Recurrence of Papillary Thyroid Cancer Predicted by Genetic Risk Model

Thyroid cancer
Thyroid cancer
The recurrence of thyroid cancer is traditionally predicted using clinical tools. A more detailed way to predict recurrence is currently being researched.

Analysis of messenger RNA (mRNA), microRNA (miRNA), and protein-encoding genes may predict the chance of recurrent papillary thyroid cancer at the first occurrence of disease, according to a study in the Journal of Clinical Endocrinology & Metabolism.

Investigators developed a risk score model after conducting a comprehensive bioinformatic and experimental analysis of 3 levels of genetic change (mRNA, microRNA, and somatic mutation) in recurrent tumors.

The Cancer Genome Atlas (TCGA) was used to identify total RNA sequencing data (RNAseq) from 501 thyroid cancer (THCA) samples, including 455 nonrecurrent and 46 recurrent tumor specimens. A total of 59 tumor/normal matched samples were also analyzed. The study authors performed functional gene analysis in cell-based assays in multiple thyroid cell lines and assessed the prognostic value of genes with TCGA datasets.

Researchers identified potential biomarkers associated with THCA recurrence, including 40 mRNAs, 39 miRNAs, and 59 genetic variants. The genes FN1, ITGa3, and MET and miR-486 and miR-1179 all had significant functional effects on thyroid cancer cell migration in vitro. In addition, ablation of miR-486 and miR-1179 increased cellular migration of TPC-1 and SW1736 cells.

A receiver operating characteristic curve was generated for each gene/miR to determine the optimal cutoff value for risk stratification. Univariate Cox regression analysis suggested each biomarker was significantly correlated with an increased risk of recurrence (P < .05) in BRAF-like tumors. The genes were then combined to develop a prognosis risk model.

Multivariate Cox regression coefficient and fragments per kilobase million (FPKM) values were used to calculate risk scores. A higher area under the curve of 0.751 indicated a greater prediction value for the 5 gene-based risk score compared with individual genes. Patients who were considered high risk by the combined risk score had a significantly worse recurrence prognosis in the BRAF-like (P = 6.8×10-5) and full THCA cohort (P = 7.0×10-6).

The researchers noted they could not experimentally consider all the genes which showed significantly altered expression in recurrent vs nonrecurrent tumors, and FN1 upregulation and ITGa3 downregulation in recurrent tumors was unclear.

“Importantly, after controlling for age, gender, disease stage, tumor stage, and node status, multivariate analysis showed that the 5 gene risk score classifier was the sole independent prognostic factor for the entire group of THCA patients, as well as for the BRAF-like cohort,” the study authors wrote. “Our data suggest that the expression of genes FN1, ITGα3, MET, miR-486, and miR-1179 can be useful future prognostic tools in indicating the likelihood of individual papillary thyroid cancer recurrence.”


Nieto HR, Thornton CEM, Brookes K, et al. Recurrence of papillary thyroid cancer: a systematic appraisal of risk factors. J Clin Endocrinol Metab. Published online November 16, 2021. doi:10.1210/clinem/dgab836