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April 23, 2026PeerJ0 citationsOpen Access

Multi-omics analysis reveals key genes associated with clear cell renal cell carcinoma

XCXiaochen ChenHTHan TianMZMingwei Zhan

Key Points

  • This research aims to find genes related to prognosis in clear cell renal cell carcinoma using advanced data analysis techniques.
  • Analyzed single-cell RNA sequencing data from ccRCC patients using R software.
  • Identified co-expression modules and their association with disease stages through advanced gene analysis methods.
  • Utilized Mendelian randomization to link genetic variations with gene expression patterns.
  • Identified 150 genes linked to tumorigenesis, with PRDX2 showing potential as a protective factor.
  • Patients with higher PRDX2 expression had better survival outcomes according to Kaplan-Meier analysis.
  • Demonstrated increased migration and proliferation of ccRCC cells upon knocking down PRDX2.

Abstract

Background The most common type of kidney cancer is ccRCC (Clear Cell Renal Cell Carcinoma). Existing research has shown that when kidney cancer progresses from T2 to T3 or T4 stage, the treatment options and prognosis significantly differ. The aim of this study is to identify prognosis-related genes in ccRCC using single-cell data and Mendelian randomization analysis. Methods Single-cell RNA sequencing (scRNA-seq) data from six ccRCC patients (GSE156632) were analyzed in R. After quality control and normalization, cells were embedded, clustered, and annotated to define major cell types. Cell–cell signaling networks were inferred using CellChat. Stage-related co-expression programs were identified using high-dimensional weighted gene co-expression network analysis (hdWGCNA), and modules enriched in advanced disease were prioritized. To connect expression patterns with germline variation, we obtained expression quantitative trait loci (eQTL) summary statistics from the UK Biobank and performed two-sample Mendelian randomization using the ukb-b-1316 exposure dataset. For clinical validation, bulk RNA-seq and survival data from The Cancer Genome Atlas (TCGA) were incorporated, and candidate genes were evaluated using univariable Cox proportional hazards models. Results hdWGCNA identified three modules, from which we selected 150 genes. eQTL combined with Mendelian randomization analysis revealed a potential causal relationship between RBP5, PRDX2, GTSF1, BSG, and COX14 and tumorigenesis. Further TCGA data analysis indicated that PRDX2 might serve as a protective factor in ccRCC, consistent with the Mendelian randomization results. Furthermore, its expression exhibited a gradual decline with tumor stage progression. Kaplan-Meier(KM) curves demonstrated better prognosis for patients with high PRDX2 expression. Cell communication analysis revealed more frequent communication between cells with reduced PRDX2 expression and vascular endothelial cells. Moreover, the experiments demonstrate that the migration and proliferation abilities of ccRCC cells are enhanced after knocking down PRDX2. Conclusion These results suggest that PRDX2 may play a role in the progression of ccRCC and could potentially serve as a prognostic factor and therapeutic target for ccRCC.

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Cite This Study

Chen et al. (2026) studied this question.

synapsesocial.com/papers/69e9baeb85696592c86ecdc1https://doi.org/10.7717/peerj.21057
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