Functional inhibition of chemokine receptor CCR2 by dicer-substrate-siRNA prevents pain development
Bibliographic record
Abstract
BACKGROUND: Accumulating evidence suggests that the C-C chemokine ligand 2 (CCL2, or monocyte chemoattractant protein 1) acts as a neuromodulator in the central nervous system through its binding to the C-C chemokine receptor 2 (CCR2). Notably, it is well established that the CCL2/CCR2 axis plays a key role in neuron-glia communication as well as in spinal nociceptive transmission. Gene silencing through RNA interference has recently emerged as a promising avenue in research and drug development, including therapeutic management of chronic pain. In the present study, we used 27-mer Dicer-substrate small interfering RNA (DsiRNA) targeting CCR2 and assessed their ability to reverse the nociceptive behaviors induced by spinal CCL2 injection or following intraplantar injection of complete Freund's adjuvant. RESULTS: To this end, we first developed high-potency DsiRNAs designed to target different sequences distributed across the rat CCR2 (rCCR2) messenger RNA. For optimization, methyl groups were added to the two most potent DsiRNA candidates (Evader and M7 2'-O-methyl modified duplexes) in order to improve in vivo duplex stability and to reduce potential immunostimulatory activity. Our results demonstrated that all modified candidates formulated with the cell-penetrating peptide reagent Transductin showed strong RNAi activity following intrathecal delivery, exhibiting >50% rCCR2 knockdown in lumbar dorsal root ganglia. Accordingly, we found that these DsiRNA duplexes were able to reduce spinal microglia activation and were effective at blocking CCL2-induced mechanical hypersensitivity. Along with similar reductions of rCCR2 messenger RNA, both sequences and methylation patterns were similarly effective in inhibiting the CCL2 nociceptive action for the whole seven days testing period, compared to mismatch DsiRNA. DsiRNAs against CCR2 also reversed the hypernociceptive responses observed in the complete Freund's adjuvant-induced inflammatory chronic pain model. CONCLUSION: Altogether, these results validate CCR2 as a an appropriate molecular target for pain control and demonstrate that RNAi-based gene therapy represent an highly specific alternative to classical pharmacological approaches to treat central pathologies such as chronic pain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 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".