Division of Cancer Therapeutics, The Institute of Cancer Research, London, SW7 3RP, UK.
School of Biosciences, University of Kent, Canterbury, UK.
Metabolomics. 2020 Apr 13;16(4):50. doi: 10.1007/s11306-020-01676-0.
To generate biomarkers of target engagement or predictive response for multi-target drugs is challenging. One such compound is the multi-AGC kinase inhibitor AT13148. Metabolic signatures of selective signal transduction inhibitors identified in preclinical models have previously been confirmed in early clinical studies. This study explores whether metabolic signatures could be used as biomarkers for the multi-AGC kinase inhibitor AT13148.
To identify metabolomic changes of biomarkers of multi-AGC kinase inhibitor AT13148 in cells, xenograft / mouse models and in patients in a Phase I clinical study.
HILIC LC-MS/MS methods and Biocrates AbsoluteIDQ™ p180 kit were used for targeted metabolomics; followed by multivariate data analysis in SIMCA and statistical analysis in Graphpad. Metaboanalyst and String were used for network analysis.
BT474 and PC3 cells treated with AT13148 affected metabolites which are in a gene protein metabolite network associated with Nitric oxide synthases (NOS). In mice bearing the human tumour xenografts BT474 and PC3, AT13148 treatment did not produce a common robust tumour specific metabolite change. However, AT13148 treatment of non-tumour bearing mice revealed 45 metabolites that were different from non-treated mice. These changes were also observed in patients at doses where biomarker modulation was observed. Further network analysis of these metabolites indicated enrichment for genes associated with the NOS pathway. The impact of AT13148 on the metabolite changes and the involvement of NOS-AT13148- Asymmetric dimethylarginine (ADMA) interaction were consistent with hypotension observed in patients in higher dose cohorts (160-300 mg).
AT13148 affects metabolites associated with NOS in cells, mice and patients which is consistent with the clinical dose-limiting hypotension.
为多靶点药物生成靶标结合或预测反应的生物标志物具有挑战性。一种这样的化合物是多 AGC 激酶抑制剂 AT13148。在临床前模型中鉴定的选择性信号转导抑制剂的代谢特征已在早期临床研究中得到证实。本研究探讨代谢特征是否可作为多 AGC 激酶抑制剂 AT13148 的生物标志物。
鉴定多 AGC 激酶抑制剂 AT13148 在细胞、异种移植/小鼠模型和 I 期临床研究中的患者中的生物标志物代谢组学变化。
使用亲水相互作用色谱-液相色谱-串联质谱法(HILIC LC-MS/MS)方法和 Biocrates AbsoluteIDQ™ p180 试剂盒进行靶向代谢组学分析;随后在 SIMCA 中进行多元数据分析,并在 Graphpad 中进行统计分析。使用 Metaboanalyst 和 String 进行网络分析。
BT474 和 PC3 细胞用 AT13148 处理后,受代谢物影响,这些代谢物与一氧化氮合酶(NOS)相关的基因-蛋白质-代谢物网络有关。在携带人肿瘤异种移植 BT474 和 PC3 的小鼠中,AT13148 治疗并未产生共同的稳健的肿瘤特异性代谢物变化。然而,AT13148 治疗非肿瘤携带小鼠时,发现 45 种代谢物与未治疗的小鼠不同。在观察到生物标志物调节的剂量下,这些变化也在患者中观察到。对这些代谢物的进一步网络分析表明,NOS 途径相关基因富集。AT13148 对代谢物变化的影响以及 NOS-AT13148-不对称二甲基精氨酸(ADMA)相互作用的参与与较高剂量组(160-300mg)中观察到的患者低血压一致。
AT13148 影响与细胞、小鼠和患者中的 NOS 相关的代谢物,这与临床剂量限制的低血压一致。