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Metabolomics in cancer research and emerging applications in clinical oncology.
Literature Information
| DOI | 10.3322/caac.21670 |
|---|---|
| PMID | 33982817 |
| Journal | CA: a cancer journal for clinicians |
| Impact Factor | 232.4 |
| JCR Quartile | Q1 |
| Publication Year | 2021 |
| Times Cited | 338 |
| Keywords | cancer, intracellular, metabolism, metabolomics |
| Literature Type | Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't, Review |
| ISSN | 0007-9235 |
| Pages | 333-358 |
| Issue | 71(4) |
| Authors | Daniel R Schmidt, Rutulkumar Patel, David G Kirsch, Caroline A Lewis, Matthew G Vander Heiden, Jason W Locasale |
TL;DR
This paper reviews the intricate relationship between cancer, its therapies, and metabolism, emphasizing the role of metabolomics in understanding these interactions at both cellular and systemic levels. It highlights current technologies for metabolite analysis and explores the potential of metabolomics to enhance cancer diagnosis, monitoring, and treatment in clinical settings.
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cancer · intracellular · metabolism · metabolomics
Abstract
Cancer has myriad effects on metabolism that include both rewiring of intracellular metabolism to enable cancer cells to proliferate inappropriately and adapt to the tumor microenvironment, and changes in normal tissue metabolism. With the recognition that fluorodeoxyglucose-positron emission tomography imaging is an important tool for the management of many cancers, other metabolites in biological samples have been in the spotlight for cancer diagnosis, monitoring, and therapy. Metabolomics is the global analysis of small molecule metabolites that like other -omics technologies can provide critical information about the cancer state that are otherwise not apparent. Here, the authors review how cancer and cancer therapies interact with metabolism at the cellular and systemic levels. An overview of metabolomics is provided with a focus on currently available technologies and how they have been applied in the clinical and translational research setting. The authors also discuss how metabolomics could be further leveraged in the future to improve the management of patients with cancer.
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Primary Questions Addressed
- How can metabolomics be integrated with existing imaging techniques for enhanced cancer diagnosis?
- What are the potential challenges in translating metabolomics findings from research into clinical practice for oncology?
- In what ways might metabolomics contribute to personalized medicine approaches in cancer treatment?
- How do changes in tumor microenvironment affect the metabolic profiles observed in cancer patients?
- What emerging technologies in metabolomics could revolutionize the monitoring of therapeutic responses in oncology?
Key Findings
Research Background and Purpose
Cancer significantly alters metabolic processes, impacting both cancer cell metabolism and normal tissue metabolism. With advancements in imaging techniques like fluorodeoxyglucose-positron emission tomography (FDG-PET), there is a growing interest in utilizing metabolomics for cancer diagnosis, monitoring, and therapy. This review aims to explore the interactions between cancer, cancer therapies, and metabolism, highlighting the role of metabolomics in understanding and managing cancer.
Main Methods/Materials/Experimental Design
The review discusses various metabolomics technologies and their applications in clinical and translational research. The methodological framework includes:
- Overview of Metabolomics: Introduction to the field and its significance in cancer research.
- Metabolomics Technologies: Detailed discussion of technologies such as mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy.
- Clinical Applications:
- Cancer Diagnosis: Utilizing metabolomic profiles for identifying cancer types.
- Monitoring Treatment Response: Tracking metabolic changes to assess treatment efficacy.
- Translational Research:
- Therapeutic Target Identification: Discovering new targets for therapy through metabolic pathways.
- Personalized Medicine: Tailoring treatment strategies based on individual metabolic profiles.
Key Results and Findings
- Metabolomics provides a comprehensive view of metabolic alterations in cancer, revealing insights that traditional imaging may miss.
- Specific metabolites have been identified as biomarkers for various cancer types, enhancing diagnostic accuracy.
- The integration of metabolomics with other -omics technologies could improve understanding of cancer biology and treatment responses.
Main Conclusions/Significance/Innovation
The review emphasizes the potential of metabolomics as a transformative tool in cancer management. By elucidating metabolic changes associated with cancer, metabolomics can lead to better diagnostic methods, improved monitoring of treatment responses, and the development of personalized therapeutic strategies. The innovation lies in the ability to leverage metabolic data for clinical decision-making, which may enhance patient outcomes.
