Comprehensive analysis of subtypes and risk model based on complement system associated genes in ccRCC

Area of Science:

• Oncology
• Immunology
• Genetics

Background:

• Clear cell renal cell carcinoma (ccRCC) treatment response to immunotherapy is difficult to predict.
• The complement system plays a role in tumor progression and immune responses.
• A link between the complement system and immunotherapy efficacy in ccRCC is hypothesized.

Purpose of the Study:

• To investigate the role of the complement system in ccRCC.
• To identify distinct complement system patterns in ccRCC tumors.
• To develop a prognostic model for ccRCC based on complement system genes.

Main Methods:

• Utilized The Cancer Genome Atlas (TCGA) data for 11 complement system-associated genes (CSAGs).
• Performed unsupervised clustering to classify ccRCC tumors into complement system (CS) patterns.
• Developed a novel scoring system (CSscore) based on CSAG expression levels.

Main Results:

• Identified two distinct CS patterns (Cluster1 and Cluster2), with Cluster1 associated with poorer outcomes.
• Cluster1 showed high tumor microenvironment (TME) immune cell infiltration but also high immune escape.
• The CSscore model independently predicted prognosis and differentiated immunotherapy efficacy.

Conclusions:

• Distinct CS patterns in ccRCC correlate with prognosis via TME immune cell infiltration and immune escape.
• The CSscore model provides a novel approach for ccRCC patient management.
• The CSscore model shows potential for broader application in other cancer types.