| dc.description.abstract | Thyroid cancer incidence is rapidly increasing in the United States, with over 45,000 patients projected to be diagnosed in 2022. While the vast majority of patients respond well to first line treatment, approximately 20% of patients will experience recurrence and 10% will develop metastatic disease. For these patients, treatment options are extremely limited. One such recurrent tumor type, anaplastic thyroid carcinoma (ATC), has a median survival of just four to six months. Little progress has been made in the treatment of these tumors due to lack of model systems, molecular characterization, and research interest. Herein, I describe the generation of spheroid and organoid models of thyroid cancer, as well as applications utilizing those model systems. I used computational immunogenomics to characterize the tumor-immune microenvironment in papillary thyroid carcinoma, and I identified canonical Wnt signaling as a viable therapeutic target in ATC. Finally, I developed a high-throughput drug screening methodology for spheroids to identify FDA-approved compounds that inhibit ATC and identified promising drug candidates. This work has enabled the development of novel therapeutic interventions for patients with ATC, a devastating cancer with few treatment options. | |
