Identification of key genes CCL5, PLG, LOX and C3 in clear cell renal cell carcinoma through integrated bioinformatics analysis

Weiming Deng^1*Xie Zhenwei²Cheng Feng³Yude Hong⁴Libo Chen¹Mingyong Li¹

• ¹Department of Urology, The First Affiliated Hospital of University of South China, Hengyang, Hunan Province, China
• ²Department of Kidney Transplantation, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
• ³Department of Thyroid and Galactophore Surgery, People's Hospital of Longhua,, Shenzhen, China
• ⁴Department of Urology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

Background: Clear Cell Renal Cell Carcinoma (ccRCC) is a malignant tumor with high mortality and recurrence rates and the molecular mechanism of ccRCC genesis remains unclear. In this study, we identified several key genes associated with the prognosis of ccRCC by using integrated bioinformatics.Methods: Two ccRCC expression profiles were downloaded from Gene Expression Omnibus (GEO), and one dataset was gained from The Cancer Genome Atlas (TCGA). The Robust Rank Aggregation (RRA) method was used to analyze the three datasets to gain integrated differentially expressed genes (DEGs). The GO and KEGG analysis were performed to explore the potential functions of DEGs. The Search Tool for the Retreival of Interacting Genes/Proteins (STRING) and Cytoscape software were used to construct PPI network and module analyses to screen the hub genes.Spearman's correlation analysis was conducted to evaluate the interrelationships among the hub genes. The prognostic value was evaluated through K-M survival analysis, Cox regression analysis, and receiver operating characteristic (ROC) curve analysis to determine their potential as prognostic biomarkers in ccRCC. The expression of hub genes between ccRCC and adjacent normal tissues was analyzed by RT-qPCR, Western blotting, and immunohistochemical (IHC).Result: 125 DEGs were identified using the limma package and RRA method, including 62 up-expressed genes and 63 down-expressed genes. GO and KEGG analysis showed some associated pathways. Spearman's correlation analysis revealed that the hub genes are not only interrelated but also closely associated with immune cell infiltration. Gene expression analysis of the hub genes based on the TCGA-KIRC cohort, along with K-M survival analysis, Cox regression, and ROC curve analysis, consistently demonstrated that CCL5, LOX, and C3 are significantly upregulated in ccRCC and are associated with poor clinical outcomes. In contrast, PLG showed opposite result. These results were further validated at the mRNA and protein levels.Our findings indicate that CCL5, LOX, C3, and PLG are significantly associated with the progression and prognosis of ccRCC, highlighting their potential as prognostic biomarkers. These results provide a foundation for future research aimed at uncovering the underlying mechanisms and identifying potential therapeutic targets for ccRCC.