Identifying the Potential Role and Prognostic Value of the Platelet-Derived Growth Factor Pathway in Kidney Renal Clear Cell Carcinoma

Abstract

The platelet-derived growth factor (PDGF) pathway is important in angiogenesis, which can accelerate the formation of vessels in tumor tissues and promote the progression of malignant tumors. To clarify the role of PDGF in the occurrence of renal cell carcinoma and targeted drug resistance, we explored the pathway in kidney renal clear cell carcinoma (KIRC) through bioinformatics analysis with the aim of supporting comprehensive and individualized therapy. First, we found 40 genes related to the PDGF pathway through gene set enrichment analysis and then obtained their expressions and clinical data in 32 different cancers from The Cancer Genome Atlas (TCGA). Mutations in these genes (including copy number and single-nucleotide variation) and mRNA expression were also detected. Next, we conducted a hazard ratio analysis to determine whether the PDGF pathway genes were risk or protective factors in tumors. Although PDGF-related genes acted as traditional oncogenes and were closely related to tumor angiogenesis in many cancers, our results indicated that most genes had a protective role in KIRC. We further analyzed the methylation modification of PDGF pathway genes and found that they were prevalent in 32 different cancers. Furthermore, 539 KIRC samples obtained from TCGA were divided into three clusters based on the mRNA expression of PDGF genes, including normal, inactive, and active PDGF gene expressions. The results from survival curve analysis indicated that the active PDGF cluster of patients had the best survival rate. Using the three clusters, we studied the correlation between the PDGF pathway and 12 common targeted drugs, as well as classical oncogenes and infiltrating immune cells. A prognostic risk model was constructed based on the PDGF score using LASSO-Cox regression analysis to analyze the value of the model in predicting the prognosis of patients with KIRC. Finally, 11 genes were selected for LASSO regression analysis, and the results demonstrated the high predictive value of this risk model and its close relationship with the pathological characteristics of KIRC (metastasis, size, grade, stage, etc.). In addition, we found that the risk score was an independent risk factor correlated with overall survival through univariate and multivariate analyses and a nomogram was built to assess patient prognosis. In conclusion, the occurrence and development of KIRC may be associated with an abnormally activated PDGF pathway, which may be a potential drug target in the treatment of KIRC.