Neoadjuvant chemotherapy (NAC) is a standard-of-care treatment for locally advanced triple negative breast cancer (TNBC) before surgery. The early assessment of TNBC response to NAC would enable an oncologist to adapt the therapeutic plan of a non-responding patient, thereby improving treatment outcomes while preventing unnecessary toxicities. To this end, a promising approach consists of obtaining in silico personalized forecasts of tumor response to NAC via computer simulation of mechanistic models constrained with patient-specific magnetic resonance imaging (MRI) data acquired early during NAC. Here, we present a new mechanistic model of TNBC growth and response to NAC, including an explicit description of drug pharmacodynamics and pharmacokinetics. As longitudinal in vivo MRI data for model calibration is limited, we perform a sensitivity analysis to identify the model mechanisms driving the response to two NAC drug combinations: doxorubicin with cyclophosphamide, and paclitaxel with carboplatin. The model parameter space is constructed by combining patient-specific MRI-based in silico parameter estimates and in vitro measurements of pharmacodynamic parameters obtained using time-resolved microscopy assays of several TNBC lines. The sensitivity analysis is run in two MRI-based scenarios corresponding to a well-perfused and a poorly perfused tumor. Out of the 15 parameters considered herein, only the baseline tumor cell net proliferation rate along with the maximum concentrations and effects of doxorubicin, carboplatin, and paclitaxel exhibit a relevant impact on model forecasts (total effect index, ST 0.1). These results dramatically limit the number of parameters that require in vivo MRI-constrained calibration, thereby facilitating the clinical application of our model. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00366-023-01873-0.
A global sensitivity analysis of a mechanistic model of neoadjuvant chemotherapy for triple negative breast cancer constrained by in vitro and in vivo imaging data.
以体外和体内成像数据为约束条件,对三阴性乳腺癌新辅助化疗机制模型进行全球敏感性分析
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作者:Lorenzo Guillermo, Jarrett Angela M, Meyer Christian T, DiCarlo Julie C, Virostko John, Quaranta Vito, Tyson Darren R, Yankeelov Thomas E
| 期刊: | Eng Comput | 影响因子: | 0.000 |
| 时间: | 2024 | 起止号: | 2024;40(3):1469-1499 |
| doi: | 10.1007/s00366-023-01873-0 | 研究方向: | 肿瘤 |
| 疾病类型: | 乳腺癌 | ||
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