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A New Ferroptosis-Related Long Non-Coding RNA Risk Model Predicts the Prognosis of Patients With Papillary Thyroid
Jun Yu Zhao1,2,3, Jin Ming Yao1,3, Xin Zhong Zhang4
1Department of Endocrinology and Metabology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Shandong Institute of Nephrology, Ji'nan 250014, China.
Background:
Ferroptosis is a novel form of regulated cell death that involves in cancer progression. However, the role of ferroptosis-related long non-coding RNAs (lncRNAs) in papillary thyroid cancer (PTC) remains to be elucidated. The purpose of this paper was to clarify the prognostic value of ferroptosis-related lncRNAs in PTC.
Methods:
The transcriptome data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. The correlation between ferroptosis-related genes (FRGs) and lncRNA was determined using Pearson correlation analysis. Multivariate Cox regression model (P < 0.01) was performed to establish a ferroptosis-related lncRNAs risk model. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves, risk curve and nomograms were then performed to assess the accuracy and clinical applicability of prognostic models. The correlations between the prognosis model and clinicopathological variables, immune and m6A were analyzed. Finally, in vitro assays were performed to verify the role of LINC00900, LINC01614 and PARAL1 on the proliferation, migration and invasion in TPC-1 and BCPAP cells, as well as the relationship between three lncRNAs and ferroptosis.
Results:
A five-ferroptosis-related lncRNAs (PARAL1, LINC00900, DPH6-DT, LINC01614, LPP-AS2) risk model was constructed. Based on the risk score, samples were divided into the high- and low-risk groups. Patients in the low-risk group had better prognosis than those in high-risk group. Compared to traditional clinicopathological features, risk score was more accurate in predicting prognosis in patients with PTC. Additionally, the difference of immune cell, function and checkpoints was observed between two groups. Moreover, experiments showed that LINC00900 promoted the proliferation, migration and invasion in TPC-1 and BCPAP cells, while LINC01614 and PARAL1 revealed opposite effects, all of which were related to ferroptosis.
Conclusions:
In summary, we identified a five-ferroptosis-related lncRNAs risk model to predict the prognosis of PTC. Furthermore, our study also revealed that LINC00900 functioned as a tumor suppressor lncRNA, LINC01614 and PARAL1 as an oncogenic lncRNA in PTC.
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