Abstract
Introduction: Vesicular transport (VT) has a complex relationship with tumor progression and immunity. But prognostic significance of VT in clear cell renal cell carcinoma (ccRCC) is unclear. Thus, we aimed to establish a prognostic model according to VT to predict overall survival of ccRCC patients. Methods: We used patient data from TCGA database and built a prognostic model with 13 VT-related genes (VTRGs) by differential expression analysis, LASSO regression, and univariate/multivariate Cox analysis. The model was validated internally and externally, and survival analysis and ROC curves depicted excellent predictive ability. Furthermore, higher modeled riskscores corresponded to more advanced tumor progression. To further understand the potential reasons for different prognoses in patients, we did enrichment analysis on differentially expressed genes identified by the model in risk groups. The expression levels and roles of SAA1 and KIF18B in ccRCC were verified by qRT-PCR and cell function experiments. Results: Humoral immune response and cAMP signaling pathway may be the biological processes and pathways leading to poor prognosis. Further analysis of immune microenvironment presented that ccRCC patients with poor prognoses had highly immune-infiltrated characteristics. We compared the drug response data of samples from different prognostic patients in the GDSC database and identified drug sensitivity differences associated with prognosis. Finally, we demonstrated that SAA1 and KIF18B could increase the proliferation, migration, and invasion ability of ccRCC cells using cellular experiments. Conclusion: In summary, we further revealed the importance of VTRGs in ccRCC prognosis.
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