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. 2024 May 17;103(20):e37939.
doi: 10.1097/MD.0000000000037939.

Function of NEK2 in clear cell renal cell carcinoma and its effect on the tumor microenvironment

Peng Tang  1   2 , Gangfu Zheng  1 , Congcong Xu  3 , Nengfeng Yu  1 , Jiaqi Du  1 , Liqian Hu  1 , Zhan Zhou  1   4 , Yichun Zheng  1   3
Affiliations

Function of NEK2 in clear cell renal cell carcinoma and its effect on the tumor microenvironment

Peng Tang et al. Medicine (Baltimore). .

Abstract

Background: Previous studies have revealed the critical functions of NEK2 in controlling the cell cycle which is linked to poor prognosis in multiple tumor types, but less research has been devoted to clear cell renal cell carcinoma (ccRCC).

Methods: We downloaded clinical data from the gene expression omnibus (GEO) and TCGA databases together with transcriptional and mutational datasets. Strongly coexpressed genes with NEK2 were extracted from TCGA-KIRC cohort, and were submitted to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional analyses. According to NEK2 levels, the survival status, mutational characteristics, response to immunotherapy and sensitivity to drugs of the patients were studied. The potential correlations between NEK2 levels and immune cell state as well as immune cell infiltration were examined using the GEPIA, TIMER and TISIDB databases. Double immunofluorescence (IF) was performed to identify the NEK2 overexpression and relationship with CD8 in ccRCC.

Results: The NEK2 gene was overexpressed and would enhance the nuclear division and cell cycle activities in ccRCC. ccRCC patients with high NEK2 expression had worse clinical outcomes, higher mutation burden and better therapeutic response. Moreover, NEK2 gene overexpression was positively related to various immune cell marker sets, which was also proved by validation cohort, and more infiltration of various immune cells.

Conclusion: ccRCC patients with NEK2 high expression have a poorer prognosis than those with NEK2 low expression, resulting from its function of promoting proliferation, accompanied by increased infiltration of CD8 + T cells and Tregs and T-cell exhaustion and will respond better to proper treatments.

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Conflict of interest statement

The authors have no conflicts of interest to disclose.

Figures

Figure 1.
Figure 1.
Variable forms of human malignancies express different amounts of NEK2 (*P < .05, **P < .01, ***P < .001). (A–B) UALCAN and TIMER were used to compare NEK2 expression levels between various tumor types from The Cancer Genome Atlas (TCGA) database. (C–D) The NEK2 expression difference between tumor and non-tumor tissues of ccRCC patients based on the GEO database. ccRCC = clear cell renal cell carcinoma, GEO = gene expression omnibus.
Figure 2.
Figure 2.
NEK2 expression levels along with clinicopathological characteristics in ccRCC. (A–C) Correlation between NEK2 expression level and clinicopathological parameters (cancer stage, cancer grade and lymph node stage) of ccRCC in the TCGA-KIRC cohort. (D–F) Survival curves of OS, DSS and PFI in ccRCC patients from TCGA database. ccRCC = clear cell renal cell carcinoma, DSS = disease-specific survival, PFI = progression-free interval, TCGA = The Cancer Genome Atlas.
Figure 3.
Figure 3.
Correlation between somatic mutations and NEK2 expression in ccRCC. (A) Somatic mutations in the NEK2 low expression groups. (B) Comparison of mutations between the high expression group and low expression group of NEK2. (C) Tumor mutational burden (TMB) between the two subgroups based on NEK2 expression. (D) Survival analysis of the various TMB-strategized groups. (*P < 0.05, **P < 0.01, ***P < 0.001).
Figure 4.
Figure 4.
Correlation between somatic mutations and NEK2 expression in ccRCC. (A) Somatic mutations in the NEK2 low expression groups. (B) Comparison of mutations between the high expression group and low expression group of NEK2. (C) Tumor mutational burden (TMB) between the 2 subgroups based on NEK2 expression. (D) Survival analysis of the various TMB-strategized groups (*P < .05, **P < .01, ***P < .001.). ccRCC = clear cell renal cell carcinoma.
Figure 5.
Figure 5.
Relevance of NEK2 and immune-related genes (A) Relationship between NEK2 and immune inhibitors. (B) Relationship between NEK2 and immune stimulators. (C) Relationship between NEK2 and MHC molecules. (D) Relationship between NEK2 and chemokines. (E) Relationship between NEK2 and chemokine receptors. (F) Relationship between NEK2 and lymphocytes.
Figure 6.
Figure 6.
The association between immune cell marker gene sets and NEK2 expression. (A) The bubble plot of the correlations of NEK2 with marker sets of 16 various immune cells. (B) The bubble plot of the correlations of NEK2 with markers of activated CD8+/CD4 + T cells. (C) Box plot of T-cell exhaustion-related immune marker (PDCD1, LAG3, CTLA4 and TIGIT) expression in ccRCC tissues. (D) K-M curves of OS in ccRCC patients based on NEK2 expression and PDCD1 expression. ccRCC = clear cell renal cell carcinoma, OS = overall survival.
Figure 7.
Figure 7.
Immune cell infiltration characteristics in ccRCCs expressing NEK2. (A–B) Differences in immune scores and stromal scores between the NEK2-low and NEK2-high expression subgroups (*P < .05, **P < .01, ***P < .001, ****P < .0001). (C–D) KM survival curve of OS based on NEK2 expression levels, immune scores and stromal scores. (E–F) The correlation between NEK2 expression and immune cell infiltrates was analyzed by xCell and TISIDB platforms. ccRCC = clear cell renal cell carcinoma, OS = overall survival.
Figure 8.
Figure 8.
Assessment of therapeutic response through 2 subgroups based on NEK2 expression. (A) Comparing CTLA4 and PD-1-strategized immunophenoscores (IPSs) between the low- and high-NEK2 expression groups. (B-E) Sensitivity analysis for axinib (B), pazopanib (C), rapamycin (D), sorafenib (E) in ccRCC patients with low and high NEK2 expression. (F) Differences between the expression levels of the target genes in the low- and high-NEK2 expression groups following targeted medication therapy. ccRCC = clear cell renal cell carcinoma.
Figure 9.
Figure 9.
Relationship between NEK2 and coexpressed genes related to the cell cycle in ccRCC. (A) Associations between NEK2 and cell cycle-related coexpressed genes. (B-E) Correlation between NEK2 expression and KIF14, CENPF, TPX2 and BUB1B based on the TIMER database. (F) Visualization of the interaction network of genes strongly associated with NEK2 by GeneMANIA. ccRCC = clear cell renal cell carcinoma.
Figure 10.
Figure 10.
Coexpression genes related to NEK2 showed proliferation-related characteristics. (A–D) KEGG pathway enrichment and GO analysis of 480 strongly correlated genes. (E–F) Gene set enrichment analysis (GSEA) indicated that NEK2 is positively related to the cell cycle and chromosome segregation. GO = gene ontology, KEGG = Kyoto encyclopedia of genes and genomes.
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