A new ferroptosis-related gene model for prognostic prediction of papillary thyroid carcinoma

Abstract

Papillary thyroid carcinoma (PTC) is a highly heterogeneous malignancy with diverse prognoses. Ferroptosis is a new type of cell death dependent on iron. Nevertheless, the predictive ability of ferroptosis-related genes for PTC is unclear. Based on the mRNA expression information from The Cancer Genome Atlas, we compared tumor and normal tissues in terms of the gene expression, for identifying differentially expressed genes (DEGs). Then, the risk score of a 5-gene signature was calculated and a prognostic model was established to test the predictive value of this gene signature by virtue of the LASSO Cox regression. The 5 genes were validated in PTC tissues by RT-qPCR.At last, functional analysis was implemented to investigate the underlying mechanisms. We found a total of 45 ferroptosis-related genes expressed differentially between tumor and normal tissues. 6 DEGs exhibited a significant relevance to the overall survival (OS) (P< 0.05). We classified patients into group with high risk and group with low risk based on the median risk score of a 5-gene signature. Patients in the group with low risk presented a remarkably higher OS relative to the group with high risk (P< 0.01). The Cox regression analysis displayed the independent predictive ability of the risk score. The receiver operating characteristic analysis helped to validate the predictive power owned by the gene signature. After validation, the 5 genes were abnormally expressed between PTC and normal tissues. Functional analysis showed two groups had different immune status. A new ferroptosis-related gene signature can predict the outcomes of PTC patients.

Identification of immune-related ferroptosis prognostic marker and in-depth bioinformatics exploration of multi-omics mechanisms in thyroid cancer

“…To compare the ability of our model to predict prognosis with other models, we selected four models constructed by Han et al (2020) , Wu et al (2021) , Huang et al (2021) , and Qian et al (2021) . These models are based on 4 pyroptosis-related genes (IL18, GSDMC, PJVK, and NOD1), 3 ferroptosis-related genes (HSPA5, AURKA, and TSC22D3), 5 ferroptosis-related genes (DPP4, GSS, HMGCR, PGD, and TFRC) and 5 autophagy-related genes (CX3CL1, ATG9B, CDKN2A, ITPR1, and DNAJB1), respectively.…”

Estimating disease-free survival of thyroid cancer based on novel cuprotosis-related gene model

“…The three-gene model (FDX1, BUB1, RPL3) was constructed to predict DFS of 1, 3 and 5 years in thyroid cancer (AUC: 0.789, 0.733, 0.757). Some predictive models for thyroid cancer from other studies showed an AUC of OS (0.621, 0.859, 0.842) (20,23,24). By combining the T-stage, the calibration curves confirmed that the 1-, 3-and 5-year survival probability predicted by the nomogram (red, yellow, grey) is close to the actual survival.…”

Estimating Disease-Free Survival of Thyroid Cancer Based on Novel Cuprotosis-Related Gene Model

“…The three-gene model (FDX1, BUB1, RPL3) was constructed to predict DFS of 1, 3 and 5 years in thyroid cancer (AUC: 0.789, 0.733, 0.757). Some predictive models for thyroid cancer from other studies showed an AUC of OS (0.621, 0.859, 0.842) [20,23,24] . By combining the T-stage, the calibration curves con rmed that the 1-, 3-and 5-year survival probability predicted by the nomogram (red, yellow, grey) is close to the actual survival.…”