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Peer-reviewedCC BY-NCDrug design, development and therapy

Metabolic State Machines and Nutritional Ecology: A New Framework for Osteosarcoma Therapy.

  • Shukai Yang1,2
  • Houlin Li3
  • Bingqi Mo2
  • Zhuming Chen4
  • Hao Lin1,2
4 affiliations
  1. 1The First Clinical Medical School of Jinan University, Jinan University, Guangzhou, Guangdong, 510632, People's Republic of China.
  2. 2Department of Orthopedics, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, 524023, People's Republic of China.
  3. 3Guangdong-Hong Kong-Macau Institute of CNS Regeneration (GHMICR), Jinan University, Guangzhou, Guangdong, 510632, People's Republic of China.
  4. 4Department of Orthopedics, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, 524003, People's Republic of China.
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Abstract

Osteosarcoma is the most common primary malignant bone tumor of children and adolescents, yet survival has plateaued for four decades despite surgery and multi-agent chemotherapy. This review argues that the clinically decisive feature of osteosarcoma metabolism is not a fixed commitment to glycolysis or to oxidative phosphorylation, but the capacity to move between metabolic states under hypoxia, acidosis, nutrient fluctuation, and treatment stress. We develop two connected frameworks. The first is a metabolic state machine, in which metabolic phenotypes are treated as stress-responsive states that are coupled to chemoresistance, radioresistance, metastatic adaptation, immune escape, and ferroptosis vulnerability. The second is a nutritional ecology of the bone microenvironment, which explains how stromal and immune cells exchange and compete for lactate, amino acids, and other substrates, and why blocking a single metabolic node is usually compensated. We then map the principal actionable modules, including lactate transport, nucleotide and serine metabolism, redox homeostasis, ferroptosis, and therapy-induced immunometabolic escape, onto candidate stratifiers and pharmacodynamic readouts. The framework is intended less as a catalogue of enzymes than as a practical route to state-matched, dynamically monitored combination therapy.

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Cite

BibTeXRIS
BibTeX
@article{yang2026metabolic,
  title = {{Metabolic State Machines and Nutritional Ecology: A New Framework for Osteosarcoma Therapy.}},
  author = {Shukai Yang and Houlin Li and Bingqi Mo and Zhuming Chen and Hao Lin},
  journal = {Drug design, development and therapy},
  year = {2026},
  month = oct,
  doi = {10.2147/dddt.s639878},
  url = {https://europepmc.org/article/MED/42953799},
  note = {CC BY-NC},
}
RIS
TY  - JOUR
TI  - Metabolic State Machines and Nutritional Ecology: A New Framework for Osteosarcoma Therapy.
AU  - Shukai Yang
AU  - Houlin Li
AU  - Bingqi Mo
AU  - Zhuming Chen
AU  - Hao Lin
PY  - 2026
DA  - 2026/10/24
JO  - Drug design, development and therapy
DO  - 10.2147/dddt.s639878
UR  - https://europepmc.org/article/MED/42953799
AB  - Osteosarcoma is the most common primary malignant bone tumor of children and adolescents, yet survival has plateaued for four decades despite surgery and multi-agent chemotherapy. This review argues that the clinically decisive feature of osteosarcoma metabolism is not a fixed commitment to glycolysis or to oxidative phosphorylation, but the capacity to move between metabolic states under hypoxia, acidosis, nutrient fluctuation, and treatment stress. We develop two connected frameworks. The first is a metabolic state machine, in which metabolic phenotypes are treated as stress-responsive states that are coupled to chemoresistance, radioresistance, metastatic adaptation, immune escape, and ferroptosis vulnerability. The second is a nutritional ecology of the bone microenvironment, which explains how stromal and immune cells exchange and compete for lactate, amino acids, and other substrates, and why blocking a single metabolic node is usually compensated. We then map the principal actionable modules, including lactate transport, nucleotide and serine metabolism, redox homeostasis, ferroptosis, and therapy-induced immunometabolic escape, onto candidate stratifiers and pharmacodynamic readouts. The framework is intended less as a catalogue of enzymes than as a practical route to state-matched, dynamically monitored combination therapy.
SN  - 1177-8881
ER  -