Decoding ecosystem heterogeneity and transcriptional regulation characteristics of multi-subtype renal cell carcinoma

Kailong Xu; Jiang Li; LiWei Qin; Jie Liu; Heng Yang; Gang Dou; LiXin Ma; Yanming Dong; Yang Wang

doi:10.1016/j.heliyon.2024.e33196

Decoding ecosystem heterogeneity and transcriptional regulation characteristics of multi-subtype renal cell carcinoma

Heliyon. 2024 Jun 25;10(13):e33196. doi: 10.1016/j.heliyon.2024.e33196. eCollection 2024 Jul 15.

Authors

Kailong Xu¹, Jiang Li¹, LiWei Qin¹, Jie Liu¹, Heng Yang¹, Gang Dou², LiXin Ma¹, Yanming Dong¹, Yang Wang¹

Affiliations

¹ State Key Laboratory of Biocatalysis and Enzyme Engineering, School of Life Sciences, Hubei University, Wuhan, China.
² College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, China.

Abstract

Background: Renal cell carcinoma (RCC) is characterized by its heterogeneity and the complexity of its tumor microenvironment. This study addresses the need to understand RCC at a cellular level, with a focus on its three main subtypes: clear cell (ccRCC), chromophobe (chRCC), and papillary renal cell carcinoma (pRCC).

Objective: This study aims to comprehensively characterize the cellular diversity and intercellular communication networks of RCC subtypes using scRNA-seq technology. By focusing on macrophages and cancer-associated fibroblasts (CAFs), we seek to reveal their functional states, developmental trajectories, and signaling pathways.

Methodology: We utilized single-cell RNA sequencing (scRNA-seq) data from various kidney cancer subtypes. Advanced analytical techniques, including Uniform Manifold Approximation and Projection (UMAP) and Reactome Gene Set Variation Analysis (ReactomeGSA), were employed to assess cellular heterogeneity and pathway activities. The developmental dynamics of macrophages were studied using CytoTRACE, and cell-to-cell communication was analyzed to identify subtype-specific interaction networks.

Results: Our comprehensive analysis revealed significant cellular diversity within RCC. Distinct macrophage and CAF subpopulations were identified, each exhibiting unique gene expression profiles and pathway activities. Notably, ccRCC showed prominent bidirectional communication between macrophages and CAFs, while chRCC and pRCC displayed disrupted signaling pathways. Metabolic pathway analysis reflected the adaptability of macrophages and CAFs to the tumor microenvironment, and the MIF signaling pathway was identified as a key mediator of cellular interactions.

Conclusion: The study highlights the cellular heterogeneity and the intricate communication networks within RCC subtypes, underscoring the complexity of the tumor microenvironment. Our findings suggest that targeting specific cellular interactions and pathways may offer new avenues for therapeutic intervention in RCC. The unique macrophage and CAF profiles across RCC subtypes provide valuable insights for the development of personalized and targeted treatment strategies.

Keywords: Cancer-associated fibroblasts; Cellular heterogeneity; Macrophages; Renal cell carcinoma; Single-cell RNA sequencing.