Gallic acid is a phenolic compound prevalent in many foods of plant origin previously found to show anticancer properties through modulation of signaling pathways such as JAK/STAT3 and PI3K/Akt. In cancer cells, gallic acid generates reactive oxygen species that induce apoptosis. Interestingly, it is also known to be a strong antioxidant and suppresses induced carcinogenesis. The mechanism behind the dual role of gallic acid has yet to be fully understood. To examine the effects of gallic acid on the metabolism and proliferation of healthy and cancerous cells, I cultured both mouse kidney epithelial cells with and without constitutive oncogene activation in media with varying concentrations of gallic acid (5 µM, 50 µM, and a control) for 24 hours. I made qualitative observations of cell morphology, as well as quantitative cell counts and metabolite concentration measurements at multiple timepoints. In both healthy and cancerous cells, the experimental gallic acid treatments did not appear to affect cell morphology or growth rate compared to the control group. However, in both cell lines, gallic acid treatment reduced glucose uptake, but only in cancerous cells treated with 50 µM gallic acid media was lactate production significantly decreased. This may indicate metabolic rewiring. Future steps include investigating molecular mechanisms behind the observed reduced aerobic glycolysis by measuring intracellular metabolite levels and fluxes as well as oxidative stress. I expect the findings from this project to spur investigation into other dietary compounds and combinatorial therapy that integrates them with existing chemotherapies.

Chimeric antigen receptor (CAR) T-cell therapy utilizes the biology of the T cell to recognize specific antigens on a target cell’s surface. Research in CAR T-cell therapy looks to find viable targets for therapy development. This CAR-T project looks to discover CAR-T cells specifically for prostate cancer, such that these modified receptors can recognize and kill specific cancer cells. The CAR-T targets provided to the Witte Lab are derived from a collaboration with the Xing Lab at the University of Pennsylvania. RNA-seq data from normal tissue and cancer databases were algorithmically analyzed to predict novel alternatively spliced targets.1 Given that one challenge to CAR development is the need for targets to be expressed on the cell surface, deep learning algorithms were utilized to model protein topography for various target sequences using pre-existing data on RNA splicing for genes. Protein topology and classification were analyzed to determine whether bioinformatically-predicted alternatively spliced targets specific to cancers could serve as potential sources for CAR-T therapy. One target, enzymatic protein A, successfully passed the CAR-T cell bioinformatic screening parameters and is in process of experimental design for wet lab validation. The target must undergo RNA level validation, protein level validation, surface level validation, and monoclonal antibody production before it can be used to produce a specific and effective CAR.

Dementia is a rapidly growing, incurable terminal disorder affecting over 50 million people worldwide. Around 10 percent of dementia is caused by underlying frontotemporal lobar degeneration (FTLD), which is associated with loss of motor control, aphasia, cognitive decline, and degeneration of the frontal cortex and temporal lobe. Half of all FTLD cases are associated with inclusions of TAR DNA-binding protein 43 (TDP43), which are also seen across a spectrum of neurodegenerative disorders. Critically, we lack understanding of the biological pathways that are affected in disease, but there is a significant hereditary component to FTLD-TDP, with around 40 percent of cases being familial, indicating genetic causes that can be further analyzed for insight into disease mechanisms. To that end, RNA-seq is a powerful method that analyzes transcriptome-wide expression to understand biological pathways and that can be used to connect transcriptomic variation to gene dysregulation. To investigate the underlying mechanisms of FTLD-TDP, we performed RNA-seq in postmortem prefrontal cortex of 60 FTLD- TDP cases and 22 controls. We subsequently ran differential gene expression analysis, followed by gene set enrichment analysis and gene ontology enrichment to determine which biological pathway dysregulated genes were enriched in FTLD-TDP. We found significant upregulation of immune processes and downregulation of synaptic processing as key disease pathways. These results offer insight into the mechanisms of FTLD-TDP and other TDP43-related neurodegenerative disorders, which may provide insights into potential therapeutic targets.