Key points are not available for this paper at this time.
Abstract Background Papillary thyroid cancer (PTC) is an indolent disease with a favorable prognosis but characterized by a high recurrence rate. We aimed to improve precise stratification of recurrence risk in PTC patients with early stage using multi-gene signatures. Patients and methods The present study was performed using data from The Cancer Genome Atlas (TCGA) and multi-center datasets. Unsupervised consensus clustering was used to obtain the optimal molecular subtypes and least absolute shrinkage and selection operator (LASSO) analysis was performed to identify potential genes for the construction of recurrence signature. Kaplan-Meier survival analysis and the log-rank test was used to detect survival differences. Harrells concordance index (C-index) was used to assess the performance of the DNA damage repair (DDR) recurrence signature. Results Through screening 8 candidate gene sets, the entire cohort was successfully stratified into two recurrence-related molecular subtypes based on DDR genes: DDR-high subtype and DDR-low subtype. The recurrence rate of DDR-high subtype was significantly lower than DDR-low subtype HR = 0.288 (95%CI, 0.084–0.986), P = 0.047. Further, a two-gene DDR recurrence signature was constructed, including PER1 and EME2. The high-risk group showed a significantly worse recurrence-free survival (RFS) than the low-risk group HR = 10.647 (95%CI, 1.363–83.197), P = 0.024. The multi-center data demonstrated that proportion of patients with low expression of PER1 and EME2 was higher in the recurrence group than those in the non-recurrence group. Conclusions These findings could help accurately and reliably identify PTC patients with high risk of recurrence so that they could receive more radical and aggressive treatment strategies and more rigorous surveillance practices.
Sun et al. (Mon,) studied this question.