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Article Open Access

Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain

  • Authors:
    • Yoshihiko Fujita
    • Hiromichi Matsuoka
    • Yasutaka Chiba
    • Junji Tsurutani
    • Takeshi Yoshida
    • Kiyohiro Sakai
    • Miki Nakura
    • Ryo Sakamoto
    • Chihiro Makimura
    • Yoichi Ohtake
    • Kaoru Tanaka
    • Hidetoshi Hayashi
    • Masayuki Takeda
    • Tatsuya Okuno
    • Naoki Takegawa
    • Koji Haratani
    • Takayuki Takahama
    • Junko Tanizaki
    • Atsuko Koyama
    • Kazuto Nishio
    • Kazuhiko Nakagawa
  • View Affiliations / Copyright

    Affiliations: Department of Genome Biology, Kindai University Faculty of Medicine, Osaka 589‑8511, Japan, Department of Psychosomatic Medicine, Kindai University Faculty of Medicine, Osaka 589‑8511, Japan, Department of Biostatics, Kindai University Faculty of Medicine, Osaka 589‑8511, Japan, Advanced Cancer Translational Research Institute, Showa University, Tokyo 142‑8555, Japan, Department of Medical Oncology, Kindai University Faculty of Medicine, Osaka 589‑8511, Japan
    Copyright: © Fujita et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 355
    |
    Published online on: July 4, 2023
       https://doi.org/10.3892/ol.2023.13941
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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.
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Copy and paste a formatted citation
Spandidos Publications style
Fujita Y, Matsuoka H, Chiba Y, Tsurutani J, Yoshida T, Sakai K, Nakura M, Sakamoto R, Makimura C, Ohtake Y, Ohtake Y, et al: Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain. Oncol Lett 26: 355, 2023.
APA
Fujita, Y., Matsuoka, H., Chiba, Y., Tsurutani, J., Yoshida, T., Sakai, K. ... Nakagawa, K. (2023). Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain. Oncology Letters, 26, 355. https://doi.org/10.3892/ol.2023.13941
MLA
Fujita, Y., Matsuoka, H., Chiba, Y., Tsurutani, J., Yoshida, T., Sakai, K., Nakura, M., Sakamoto, R., Makimura, C., Ohtake, Y., Tanaka, K., Hayashi, H., Takeda, M., Okuno, T., Takegawa, N., Haratani, K., Takahama, T., Tanizaki, J., Koyama, A., Nishio, K., Nakagawa, K."Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain". Oncology Letters 26.2 (2023): 355.
Chicago
Fujita, Y., Matsuoka, H., Chiba, Y., Tsurutani, J., Yoshida, T., Sakai, K., Nakura, M., Sakamoto, R., Makimura, C., Ohtake, Y., Tanaka, K., Hayashi, H., Takeda, M., Okuno, T., Takegawa, N., Haratani, K., Takahama, T., Tanizaki, J., Koyama, A., Nishio, K., Nakagawa, K."Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain". Oncology Letters 26, no. 2 (2023): 355. https://doi.org/10.3892/ol.2023.13941
Copy and paste a formatted citation
x
Spandidos Publications style
Fujita Y, Matsuoka H, Chiba Y, Tsurutani J, Yoshida T, Sakai K, Nakura M, Sakamoto R, Makimura C, Ohtake Y, Ohtake Y, et al: Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain. Oncol Lett 26: 355, 2023.
APA
Fujita, Y., Matsuoka, H., Chiba, Y., Tsurutani, J., Yoshida, T., Sakai, K. ... Nakagawa, K. (2023). Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain. Oncology Letters, 26, 355. https://doi.org/10.3892/ol.2023.13941
MLA
Fujita, Y., Matsuoka, H., Chiba, Y., Tsurutani, J., Yoshida, T., Sakai, K., Nakura, M., Sakamoto, R., Makimura, C., Ohtake, Y., Tanaka, K., Hayashi, H., Takeda, M., Okuno, T., Takegawa, N., Haratani, K., Takahama, T., Tanizaki, J., Koyama, A., Nishio, K., Nakagawa, K."Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain". Oncology Letters 26.2 (2023): 355.
Chicago
Fujita, Y., Matsuoka, H., Chiba, Y., Tsurutani, J., Yoshida, T., Sakai, K., Nakura, M., Sakamoto, R., Makimura, C., Ohtake, Y., Tanaka, K., Hayashi, H., Takeda, M., Okuno, T., Takegawa, N., Haratani, K., Takahama, T., Tanizaki, J., Koyama, A., Nishio, K., Nakagawa, K."Novel single nucleotide polymorphism biomarkers to predict opioid effects for cancer pain". Oncology Letters 26, no. 2 (2023): 355. https://doi.org/10.3892/ol.2023.13941
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