2.1 The low expression of MCUR1 may be closely related to the development and prognosis of breast cancer
We compared the expression of MCUR1 in different TNM stage of breast cancer samples from TCGA, and found that there was a significant difference in the expression of MCUR1 between different TNM stages, with the increase of stage following the dramatic decrease of MCUR1 expression (Fig. 1A).
In order to study the effect of MCUR1 expression on the prognosis of patients with breast cancer, we analyzed the survival rate of the high and low expression groups of MCUR1 and found that the overall survival of breast cancer patients with MCUR1 low expression was poor (P = 0.024, HR = 1.35, 95% CI: 1.04–1.75) (Fig. 1B) compared with the high expression group of MCUR1 as a reference. In addition, GEPIA was developed to analyze the survival of TCGA and GTEx. It was demonstrated that the overall survival and disease-free survival of breast cancer patients with MCUR1 low expression were poor (Fig. 1C and 1D). These results suggest that MCUR1 low expression is closely associated with progression and prognosis of breast cancer.
2.2 Comparison of immune infiltration of breast cancer patients in high and low expression groups of MCUR1
We analyzed the infiltration of 22 immune cells in TCGA breast cancer patients using CIBERSORT method combined with LM22 characteristic matrix, in which the infiltration ratio of T cells CD4 naïve in all cancer samples was 0. Figure 2A was the results of immune cell infiltration in TCGA breast cancer patients, where the 21 immune cell infiltration ratios were diverse in different patients. We found that there was a significant difference in the infiltration degree of macrophages M1 and T cells CD8 between MCUR1 high and low expression groups (Fig. 2B), which may represent a potential pathway for prognostic differences between MCUR1 high and low expression groups. The expression of immune checkpoint has become a biomarker for cancer patients to choose immunotherapy. We found that there was a significant correlation between the expression of MCUR1 and the expression of CTLA4, PDL1, PDL2, TIM3, LAG3 and TIGIT (Fig. 2C). In addition, we studied the expression of 6 checkpoints in the low and high expression group of MCUR1, suggesting that the expression of 6 checkpoints in low expression group of MCUR1 was significantly lower than that in high expression group of MCUR1(P < 0.05) (Fig. 2D)(Table S2).
2.3 GSEA enrichment analysis
We selected the 10 samples with the highest and lowest expression levels of MCUR1 for gene set enrichment analysis (GSEA) using CP: KEGG gene set and C5: GO gene set, with the P < 0.05 as a criteria. The KEGG pathway and GO terms are both enriched in samples with high expression of MCUR1. According to the normalized enrichment score from high to low, the enriched KEGG pathways and GO terms are displayed, shown as Fig. 3A-3D. The results show that compared with the samples with low MCUR1 expression, the glycine serine and threonine metabolism related pathway in the samples with high MCUR1 expression are activated. The GO terms such as oxidoreductase activity acting on the CH_NH2 group of donors oxygen as acceptor, negative regulation of interleukin 10 production, regulation of tolerance induction are activated.
2.4 Co-expression network analysis
We selected genes from the metabolic pathway, glycine serine and threonine metabolism, to generate co-expression network analysis with MCUR1. The Spearman correlation coefficient between the genes in the pathway and MCUR1 can be seen in Table S3. The co-expression network showed that there was a strong positive correlation between MCUR1 and the eight genes of MAOA, DLD, GOT1, GOT2, GCAT, GATM, GNMT as well as PSAT1 using Spearman correlation coefficient > 0.8 as criteria (Fig. 4).