Boerrigter Emmy, Benoist Guillemette E, van Oort Inge M, Verhaegh Gerald W, de Haan Anton F J, van Hooij Onno, Groen Levi, Smit Frank, Oving Irma M, de Mol Pieter, Smilde Tineke J, Somford Diederik M, Hamberg Paul, Dezentjé Vincent O, Mehra Niven, van Erp Nielka P, Schalken Jack A
Radboud University Medical Center, Department of Pharmacy, Radboud Institute for Health Sciences, 6525 GA Nijmegen, The Netherlands.
Radboud University Medical Center, Department of Urology, Radboud Institute for Molecular Life Sciences, 6525 GA Nijmegen, The Netherlands.
Cancers (Basel). 2021 Dec 14;13(24):6279. doi: 10.3390/cancers13246279.
Treatment evaluation in metastatic castration-resistant prostate cancer is challenging. There is an urgent need for biomarkers to discriminate short-term survivors from long-term survivors, shortly after treatment initiation. Thereto, the added value of early RNA biomarkers on predicting progression-free survival (PFS) and overall survival (OS) were explored. The RNA biomarkers: mRNA, miR-375, miR-3687, and were measured in 93 patients with mCRPC, before and 1 month after start of first-line abiraterone acetate or enzalutamide treatment, in two prospective clinical trials. The added value of the biomarkers to standard clinical parameters in predicting PFS and OS was tested by Harell's C-index. To test whether the biomarkers were independent markers of PFS and OS, multivariate Cox regression was used. The best prediction model for PFS and OS was formed by adding miR-375 and (at baseline and 1 month) to standard clinical parameters. Baseline miR-375 and detectable after 1 month of therapy were independently related to shorter PFS, which was not observed for OS. In conclusion, the addition of and miR-375 (at baseline and 1 month) to standard clinical parameters resulted in the best prediction model for survival assessment.
转移性去势抵抗性前列腺癌的治疗评估具有挑战性。在治疗开始后不久，迫切需要生物标志物来区分短期幸存者和长期幸存者。为此，研究了早期RNA生物标志物在预测无进展生存期（PFS）和总生存期（OS）方面的附加价值。在两项前瞻性临床试验中，对93例转移性去势抵抗性前列腺癌（mCRPC）患者在开始一线醋酸阿比特龙或恩杂鲁胺治疗前及治疗1个月后，检测了RNA生物标志物：mRNA、miR-375、miR-3687等。通过Harell's C指数检验生物标志物对预测PFS和OS的标准临床参数的附加价值。为了检验这些生物标志物是否是PFS和OS的独立标志物，使用了多变量Cox回归。通过将miR-375和（基线和1个月时）添加到标准临床参数中，形成了PFS和OS的最佳预测模型。基线miR-375和治疗1个月后可检测到的与较短的PFS独立相关，而OS未观察到这种情况。总之，将和miR-375（基线和1个月时）添加到标准临床参数中，可得到生存评估的最佳预测模型。
