Author: Davin A. Means                Major: Biology

Davin Means, preparing glioblastoma cells for radiation treatment.

I began working with Dr. Rajaram during the spring semester of 2020, but it wasn’t until my first grant term (spring 2021), that I began to focus on glioblastomas, and the differentiation between IDH mutant and IDH wildtype cells. Glioblastomas are responsible for 80% of primary malignant central nervous system tumors in adults and have one of the poorest prognoses of all cancers. Invasion into the surrounding brain (the main contributor to patient death) is stem cell mediated, and diffuse gliomas have malignancy grades I-IV and diagnostic genotypes of IDH mutant and IDH wildtype. Around 80% of low-grade diffuse gliomas (grades I and II) are IDH mutant and 90% of high-grade diffuse gliomas (grades III and IV) are IDH wildtype. While standard therapy for these tumors involves surgical resectioning followed by adjuvant chemoradiation, outcomes are poor, and relapse is inevitable. The stem cell characteristics within glioma cells are what enable them to evade chemotherapy and radiation treatment and leave residual cell populations that cause resurgence and relapse. While this outcome is unfavorable, the fact that IDH mutant gliomas have improved patient prognosis compared to IDH wildtype gliomas, provides hope and an avenue for better treatment outcomes. Thus, it is of great importance to be able to detect, monitor, and elucidate, IDHm and IDHwt cells and their response to stress in order to therapeutically target diffuse gliomas and develop precision medicine and new medications to improve health outcomes for diffuse glioma patients.

IDH is a key metabolic enzyme within the tricarboxylic acid cycle. Thus, I believe that focusing on the comparative metabolic pathways, signals, and phenotypes of IDHm and IDHwt cells is key to their differentiation. During my first grant term, I utilized a Seahorse XFp Extracellular Flux Analyzer to aid in differentiation. I ran Cell Mito and Glycolysis stress tests on IDHm and IDHwt cells. The cell mito stress test is used to measure mitochondrial function in cells. It directly measures the oxygen consumption rate (OCR) of cells by using chemicals to modulate respiration and key components of the electron transport chain. The chemicals Oligomycin, FCCP, and a mix of rotenone and antimycin A are serially injected to measure ATP-linked respiration, maximal respiration, and non-mitochondrial respiration, respectively. The glycolysis stress test is used to measure the glycolytic function in cells. Glycolysis, which consists of the conversion of glucose to pyruvate and subsequently to lactate, results in a net production and expulsion of protons into the extracellular medium. This results in medium acidification which is measured as ECAR (extracellular acidification rate). During the assay, glucose is first injected into the medium to get the glycolytic rate of the cells under basal conditions. Then oligomycin is injected to inhibit mitochondrial ATP production and maximize glycolytic capacity. Finally, 2-deoxy-glucose is injected to inhibit glycolysis and confirm how much ECAR was due to glycolysis. Both the glycolysis and cell mito stress tests provide key parameters for the differentiation of IDHm and IDHwt cells.

Radiation therapy is an integral treatment method for those suffering from glioblastoma, and since the primary goal is the early differentiation of IDHm and IDHwt cells, I attempted to simulate the early phases of radiation therapy in my experimental setting. Thus, in conjunction with running seahorse assays on untreated diffuse glioma cells, I also ran glycolysis and cell mito stress tests on cells treated with 2Gy and 10Gy radiation in order to elucidate how IDHm and IDHwt differentiation might change within different phases of treatment. Prior to working with glioblastomas, a grad student and I employed radiation dose therapy and diffuse reflectance spectroscopy to investigate changes of the mammary tumor microenvironment within mice in response to treatment. In this experimentation, radiation dose therapy was essential in studying the relationship between tumor oxygenation and metabolism and its role in promoting undesirable tumor outcomes, such as treatment resistance, recurrence, and metastasis. As I move forward with the next stage of my current work, I expect the instrumentation of radiation therapy to be just as important in the differentiation of IDHm and IDHwt glioblastomas as it was for my investigation of mammary cancers.

There were many challenges within this first grant term. Aside from the steep learning curve of navigating the various procedures necessary for IDHm and IDHwt cell differentiation, one major challenge I faced was the optimization of cell counts for various assays and radiation dosages. While I started with the belief that 4,000 cells per well would be sufficient for differentiation, numerous experiments revealed that 6,000 cells per well are required for baseline assays and that this number fluctuates depending on radiation dosage and the number of days radiation therapy is done. This, among other setbacks, revealed to me that experimentation is a process of trial and error and reinforced the necessity of experimental repeats.

Because of the Honors College Research Grant, I’ve become a more patient, detail-oriented person and learned that outcomes unaligned with your expectations are just as informative as those that support your hypotheses. Furthermore, I’ve gained crucial micro pipetting skills and learned how to operate the Seahorse XFp Extracellular Flux Analyzer as well as radiation dose therapy equipment. Throughout the summer and next grant term (Fall 2021), I will repeat previous experiments as well as run more assays on cells treated with varying radiation doses. More importantly, I will attempt to differentiate IDHm and IDHwt glioblastoma cells using autofluorescence based metabolic imaging. Furthermore, I plan to use metabolic imaging to determine if exposure to radiation or hypoxic stress elicits real-time metabolic changes that let us clearly distinguish between IDHm and IDHwt cells, thus allowing for real time sensing of the phenotype of glioma stem cells undergoing mesenchymal transition.