Research Limitations and Future Directions
While the review presents a promising outlook on the application of metabolomics in cancer, several limitations are acknowledged:
- Variability in metabolomic data due to sample handling, processing, and analysis techniques.
- The need for standardization in metabolomics methodologies to ensure reproducibility and reliability of results.
Future directions include:
- Expanding the use of metabolomics in clinical trials to validate findings and establish clinical utility.
- Integrating metabolomics with genomic and proteomic data to create a holistic understanding of cancer biology.
- Exploring the role of metabolomics in predicting treatment responses and resistance mechanisms.
| Aspect | Current Status | Future Directions |
|---|---|---|
| Methodologies | Diverse techniques (mass spectrometry, NMR) | Standardization and validation in clinical settings |
| Clinical Applications | Diagnostic biomarkers identified | Broader integration in treatment protocols |
| Research Integration | Limited integration with other -omics | Holistic approaches combining multiple data types |
| Challenges | Data variability and reproducibility issues | Development of robust analytical frameworks |
This structured summary captures the essence of the review, emphasizing the importance of metabolomics in cancer research and its potential to revolutionize patient management.
References
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Literatures Citing This Work
- Knockout of Putative Tumor Suppressor Aldh1l1 in Mice Reprograms Metabolism to Accelerate Growth of Tumors in a Diethylnitrosamine (DEN) Model of Liver Carcinogenesis. - Natalia I Krupenko;Jaspreet Sharma;Halle M Fogle;Peter Pediaditakis;Kyle C Strickland;Xiuxia Du;Kristi L Helke;Susan Sumner;Sergey A Krupenko - Cancers (2021)
- Early screening and diagnosis strategies of pancreatic cancer: a comprehensive review. - Jinshou Yang;Ruiyuan Xu;Chengcheng Wang;Jiangdong Qiu;Bo Ren;Lei You - Cancer communications (London, England) (2021)
- Primary Aldosteronism: Metabolic Reprogramming and the Pathogenesis of Aldosterone-Producing Adenomas. - Siyuan Gong;Martina Tetti;Martin Reincke;Tracy Ann Williams - Cancers (2021)
- LC-MS Based Metabolomics Study of the Effects of EGCG on A549 Cells. - Tingyu Pan;Di Han;Yong Xu;Wenpan Peng;Le Bai;Xianmei Zhou;Hailang He - Frontiers in pharmacology (2021)
- Colony Stimulating Factor-1 and its Receptor in Gastrointestinal Malignant Tumors. - Hong-Wu Li;Shi-Lei Tang - Journal of Cancer (2021)
- Integrating Whole Blood Transcriptomic Collection Procedures Into the Current Anti-Doping Testing System, Including Long-Term Storage and Re-Testing of Anti-Doping Samples. - Giscard Lima;Alexander Kolliari-Turner;Fernanda Rossell Malinsky;Fergus M Guppy;Renan Paulo Martin;Guan Wang;Sven Christian Voss;Costas Georgakopoulos;Paolo Borrione;Fabio Pigozzi;Yannis Pitsiladis - Frontiers in molecular biosciences (2021)
- Unravelling the Anticancer Mechanisms of Traditional Herbal Medicines with Metabolomics. - Omolola R Oyenihi;Ayodeji B Oyenihi;Joseph O Erhabor;Motlalepula G Matsabisa;Oluwafemi O Oguntibeju - Molecules (Basel, Switzerland) (2021)
- Optimizing Adaptive Therapy Based on the Reachability to Tumor Resistant Subpopulation. - Jiali Wang;Yixuan Zhang;Xiaoquan Liu;Haochen Liu - Cancers (2021)
- Cancer-A Major Cardiac Comorbidity With Implications on Cardiovascular Metabolism. - Daniel Finke;Markus B Heckmann;Norbert Frey;Lorenz H Lehmann - Frontiers in physiology (2021)
- Metabolomics in Autoimmune Diseases: Focus on Rheumatoid Arthritis, Systemic Lupus Erythematous, and Multiple Sclerosis. - Naeun Yoon;Ah-Kyung Jang;Yerim Seo;Byung Hwa Jung - Metabolites (2021)
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