NUF2 is correlated with a poor prognosis and immune infiltration in clear cell renal cell carcinoma

NUF2 mRNA expression in ccRCC patients

Evaluation of NUF2 transcript levels differentially expressed in multiple cancer samples via the TIMER database. NUF2 transcription levels were found to be high in a variety of human tumor samples, including ccRCC and 15 other kinds of cancers, such as hepatocellular carcinoma, Esophageal squamous cell carcinoma, gastric adenocarcinoma, urothelial carcinoma, lung cancer, glioma, ovarian cancer, breast cancer, cervical squamous cell carcinoma, colorectal cancer, pancreatic cancer and prostate adenocarcinoma (Fig. 1A). Furthermore, the transcript levels of NUF2 in ccRCC samples and normal samples were compared via the GEPIA database (Fig. 1B). The results suggested that the transcript level of NUF2 in ccRCC patients was notably upregulated. We retrieved four microarray data sets from the GEO database (GSE53000 GSE53757, GSE46699, GSE36895) and assessed the expression of NUF2 in ccRCC and normal samples to further validate the authenticity and accuracy of the results of NUF2 expression in ccRCC (Fig. 1C-F). In addition, immunohistochemistry confirmed high expression of NUF2 in ccRCC specimens (Fig. 1G-H). Our findings are in agreement with the results from these database analyses. All sets of figures showed high expression of NUF2 in ccRCC, indicating that NUF2 may play an irreplaceable role in tumor growth and development of various cancers, especially ccRCC, and may be a meaningful gene in ccRCC and other cancers.

Fig. 1figure 1

Analysis of the NUF2 gene expression in cancers. (A) NUF2 expression in multiple cancers (data from TCGA via TIMER) (***P < 0.001). (B) NUF2 mRNA expression in ccRCC tissues and normal tissues (***P < 0.001). (C ~ D) Validation of higher NUF2 mRNA expression in ccRCC than that in normal tissues in GSE53000 and GSE53727dataset. (E ~ F) Validation of higher NUF2 expression in ccRCC than that adjacent tissues in GSE46699 and GSE36895 dataset.(G-H)NUF2 protein levels in normal kidney sample(right) and ccRCC sample(left)

Correlation between clinicopathologic features and NUF2 expression in patients with ccRCC

We investigated the clinicopathological features of ccRCC patients with different NUF2 expression levels (Table 1). Patients in the high NUF2 expression group had higher clinical tumor-node-metastasis (TNM) stage, worse pathological stage and higher tumor grades than those in the low NUF2 expression group; however, there were no significant differences between the tumor group and the normal group in terms of age, gender, or race.

Table 1 Clinicopathological characteristics of ccRCC patients with differential NUF2 expression

In addition, we analyzed the expression of NUF2 in patients with different clinical characteristics through the UALCAN database. Up-regulated NUF2 in ccRCC patients was significantly correlated with gender, pathological stage, tumor grade, and lymph node metastasis, especially in men, patients with high tumor stage and grade, and multiple lymph node metastases, suggesting that high expression of NUF2 may be an adverse prognostic factor in RCC patients (Fig. 2).

Fig. 2figure 2

Association with NUF2 mRNA expression and clinicopathologic characteristics. (A) Gender(P = 0.03). (B) Grade(P = 8.09E-05). (C) Tumor stage(P = 4.05E-05). (D) lymph node metastasis(P = 3.65E-03).

Prognostic value of NUF2 in ccRCC

We evaluated the expression of NUF2 and verified whether it is related to the OS of ccRCC patients via GEPIA, LinkedOmics database analysis and Kaplan–Meier plotter analysis. GEPIA (Fig. 3A, P = 7.1E − 05), LinkedOmics analysis (Fig. 3B, P < 0.01) and Kaplan–Meier plotter analysis (Fig. 3C, P = 2.4e − 15) showed that high NUF2 expression was linked to poor OS in ccRCC, indicating that NUF2 is an independent prognostic factor and may be meaningful biomarker in ccRCC patients.

