Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
Department of Urology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Cancer Sci. 2023 Apr;114(4):1625-1634. doi: 10.1111/cas.15718. Epub 2023 Jan 20.
Genetic variations represented by single-nucleotide polymorphisms (SNPs) could be helpful for choosing an effective treatment for patients with prostate cancer. This study investigated the prognostic and predictive values of SNPs associated with the prognoses of pharmacotherapy for prostate cancer through their pharmacological mechanisms. Patients treated with docetaxel or androgen receptor pathway inhibitors (ARPIs), such as abiraterone and enzalutamide, for castration-resistant prostate cancer were included. The SNPs of interest were genotyped for target regions. The prognostic and predictive values of the SNPs for time to progression (TTP) were examined using the Cox hazard proportional model and interaction test, respectively. Rs1045642 in ABCB1, rs1047303 in HSD3B1, rs1856888 in HSD3B1, rs523349 in SRD5A2, and rs34550074 in SLCO2A1 were differentially associated with TTP between docetaxel chemotherapy and ARPI treatment. In addition to rs4775936 in CYP19A1, rs1128503 in ABCB1 and rs1077858 in SLCO2B1 might be differentially associated with TTP between abiraterone and enzalutamide treatments. Genetic predictive models using these SNPs showed a differential prognosis for treatments. This study identified SNPs that could predict progression as well as genetic models that could predict progression when patients were treated with docetaxel versus ARPI and abiraterone versus enzalutamide. The use of genetic predictive models is expected to be beneficial in selecting the appropriate treatment for the individual patient.
单核苷酸多态性(SNP)所代表的遗传变异可能有助于为前列腺癌患者选择有效的治疗方法。本研究通过其药理机制,研究了与前列腺癌药物治疗预后相关的 SNP 的预后和预测价值。纳入接受多西他赛或雄激素受体通路抑制剂(ARPI),如阿比特龙和恩扎鲁胺,治疗去势抵抗性前列腺癌的患者。对感兴趣的 SNP 进行了目标区域的基因分型。使用 Cox 风险比例模型和交互检验分别检查 SNP 对无进展时间(TTP)的预后和预测价值。ABCB1 中的 rs1045642、HSD3B1 中的 rs1047303、HSD3B1 中的 rs1856888、SRD5A2 中的 rs523349 和 SLCO2A1 中的 rs34550074 在多西他赛化疗与 ARPI 治疗之间与 TTP 差异相关。除了 CYP19A1 中的 rs4775936、ABCB1 中的 rs1128503 和 SLCO2B1 中的 rs1077858 之外,这些 SNP 可能与阿比特龙和恩扎鲁胺治疗之间的 TTP 差异相关。使用这些 SNP 的遗传预测模型显示出对治疗的不同预后。本研究鉴定了能够预测进展的 SNP,以及在患者接受多西他赛与 ARPI、阿比特龙与恩扎鲁胺治疗时能够预测进展的遗传模型。预计使用遗传预测模型在为个体患者选择适当的治疗方法方面将是有益的。