INTRODUCTION AND HISTORICAL PERSPECTIVE
Cancer’s perplexing metabolic sine qua non endures: the Warburg Effect. The Warburg Effect is the shift in cancer cell metabolism to anaerobic glucose metabolism and a stark diminishment of oxidative metabolism. This phenomenon was discovered by Otto Warburg, for which, in part, he received a Nobel prize in 1931. Fermentation, the primary mode of cancer metabolism, generates lactate from glycolysis, with greatly reduced oxidative metabolism to carbon dioxide.
The enigma is that glycolysis to lactate produces only 2 molecules of ATP per glucose molecule versus more than ten times that amount for oxidative metabolism – a seeming paradox for rapidly growing cancer cells. An early hypothesis of mitochondrial damage has been largely disproven, other than for a small number of oxidative enzyme mutations. The Warburg Effect is manifested by increased glycolytic enzymes and glucose transporter number, forming the basis of cancer imaging using 18F-FDG PET scanning, now ubiquitous throughout cancer staging and therapy monitoring.
WHY RAPID GROWTH FAVORS FERMENTATION
The rapid growth rate of cancer is, however, significantly aided by the shunting of glycolytic carbon-carbon bond intermediates into nucleic acids, fatty acids, and other essential cellular building blocks – yet ATP-generated energy remains essential for growth and spread. A recent PNAS article entitled The Warburg Effect is the result of faster ATP production by glycolysis than respiration by Kukurugya, Rosset, and Titov provides radical new insight into the Warburg puzzle. Here, the investigators used a combined modeling and experimental approach to show that cancer generates faster ATP synthesis by “switching from high-yielding respiration to faster glycolysis when excess glucose is available and respiration rate becomes limited by proteome occupancy”.
Thus, even though oxidation is more efficient at producing ATP compared to fermentation, the intrinsic production rate of ATP is greater with fermentation, resulting in more ATP production per time under the Warburg Effect. The theoretical model incorporates 5 inputs, experimentally determined parameters: the ATP yield for glycolysis and respiration (oxidation); the specific activity of glycolysis and respiration; and the fraction of the proteome occupied by ATP-producing enzymes. This last parameter is important since the relative occupancy of a cancer cell by proteins, ATP-producing and others, is finite, that is, if the glycolytic enzyme proteome increases then the oxidative proteome must decrease, all else equal; the cell reaches an optimum equilibrium for maximum fitness.
"This progression can be increasingly catalyzed by, and coupled to, advancements in molecular imaging - as will be the case for metabolic treatments." Dr. J. James Frost, President & Founder www.BioMolecularImaging.com
HOW GLUCOSE AVAILABILITY INFLUENCES METABOLIC CHOICE
The model permits the estimation of glycolysis versus respiration as a function of the glucose availability. At low glucose uptake “respiration proves beneficial when glucose is limited as it maximizes ATP production per glucose molecule”. At higher glucose uptake and “when the proteome allocation to ATP-producing enzymes is filled by respiratory enzymes, glycolysis can be substituted for respiration to further increase the ATP production rate since it generates ATP more rapidly per unit of protein”, thus demonstrating important limitations based on proteome fraction. The model also handles intermediate glucose availability, as shown in the multiple simulation figures. The proteome constraint is critical because without it the cell “would always be able to express more respiratory proteins to increase ATP production without compromising on ATP yield”. In addition to mammalian cells, the metabolism of E. coli and S. cerevisiae were also addressed as they have similar Warburg Effect-like switches.
CLINICAL AND EXPERIMENTAL IMPLICATIONS
There are many more intriguing aspects of this publication, including the role of cellular growth rate versus glucose availability in driving the onset of the Warburg Effect. It is an excellent theoretical and conceptual framework for further elucidation of cancer cell metabolism, perhaps leading to new therapeutic approaches. Indeed, metabolic approaches to cancer therapy have a long, yet rather irregular history. A highpoint was the discovery and clinical implementation of 18F-FDG as a cancer imaging agent based on the high cancer cell uptake and utilization of glucose.
Another was the role of PI3-kinase, a regulator of glucose uptake, in transforming chicken cells. It is, however, noteworthy that many cancers and precancerous lesions have only a modest, often undetectable, elevation of 18F-FDG uptake. An interesting example is the premalignant adenomatous hyperplasias of the lung with the upregulated sodium-dependent glucose transporter 2 that does not transport 18F-FDG. As an alternative, the tracer methyl-4-deoxy-4-[18F]-fluoro-a-D-glucopyranoside is taken up by these cells and can identify low grade adenocarcinomas. Another recent PET tracer is 4-[18F]fluorobenzyl-triphenylphosphonium (18F-BnTP), a membrane potential imaging agent, accumulates in tumors in proportion to their reliance on oxidative phosphorylation.
