Tumour-Derived Glutamate: Linking Aberrant Cancer Cell Metabolism to Peripheral Sensory Pain Pathways
Bibliographic record
Abstract
BACKGROUND: Chronic pain is a major symptom that develops in cancer patients, most commonly emerging during advanced stages of the disease. The nature of cancer-induced pain is complex, and the efficacy of current therapeutic interventions is restricted by the dose-limiting sideeffects that accompany common centrally targeted analgesics. METHODS: This review focuses on how up-regulated glutamate production and export by the tumour converge at peripheral afferent nerve terminals to transmit nociceptive signals through the transient receptor cation channel, TRPV1, thereby initiating central sensitization in response to peripheral disease-mediated stimuli. RESULTS: Cancer cells undergo numerous metabolic changes that include increased glutamine catabolism and over-expression of enzymes involved in glutaminolysis, including glutaminase. This mitochondrial enzyme mediates glutaminolysis, producing large pools of intracellular glutamate. Upregulation of the plasma membrane cystine/glutamate antiporter, system xc -, promotes aberrant glutamate release from cancer cells. Increased levels of extracellular glutamate have been associated with the progression of cancer-induced pain and we discuss how this can be mediated by activation of TRPV1. CONCLUSION: With a growing population of patients receiving inadequate treatment for intractable pain, new targets need to be considered to better address this largely unmet clinical need for improving their quality of life. A better understanding of the mechanisms that underlie the unique qualities of cancer pain will help to identify novel targets that are able to limit the initiation of pain from a peripheral source-the tumour.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".