Applications | Oncology
Cancer and Metabolism
Explore the power of metabolomics to discover its potential in advancing oncology research.
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Metabolomics in Oncology
Disrupted cellular metabolism is a key feature of cancer cells. In 1923, Otto Warburg observed that they consume 200 times more glucose than normal cells. More recently, in 2011, Doug Hanahan and Bob Weinberg added “cellular energetics,” later renamed “reprogramming cellular metabolism” to their original list of six hallmarks of cancer. Cancer has numerous effects on metabolism, including rewiring of intracellular metabolism, rewiring of the tumor microenvironment, and changes in the metabolism of normal tissues . Metabolism in cancer is further affected by treatment, diet, and physical activity.
Metabolomics is the global analysis of small molecules that provide vital information about the machinery of the cancer cells and environment that can be difficult to acquire. Metabolomics, when performed and analyzed correctly, gives a read-out of the phenotype that is the result of interactions between exposures, treatments, and all other factors that can alter DNA and RNA functionality, as well as protein activity. Integrating metabolomics in to oncology research provides insight not only into the cellular and microenvironment metabolism, but also informs feedback loops, epigenetic influences, treatment and efficacy solutions and biomarker discovery. Sometimes, metabolomics may be the most sensitive method to identify pathogenic variants, as minute changes in protein structure or its expression levels can result in significant changes in its activity causing alterations to metabolite levels.
Uncover Functional, Actionable Insights with Metabolomics
Cancer is a complex set of diseases requiring a greater understanding of the complex molecular interactions that impact disease risk, development, and progression. Metabolon can help oncology researchers unravel complex genotype-phenotype associations and identify promising diagnostic and therapeutic biomarkers with our global and targeted metabolite panels.
Cancer Risk Assessment
Metabolomics can help assess cancer risk by providing valuable insights into the intricate biochemical changes associated with malignancies. By analyzing the small molecules and enzymatic products within cells and body fluids, metabolomics enables researchers to detect early alterations in biological pathways that may be indicative of cancer development and disease progression. The integration of metabolomics data with other clinical and genetic information enhances our ability to predict and stratify cancer risk, ultimately facilitating more targeted and personalized strategies for cancer prevention and early intervention. With its potential to revolutionize cancer risk assessment, metabolomics holds great promise in advancing our understanding of cancer biology and improving patient outcomes.
Zhong H, Liu S, Zhu J, Wu L. Associations between genetically predicted levels of blood metabolites and pancreatic cancer risk. Int J Cancer. 2023; 153(1): 103-110. doi:10.1002/ijc.34466
Yang M, Zhu C, Du L, et al. A Metabolomic Signature of Obesity and Risk of Colorectal Cancer: Two Nested Case–Control Studies. Metabolites. 2023; 13(2):234. https://doi.org/10.3390/metabo13020234
Monitor Treatment Response
Metabolomics plays a pivotal role in monitoring treatment response in oncology, offering a nuanced understanding of the intricate metabolic alterations occurring both within cancer cells and systemically during therapy. Metabolomics can identify biomarkers, distinguish responders from non-responders, and characterize resistance mechanisms. This information is instrumental in refining treatment strategies, personalizing patient care, and ultimately improving the overall outcomes in the fight against cancer.
Zapater-Moros A, Díaz-Beltrán L, Gámez-Pozo A, et al. Metabolomics unravels subtype-specific characteristics related to neoadjuvant therapy response in breast cancer patients. Metabolomics. 2023/06/21 2023;19(7):60. doi:10.1007/s11306-023-02024-8
Jalota A, Hershberger CE, Patel MS, et al. Host metabolome predicts the severity and onset of acute toxicities induced by CAR T-cell therapy. Blood Advances. 2023/09/12/ 2023;7(17):4690-4700. doi:https://doi.org/10.1182/bloodadvances.2022007456
Prognostic assessment
Prognostic assessment using metabolomics in oncology holds significant promise for improving our ability to predict the likely course of a patient’s disease, enabling more informed clinical decisions and personalized treatment plans. Metabolomics can help predict disease progression, survival outcomes, treatment response, and risk of recurrence. Metabolomics enhances prognostic assessment in oncology by providing valuable information about the metabolic characteristics of tumors, their environment and systemic implications. This knowledge is instrumental in predicting disease outcomes, tailoring treatment plans, and improving the overall management of cancer patients by moving towards a more personalized and precise approach to oncology care.
