bioRxivSystems BiologyPreprint
Metabolic Reprogramming and Therapeutic Vulnerabilities in the Tumor Microenvironment Revealed by Multi-scale Network Geometry
Handan ÇetiniD, Paul BogdaniD, Shannon M. MumenthaleriD, Stacey D. FinleyiD
Abstract
The tumor microenvironment comprises diverse cell populations that coordinate metabolic activities to sustain malignant growth, yet the systems-level organization of these interactions remains poorly understood. Here, we present an integrated framework combining single-cell transcriptomics, genome-scale metabolic modeling, and multi-scale network geometry to decode metabolic coordination in colorectal cancer. We demonstrate that FAP+ cancer-associated fibroblasts and MARCO+ tumor-associated macrophages undergo extensive reprogramming, establishing metabolic division of labor: fibroblasts specialize in amino acid and fatty acid metabolism while macrophages adopt cancer-like nucleotide biosynthesis programs. Systematic knockout analysis identified 19 tumor-selective vulnerabilities in branched-chain amino acid catabolism, with MAOB validated as a prognostic marker through patient survival analysis. To reveal architectural organization, we applied multifractal geometric characterization and Ollivier-Ricci curvature analysis for the first time to flux-weighted metabolic networks derived from context-specific genome-scale models. While conventional network metrics failed to distinguish tumor from normal phenotypes, multifractal analysis successfully separated tissue states through coordinated architectural changes across hierarchical scales. Role transition analysis revealed that 20-25% of metabolites undergo functional reorganization, with prostaglandin and bile acid derivatives emerging as critical communication hubs between stromal populations. Curvature analysis identified pathway-specific geometric remodeling in fatty acid metabolism (fibroblasts) and leukotriene metabolism (macrophages). Our findings establish that metabolic adaptation represents ecosystem-level network reorganization rather than isolated pathway changes, providing a generalizable framework for identifying therapeutic strategies targeting cooperative metabolic networks.
- organism: human
- assay: scRNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- approach: matrix factorization
- Citations
- 0
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