Integrated multi-omic profiling reveals macrophage-driven prognostic signatures in clear cell renal cell carcinoma through machine learning optimization.

ABSTRACT:

Objective

Clear cell renal cell carcinoma (KIRC) is the most prevalent and aggressive form of kidney cancer, with limited survival despite advances in combination immunotherapy. Tumor-associated macrophages (TAMs) critically shape the tumor microenvironment (TME) and influence treatment resistance. We aimed to delineate TAM heterogeneity, identify prognostic macrophage signatures, and characterize the immune-metabolic programs underpinning KIRC progression.

Methods

We integrated single-cell RNA sequencing (scRNA-seq) data from ten KIRC tumors with high-dimensional weighted gene co-expression network analysis (hdWGCNA) and twenty machine-learning models. Five macrophage subpopulations were defined by canonical markers and validated spatially. A macrophage-centric prognostic s

SUBMITTER: Cao W 

PROVIDER: S-EPMC12833068 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature