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Pain is critical to various clinical pathologies, provoking an urgent need for effective management. Pain, whether acute or chronic, is a complex neurochemical process. Its alleviation depends on the type, with nonopioid analgesics effective for mild to moderate pain, such as musculoskeletal or inflammatory pain, while neuropathic pain responds best to anticonvulsants, tricyclic antidepressants, or serotonin/norepinephrine reuptake inhibitors. For severe acute or chronic pain, opioids may be...
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Dual single‑nucleotide polymorphism biomarker combination for opioid selection to treat cancer pain.

Yoshihiko Fujita1, Hiromichi Matsuoka2,3,4, Yasutaka Chiba5

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Researchers identified two genetic biomarkers, CCL11 (rs17809012) and IL-16 (rs4778889) SNPs, that can predict the best opioid for cancer pain relief. This discovery supports personalized pain management strategies.

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Area of Science:

  • Pharmacogenomics
  • Oncology
  • Pain Management

Background:

  • Individualized treatment selection for cancer pain remains a challenge.
  • Previous research identified a single nucleotide polymorphism (SNP) in CCL11 (rs17809012) associated with morphine's analgesic effect.
  • Cytokines and chemokines are implicated in pain pathways and opioid response.

Purpose of the Study:

  • To investigate the role of plasma cytokine concentrations and specific gene SNPs in predicting patient response to morphine versus oxycodone for cancer pain.
  • To assess the potential of combining CCL11 and IL-16 SNPs as dual biomarkers for personalized opioid selection in cancer pain management.

Main Methods:

  • Plasma samples from 138 cancer pain patients randomized to morphine or oxycodone were analyzed for chemokine/cytokine concentrations.
  • Genotypic analysis was performed for SNPs in CCL11 (rs17809012) and IL-16 (rs4778889).
  • Statistical analysis evaluated the association between genotypes, cytokine levels, and analgesic response to opioids.

Main Results:

  • Plasma IL-16 concentrations differentiated between good and poor responders to oxycodone.
  • The IL-16 gene SNP (rs4778889) was significantly associated with oxycodone's analgesic effect.
  • A significant interaction (P=0.0012) was observed between IL-16 rs4778889 and CCL11 rs17809012 genotypes in predicting differential opioid response, favoring morphine in certain genotypes and oxycodone in others.

Conclusions:

  • The IL-16 (rs4778889) and CCL11 (rs17809012) SNPs show potential as a dual-biomarker combination for guiding personalized opioid therapy in cancer pain.
  • This pharmacogenetic approach may improve analgesic efficacy and treatment selection for patients with cancer pain.