Identification of novel prognostic biomarkers for thyroid cancer by integrated transcriptome analysis of metastasis-associated genes.

INTRODUCTION

Distant metastasis (DM) is the most important prognostic factor affecting the overall survival (OS) of thyroid cancer. The current study aimed to discover prognostic biomarkers to predict thyroid cancer survival, particularly papillary thyroid carcinoma (PTC), the most common subtype of thyroid cancer.

METHODS

Four RNA sequencing (RNA-Seq) datasets of experimental lung metastasis from four transgenic mouse models of PTC, follicular thyroid cancer (FTC), poorly differentiated thyroid cancer (PDTC), and anaplastic thyroid cancer (ATC) were integrated to screen for candidate genes involved in DM. The Cancer Genome Atlas-Thyroid Cancer (TCGA-THCA) dataset was used to validate the candidate genes.

RESULTS

A total of 105 upregulated and 25 downregulated differentially expressed genes (DEGs) were identified to be present in all four datasets. Regulation of cytokine production, inflammation, immune checkpoint regulation, and MAPK/ERK cascade were major enriched pathways in metastatic tumor cells. Seven genes were identified whose overexpression was present in 63 of 498 PTC patients (13%) and was associated with poor OS (p < 0.01). Clinically, the seven-gene expression signature was associated with older age at the diagnosis, late stage of tumor, tall cell variant, and higher aneuploidy and hypoxia score. Mutation load was increased in patients with seven-gene expression signature: 26 samples had more than one driver mutation (47%, 26/55). Deep deletions in other chromosomal loci were frequently found in patients with BRAFV600E mutations. In contrast, only 7% of patients without a seven-gene expression signature had more than one driver mutation (24/243). Increased chromosomal instability was also observed in patients with a seven gene expression signature.

CONCLUSION

The seven-gene expression signature is associated with poor prognosis and chromosomal instability. These genes may be useful biomarkers for risk stratification for DM and help decision-making in initial surgical recommendations.