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. 2022 Apr 25:12:777824.
doi: 10.3389/fonc.2022.777824. eCollection 2022.

NR4A Family Genes: A Review of Comprehensive Prognostic and Gene Expression Profile Analysis in Breast Cancer

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NR4A Family Genes: A Review of Comprehensive Prognostic and Gene Expression Profile Analysis in Breast Cancer

Hassan Yousefi et al. Front Oncol. .

Abstract

This report analyzes nuclear receptor (NR) subfamily 4A's potential role in treating those diagnosed with breast cancer. Here we reviewed the current literature on NR4 family members. We also examined the relative gene expression of the NR4A receptor subfamily in the basal, HER2 (human epidermal growth factor receptor 2) positive, luminal A, and luminal B subtypes using data from tumor samples in The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). These data showed a positive link between NR4A1-NR4A3 expression and increased overall survival and relapse-free survival in breast cancer patients. In addition, we observed that high expression of NR4A1, NR4A2, and NR4A3 led to better survival. Furthermore, NR4A family genes seem to play an essential regulatory role in glycolysis and oxidative phosphorylation in breast cancer. The novel prognostic role of the NR4A1-NR4A3 receptors implicates these receptors as important mediators controlling breast cancer metabolic reprograming and its progression. The review establishes a strong clinical basis for the investigation of the cellular, molecular, and physiological roles of NR4A genes in breast cancer.

Keywords: METABRIC; NR4A; TCGA; breast cancer; survival.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
NR4A family gene expression in breast cancer increases survival. (A) RNA-Seq mRNA expression data for normal and breast cancer tissue from METABRIC database in normal (n = 148) and cancerous (n = 1826) breast tissue samples. (B) Kaplan–Meier overall survival (OS) curves for patients with breast cancer divided by the median value into low and high NR4A mRNA expression (n = 251 per group) using the GENT2 data set. (C) Kaplan-Meier analysis (kmplot.com) of relapse-free survival (RFS) based on the mean value of NR4A1, NR4A2, and NR4A3 in breast cancer (n = 4934), with the cutoff values of 282, 373, and 74, respectively. Probes 202340_x_at, 216248_s_at, and 207978_s_at used, respectively. P values calculated using a logrank test for OS and Cox regression model was used for RFS. Data were analyzed by an unpaired t-test. Statistically significant values of **p < 0.01, ***p < 0.001 and ****p < 0.0001 were determined.
Figure 2
Figure 2
Differential NR4A family gene expression in breast cancer subtypes. (A–C) Gene expression of the NR4A1–NR4A3 in METABRIC by Pam50 gene expression subtype classification. Scatterplots show that there is significant association between breast cancer subtypes and the level of NR4A gene expression in breast cancer patients. Basal (n=199), HER2+ (n=220), Lum A (n=679), Lum B (n=461) and Normal-like (n=140) subtypes. Data were analyzed by one-way ANOVA followed by Tukey’s post hoc test. Statistically significant values of *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001 were determined.
Figure 3
Figure 3
NR4A family gene expression is partially correlating with estrogen receptor breast cancer ER+, PR+ and HER2 subtypes. (A–C) Relative expression of NR4A family genes in different breast cancer tumors based on ER (ER+ = 1511, ER- = 474), PR (PR+ = 1040, PR- = 940), and HER2 (HER2+ =247, HER2- = 1733) status examined by IHC. Data were analyzed by an unpaired t-test. Statistically significant values of *p < 0.05, **p < 0.01, ****p < 0.0001, and ns: not significant were determined.
Figure 4
Figure 4
Relative expression of NR4A family genes in different breast cancer tumors, (A) stages, (B) grades, (C) lymph node metastasis, and (D) tumor sizes and patients’ age (E). NR4A2 mRNA expression was significantly elevated with increasing age in breast cancer patient while NR4A1 mRNA expression was significantly downregulated with increasing age in breast cancer patient. Tumor size (1-20 = 593, 20-30 = 724, 30-180 =567), tumor stage (I = 475, II = 800, III = 115, IV = 9), tumor grade (I = 165, II = 740, III = 927), lymph node status (LN- = 993, LN+ = 911), Age ( 20-45 = 247, 45-55 = 368, 55-65 = 502, 65-85 = 749, >85 = 38). Data were analyzed by one-way ANOVA followed by Tukey’s post hoc test. Statistically significant values of *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001, and ns, not significant were determined.
Figure 5
Figure 5
Expression of NR4A family gene is not correlated with the promoter methylation in breast tumors. (A) TCGA breast invasive carcinoma DNA methylation (Illumina Infinium HumanMethylation450) and gene expression microarray datasets were analyzed. (B) Representative statistics demonstrated correlation between NR4A family gene expression and its DNA methylation. Gene expression were not found to be correlated with DNA methylation.
Figure 6
Figure 6
Co-expression correlation analysis between NR4A1–NR4A3 genes and the (A) glycolysis and (B) oxidative phosphorylation marker genes related markers using HALLMARK_GLYCOLYSIS and KEGG_OXIDATIVE_PHOSPHORYLATION gene sets. The association between genes was measured using the Pearson correlation coefficient (r). Correlation heatmap (Pearson r) of the transcriptomes from METABRIC breast cancer project samples (n= 1985). Red color refers to negative correlation, and the blue color indicates positive correlation.
Figure 7
Figure 7
Co-expression correlation analysis between NR4A1–NR4A3 genes and the (A) glycolysis and (B) oxidative phosphorylation marker genes related markers using HALLMARK_GLYCOLYSIS and KEGG_OXIDATIVE_PHOSPHORYLATION gene sets. The association between genes was measured using the Pearson correlation coefficient (r). Correlation heatmap (P values) of the transcriptomes from METABRIC breast cancer project samples (n= 1985). Red color refers to P values< 0.05, and the white and blue colors indicates P values > 0.05.

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