METABOLIC HETEROGENEITY AND NEW RESEARCH DIRECTIONS
Thereafter in the later 2000’s, empirical data began to show heterogeneity in the metabolic profile of many cancers, including more variable fractions of pure glycolytic versus oxidative metabolism and even enhanced use of oxidative metabolism in metastasizing cells. Still though, the goal of metabolic reprogramming of cancer cells has persisted and clinical trials remain in place to investigate the predictive value of the metabolic profile in tailoring individual patient treatments. Since metabolism is a dynamic process, it is difficult to quantify with pathological assay using biopsy samples alone. Thus, new opportunities for external molecular imaging using PET and other technologies exist if new tracers can be developed.
These might include for IDH, FH, SDH and other oxidative enzymes; the phosphocreatine transporter SLC6A8 and the scavenger receptor B2, factors involved in casting the metabolic phenotype; and oncogenes like MYC, TP53, and KRAS, known to regulate metabolism. Not to be forgotten is the original focus of Otto Warburg that cancer is, in part, a nutritional problem that could be addressed by starving cancer and related interventions. Indeed, there are a number of active clinical trials coupling dietary interventions with cancer treatments (see references below).
TUMOR HETEROGENEITY AND THE MICROENVIRONMENT
Tumor heterogeneity, a primary cancer survival feature through selection based on somatic mutations, is reflected in metabolic heterogeneity. Recent studies using 13C-glucose and other 13C tracers has shown a remarkable diversity of metabolic patterns that, in many cases, correlate with the presence of certain driver oncogenes and with treatment outcomes.
Here, the microenvironment also plays a role where “oncogene-driven expression of nutrient transporters, the ability to derive energy from diverse nutrient sources—including scavenged protein, recycled organelles, and necrotic debris and metabolic cooperativity among cancer cells or between cancer cells and stromal cells likely contribute to tumor cell fitness in stressful tumor microenvironments”. A prevalent viewpoint strongly suggests an expanded role for non-invasive molecular imaging agents: “We need better methods to assess regional metabolic phenotypes in human cancer because inconsistency of metabolic vulnerabilities across a tumor will limit the utility of metabolic therapies”.
IMPACT ON METASTASIS
Metastatic spread requires a different set of metabolic features compared to tumor growth, as “cells navigate a sequence of biological challenges, including escape from the primary tumor, survival in the circulation, colonization of distant organs, and growth into tumors at these remote sites”. Many biological changes, such as acidification of the extracellular space, decreasing the number of cancer cell adherens junctions, activation of proteolytic enzymes to degrade the ECM, and others are well known, yet much less is known about the metabolic correlates of these steps in the progression to metastasis. The epithelial-mesenchymal transition (EMT) is another process with distinct metabolic features. “Oncogene-dependent activation of uridine 5′-diphosphate (UDP)–glucose 6 dehydrogenase (UGDH) depletes UDP-glucose, resulting in enhanced expression of SNAIL—a transcription factor that promotes mesenchymal properties— and increased migration and metastasis in mice”. Several other examples can be studied in the publications below – the majority of which suggest new opportunities for non-invasive molecular imaging technologies.
FUTURE DIRECTIONS AND CONCLUSION
Many established cancer therapies go through periods of conceptual advancements, encouraging early clinical results, disappointing longer-term outcomes, and greater sophistication in the theory and trial design of new treatments of proven benefit to patients. This progression can be increasingly catalyzed by, and coupled to, advancements in molecular imaging - as will be the case for all metabolic treatments. Identification of patients most likely to benefit from metabolic treatments is a distinctly possible benefit of enhanced metabolic molecular imaging. The current PNAS article in focus advances the theory that in turn stimulates the thinking about new therapeutic approaches and their coupled in vivo imaging technologies, eventually leading to new patient therapies, including with diet and novel drug molecules.
REFERENCES
Faubert B, Solmonson A, DeBerardinis RJ. Metabolic reprogramming and cancer progression. Science. 2020; 368. doi: 10.1126/science.aaw5473.
Fendt SM. 100 years of the Warburg effect: A cancer metabolism endeavor. Cell. 2024; 187: 3824-8. doi: 10.1016/j.cell.2024.06.026.
Kukurugya MA, Rosset S, Titov DV. The Warburg Effect is the result of faster ATP production by glycolysis than respiration. Proc Natl Acad Sci U S A. 2024; 121: e2409509121. doi: 10.1073/pnas.2409509121.
Reinfeld BI, Madden MZ, Wolf MM, Chytil A, Bader JE, Patterson AR, Sugiura A, Cohen AS, Ali A, Do BT, Muir A, Lewis CA, Hongo RA, et al. Cell-programmed nutrient partitioning in the tumour microenvironment. Nature. 2021; 593: 282-8. doi: 10.1038/s41586-021-03442-1.
Wang Y, Patti GJ. The Warburg effect: a signature of mitochondrial overload. Trends Cell Biol. 2023; 33: 1014-20. doi: 10.1016/j.tcb.2023.03.013. About BioMolecular Imaging
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