NNMT-associated metabolic-thromboinflammatory-immune co-activation in heterogeneous CTC clusters: a hypothesis-generating computational framework".

BACKGROUND: Heterogeneous circulating tumor cell (CTC) clusters interact with platelets, neutrophils, stromal cells, and immune cells, forming a protective state that may facilitate survival in the circulation and metastatic dissemination. Nicotinamide N-methyltransferase (NNMT) is associated with metabolic reprogramming, stromal activation, epithelial-mesenchymal plasticity, and immune suppression. However, its coordinated relationship with platelet/coagulation, neutrophil/ neutrophil extracellular trap (NET), and immune exhaustion programs in CTC-associated states has not been systematically evaluated. Therefore, we constructed a hypothesis-generating framework integrating mechanistic evidence, pan-cancer computational analyses, and single-cell transcriptomic analyses. METHODS: We performed a mechanistic evidence synthesis combined with TCGA PanCancer bulk RNA-seq analysis and cross-dataset evaluation of eight publicly available multi-cancer single-cell RNA-seq cohorts. Module scores were constructed for metabolic/EMT, platelet/coagulation, neutrophil/NET, immune checkpoint/exhaustion, and cytotoxic/NK cell programs. Correlation analyses across cancer types, feature-level pseudotime analysis, ligand- receptor mapping, and in silico perturbation simulations were applied to evaluate associations between NNMT and the composite tri-axial state. In addition, exploratory supervised machine learning models were used to determine whether axis-related features and ligand-receptor features could discriminate single CTCs from clustered or leukocyte-associated CTC states. Leave-one-cancer-out cross-validation was further used to assess the reproducibility of axis- associated survival risk across cancer types. No new experimental, animal, or clinical intervention data were generated. RESULTS: Across 483,590 cells from eight publicly available single-cell datasets, NNMT expression was positively correlated with the composite tri-axial score across multiple cancer contexts. Feature-level pseudotime analysis indicated convergence of NNMT-associated metabolic, platelet/coagulation, neutrophil/NET, and immune exhaustion programs toward a common trajectory endpoint, although this analysis does not establish temporal causality. In silico NNMT perturbation preferentially implicated stromal and fibroblast-like populations as candidate responsive compartments. Ligand-receptor analyses further suggested an interconnected communication network involving CTC/epithelial and CAF/endothelial compartments, platelet/coagulation bridging, myeloid/NET recruitment, and downstream T/NK cell exhaustion. CONCLUSION: These integrated findings support NNMT-associated metabolic-thromboinflammatory-immune co-activation as a candidate feature of heterogeneous CTC-associated states and provide mechanistic rationale for a "disaggregation-exposure-clearance" strategy combining αIIbβ3 inhibition, NNMT inhibition, and PD-1/PD-L1 blockade.