Institute for Medical Biomathematics (IMBM), Bene Ataroth, Israel.
Front Immunol. 2021 Mar 1;12:616881. doi: 10.3389/fimmu.2021.616881. eCollection 2021.
Recently, there has been a growing interest in applying immune checkpoint blockers (ICBs), so far used to treat cancer, to patients with bacterial sepsis. We aimed to develop a method for predicting the personal benefit of potential treatments for sepsis, and to apply it to therapy by meropenem, an antibiotic drug, and nivolumab, a programmed cell death-1 (PD-1) pathway inhibitor. We defined an optimization problem as a concise framework of treatment aims and formulated a fitness function for grading sepsis treatments according to their success in accomplishing the pre-defined aims. We developed a mathematical model for the interactions between the pathogen, the cellular immune system and the drugs, whose simulations under diverse combined meropenem and nivolumab schedules, and calculation of the fitness function for each schedule served to plot the fitness landscapes for each set of treatments and personal patient parameters. Results show that treatment by meropenem and nivolumab has maximum benefit if the interval between the onset of the two drugs does not exceed a dose-dependent threshold, beyond which the benefit drops sharply. However, a second nivolumab application, within 7-10 days after the first, can extinguish a pathogen which the first nivolumab application failed to remove. The utility of increasing nivolumab total dose above 6 mg/kg is contingent on the patient's personal immune attributes, notably, the reinvigoration rate of exhausted CTLs and the overall suppression rates of functional CTLs. A baseline pathogen load, higher than 5,000 CFU/μL, precludes successful nivolumab and meropenem combination therapy, whereas when the initial load is lower than 3,000 CFU/μL, meropenem monotherapy suffices for removing the pathogen. Our study shows that early administration of nivolumab, 6 mg/kg, in combination with antibiotics, can alleviate bacterial sepsis in cases where antibiotics alone are insufficient and the initial pathogen load is not too high. The study pinpoints the role of precision medicine in sepsis, suggesting that personalized therapy by ICBs can improve pathogen elimination and dampen immunosuppression. Our results highlight the importance in using reliable markers for classifying patients according to their predicted response and provides a valuable tool in personalizing the drug regimens for patients with sepsis.
最近,人们越来越关注将免疫检查点抑制剂(ICBs)应用于治疗癌症,以应用于治疗细菌败血症患者。我们旨在开发一种预测潜在治疗败血症的个人益处的方法,并将其应用于美罗培南(一种抗生素药物)和纳武单抗(一种程序性细胞死亡-1(PD-1)途径抑制剂)的治疗。我们将优化问题定义为一个简洁的治疗目标框架,并为根据其在完成预定义目标方面的成功程度对败血症治疗进行分级制定了一个适合度函数。我们开发了一个病原体、细胞免疫系统和药物相互作用的数学模型,根据不同的美罗培南和纳武单抗联合方案进行模拟,并计算每个方案的适合度函数,从而为每个治疗方案和个人患者参数绘制适合度景观。结果表明,如果两种药物的间隔不超过剂量依赖性阈值,美罗培南和纳武单抗联合治疗的获益最大,超过该阈值后,获益急剧下降。然而,在第一次纳武单抗应用后 7-10 天内进行第二次纳武单抗应用,可以消除第一次纳武单抗应用未能清除的病原体。增加纳武单抗总剂量至 6mg/kg 以上的效用取决于患者的个人免疫属性,尤其是耗竭 CTL 的再刺激率和功能性 CTL 的整体抑制率。基线病原体载量高于 5000 CFU/μL 时,纳武单抗和美罗培南联合治疗无法成功,而初始载量低于 3000 CFU/μL 时,美罗培南单药治疗足以清除病原体。我们的研究表明,早期给予纳武单抗(6mg/kg)联合抗生素治疗,可以缓解抗生素单独治疗不足且初始病原体载量不太高的细菌败血症。该研究指出了精准医学在败血症中的作用,表明 ICB 的个体化治疗可以提高病原体的清除率并抑制免疫抑制。我们的研究结果强调了使用可靠标志物根据预测的反应对患者进行分类的重要性,并为败血症患者的个体化药物治疗提供了有价值的工具。