Background For precision medicine for cancer pain, we identified a SNP in CCL11 (rs17809012) as one of the biomarkers significantly associated with the analgesic effect of morphine by screening 74 pain-related single nucleotide polymorphisms (SNPs).¹ In this study, to explore biomarkers for predicting opioid efficacy, we aimed to evaluate whether plasma concentrations of chemokines/cytokines and their SNPs in combination can accurately predict the most appropriate opioid for pain relief in cancer patients.

Methods In this study, plasma concentrations of several chemokines/cytokines were determined in pretreatment plasma samples obtained from a total of 138 patients enrolled in our previous clinical trial² who were randomly assigned to the morphine (N=70) and oxycodone (N=68) groups. The relationship between pre-treatment blood concentrations of various chemokines/cytokines and NRS (opioid analgesic effect) in the oxycodone group was investigated using simple regression analysis. Regarding IL-16, which showed promising results, we performed simple regression analysis using opioid type as independent variable and ΔNRS as dependent variable and multiple regression analysis using opioid type and IL-16 concentration (high or low) and opioid type IL-16 concentration (interaction term) as independent variables and NRS as dependent variable among all patients. Finally, we evaluated the relationship between the combination of both CCL11 and IL-16 SNPs and opioid efficacy using multiple regression analysis.

Results In the oxycodone group, there was a significant difference in NRS between groups (p=0.013) of patients with high (n=34) and low (n=34) blood levels of IL-16, and oxycodone was more effective in patients with lower IL-16 levels (p=0.038), whereas morphine was more effective in patients with higher IL-16 levels, although insignificant (p=0.241; p for interaction=0.020). Morphine tended to provide a better analgesic effect than oxycodone in patients with the rs4778889 TT genotype and the rs17809012 AG/GG genotype (n=45), while a trend toward a better analgesic effect of oxycodone was observed in patients with other genotype combinations of the SNPs (n=93) (p=0.001 for interaction).

Discussion Our study suggests that IL-16 blood levels and polymorphism (rs4778889) may be useful as a possible biomarker for oxycodone selection. Only patients with IL-16(rs4778889) TT and CCL11(rs17809012) AG/GG SNPs responded well to morphine, but only about 30% clinically (Japanese), suggesting that oxycodone may be superior for about 70% of patients. Combining these with IL-16 concentrations would further increase accuracy. It is hoped that a larger sample size will lead to the realization of personalized medicine for pain relief in the future through the revalidation of biomarker such as IL-16 identified in this study.

References

1. Fujita Y, Matsuoka H, et al. Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain. Oncol Lett. 2023 Jul 4;26(2):355.

2. Matsuoka H, et al. Morphine versus oxycodone for cancer pain using a catechol-o-methyltransferase genotype biomarker: a multicenter, randomized, open-label, phase III clinical trial (RELIEF Study). Oncologist. 2023 Mar 17;28(3):278-e166.