Faculty, Staff and Student Publications

Language

English

Publication Date

11-6-2025

Journal

Cells

DOI

10.3390/cells14211740

PMID

41227385

PMCID

PMC12610877

PubMedCentral® Posted Date

11-6-2025

PubMedCentral® Full Text Version

Post-print

Abstract

Renal cell carcinoma (RCC) accounts for 90% of adult renal cancer cases and is characterized by significant heterogeneity within its tumor microenvironment. This study tests the hypothesis that tumor-associated macrophages (TAMs) influence RCC progression and patient response to treatment by investigating the prognostic implications of TAM signatures. Utilizing independent single-cell RNA sequencing data from RCC patients, we developed eight distinct TAM signatures reflective of TAM presence. A LASSO Cox regression model was constructed to predict survival outcomes, evaluated using the TCGA dataset, and validated across independent RCC cohorts. Model performance was assessed through Kaplan-Meier survival plots, receiver operating characteristic (ROC) curves, and principal component analysis. Survival analysis demonstrated that specific TAM signature gene expressions serve as significant prognostic markers, identifying TAM signatures positively correlated with patient survival and macrophage infiltration. A 27-gene TAM risk model was established, successfully stratifying patients into risk categories, with low-risk patients showing improved overall survival. These findings provide insights into the role of TAMs in modulating the RCC tumor immune microenvironment and their impact on patient prognosis, suggesting that TAM-based signatures may serve as useful prognostic markers and potential targets to enhance RCC treatment strategies.

Keywords

Humans, Carcinoma, Renal Cell, Tumor Microenvironment, Tumor-Associated Macrophages, Prognosis, Kidney Neoplasms, Gene Expression Regulation, Neoplastic, Male, Female, Biomarkers, Tumor, Middle Aged, Transcriptome, Kaplan-Meier Estimate, tumor-associated macrophages, renal cell carcinoma, prognosis, tumor immune microenvironment, machine learning

Published Open-Access

yes

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