Genetic architecture of thyroid cancer and its clinical utility

Thyroid cancer incidence is high, with 44,280 new cases diagnosed in the US in 2021. Thyroid nodule incidence is rising primarily due to increased detection, necessitating more procedures such as fine needle aspiration (FNA) biopsies to rule out cancer. However, most thyroid nodule biopsies produce benign, indeterminate, or non-diagnostic results and are potentially avoidable. Our long-term goal is to improve risk stratification of thyroid nodules, reduce the number of unnecessary biopsies, and minimize the burden of thyroid cancer diagnosis for patients and the healthcare system. Our central hypothesis is that thyroid cancer genetic risk estimate will improve risk stratification of thyroid nodules and reduce the number of avoidable FNA biopsies of benign thyroid nodules. Supported by robust preliminary data, the central hypothesis will be tested by pursuing two specific aims: Aim 1. Define the genetic architecture of thyroid cancer. Aim 2. Develop and assess the clinical utility of a genetic thyroid nodule classifier that discriminates between benign and malignant thyroid nodules. Under the first aim, we will explore genetic associations with thyroid malignancy independent of benign goiter to discover novel thyroid cancer biomarkers and develop a clinically useful polygenic risk score (PRS). We will use two approaches: 1) test genetic associations directly using a GWAS meta-analysis with 4,994 thyroid cancer cases and 20,917 patients with benign nodules as controls, and 2) use a computational GWAS-by-subtraction method to derive summary statistics for the thyroid cancer free from genetic associations with benign nodular goiter. We will use publicly available genome-wide association studies, such as from the Global Biobank Meta-analysis Initiative, and perform our meta-analyses using the Colorado Center for Personalized Medicine Biobank and other Biobanks from around the world. We hypothesize that a thyroid nodule classifier PRS in combination with standard of care Thyroid Imaging Reporting and Data System (TIRADS) ultrasound schema will improve risk stratification of thyroid nodules and ultimately reduce the number of unnecessary thyroid nodule biopsies. We developed a thyroid nodule classifier PRS that differentiates malignant and benign thyroid nodules with an area under the receiver operating characteristic curve of 0.61. We will apply this score to ~600 thyroid nodules from genotyped patients with known cytologic or histopathologic diagnoses of benign goiter or thyroid cancer. Three expert physicians will estimate TI-RADS points and categories. We will evaluate the efficacy of the TI-RADS algorithm alone and in combination with our novel PRS to distinguish benign from malignant thyroid nodules. We will use the precisely defined genetic landscape of thyroid malignancy (Aim 1) to improve the thyroid nodule classifier PRS. This study will pave the way for personalized management of thyroid nodules and inform future mechanistic studies aimed at better understanding the risk of thyroid cancer.