Genomic-oriented Multi-level Regulatory Landscape of Renal Tumor Metastasis- Related Key Genes

Abstract

Abstract Metastasis of renal tumor leads to poor prognosis of patients and increased therapeutic challenges. Nevertheless, the molecular mechanism underlying this clinical phenomenon remain to be elucidated. In this study, we identified 81 metastasis-related key genes and systematically explored their regulatory axis in renal tumor metastasis. In detail, both copy number variation and DNA methylation can partially affect the expressions of these key genes and showed differential distribution in the metastatic group. Path analysis modeling evaluated the potential overall causal effects from genomic level to phenotype and determined five statistical models. Additionally, the competing endogenous network revealed the post-transcriptional regulation of these key genes. Besides that, immune cell infiltration analyses suggested that some key genes may be involve in the regulation of tumor immunologic microenvironment. Furthermore, we built an effective machine learning model to predict renal tumor metastasis for clinical application. In summary, our research systematically described the potential biological roles and regulatory profiles of renal tumor metastasis-related genes, which may contribute to the improvement of clinical targeted therapy for renal tumor.