Journal
CANCER RESEARCH
Volume 77, Issue 7, Pages 1564-1574Publisher
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/0008-5472.CAN-16-2074
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Funding
- Frontiers Center NSF grant [PHY-1427654]
- NSF [DMS-1361411]
- Cancer Prevention and Research Institute of Texas (CPRIT) grants [R1110, R1111]
- Keck Center for Interdisciplinary Bioscience Training of the Gulf Coast Consortia (CPRIT Grant) [RP140113]
- National Institutes of Health [R01-GM067801, R01-GM116280]
- Welch Foundation [Q-1512]
- Tauber Family Funds
- Maguy-Glass Chair in Physics of Complex Systems
- National Cancer Institute (NCI) grants [R21CA173150, R21CA179720]
- Direct For Mathematical & Physical Scien
- Division Of Physics [1427654] Funding Source: National Science Foundation
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1361411] Funding Source: National Science Foundation
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Abnormal metabolism is a hallmark of cancer, yet its regulation remains poorly understood. Cancer cells were considered to utilize primarily glycolysis for ATP production, referred to as the Warburg effect. However, recent evidence suggests that oxidative phosphorylation (OXPHOS) plays a crucial role during cancer progression. Here we utilized a systems biology approach to decipher the regulatory principle of glycolysis and OXPHOS. Integrating information from literature, we constructed a regulatory network of genes and metabolites, from which we extracted a core circuit containing HIF-1, AMPK, and ROS. Our circuit analysis showed that while normal cells have an oxidative state and a glycolytic state, cancer cells can access a hybrid state with both metabolic modes coexisting. This was due to higher ROS production and/or oncogene activation, such as RAS, MYC, and c-SRC. Guided by the model, we developed two signatures consisting of AMPK and HIF-1 downstream genes, respectively, to quantify the activity of glycolysis and OXPHOS. By applying the AMPK and HIF-1 signatures to The Cancer Genome Atlas patient transcriptomics data of multiple cancer types and single-cell RNA-seq data of lung adenocarcinoma, we confirmed an anticorrelation between AMPK and HIF-1 activities and the association of metabolic states with oncogenes. We propose that the hybrid phenotype contributes to metabolic plasticity, allowing cancer cells to adapt to various microenvironments. Using model simulations, our theoretical framework of metabolism can serve as a platform to decode cancer metabolic plasticity and design cancer therapies targeting metabolism.
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