Abstract
There have been few studies on predictive biomarkers that may be useful to select the most suitable opioids to optimize therapeutic efficacy in individual patients with cancer pain. We recently investigated the efficacy of morphine and oxycodone using single nucleotide polymorphisms (SNPs) of the catechol-O-methyltransferase (COMT) rs4680 gene as a biomarker (RELIEF study). To explore additional biomarkers that may enable the selection of an appropriate opioid for individual patients with cancer pain, three SNPs were examined: C-C motif chemokine ligand 11 (CCL11; rs17809012), histamine N-methyltransferase (HNMT; rs1050891) and transient receptor potential V1 (TRPV1; rs222749), which were screened from 74 pain-related SNPs. These SNPs, which were identified as being significantly associated with the analgesic effect of morphine, were then used to genotype the 135 patients in the RELIEF study who had been randomized into a morphine group (n=69) or an oxycodone group (n=66). The present study then assessed whether the SNPs could also be used as selective biomarkers to predict which opioid(s) might be the most suitable to provide pain relief for patients with cancer. Oxycodone tended to provide superior analgesic effects over morphine in patients carrying the genotype AA for the CCL11 rs17809012 SNP (P=0.012 for interaction), suggesting that it could serve as a potential biomarker for personalized analgesic therapy for patients suffering with cancer pain.