Identification of TFR2 as a novel ferroptosis‑related gene that serves an important role in prognosis and progression of triple‑negative breast cancer

Abstract

Effective targeted therapeutic strategies for triple-negative breast cancer (TNBC), the most malignant subtype of breast cancer, are currently lacking. Ferroptosis has been reported to be associated with the onset and advancement of various cancer types, including TNBC. However, there are limited studies on the correlation between TNBC and ferroptosis-related genes. In addition, the potential biomarkers of ferroptosis in TNBC need further investigation. The present study aimed to assess the prognostic role of a novel ferroptosis-related gene signature in the context of TNBC. The signature was established utilizing The Cancer Genome Atlas dataset. This three-gene model [transferrin receptor 2 (TFR2), regulator of G protein signaling 4 and zinc finger protein 36] was developed utilizing least absolute shrinkage and selection operator regression analysis and demonstrated satisfactory predictive performance in TNBC. The area under the curve values of the receiver operating characteristic curves in this model concerning the 1-, 2- and 3-year survival prediction were 0.721, 0.840 and 0.856, respectively. The predictive performance of the model was verified using the TNBC dataset GSE25307. Gene set enrichment analysis (GSEA) demonstrated the enrichment of genes in the low-risk group in a number of important metabolic pathways. Single-sample GSEA demonstrated a variation in the expression levels of immune checkpoint molecules between the high- and low-risk groups. The inhibitory impact of TFR2 knockdown on the proliferative capacity of TNBC cells was verified through in vitro experiments. The data also demonstrated that TFR2 knockdown facilitated the ferroptosis of TNBC cells. Additional assessments indicated that the effects of TFR2 knockdown were partially reversed upon treatment with the ferroptosis inhibitor ferrostatin-1. In conclusion, in the present study, a novel and accurate ferroptosis-related predictive signature was established for TNBC with potential future clinical applications. To the best of our knowledge, the present study is the first to report that TFR2 regulated ferroptosis in TNBC cells in vitro.

Keywords: ferroptosis; gene signature; prognosis; transferrin receptor 2; triple-negative breast cancer.

Figure 1.

Identification of ferroptosis-related DEGs of TNBC in The Cancer Genome Atlas cohort. (A) Heatmap and (B) volcano plot of the ferroptosis-related DEGs between TNBC and healthy breast tissue. |Log FC|>1 and fdr <0.05. Significantly upregulated and downregulated genes are depicted as red and green dots, respectively. (C) Interactions among candidate genes are shown by the protein-protein interaction network through the Search Tool for the Retrieval of Interacting Genes and proteins database. Results of (D) Gene Ontology biological process enrichment and (E) Kyoto Encyclopedia of Genes and Genomes pathways analysis of DEGs. DEG, differentially expressed gene; TNBC, triple-negative breast cancer; FC, fold change; fdr, false discovery rate.

Figure 2.

Evaluation of prognostic ferroptosis-related DEGs. (A) A total of five ferroptosis-related genes were identified by univariate Cox regression analysis with prognostic value (95% CI) in triple-negative breast cancer. (B) The expression of TFR2, ATF3 and ZFP36 in healthy breast tissue and breast cancer samples from the Human Protein Atlas database (magnification, ×100). Association of the expression levels of ferroptosis-related DEGs with overall survival, including (C) TFR2, (D) ATF3, (E) MKP-1, (F) RGS4 and (G) ZFP36; information in brackets represents gene probes. HR, hazard ratio; TFR2, transferrin receptor 2; ATF3, activating transcription factor 3; MKP-1, MAPK phosphatase 1; DUSP1, dual specificity phosphatase 1; RSG4, regulator of G protein signaling 4; ZFP36, zinc finger protein 36; DEG, differentially expressed gene.

Figure 3.

Construction and validation of a three-gene model based on least absolute shrinkage and selection operator Cox regression analysis. (A) Heatmap showing the expression of three genes in different risk groups of patients with triple-negative breast cancer according to the risk score in the TCGA cohort. Kaplan-Meier survival curves of the overall survival of high-risk and low-risk groups in (B) TCGA and (C) GEO (GSE25307) datasets (95% CI). The distribution of the risk scores and the relationship between survival time, survival status and risk scores in (D) TCGA and (E) GEO (GSE25307) datasets. The areas under the curve of time-dependent receiver operating characteristic curves for the three-gene signature in the (F) TCGA and (G) GEO (GSE25307) cohorts. TCGA, The Cancer Genome Atlas; GEO, Gene Expression Omnibus; AUC, area under the curve.

Figure 4.

Relationship between risk scores and clinicopathological factors in TNBC. Forest plots of the prognostic role of risk scores in predicting overall survival of TNBC as examined using (A) univariate and (B) multivariate Cox regression analyses (95% CI). (C) Heatmap of the distribution of ferroptosis-related gene expression and clinical factors. (D) Comparison of the risk scores with traditional clinicopathological factors in the prognostic prediction based on the receiver operating characteristic curve analysis. (E) Decision curve analysis comparing the net survival benefit of the risk scores with clinicopathological factors (red represents upregulation and green represents downregulation). (F) Nomogram used to predict prognosis based on the risk scores and clinicopathological factors. TNBC, triple-negative breast cancer; TFR2, transferrin receptor 2; RSG4, regulator of G protein signaling 4; ZFP36, zinc finger protein 36; AUC, area under the curve; T, tumor size; N, lymph node metastasis; MNA, distant metastasis; Pr, survival probability.

Figure 5.

Risk score of ferroptosis-related gene models is closely related to metabolic and immune function in triple-negative breast cancer. GSEA of the associated (A) glutathione metabolism, (B) fructose and mannose metabolism and (C) pentose phosphate signaling pathways in the low-risk group. (D) Heatmap of the correlation between risk score and immune status was explored by ssGSEA. (E) The differences in the expression levels of immune check-point molecules between the high- and low-risk score groups. *P<0.05; **P<0.01 vs. low risk. GSEA, gene set enrichment analysis; ssGSEA, single-sample GSEA; KEGG, Kyoto Encyclopedia of Genes and Genomes; TNFS, TNF superfamily member; ADORA2A, adenosine A2a receptor; NRP1, neuropilin-1.

Figure 6.

Knockdown of TFR2 promotes ferroptosis in the triple-negative breast cancer cell line MDA-MB-436. (A) The expression levels of TFR2 were detected by reverse transcription-quantitative PCR in healthy breast and breast cancer cell lines. (B) Western blot analysis of si-TFR2 knockdown efficiency. (C) Relative changes in the mRNA and protein expression levels of TFR2 in MDA-MB-436 cells after transfection with siRNA. (D) Cell viability of MDA-MB-436 cells was analyzed by a CCK-8 assay at 0, 24, 48 and 72 h after knockdown of TFR2 with siRNA. (E) Relative changes of MDA levels in MDA-MB-436 cells after knockdown of TFR2 compared with negative controls. (F) The expression levels of ferroptosis-related proteins were analyzed by western blot. (G) The viability of MDA-MB-436 cells was determined using a CCK-8 assay at 0, 24, 48 and 72 h after transfection with siRNA with or without 0.5 µM ferrostatin-1 treatment. Values are expressed as the mean ± standard deviation (n=3 independent experiments). *P<0.05, **P<0.01 and ***P<0.001 vs. NC. CCK-8, cell counting kit-8; OD, optical density; TFR2, transferrin receptor 2; NC, negative control; si, short interfering; MDA, malondialdehyde; LOX, lysyl oxidase; SLC7A11, solute carrier family 7 member 11; GPX4, glutathione peroxidase 4; FTH1, ferritin heavy chain 1; ns, not significant.