A Dynamic Metabolic Flux Analysis of Myeloid-Derived Suppressor Cells Confirms Immunosuppression-Related Metabolic Plasticity
Bibliographic record
Abstract
Recent years have witnessed an increasing interest at understanding the role of myeloid-derived suppressor cells (MDSCs) in cancer-induced immunosuppression, with efforts to inhibit their maturation and/or their activity. We have thus modelled MDSCs central carbon metabolism and bioenergetics dynamic, calibrating the model using experimental data on in vitro matured mice bone marrow cells into MDSCs. The model was then used to probe the cells metabolic state and dynamics, performing a dynamic metabolic flux analysis (dMFA) study. Indeed, MDSCs maturation correlates with a high glycolytic flux contributing to up to 95% of the global ATP turnover rate, while most of the glucose-derived carbon enters the TCA cycle. Model simulations also reveal that pentose phosphate pathway and oxidative phosphorylation activities were kept at minimal levels to ensure NADPH production and anabolic precursors synthesis. Surprisingly, MDSCs immunosuppressive activity, i.e. L-arginine uptake, metabolism and endogenous synthesis, only consumes sparse quantities of energy-rich nucleotides (ATP and NADPH). Therefore, model simulations suggest that MDSCs exhibit a heterogeous metabolic profile similar to tumour cells. This behavior is probably an indirect immunosuppressive mechanism where MDSCs reduce the availability of carbon sources in the tumour periphery microenvironment, which could explain the dysfuntion and death of immune effector cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".