Construction of a ferroptosis-related five-lncRNA signature for predicting prognosis and immune response in thyroid carcinoma

Abstract

Background Thyroid carcinoma (THCA) is the most common endocrine-related malignant tumor. Despite the good prognosis, some THCA patients may deteriorate into more aggressive diseases, leading to poor survival. This may be alleviated by developing a novel model to predict the risk of THCA, including recurrence and survival. Ferroptosis is an iron-dependent, oxidative, non-apoptotic form of cell death initially described in mammalian cells, and plays an important role in various cancers. To explore the potential prognostic value of ferroptosis in THCA, ferroptosis-related long non-coding RNAs (FRLs) were used to construct model for risk prediction of THCA. Methods RNA-sequencing data of THCA patients and ferroptosis-related genes were downloaded from The Cancer Genome Atlas (TCGA) and FerrDb, respectively. A total of 502 patients with complete data were randomly separated into a training cohort and a validation cohort at the ratio of 2:1. The Pearson correlation coefficients were calculated to determine the correlation between ferroptosis-related genes (FRGs) and the corresponding lncRNAs, and those meeting the screening conditions were defined as FRLs. Gene Expression Omnibus (GEO) database and qRT-PCR were used to verify the expression level of FRLs in THCA tissues. Univariate and multivariate cox regression analysis were performed to construct a FRLs signature based on lowest Akaike information criterion (AIC) value in the training cohort, then further tested in the validation cohort and the entire cohort. Gene set enrichment analysis (GSEA) and functional enrichment analysis were used to analyze the biological functions and signal pathways related to differentially expressed genes between the high-risk and low-risk groups. Finally, the relative abundance of different tumor-infiltrating immune cells were calculated by CIBERSORT algorithm. Results The patients were divided into high-risk group and low-risk group based on a 5-FRLs signature (AC055720.2, DPP4-DT, AC012038.2, LINC02454 and LINC00900) in training cohort, validation cohort and entire cohort. Through Kaplan–Meier analysis and area under ROC curve (AUC) value, patients in the high-risk group exhibited worse prognosis than patients in the low-risk group. GEO database and qRT-PCR confirmed that LINC02454 and LINC00900 were up-regulated in THCA. Univariate and multivariate cox regression analyses showed that the risk score was an independent prognostic indicator. GSEA and functional enrichment analysis confirmed that immune-related pathways against cancer were significantly activated in the low-risk THCA patients. Further analysis showed that the immune cells such as plasma cells, T cells CD8 and macrophages M1, and the expression of immune checkpoint molecules, including PD-1, PD-L1, CTLA4, and LAG3, were remarkably higher in the low-risk group. Conclusion Our study used the TCGA THCA dataset to construct a novel FRLs prognostic model which could precisely predict the prognosis of THCA patients. These FRLs potentially mediate anti-tumor immunity and serve as therapeutic targets for THCA, which provided the novel insight into treatment of THCA.

Prognosis and chemotherapy drug sensitivity in liver hepatocellular carcinoma through a disulfidptosis-related lncRNA signature

“…In recent years, several prognostic models based on autophagy-related genes 21 , ferroptosis-related genes 22 , cuproptosis-related genes 23 , pyroptosis-related genes 24 have been constructed to predict the prognosis of different cancers. Not only mRNAs but also lncRNAs had been used to establish prognostic models for predicting prognosis 25 – 28 . Disulfidptosis is a novel type of cell death.…”

Construction and validation of a PANoptosis-related lncRNA signature for predicting prognosis and targeted drug response in thyroid cancer

“…A calibration curve was used to test the agreement between the actual results and model predictions according to the Hosmer–Lemeshow test. To compare the accuracy, we calculated the consistency index (c-index) and restricted mean survival (RMS) of the published models ( Guo et al, 2022 ; Qin et al, 2022 ; Ding et al, 2022 ; Liu et al, 2022 ; Shan et al, 2022 ) and the model we developed.…”

“… Guo et al (2022) revealed that a model composed of seven prognostic lncRNAs of papillary thyroid cancer (PTC). Qin et al (2022) validated a signature supported by four Ferroptosis-related lncRNAs as predictive markers for TC. Numerous studies have shown that lncRNAs influence TC prognosis, which means that we could develop a more accurate TC biomarker based on lncRNAs.…”

Mechanism of ferroptosis in traditional chinese medicine for clinical treatment: A review

“…Cancer immunotherapy, such as anti-PDL1-mediated tumor immunotherapy, can downregulate SLC7A11 expression to trigger ferritin responses in cancer cells. Combination treatment with an anti-PDL1 antibody and a ferroptosis inducer also showed synergistic anticancer effects in a mouse model (Stockwell and Jiang, 2019;Qin et al, 2022). The activator of ferroptosis strengthens the immune microenvironment link between ferroptosis and cancer (Yang et al, 2021b).…”