Metastatic renal cell carcinoma (mRCC) treatment has been revolutionized by the introduction of immune checkpoint inhibitors (ICI), yet reliable predictive biomarkers are lacking. The International mRCC Database Consortium (IMDC) score is widely used for risk stratification but has limitations, including complexity and diagnostic-access biases. The modified Glasgow Prognostic Score (mGPS), a simpler alternative based on serum C-reactive protein (CRP) and albumin, has demonstrated superior prognostic value and dynamic applicability in clinical trials. Beyond its prognostic role, mGPS is associated with distinct molecular features of RCC, suggesting its potential as a predictive biomarker for therapy selection.

Emerging proteomics technologies now enable deep profiling of the serum proteome, detecting thousands of proteins that reflect tumor biology, immune responses, and systemic metabolic alterations. In RCC, inflammatory markers such as CRP have been linked to myeloid-driven immune evasion and reduced treatment efficacy. By integrating molecular characterization with comprehensive serum proteomics, this project aims to refine risk stratification, identify novel biomarkers, and improve treatment personalization. The goal of this project is the establishment of a serum-based framework for RCC classification, which could provide a scalable, minimally invasive tool for risk assessment, therapy selection, and treatment monitoring, addressing the current limitations of clinical decision-making in mRCC.