Department of Bioengineering, University of Louisville, Lutz Hall 419, Louisville, KY 40208, USA.
Department of Cardiovascular and Thoracic Surgery, University of Louisville, KY, USA; James Graham Brown Cancer Center, University of Louisville, KY, USA.
J Theor Biol. 2018 Jul 7;448:38-52. doi: 10.1016/j.jtbi.2018.03.035. Epub 2018 Apr 1.
Chemotherapy for non-small cell lung cancer (NSCLC) typically involves a doublet regimen for a number of cycles. For any particular patient, a course of treatment is usually chosen from a large number of combinational protocols with drugs in concomitant or sequential administration. In spite of newer drugs and protocols, half of patients with early disease will live less than five years and 95% of those with advanced disease survive for less than one year. Here, we apply mathematical modeling to simulate tumor response to multiple drug regimens, with the capability to assess maximum tolerated dose (MTD) as well as metronomic drug administration. We couple pharmacokinetic-pharmacodynamic intracellular multi-compartment models with a model of vascularized tumor growth, setting input parameters from in vitro data, and using the models to project potential response in vivo. This represents an initial step towards the development of a comprehensive virtual system to evaluate tumor response to combinatorial drug regimens, with the goal to more efficiently identify optimal course of treatment with patient tumor-specific data. We evaluate cisplatin and gemcitabine with clinically-relevant dosages, and simulate four treatment NSCLC scenarios combining MTD and metronomic therapy. This work thus establishes a framework for systematic evaluation of tumor response to combination chemotherapy. The results with the chosen parameter set indicate that although a metronomic regimen may provide advantage over MTD, the combination of these regimens may not necessarily offer improved response. Future model evaluation of chemotherapy possibilities may help to assess their potential value to obtain sustained NSCLC regression for particular patients, with the ultimate goal of optimizing multiple-drug chemotherapy regimens in clinical practice.
非小细胞肺癌(NSCLC)的化疗通常涉及多个周期的双联方案。对于任何特定的患者,通常可以从许多联合方案中选择一种治疗方案,这些方案中的药物可以同时或序贯给药。尽管有了更新的药物和方案,但一半的早期疾病患者的生存期不到五年,95%的晚期疾病患者的生存期不到一年。在这里,我们应用数学模型来模拟肿瘤对多种药物方案的反应,具有评估最大耐受剂量(MTD)和节拍式药物给药的能力。我们将药代动力学-药效学细胞内多隔室模型与血管化肿瘤生长模型相结合,从体外数据中设置输入参数,并使用这些模型预测体内的潜在反应。这是朝着开发全面的虚拟系统以评估组合药物方案对肿瘤反应的方向迈出的第一步,目标是使用患者肿瘤特异性数据更有效地确定最佳治疗方案。我们用临床相关剂量评估顺铂和吉西他滨,并模拟四种联合 MTD 和节拍式疗法治疗 NSCLC 的情况。因此,这项工作建立了一个系统评估肿瘤对联合化疗反应的框架。选择参数集的结果表明,尽管节拍式疗法可能比 MTD 更有优势,但这些方案的联合不一定能提供更好的反应。未来对化疗可能性的模型评估可能有助于评估它们对特定患者获得持续 NSCLC 消退的潜在价值,最终目标是优化临床实践中的多药物化疗方案。