Ippolito Alberto, Wang Hanwen, Zhang Yu, Vakil Vahideh, Popel Aleksander S
Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
Clinical and Quantitative Pharmacology, CytomX Therapeutics, Inc., South San Francisco, CA, USA.
J Pharmacokinet Pharmacodyn. 2024 Dec;51(6):747-757. doi: 10.1007/s10928-024-09928-5. Epub 2024 Jun 10.
Recently, immunotherapies for antitumoral response have adopted conditionally activated molecules with the objective of reducing systemic toxicity. Amongst these are conditionally activated antibodies, such as PROBODY® activatable therapeutics (Pb-Tx), engineered to be proteolytically activated by proteases found locally in the tumor microenvironment (TME). These PROBODY® therapeutics molecules have shown potential as PD-L1 checkpoint inhibitors in several cancer types, including both effectiveness and locality of action of the molecule as shown by several clinical trials and imaging studies. Here, we perform an exploratory study using our recently published quantitative systems pharmacology model, previously validated for triple-negative breast cancer (TNBC), to computationally predict the effectiveness and targeting specificity of a PROBODY® therapeutics drug compared to the non-modified antibody. We begin with the analysis of anti-PD-L1 immunotherapy in non-small cell lung cancer (NSCLC). As a first contribution, we have improved previous virtual patient selection methods using the omics data provided by the iAtlas database portal compared to methods previously published in literature. Furthermore, our results suggest that masking an antibody maintains its efficacy while improving the localization of active therapeutic in the TME. Additionally, we generalize the model by evaluating the dependence of the response to the tumor mutational burden, independently of cancer type, as well as to other key biomarkers, such as CD8/Treg Tcell and M1/M2 macrophage ratio. While our results are obtained from simulations on NSCLC, our findings are generalizable to other cancer types and suggest that an effective and highly selective conditionally activated PROBODY® therapeutics molecule is a feasible option.
最近，用于抗肿瘤反应的免疫疗法采用了条件激活分子，目的是降低全身毒性。其中包括条件激活抗体，如PROBODY®可激活治疗剂（Pb-Tx），其设计为可被肿瘤微环境（TME）中局部存在的蛋白酶进行蛋白水解激活。这些PROBODY®治疗分子在几种癌症类型中已显示出作为PD-L1检查点抑制剂的潜力，包括分子的有效性和作用部位，这在多项临床试验和影像学研究中得到了证实。在此，我们使用我们最近发表的定量系统药理学模型进行了一项探索性研究，该模型先前已针对三阴性乳腺癌（TNBC）进行了验证，以通过计算预测与未修饰抗体相比PROBODY®治疗药物的有效性和靶向特异性。我们从非小细胞肺癌（NSCLC）中的抗PD-L1免疫疗法分析开始。作为第一个贡献，与文献中先前发表的方法相比，我们使用iAtlas数据库门户提供的组学数据改进了先前的虚拟患者选择方法。此外，我们的结果表明，掩盖抗体在维持其疗效的同时，还改善了活性治疗剂在TME中的定位。此外，我们通过评估对肿瘤突变负担的反应依赖性来推广该模型，该依赖性与癌症类型无关，以及与其他关键生物标志物有关，如CD8/Treg T细胞和M1/M2巨噬细胞比率。虽然我们的结果是通过对NSCLC的模拟获得的，但我们的发现可推广到其他癌症类型，并表明一种有效且高度选择性的条件激活PROBODY®治疗分子是一种可行的选择。
