The ThyroSeq v3 GC analyzes 5 different classes of molecular alterations and provides high accuracy for detecting all common types of thyroid cancer and parathyroid lesions. The analytical sensitivity, specificity, and robustness of the test have been successfully validated and indicate its suitability for clinical use. Cancer 2018;124:1682-90. © 2018 American Cancer Society.

Primary bladder adenocarcinoma is a rare and aggressive tumor with poor clinical outcomes and no standard of care therapy. Molecular biology of this tumor is unknown due to the lack of comprehensive molecular profiling studies. The study aimed to identify genomic alterations of clinical and therapeutic significance using next-generation sequencing and compare genomic profile of primary bladder adenocarcinoma with that of high-grade urothelial carcinoma and colorectal adenocarcinoma. A cohort of 15 well-characterized primary bladder adenocarcinoma was subjected to targeted next-generation sequencing for the identification of mutations and copy-number changes in 51 cancer-related genes. Genomic profiles of 25 HGUCs and 25 colorectal adenocarcinomas using next-generation sequencing of 50 genes were compared with primary bladder adenocarcinoma. Genomic profiles were visualized using JavaScript library D3.js. A striking finding was the distinct lack of genomic alterations across the 51 genes assessed in mucinous subtype of primary bladder adenocarcinoma. Eleven of 15 primary bladder adenocarcinoma harbored at least one genomic alteration in TP53, KRAS, PIK3CA, CTNNB1, APC, TERT, FBXW7, IDH2 and RB1, many of which are novel findings and of potential therapeutic significance. CTNNB1 and APC mutations were restricted to enteric subtype only. While genomic alterations of primary bladder adenocarcinoma showed substantial overlap with colorectal adenocarcinoma, FGFR3 and HRAS mutations and APC, CTNNB1 and IDH2 alterations were mutually exclusive between primary bladder adenocarcinoma and high-grade urothelial carcinoma. These alterations affecting the MAP kinase, PI3K/Akt, Wnt, IDH (metabolic) and Tp53/Rb1 signaling pathways may provide the opportunity for defining targeted therapeutic approaches.

Background: Genetic profiling of resected tumor or biopsy samples is increasingly used for cancer diagnosis and therapy selection for thyroid and other cancer types. Although mutations occur in cell DNA and are typically detected using DNA sequencing, recent attempts focused on detecting pathogenic variants from RNA. The aim of this study was to determine the completeness of capturing mutations using RNA sequencing (RNA-Seq) in thyroid tissue and fine-needle aspiration (FNA) samples. Methods: To compare the detection rate of mutations between DNA sequencing and RNA-Seq, 35 tissue samples were analyzed in parallel by whole-exome DNA sequencing (WES) and whole-transcriptome RNA-Seq at two study sites. Then, DNA and RNA from 44 thyroid FNA samples and 47 tissue samples were studied using both targeted DNA sequencing and RNA-Seq. Results: Of 162 genetic variants identified by WES of DNA in 35 tissue samples, 77 (48%) were captured by RNA-Seq, with a detection rate of 49% at site 1 and 46% at site 2 and no difference between thyroid and nonthyroid samples. Targeted DNA sequencing of 91 thyroid tissue and FNA samples detected 118 pathogenic variants, of which 57 (48%) were identified by RNA-Seq. For DNA variants present at >10% allelic frequency (AF), the detection rate of RNA-Seq was 62%, and for those at low (5-10%) AF, the detection rate of RNA-Seq was 7% (p < 0.0001). For common oncogenes (BRAF and RAS), 94% of mutations present at >10% AF and 11% of mutations present at 5-10% AF were captured by RNA-Seq. As expected, none of TERT promoter mutations were identified by RNA-Seq. The rate of mutation detection by RNA-Seq was lower in FNA samples than in tissue samples (32% vs. 49%, p = 0.02). Conclusions: In this study, RNA-Seq analysis detected only 46-49% of pathogenic variants identifiable by sequencing of tumor DNA. Detection of mutations by RNA-Seq was more successful for mutations present at a high allelic frequency. Mutations were more often missed by RNA-Seq when present at low frequency or when tested on FNA samples. All TERT mutations were missed by RNA-Seq. These data suggest that RNA-Seq does not detect a significant proportion of clinically relevant mutations and should be used with caution in clinical practice for detecting DNA mutations.