P-30 IL-16 blood levels and combined polymorphism of CCL11 and IL-16 are the biomarkers to select oxycodone for cancer pain management
<h3>Background</h3> 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).<sup>1</sup> 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. <h3>Methods</h3> 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 trial<sup>2</sup> 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. <h3>Results</h3> 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). <h3>Discussion</h3> 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. <h3>References</h3> Fujita Y, Matsuoka H, <i>et al</i>. Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain. <i>Oncol Lett</i>. 2023 Jul 4;<b>26</b>(2):355. Matsuoka H,<i> et al</i>. 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;<b>28</b>(3):278-e166.
Authors
- Yoshihiko Fujita (ORCID: https://orcid.org/0009-0006-2831-2964)
- Junji Tsurutani (ORCID: https://orcid.org/0000-0002-6260-6943)
- Hiromichi Matsuoka (ORCID: https://orcid.org/0000-0002-7276-1971)
- Takeshi Yoshida (ORCID: https://orcid.org/0000-0003-3951-4618)
- Kazuhiko Nakagawa
- Atsuko Koyama (ORCID: https://orcid.org/0000-0003-3411-3313)
- Kazuto Nishio
Institutions
- National Cancer Centre Japan (JP)
- Kindai University (JP)
Publication Details
- Journal
- Poster presentations
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1136/spcare-2024-anzspm.78
- Primary Topic
- Vitamin K Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00