Fig. 3figure 3

Overall survival analysis with NUF2 mRNA expression in different databases. (A) NUF2 expression and overall survival in ccRCC patients via GEPIA(P = 7.1E-05). (B) NUF2 expression and overall survival in ccRCC patients via LinkedOmics database (P < 0.01). (C) NUF2 expression and overall survival in ccRCC patients via Kaplan-Meier plotter analysis(P = 2.4E-15). (D) Uni-Cox analysis of overall survival of ccRCC patients. (E) Multi-Cox analysis of the overall survival of ccRCC patients

In addition, we performed univariate and multivariate Cox regression analyses to further assess the predictive value of NUF2 in several clinicopathological subgroups and presented the results as forest plots. As shown in Fig. 3D, gender, TNM stage, histological grade and pathological stage, and high NUF2 expression were independent risk factors for OS in the univariate Cox regression analysis. Furthermore. multifactor Cox regression analysis of the above factors (as shown in Fig. 3E), gender, M stage, and NUF2 expression still showed predictive advantages for clinical outcomes.

Correlation between NUF2 expression level and immune cell in ccRCC

Infiltrating immune cells may influence the development of multiple cancers. In this research, we discussed the connection between NUF2 expression and immune cells using the TIMER database. In general, a high transcript level of NUF2 was closely related to immune cell infiltration in ccRCC (Fig. 4). In ccRCC, NUF2 expression was significantly positively correlated with dendritic cell (DCs) (r = 0.382, P = 2.86E-17), B cells (r = 0.251, P = 4.75E-08), macrophages (r = 0.231, P = 7.36E-07), neutrophils (r = 0.386, P = 1.00E-17), CD4 + T cells (R = 0.219, P = 2.20E-06) and CD8 + T cells (r = 0.25, P = 5.515E-08).

Fig. 4figure 4

Correlation between NUF2 expression and immune cells in ccRCC tissues (n = 533)

Correlations between the expression levels of NUF2 and markers of immune cells in ccRCC

The relationship between NUF2 expression and the state of tumor-infiltrating immune cells was further investigated on the basis of the expression level of immune markers in ccRCC. Immune cells in ccRCC include B cells, monocytes, NKcells, CD4 + T cells, CD8 + T cells, neutrophils, Macrophages and DCs. Furthermore, regulatory T cells (Tregs) and different T helper cells were deeply investigated.

To further analyze the role of NUF2 in tumor immunity, the GEPIA and TIMER databases were used to assess the association between NUF2 expression and immune cell markers in ccRCC tissues. We discovered that NUF2 expression had a significant positive correlation with most specific immune cell markers (Table 2), including CD8 + T cell markers (CD8A, CD8B), monocyte markers (CD86, CD115), T cell (general) markers (CD2, CD3E, CD3D),DC markers (CD11c), tumor-associated macrophage (TAM) markers (IL-10), M2 macrophage markers (CD163, VSIG4, MS4A4A), Th17 markers (STAT3), NKcell markers (KIR2DL4), Th1 markers (STAT1, STAT4, T-BET, IFN-γ), TFH markers (IL21),Th2 markers (GATA3, STAT5A), Tregs markers (TGFB1, STAT5B, CCR8, FOXP3) and T cell depletion markers (CTLA4, PD-1, TIGIT, TOX, LAG3).

Table 2 Correlation analysis between Nuf2 and biomarker genes of immune cells in ccRCC Functional annotation and PPI network analysis

As shown in Fig. 5, functional enrichment analysis revealed that NUF2-related genes were mainly enriched in organelle division and chromosome segregation in biological processes and in ATPase activity and chromosomal regions in molecular functions and cellular components (Fig. 5A, C, E). According to KEGG pathway analysis, NUF2-associated genes are mainly involved in cell cycle regulation and may also be involved in classical pathways such as the P53 signaling pathway and the regulation of microRNAs in tumors (Fig. 5B).

Fig. 5figure 5

Functional enrichment and PPI. (A, C, E) GO terms of NUF2 in ccRCC. (B) KEGG pathways of NUF2 in ccRCC. (C) PPI network of NUF2 in ccRCC.

It is well known that a more comprehensive understanding of protein functions can be achieved by studying protein interactions. We constructed an 11-point, 42-edge interactions network map of NUF2-related proteins via the STRING database (Fig. 5D), and the top 10 proteins and their genes in terms of the degree of association are as follows: NDC80, SPC25, SPC24, BUB1, DSN1, TTK, CENPE, CASC5, KIF11, and MIS12.

SPC25 and SPC24 are all part of the NDC80 complex, mainly involved in cellular chromosome segregation and spindle checkpoint activity. The 10 most correlated proteins are mainly involved in the cell cycle and essential for normal chromosome alignment, segregation and kinetochore formation during mitosis. In addition, up-regulated BUB1 is associated with a poor prognosis in ccRCC patients.

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