Thyroseq Test Descrption

• ThyroSeq Genomic Classifier (GC) is a test for the pre-operative assessment of thyroid nodules with indeterminate cytology:
  • Which offers accurate assessment of cancer probability in a given nodule and additionally provides information on cancer prognostication, helping to select the most optimal patient management

• ThyroSeq incorporates all major scientific advances in thyroid cancer genetics and has more than 10-years’ experience serving physicians and their patients with thyroid nodules and cancer:
  • The first version of ThyroSeq was launched for clinical use at the University of Pittsburgh Medical Center as a seven-gene panel (ThyroSeq v0) in April of 2007.
• Until recently, the test was offered as ThyroSeq v2. Today, ThyroSeq v3 is available for clinical use

• ThyroSeq v3 is also based on next-generation sequencing of DNA and RNA:
  • However, it is expanded to analyze 112 genes, providing information on greater than 12,000 mutation hotspots and greater than 150 gene fusion types (Nikiforova MN et al. 2018).
• The test detects four classes of genetic alterations:
  • Mutations (SNVs, indels)
  • Gene fusions
  • Gene expression alterations
  • Copy number variations (CNVs)
• The test utilizes a proprietary Genomic Classifier (GC) based on the algorithmic analysis of all detected genetic alterations to report:
  • The test result as Positive or Negative

• ThyroSeq test consists of several steps:
  • It starts with the assessment of FNA sample cellularity:
    • This is a quality assurance (QA) step that determines if the provided sample has sufficient number of cells to proceed with the analysis
    • If the number of cells is below the required limit, the test is cancelled and no charges are posted.
  • Next, cellular composition of the sample is evaluated:
    • This step assures that the provided sample has an adequate proportion of thyroid follicular cells
    • It also allows accurate detection of c-cells (MTC), parathyroid cells, and other non-thyroidal cells
  • Then, the generated next generation sequencing data on 112 genes are processed using an in-house bioinformatic pipeline that applies a complex algorithm to estimate cancer probability in the tested nodule:
    • The algorithm was built based on cancer probability associated with each genetic alteration and their combination and validated in a prospective, multicenter, double-blind study.
  • Next, the test results and findings are reviewed by a board-certified pathologist who verifies all findings and releases the test report.
  • ThyroSeq test report is provided in a user-friendly format that states the probability of cancer in the patient’s nodule, suggests potential patient management, and also lists specific genomic alterations that are relevant to the individual patient