Related Experiment Video
Updated: May 19, 2026
Cancer-Associated Fibroblasts from Mouse Mammary Tumors as Tools for Molecular and Computational Studies
Published on: July 3, 2025
Integrating Bulk and Single-Cell RNA-Seq Reveals Glycolysis-Associated Macrophages and Its Related Tumor Subgroup
Yang Li1, Yuan Chen1,2, Ling Wang3
1Department of Geriatric Medicine, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, China.
Background:
Clear cell renal cell carcinoma (ccRCC) is the most common histological type of RCC and is marked by aggressive nature and poor survival. However, therapeutic options remain limited and yield suboptimal outcomes. Macrophages exhibit marked heterogeneity within ccRCC, exerting a substantial impact on the malignant progression of tumors and resistance to therapeutics.
Methods:
This study utilized single-cell sequencing and transcriptomics to identify a subset of macrophages associated with glycolysis and the most interactive tumor subpopulation, in order to explore the link between macrophages and ccRCC risk. Moreover, employing machine learning techniques, we crafted a precise gene signature to predict patient prognosis, with clinical implications.
Results:
We identified a macrophage subpopulation primarily characterized by glycolytic metabolism and a closely associated tumor cell subpopulation, both significantly correlated with poor prognoses in ccRCC patients. Then, we use hdWGCNA to identify key genes and functional modules of cell subgroups, and use 101 types of machine learning methods to establish a prognosis model of six genes: CENPA, ITM2B, TUBA1B, TNFSF13B, SNX3, and TNNT1 in the RNAseq cohorts of ccRCC patients. Patients in the high-risk group exhibited poorer prognoses, with functional enrichment indicating the presence of modules associated with malignant progression. Additionally, immune infiltration analysis revealed higher levels of immune cell infiltration in this group, suggesting their potential responsiveness to immunotherapeutic interventions.
Conclusion:
Our study introduces a novel, robust ccRCC prognostic model, providing new insights and potential therapeutic strategies for precision treatment of ccRCC patients.
