The CCL17/CCL22–CCR4 Axis in Pain Pathogenesis: A Comprehensive Review of Immune-Mediated Mechanisms and Therapeutic Opportunities
Bibliographic record
Abstract
The role of C-C motif chemokine ligand (CCL) 17 and CCL22 signalling has been demonstrated in allergic disorders, such as asthma and atopic dermatitis, as well as multiple types of neoplastic disorders. New evidence has identified that CCL17/CCL22 activation of the receptor CCR4 functions to mediate pain, with distinct roles in arthritic, neuropathic, and inflammatory postoperative pain. CCR4 blockade is suggested to prevent the development of neuropathic pain by inhibiting microglia activation and the subsequent increase in pronociceptive cytokines. CCL17 can also play a key role in the pathophysiology of arthritic pain. Further, CCL17 expression is increased in response to granulocyte-macrophage colony-stimulating factor. Both CCL17 and CCL22, produced by skin-resident dendritic cells in response to incisional wounds, bind CCR4 expressed on peripheral sensory neurons, directly inducing pain signalling. These findings suggest that CCR4 may represent a therapeutic target for reducing pain. Understanding the role of CCR4 in the process of pain may also provide essential insight into the development of these therapeutic agents. The present paper provides a comprehensive review of the current literature on the role of the immune system in the inflammatory pain response, with a specific focus on the role of CCL17 and CCL22 activity in the pathophysiology of pain. Also, we discuss the potential for therapeutically targeting CCR4 and its clinical implications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".