Kinesin-related genes stratified the prognosis and immune responses of clear cell renal cell carcinoma

Abstract

Background: Clear cell renal cell carcinoma (ccRCC) is a prevalent and aggressive form of kidney cancer. Recently, the identification of suitable subtypes in ccRCC for the prediction of prognosis and immune infiltration remains limited. Kinesin superfamily proteins (KIFs), a group of molecular motor proteins, have been found to play crucial roles in tumor progression and patient prognosis in various cancers. However, the subtypes in ccRCC based on KIFs remain poorly understood.

Methods: In this study, transcriptional profiles of ccRCC were analyzed using data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Differential expression of KIFs was identified using R software. Subsequently, ccRCC patients were stratified into two distinct subgroups based on non-negative matrix factorization (NMF) analysis. Comparative analyses were performed to evaluate prognosis, mutations, and immune cell infiltration between these subtypes. Furthermore, signature genes associated with the identified subtypes were determined, followed by an investigation into their relationship with clinical characteristics and response to immune checkpoint inhibitors. Validation studies involving immunohistochemical staining, malignant phenotype assays, and immunofluorescence were conducted to assess the expression and function of these signature genes.

Results: Five KIFs genes, namely, KIF21B, KIF18B, KIF20A, KIF4A, and KIF13B, were identified as classifiers for categorizing ccRCC patients into two distinct subtypes known as KPCS1 and KPCS2. The aggressive subtype, KPCS2, was found to be associated with poorer survival outcomes. Furthermore, higher immune infiltration and copy number variations were observed in the KPCS2 subtype. Four signature genes (SLCA15, WDR72, PSAT1, and HJURP) displayed significant correlations with clinical characteristics and were determined to be linked to the ccRCC subtypes. The expression patterns and functional roles of these signature genes were subsequently validated in both ccRCC cells and tissues.

Conclusion: KIFs-associated subtypes provide valuable insights into the molecular characteristics and prognostic implications of ccRCC, thereby suggesting potential therapeutic targets for intervention.

Keywords: Clear cell renal cell carcinoma; Immune response; Kinesin superfamily proteins; Molecular subtypes; Targets.

Fig. 1

Flowchart of the present study design. The TCGA-KIRC and GSE126964 datasets were utilized to screen for differentially expressed KIFs. Subsequently, ccRCC patients were stratified into two distinct subgroups (KPCS1 and KPCS2) based on NMF analysis. Comparative analyses were performed to evaluate prognosis, mutations, and immune cell infiltration between these two clusters. Furthermore, signature genes associated with the identified subtypes were determined, followed by an investigation into their relationship with clinical characteristics and response to immune checkpoint inhibitors. Validation studies involving immunohistochemical staining, malignant phenotype assays, and immunofluorescence were conducted to assess the expression and function of these signature genes

Fig. 2

Identification of differentially expressed kinesin genes in ccRCC. A DEGs in GSE126964 and TCGA-KIRC databases. B Differentially expressed kinesin genes in GSE126964 and TCGA-KIRC databases. C Venn diagram showing 5 differentially expressed kinesin genes (DEKGs). D The heat map displaying the expression profile of 5 DEKGs in ccRCC tissue (T) and normal tissue (N) in GSE126964 and TCGA-KIRC databases

Fig. 3

Classification of patients into two clusters by NMF analysis. A NMF rank survey performed on the two clusters. B Two subgroups were identified as optimal values for consensus clustering. C Survival analysis for two clusters of ccRCC. D Mutation frequency of top 20 genes in two clusters of ccRCC. E, F Correlations between two clusters and immune cell infiltration by quanTIseq method. G, H Correlations between two clusters and immune cell infiltration by cibersort method

Fig. 4

Identification of cluster-specific genes and perform the functional annotation. A Venn diagram for screening cluster-specific genes. B The heat map showing clinicopathological features of two clusters and gene expression of cluster-specific genes of each cluster. C Propotion of clinicopathological features in the two clusters. D Functional enrichment analysis of genes from four groups. E Forest plot of univariate Cox analysis

Fig. 5

Correlation of four signature genes with clinical characteristics. A Survival analysis of four signature genes (SLCA15, WDR72, PSAT1, and HJURP). B–E Signature gene expressions in normal tissues and ccRCC at different tumor grades, and TNM stages. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ns, not significant

Fig. 6

Correlation of four signature genes with clinical characteristics and immune responses. A Signature gene expression in normal tissues and ccRCC at different tumor stages. B The immunohistochemical results of SLCA15, WDR72, PSAT1, and HJURP in ccRCC at different stages. C IHC score of SLCA15, WDR72, PSAT1, and HJURP expression in ccRCC at different stages. D Prediction of immune response of four signature genes to anti-PD-1 immunotherapy by the MIAS.IMPRES analysis *, P < 0.05; **, P < 0.01; ***, P < 0.001; ns, not significant

Fig. 7

Validation of the role of four signature genes in ccRCC. A–C Overexpression or silencing validation of SLC5A1, PSAT1, and HJURP in ccRCC cells by Western blot. D–F Wound healing results showed that overexpression of SLC5A1 or knockdown of PSAT1 and HJURP inhibited the ccRCC cells migration. G–I Transwell assay showed overexpression of SLC5A1 or knockdown of PSAT1 and HJURP suppressed the ccRCC cells migration and invasion

Fig. 8

Functional evaluation of PSAT1 and HJURP in ccRCC cells. A, B mRNA expression of serine metabolism associated genes in 786-O and 769-P cells with PSAT1 knockdown. C, D Protein expression of CENPC in 786-O and 769-P cells with HJURP knockdown. E, F Immunofluorescence of CENPC in 786-O and 769-P cells with HJURP knockdown