4.6 Article

Ferroptosis and triple-negative breast cancer: Potential therapeutic targets

Journal

FRONTIERS IN ONCOLOGY
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2022.1017041

Keywords

triple-negative breast cancer; ferroptosis; prognostic model; immune infiltration; drug prediction

Categories

Funding

  1. Key Discipline Construction Project of Guangdong Medical University
  2. Innovation Project of Guangdong Graduate Education
  3. [4SG22004G]
  4. [2020JGXM053]

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This study identified biomarkers and potential targets for triple-negative breast cancer (TNBC) related to ferroptosis. A prognostic model composed of 12 ferroptosis-related genes was constructed and validated. Seven genes were identified as potential therapeutic targets, and two drugs were found to have potential for treating TNBC.
PurposeTriple-negative breast cancer (TNBC) is an aggressive tumor with poor prognosis, it has higher recurrence and metastatic rates than other breast cancer subtypes. This study aims to investigate biomarkers and potential targets for TNBC related to ferroptosis through data mining and bioinformatics analysis. The findings may provide new insights for treating TNBC. MethodsThe TNBC patients' data from the Cancer Genome Atlas (TCGA) database were extracted for differential expression and prognosis analysis. Consensus genes obtained by intersecting differential expressed and ferroptosis-related genes was used to establish the prognostic model by the univariate and multivariate Cox analyses. Besides, TNBC data from the Gene Expression Omnibus (GEO) database was used to confirm the reliability of the prognosis model. Moreover, clinical information was analyzed by multifactorial independent analysis to identify independent prognostic factors. The expression of genes constituting the prognostic model was further validated using the Human Protein Atlas (HPA) database. Finally, the Comparative Toxicogenomic Data (CTD) database was used to explore possible treatment drugs for TNBC. ResultsWe obtained 13,245 differential expressed genes, and 177 consensus genes. 98 genes with prognostic implication were obtained by univariable Cox. Then, a prognostic model including 12 ferroptosis-related genes was constructed by multivariable Cox. The area under curve (AUC) value of the prognostic model for TNBC was 0.82. The GEO database validated that the model (AUC = 0.77) could predict the patient outcomes. The staining results of 10 out of 12 prognostic model genes in HPA database showed that their expression was consistent with our predictions. Clinical risk analysis indicated that risk score of patients could act as an independent prognostic factor. Finally, six drugs that may have interaction with 12 ferroptosis-related genes were obtained using the CTD database. ConclusionThe prognostic model composed of 12 ferroptosis-related genes could predict the prognosis of TNBC patients, and seven genes (ASNS, LAMP2, CAV1, DPP4, HELLS, TF, ZFP69B) could be potential new therapeutic targets for TNBC, and two drugs (1-methyl-3-isobutylxanthine, rosiglitazone) could act as potential therapeutic drugs for the treatment of TNBC.

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