MON-LB75 Stratifying the Risk of Malignancy in Indeterminate Thyroid Nodules

Abstract

Background Thyroid cancer is the most common endocrine cancer globally, and accounts for 3.4% of all new cancer cases in the US. Although several clinical guidelines to detect/manage thyroid nodules are available, a great deal of controversy still exists around the optimal approach for diagnosis. Approximately 20-30% of cytology results from thyroid fine-needle aspiration (FNA) fall into one of three indeterminate diagnostic categories. In recent years, a number of molecular and gene mutation diagnostic tests have been developed to diagnose the indeterminate thyroid nodules in FNA specimens. However, nearly half of patients recommended for surgery based on these tests were found to have a benign nodule. Therefore, there is a need for a more accurate predictive and prognostic test for thyroid cancer. In case of Euthyroid Hashimoto Thyroiditis condition (EHT), where patient required a partial thyroxin replacement dose, having about 48% risk of thyroid cancer. However, there is still not a very accurate predictive marker for early detection of thyroid cancer in EHT. Invention DescriptionResearchers at the University of Toledo have found that thyroid nodule microenvironment cell profiling can be used as a predictive and prognostic marker for thyroid cancer. This approach uniquely focuses on the phenotype, rather than the genotype, of the microenvironment. Recently described Double Negative (DN) T-cells were significantly more abundant in lymphocytic infiltrates of thyroid cancer. They were shown to downregulate proliferation and cytokine production of activated effector T cells present in the tumor microenvironment and contribute to tumor tolerance and active avoidance of tumor immunity. If the quantify of DN T cells exceeds the defined threshold, it indicates a likelihood of cancer presence. Aside from immune cell profiling, our approach further establishes an integration of the information derived from transcriptome/meta-analysis of the genome and cytokine/chemokine signal analysis all from thyroid FNA. Applications[[Unsupported Character - Symbol Font •]] Diagnosis of thyroid cancer from FNA samples[[Unsupported Character - Symbol Font •]] Predictive tool of severity of disease Advantages[[Unsupported Character - Symbol Font •]] Microenvironment profiling can provide a unique way to diagnose and assess disease progression[[Unsupported Character - Symbol Font •]] Sheds light on cellular cross-talk; more accurate diagnose; can prevent unnecessary surgery IP Status:​Patent Pending