Scott AJ, Correa LO, Edwards DM, et al. Metabolomic Profiles of Human Glioma Inform Patient Survival. Antioxid Redox Signal. 2023;39(13-15):942-956. doi:10.1089/ars.2022.0085
Metabolomics Applications for Oncology Research
- EBiomarker discovery
- EPersonalized medicine research
- EDisease risk assessment
- EMonitoring treatment response
- EPrediction of disease progression
- EDrug discovery and development
- EUnderstanding tumor physiology
- EEarly detection of altered pathways
- ECharacterize disease resistance mechanisms
“Metabolomics has emerged as a promising tool to find circulating metabolites associated with breast cancer risk.”
Stevens, V.L., Carter, B.D., Jacobs, E.J. et al.
A prospective case–cohort analysis of plasma metabolites and breast cancer risk. Breast Cancer Res. 2022;25(5).https://doi.org/10.1186/s13058-023-01602-x Available under CC BY 4.0.
Metabolomics Insights into Oncology
Busulfan is a chemotherapy drug used to treat certain types of cancer, including chronic myeloid leukemia (CLM) and some types of non-Hodgkin’s lymphoma. Many patients also receive high-dose busulfan as part of a conditioning regimen before a bone marrow transplant. Busulfan works by killing fast-growing cells, but also affects normal cells that divide quickly—this can lead to side effects such as low blood counts, nausea, and diarrhea. Pharmacokinetic (PK)-guided busulfan dosing strategies aim to achieve a target therapeutic level of the drug in the patient’s bloodstream while minimizing toxicity. Although PK-guided busulfan dosing is considered an effective way to ensure optimal busulfan efficacy, this process is resource-intensive, labor-intensive, and time-sensitive. Thus, alternative approaches are needed to determine the appropriate busulfan dose for each patient. Metabolomics could improve or ideally replace PK-guided busulfan dosing to achieve the desired therapeutic effect while minimizing the risk of toxicity.
Figure 1. Working hypothesis for the pathways associated with busulfan clearance. Our working hypothesis is that glutathione metabolism (yellow box) continues to be central to busulfan clearance. We confirmed our prior findings of the association of the glycine, serine, and threonine pathway (red box) and bile acids (green box) with busulfan clearance. The impact of mitochondrial dysfunction (blue box) and reactive oxygen species was also found.
The Global Discovery Panel helped this research group develop a more efficient method of estimating busulfan clearance. Metabolon data enabled the identification of liquid biospy drug clearance predictive markers. By correlating plasma metabolites and clinical data , 13 endogenous metabolomic compounds, including urate, mannonate, lysine, cortisone, and cortisol, could accurately predict the clearance of intravenous busulfan, particularly in patients with slow clearance. These results demonstrate that metabolomics can guide busulfan dosage to ensure that each patient receives the appropriate dosing. The study shows that metabolomics can be leveraged to optimize drug dosing.
McCune JS, Navarro SL, Baker KS, et al. Prediction of Busulfan Clearance by Predose Plasma Metabolomic Profiling. Clin Pharmacol Ther. 2023;113(2):370-379. doi:10.1002/cpt.2794. Available under CC BY 4.0.
Oncology Publications and Citations
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Dive deeper by viewing our case studies and webinars. Learn more about how Metabolon furthers oncology research and check back for more to stay up to date on the latest developments in metabolomics in oncology.
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