Genomic Researchers Propose Reclassifying Thyroid Cancers into Molecular Subtypes

The Cancer Genome Atlas began as a three-year pilot in 2006 with an investment of USD 50 million each from the [US] National Cancer Institute (NCI) and [US] National Human Genome Research Institute (NHGRI). The TCGA pilot project confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Furthermore, it proved that making the data freely available would enable researchers anywhere around the world to make and validate important discoveries. The success of the pilot led the [US] National Institutes of Health to commit major resources to TCGA to collect and characterize more than 20 additional tumor types. Thyroid cancer comprises one of the largest sample sizes, with nearly 500 tumors studied.

It was intended that each cancer would undergo comprehensive genomic characterization and analysis. The comprehensive data generated by TCGA’s network approach are freely available to the cancer research community through the TCGA Data Portal.

Results of the thyroid cancer study, which were published in the October 13, 2014, issue of the journal Cell, revealed that PTCs demonstrated a low frequency of somatic alterations (relative to other carcinomas) and extended the set of known PTC driver alterations to include the EIF1AX, PPM1D, and CHEK2 genes as well as diverse gene fusions. These discoveries reduced the fraction of PTC cases with unknown oncogenic driver from 25% to 3.5%. 

Combined analyses of genomic variants, gene expression, and methylation demonstrated that different driver groups led to different pathologies with distinct signaling and differentiation characteristics. These results led the authors to propose a reclassification of thyroid cancers into molecular subtypes that would better reflect their underlying signaling and differentiation properties. This new classification strategy would have the potential to improve their pathological classification and better inform the management of the disease.

“These findings are a major step forward in how doctors and patients will address thyroid cancer diagnosis and treatment. Researchers around the world will be using this data, coming back to it and asking other scientific questions,” said Dr. Carolyn Hutter, program director in the division of genomic medicine at the [US] National Human Genome Research Institute (Bethesda, MD, USA). 

Related Links:
The Cancer Genome Atlas Research Network
TCGA Data Portal
National Human Genome Research Institute