the internal workings, this project sought to measure metabolic fluxes and dynamic metabolic pathway usage. The approach involved conducting flux balance analysis within Cobra Toolbox. First, experimental measurements of cellular nutrient requirements and gene expression data from The Cancer Genome Atlas were mapped in Rstudio. By incorporating those experimental measurements, the human Recon3D model was tailored to model non-small cell lung cancer. Conducting flux balance analysis on the model using appropriate parameters will yield an approximate growth rate of lung cancer cells. Data collection has not yet been completed. This research is important because if it is possible to predict whether or not cancer cells can complete gluconeogenesis, specific therapies for distinct cancer cells can be developed. The predictive abilities that will be gained from completing this project will provide much needed insight into the dynamic systems of cancer cell growth.

Numerous species of animals are known to have magnetoreception, or the ability to detect the Earth's magnetic field, for orientation and navigation. However, more research is needed to confirm the underlying mechanics of magnetoreception in animals. Compelling evidence has suggested that dogs align to the Earth’s magnetic field during excremental activity if the nearby magnetic field declination, or the difference between true north and magnetic north, is stagnant. Nonetheless, this phenomenon needs a robust source of experimental data before it can be established. We are compiling a large image dataset of urinating and defecating dogs with citizen science and automating the analysis of geomagnetic metadata embedded within these images. We hope to verify whether canine alignment in urination and defecation depends on magnetic field declination. Initial results from a low sample size indicate dogs face random directions even when the percent change in magnetic field declination is less than 1%. However, the project will require more image submissions from across the world to yield more refined results. If dogs demonstrate magnetoreception in the course of this project, their potential role as experimental subjects will be pivotal in developing future magnetoreception research.

Metal oxide nanoparticles hold great promise for application in a wide variety of fields due to their exploitable physical properties, which are size dependent. These materials have commonly been synthesized in a solvothermal reaction that proceeds via a burst nucleation event, followed by nanoparticle growth. Under this classical growth scheme, precise size control of synthesized nanoparticles is difficult due to the rapid nature of the nucleation step, thus presenting a problem for the industrial application of the particles. This work demonstrates the improved size and shape uniformity of cobalt ferrite (CFO) nanoparticles produced via a novel esterification synthesis method as compared to the commonly used solvothermal procedure using TEM imaging and ImageJ software. It is shown that the more gradual continuous growth scheme of the esterification synthesis method allows for more precise control in the selection of desired particle properties and allows for the formation of smaller particles than possible with the classical method. Our findings also indicate that particles grown via the esterification method follow a less continuous growth scheme at higher temperatures, likely due to an additional nucleation pathway.

Reversal learning paradigms are widely used as measures of cognitive flexibility. Such methods typically require animals to form associations between a spatial location and reward (action-outcome, A-O) or a visual stimulus and reward (stimulus-outcome, S-O). The present research investigated the dissociable contributions of the rodent ventrolateral orbitofrontal cortex (OFC) and basolateral amygdala (BLA) using chemogenetic manipulation on the learning of both S-O and A-O associations. Rats were prepared with bilateral inhibitory hM4Di DREADDs or eGFP in either the OFC or BLA and were administered clozapine-N-oxide or a vehicle solution to manipulate DREADD expression. We fitted S-O and A-O reversal choice behavior with reinforcement learning models: a model with a single learning rate alpha parameter (model 1) versus a model with two learning rates, one for learning from unrewarded and another from rewarded trials (model 2). Analyses revealed that model 1 better captured rodent behavior than model 2, and model 1 better fit S-O than A-O learning. Moreover, we found that S-O tasks drove higher learning rates than A-O tasks across most region and drug conditions, while rodents forming A-O associations had higher inverse temperatures, beta (i.e., sensitivity to difference in subjective reward values). Though there were no significant differences between parameters due to the region of inhibition, these results expose the differential mechanisms involved in flexible learning in S-O and A-O tasks. The importance of the nature of association in reversal learning paradigms suggests the need for different, more sensitive metrics to investigate region-specific contributions in cognitive flexibility.

Lysine acetyltransferases (KATs) regulate gene transcription in a cell-specific fashion. The KAT6A gene contains a highly conserved histone acetyltransferase domain (HAT), which has been implicated in chromatin remodeling, gene regulation, protein translation, metabolism, and DNA replication. Pathogenic protein-truncating mutations in KAT6A lead to the rare genetic syndrome disorder known as KAT6A syndrome where individuals have developmental delay, microcephaly and cardiac defects; however, little is known about the specifics of how mutations lead to disease symptoms. To assess KAT6A’s effect on gene expression, HEK293T (human embryonic kidney) cells that harbor truncating mutations in the KAT6A gene were grown and compared to wild-type cells using assays of whole transcriptomics, global chromatin accessibility, cellular proliferation, and metabolism. Previous work had shown that these truncating mutations did not have a significant effect on the proliferation rate. It was hypothesized that either this particular mutation does not affect the cell cycle pathways or that there are other genes compensating for the mutated KAT6A function and allowing those cells to grow. Differences in histone acetylation and RNA expression between the KAT6A-mutated and wild-type cell lines suggested metabolic differences that will be explored in metabolic assays and western blotting experiments of associated histone proteins. It is expected that these assays will reveal differences between the wild-type and mutant cell’s metabolic activity and protein expression. Better understanding how exactly truncating mutations affect aspects of cellular function may allow us to understand how genetic mutation leads to specific phenotypes associated with KAT6A syndrome.

Analysis of spinal segments can help develop a better understanding of the architecture of the central nervous system. More specifically, understanding the distribution of motor neurons (MN) in the mouse spinal cord and the muscles MNs respectively stimulate can help develop cell-type specific treatments for spinal cord injuries. In this study, we aimed to improve the current mouse spinal cord atlas with a focus on MN groups and their characteristics to obtain a better idea of the extent of MNs at each vertebrae. We hypothesized that by making injections of neuronal tracers into specific muscle groups, for example the triceps and quadriceps, their specific MN groups could be visualized in greater detail in the spinal cord. These injections help delineate MN groups since it is difficult to determine their beginning and end when examining the spinal cord, and allow us to create a higher resolution atlas that uses the entire spinal cord as opposed to a single slice from each section. To render an atlas of the mouse spinal cord, tissue slices were assigned to regions of the spinal cord based on the tissue and region length. We then delineated gray matter regions and demarcated layers in the sections to outline MN groups. Current results lend support to the idea that injections in specific muscles will help visualize these segments in higher resolution to improve the atlas. Ultimately, we intend to use data from spinal segments to establish a 3D spinal reference atlas using the entire spinal cord.

The mechanical properties of tissues have a profound impact on a wide range of biological processes, including organ health, disease progression, and wound healing. More specifically, the stiffness of cells within a tissue influences cell behavior, although the precise mechanism is not fully understood. As an example, regions of cancer development within tissues have been observed to be softer than the surrounding cells. Therefore, quantification of individual cells within a tissue can provide insight on the condition of cells during disease and treatment. Thus, it is important to develop a method capable of measuring the spatially varying modulus in mechanically heterogeneous tissues. Conventional modulus measurements such as AFM, rheometry, and stand-alone cell stretchers are either invasive, time-consuming, or lack optimal spatial resolution. Here, we developed a tissue modulus visualization tool by integrating a custom cell stretcher, light microscopy, and AI-based inference. Using light microscopy to capture the displacement of cells during extension on the cell stretcher, our trained AI algorithm was able to correctly predict modulus values at cellular resolution with >95% accuracy. We envision that our modulus measurement method will be a useful tool for identifying mechanical signatures and monitoring cell condition during treatment and disease progression.