Multiomics in Renal Cell Carcinoma: Current Landscape and Future Directions for Precision Medicine

Renal cell carcinoma (RCC) is a prevalent and increasingly diagnosed malignancy associated with high mortality and recurrence rates. Traditional diagnostic and therapeutic approaches have limitations due to the disease's molecular heterogeneity. This review aims to explore how the integration of omics sciences-genomics, transcriptomics, proteomics, and metabolomics-can enhance the diagnosis, prognosis, and treatment of RCC.

Genomic analyses have uncovered critical mutations, including VHL, PBRM1, and BAP1, which support improved risk stratification and the development of targeted therapies. Transcriptomic and spatial transcriptomic studies have provided deeper insights into RCC heterogeneity and tumor microenvironment dynamics. Proteomic investigations have revealed potential biomarkers, while metabolomic approaches have highlighted RCC-specific metabolic shifts. Despite these advancements, several challenges persist, including intratumoral heterogeneity, difficulties in multi-omics data integration, and the limited clinical validation of biomarkers. Omics-driven approaches hold significant promise for advancing precision medicine in RCC. These technologies can facilitate earlier diagnosis, guide individualized therapies, and enhance prognostic evaluations. Future research must focus on validating multi-omic biomarkers and leveraging artificial intelligence to manage complex datasets, thereby supporting more informed clinical decision-making and personalized treatment strategies.