Upregulation of the ferroptosis-related gene is a specific predictor of poor triple-negative breast cancer patient outcomes.

OBJECTIVE

This study was designed to assess ferroptosis regulator gene (FRG) expression patterns in patients with TNBC based on data derived from The Cancer Genome Atlas (TCGA). Further, it was utilized to establish a TNBC FRG signature, after which the association between this signature and the tumor immune microenvironment (TIME) composition was assessed, and relevant prognostic factors were explored.

METHODS

The TCGA database was used to obtain RNA expression datasets and clinical information about 190 TNBC patients, after which a prognostic TNBC-related FRG signature was established using a least absolute shrinkage and selection operator (LASSO) Cox regression approach. These results were validated with separate data from the Gene Expression Omnibus (GEO). The TNBC-specific prognostic gene was identified this method. The STEAP3 was then validated through Western immunoblotting, immunohistochemical staining, and quantitative real-time polymerase chain reaction (RT-qPCR) analyses of clinical tissue samples and TNBC cell lines. Chemotherapy interactions and predicted drug sensitivity studies were investigated to learn more about the potential clinical relevance of these observations.

RESULTS

These data revealed that 87 FRGs were differentially expressed when comparing TNBC tumors and healthy tissue samples (87/259, 33.59%). Seven of these genes () are significantly related to the overall survival of TNBC patients. Kaplan-Meier analyses and established FRG signatures and nomograms identified and genes of prognostic relevance. Prognostic Risk Score values were positively correlated with the infiltration of CD4+ T cells (p = 0.001) and myeloid dendritic cells (p =0.004). Further evidence showed that was strongly and specifically associated with TNBC patient OS (P<0.05). The results above were confirmed by additional examinations of expression changes in TNBC patient samples and cell lines. High levels were negatively correlated with half-maximal inhibitory concentration (IC50) values for GSK1904529A (IGF1R inhibitor), AS601245 (JNK inhibitor), XMD8-85 (Erk5 inhibitor), Gefitinib, Sorafenib, and 5-Fluorouracil (P < 0.05) in patients with TNBC based on information derived from the TCGA-TNBC dataset.

CONCLUSION

In the present study, a novel FRG model was developed and used to forecast the prognosis of TNBC patients accurately. Furthermore, it was discovered that was highly overexpressed in people with TNBC and associated with overall survival rates, laying the groundwork for the eventually targeted therapy of individuals with this form of cancer.