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bioRxiv · 10.64898/2026.04.05.715441

A Spin-Glass Metabolic Hamiltonian optimized by Quantum Annealing Reveals Thermodynamic Phases of Cancer Metabolism

Sung, J.-Y.·Baek, K.·Park, I.·Bang, J.·Cheong, J.-H.
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Abstract

Understanding why specific metabolic states become stable in cancer has remained a fundamental challenge, as current pathway-centric frameworks lack a unifying physical principle governing global metabolic organization. We introduce the Metabolic Spin-Glass (MSG) model, which represents cellular metabolism using a thermodynamically informed effective Hamiltonian that integrates reference reaction free energies, cofactor-mediated network couplings, and patient-specific transcriptomic fields within a frustrated many-body optimization framework. The Hamiltonian is formulated as a binary optimization problem and solved using hybrid quantum annealing. Embedding gastric cancer transcriptomes (n = 497) reveals that malignant phenotypes occupy distinct low-energy configurations within the effective metabolic landscape rather than representing isolated pathway perturbations. A thermodynamic order parameter stratifies patients into prognostically distinct subtypes independently of transcriptomic classification, suggesting clinically applicable non-redundant biomarkers. This work establishes a thermodynamically informed spin-glass energy-landscape framework for patient-specific characterization and stratification of cancer metabolic organization.

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Sung, J.-Y., Baek, K., Park, I., Bang, J., Cheong, J.-H.. 2026-04-07. A Spin-Glass Metabolic Hamiltonian optimized by Quantum Annealing Reveals Thermodynamic Phases of Cancer Metabolism. https://doi.org/10.64898/2026.04.05.715441

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