IntroductionA comprehensive investigation of the genomic landscape of papillary thyroid carcinomas (PTC), the most common thyroid malignancy, was recently reported by The Cancer Genome Atlas Network (TCGA Network) (1). These well-differentiated tumors were found to have a low frequency of somatic alterations (2), with the majority harboring mutually exclusive activating mutations in BRAF (60%) and RAS-family genes (13%), as well as fusion oncoproteins, primarily involving receptor tyrosine kinases (RTKs) such as RET, NTRK1 or -3, and ALK. Distinct signaling and transcriptomic consequences were observed between BRAF V600E -like tumors, which showed higher MAPK transcriptional output and lower expression of genes involved in iodine metabolism, and RAS-like tumors, which had lower MAPK signaling and comparatively preserved expression of iodine-related genes.The TCGA study excluded poorly differentiated thryoid cancers (PDTCs) and anaplastic thyroid cancers (ATCs) from their analysis in order to focus on a homogeneous histological cohort that would provide sufficient power to identify low-frequency genomic events. Although PDTCs and ATCs account for approximately 5%-10% of thyroid cancers, they represent a major clinical challenge. Patients with PDTC and ATC have a mean survival after diagnosis of 3.2 and 0.5 years, respectively, and account for approximately a third of deaths caused by this disease (3). Virtually all cases are refractory to radioiodine therapy, and traditional chemotherapy and radiotherapy are of marginal benefit (4, 5).Molecularly targeted approaches are being tested in preclinical BACKGROUND. Poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) are rare and frequently lethal tumors that so far have not been subjected to comprehensive genetic characterization. METHODS.We performed next-generation sequencing of 341 cancer genes from 117 patient-derived PDTCs and ATCs and analyzed the transcriptome of a representative subset of 37 tumors. Results were analyzed in the context of The Cancer Genome Atlas study (TCGA study) of papillary thyroid cancers (PTC). RESULTS.Compared to PDTCs, ATCs had a greater mutation burden, including a higher frequency of mutations in TP53, TERT promoter, PI3K/AKT/mTOR pathway effectors, SWI/SNF subunits, and histone methyltransferases. BRAF and RAS were the predominant drivers and dictated distinct tropism for nodal versus distant metastases in PDTC. RAS and BRAF sharply distinguished between PDTCs defined by the Turin (PDTC-Turin) versus MSKCC (PDTC-MSK) criteria, respectively. Mutations of EIF1AX, a component of the translational preinitiation complex, were markedly enriched in PDTCs and ATCs and had a striking pattern of co-occurrence with RAS mutations. While TERT promoter mutations were rare and subclonal in PTCs, they were clonal and highly prevalent in advanced cancers. Application of the TCGA-derived BRAF-RAS score (a measure of MAPK transcriptional output) revealed a preserved relationship with BRAF/RAS mutation in PDTCs, whereas ATCs w...

Acquired mutations are pervasive across normal tissues. However, our understanding of the processes that drive transformation of certain clones to cancer is limited. Here we study this phenomenon in the context of clonal hematopoiesis (CH) and the development of therapy-related myeloid neoplasms (tMN). We find mutations are selected differentially based on exposures. Mutations in ASXL1 are enriched in current or former smokers, whereas cancer therapy with radiation, platinum and topoisomerase II inhibitors preferentially selects for mutations in DNA damage response (DDR) genes ( TP53, PPM1D, CHEK2 ). Sequential sampling provides definitive evidence that DDR clones outcompete other clones when exposed to certain therapies. Among cases where CH was previously detected, the CH mutation was present at tMN diagnosis. We identify the molecular characteristics of CH that increase risk of tMN. The increasing implementation of clinical sequencing at diagnosis provides an opportunity to identify patients at risk of tMN for prevention strategies.

The rates of tumor growth during active surveillance in a US cohort with PTCs measuring 1.5 cm or less were low. Serial measurement of tumor volumes may facilitate early identification of tumors that will continue to grow and thereby inform the timing of surveillance imaging and therapeutic interventions.

Background: The use of age-and ethnicity-specific thyrotropin (TSH) reference limits decreases misclassification of patients with thyroid dysfunction. Developing such limits requires TSH measurements in different subpopulations. Methods: We determined, in the National Health and Nutrition Examination Survey III, the TSH median, 2.5th and 97.5th centiles as a function of age, and anti-thyroid antibodies (ABs) in specific racial/ethnic groups (REGs) designated as non-Hispanic Whites, non-Hispanic Blacks, and Mexican Americans, as classified by the U.S. Office of Management and Budget (OMB) Directive 15. We compared TSH limits of a thyroid disease-free population (n ¼ 15,277) to a reference population (n ¼ 13,344) formed by exclusion of AB+ subjects and TSH >10 mIU/L or <0.1 mIU/L. With quantile regression, we examined the effect of age, REG, gender, body weight, and urinary iodine concentration on TSH reference limits in the ABÀ population. Results: AB status did not affect the 2.5th centile and median TSH in any REG or the 97.5th centile in Blacks. The average 97.5th centile of the disease-free Whites and Mexican Americans was 1.0 mIU/L higher than the reference population group. The TSH 2.5th, 50th, and 97.5th centiles increased with age and were lower in Blacks than in Whites or Mexican Americans. Women had lower 2.5th and 50th centiles than males. From these data, we developed equations to predict subpopulation-specific TSH reference limits. Conclusions: Our study provides a method to determine TSH limits in individual patients of different ages, gender, and REG criteria whose AB status is uncertain and it will enable clinicians to better classify patients within their subpopulation-specific TSH reference range.