Metabolic plasticity in CLL: adaptation to the hypoxic niche
Open accessAbstract
Metabolic transformation in cancer is increasingly well understood. However, little is known about the metabolic responses of cancer cells that permit their survival in different microenvironments. We have used a nuclear magnetic resonance based approach to monitor metabolism in living primary chronic lymphoid leukemia (CLL) cells and to interrogate their real-time metabolic responses to hypoxia. Our studies demonstrate considerable metabolic plasticity in CLL cells. Despite being in oxygenated blood, circulating CLL cells are primed for hypoxia as measured by constitutively low level hypoxia-inducible factor (HIF-1α) activity and modest lactate production from glycolysis. Upon entry to hypoxia we observed rapid upregulation of metabolic rates. CLL cells that had adapted to hypoxia returned to the 'primed' state when re-oxygenated and again showed the same adaptive response upon secondary exposure to hypoxia. We also observed HIF-1α independent differential utilization of pyruvate in oxygenated and hypoxic conditions. When oxygenated, CLL cells released pyruvate, but in hypoxia imported pyruvate to protect against hypoxia-associated oxidative stress. Finally, we identified a marked association of slower resting glucose and glutamine consumption, and lower alanine and lactate production with Binet A0 stage samples indicating that CLL may be divided into tumors with higher and lower metabolic states that reflect disease stage.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Complex real-time and in vivo data require dedicated software to investigate them, and current data collection surpasses capacity to extract and interpret information effectively.
“A limiting factor of the utilization of such unique tools is that complex real-time and in vivo data require dedicated software to investigate them, however nowadays this surge in data collection surpasses the current capacity to extract and interpret information effectively and computational tools are emerging.150–152”
From Connecting metabolome and phenotype: recent advances in functional metabolomics tools for the identification of bioactive natural products (2024) · cites this paper as [150]
The Materials and methods section (‘NMR time-course data analysis’; page unavailable) describes using several software packages to process and model real-time NMR data. It does not address in vivo data or say that data collection has outpaced the capacity to extract and interpret information; the Discussion describes the work as ex vivo. (LLM, conf=0.85)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 23 · Cited by 91
- Authors
- Koczula, K. M., Ludwig, C., Hayden, R., Cronin, L., Pratt, G., Parry, H., Tennant, D., Drayson, M., Bunce, C. M., Khanim, F. L., & Günther, U. L.
- Affiliations
- University of Birmingham (GB)
- Heartlands Hospital (GB)
- Corresponding author
- Günther, U L
- Venue
- Leukemia
- Published
- 2015-07-23
- Volume
- 30
- Issue
- 1
- Pages
- 65-73
- ISSN
- 0887-6924 (ISSN-L)
- 1476-5551
- PMC
- PMC4705428
- OpenAlex
- W1786044410
- Cited by
- 91
- References
- 23
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 7 · 2023: 6 · 2022: 15 · 2021: 11 · 2020: 13 · 2019: 9 · 2018: 10 · 2017: 4 · 2016: 7 · 2015: 1
- FWCI
- 2.43
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Leukemia (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- University of Birmingham Research Portal (University of Birmingham) (publishedVersion, cc-by)
- Funders
- FP7 People: Marie-Curie Actions (FP7-PEOPLE-2010-ITN)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
- Health Sciences › Medicine › Genetics › Chronic Lymphocytic Leukemia Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Keywords
- chronic lymphocytic leukemia, cancer metabolism, metabolic plasticity, hypoxia, hypoxia-inducible factor-1α, glycolysis, lactic acid production, pyruvate utilization, oxidative stress, glucose utilization, glutamine consumption, alanine production, disease stage, tumor microenvironment
- MeSH terms
- Adaptation, Physiological, Citric Acid Cycle, Humans, Magnetic Resonance Spectroscopy, Leukemia, Lymphocytic, Chronic, B-Cell, Cell Hypoxia, Pyruvic Acid, Hypoxia-Inducible Factor 1, alpha Subunit, Cell Cycle Checkpoints
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review