Metabolite-mediated communication reshapes macrophages in hepatocellular carcinoma: single-cell and bulk evidence
Year: 2026
Type: preprint
Abstract: Background This study characterized metabolite-mediated cell-cell communication (mCCC) in the hepatocellular carcinoma (HCC) tumor microenvironment and identified genes with potential therapeutic relevance. Methods : Single-cell and bulk RNA sequencing datasets were analyzed. MEBOCOST was used to infer mCCC networks, followed by high-dimensional weighted gene co-expression network analysis in the main receiver cell type. Candidate genes were obtained by intersecting receiver-related module genes with upregulated differentially expressed genes, then refined using five machine-learning algorithms and cross-cohort validation. Functional analyses included gene set enrichment analysis, immune infiltration profiling, pseudotime analysis, molecular docking, and 100 ns molecular dynamics simulations. Results : Macrophages were identified as the predominant mCCC receiver population, with iron, farnesyl pyrophosphate, and L-glutamine among the prominent signaling metabolites. A co-expression module of 666 genes most strongly correlated with macrophages was identified, and intersection with upregulated DEGs yielded 22 candidate genes. Cross-cohort validation narrowed the machine learning consensus to SNX27 and PEA15 as key genes. Both were negatively enriched in fatty acid metabolism and functionally linked to apoptotic signaling components. Their expression was inversely correlated with infiltration of multiple immune cell populations. SNX27 expression was progressively upregulated along the macrophage differentiation trajectory. Trabectedin exhibited favorable binding affinities for SNX27 (− 10.2 kcal/mol) and PEA15 (− 9.7 kcal/mol), and both complexes maintained stable conformations over 100 ns MD simulations. Conclusion : These findings suggest that SNX27 and PEA15 may link metabolite-mediated signaling to macrophage-associated remodeling in HCC, and provided preliminary bioinformatic support for further experimental investigation.
Source: Research Square
Authors: Jianfei Shi, Hua Zhang, Xin Han, Jinfeng Wang, Fei Yin
Institution: Fourth Hospital of Hebei Medical University
Language: English
Topic: Immune cells in cancer
Subfield: Immunology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7225426472