基于 DNA 超分子水凝胶的保护性 NK 细胞储库用于增强三阴性乳腺癌治疗
Protective NK Cell Reservoir Based on DNA Supramolecular Hydrogel for Enhanced Triple-Negative Breast Cancer Therapy.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Computational reactive-diffusive modeling for stratification and prognosis determination of patients with breast cancer receiving Olaparib.
Computational reactive-diffusive modeling for stratification and prognosis determination of patients with breast cancer receiving Olaparib.
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基于偏微分方程(PDE)的数学模型可用于处理具有时空维度的临床数据,例如新辅助治疗下的肿瘤生长。本研究在OLTRE试验中运用一种基于简化肿瘤恶性程度和药效动力学效率评估的模型,探索患者预后新指标。研究在17例早期三阴性乳腺癌(TNBC)患者队列中开展;患者接受3周奥拉帕利治疗。研究考察PDE反应-扩散肿瘤生长模型能否利用表征肿瘤扩散和增殖的特定参数,基于¹⁸F-FDG PET/CT扫描检测的SUVmax有效预测奥拉帕利应答。计算采用COMSOL Multiphysics完成,数学模型的驱动参数通过Pearson相关分析筛选。使用Student t检验和Wilcoxon秩和检验评估实际与计算SUVmax值之间的差异,并以Pearson r和Spearman rho评估奥拉帕利治疗后真实和计算SUVmax的相关性。
在定义适当数学假设后,计算评估名义药物疗效(εPD)和肿瘤恶性度(rc)。前者反映奥拉帕利对肿瘤的作用,后者代表由SUVmax反映的代谢活性增长率。εPD与基线TIL和Ki67%呈直接依赖关系,并可根据TIL值通过适当线性回归函数估算;rc则由基线Ki67/TIL比值表征。整体、gBRCA突变和gBRCA野生型亚组中,预测的奥拉帕利治疗后SUV*max与原始SUVmax均无显著差异(均P>.05),且均呈强正相关(r=.9、rho=.9,均P<.0001)。该简化肿瘤动力学模型可有效预测3周新辅助奥拉帕利治疗对SUVmax的影响。仍需在独立队列中开展前瞻性评估,并将预测结果与更常用疗效终点相关联,以验证模型并指导早期TNBC患者治疗升级或降阶。
Mathematical models based on partial differential equations (PDEs) can be exploited to handle clinical data with space/time dimensions, e. g. tumor growth challenged by neoadjuvant therapy. A model based on simplified assessment of tumor malignancy and pharmacodynamics efficiency was exercised to discover new metrics of patient prognosis in the OLTRE trial.
We tested in a 17-patients cohort affected by early-stage triple negative breast cancer (TNBC) treated with 3 weeks of olaparib, the capability of a PDEs-based reactive-diffusive model of tumor growth to efficiently predict the response to olaparib in terms of SUV max detected at 18 FDG-PET/CT scan, by using specific terms to characterize tumor diffusion and proliferation. Computations were performed with COMSOL Multiphysics. Driving parameters governing the mathematical model were selected with Pearson's correlations. Discrepancies between actual and computed SUV max values were assessed with Student's t test and Wilcoxon rank sum test. The correlation between post-olaparib true and computed SUV max was assessed with Pearson's r and Spearman's rho. After defining the proper mathematical assumptions, the nominal drug efficiency (ε PD ) and tumor malignancy (r c ) were computationally evaluated. The former parameter reflected the activity of olaparib on the tumor, while the latter represented the growth rate of metabolic activity as detected by SUV max .
ε PD was found to be directly dependent on basal tumor-infiltrating lymphocytes (TILs) and Ki67% and was detectable through proper linear regression functions according to TILs values, while r c was represented by the baseline Ki67-to-TILs ratio. Predicted post-olaparib SUV* max did not significantly differ from original post-olaparib SUV max in the overall, gBRCA-mutant and gBRCA-wild-type subpopulations (p > 0. 05 in all cases), showing strong positive correlation (r = 0.
9 and rho = 0. 9, p < 0. 0001 both). A model of simplified tumor dynamics was exercised to effectively produce an upfront prediction of efficacy of 3-week neoadjuvant olaparib in terms of SUV max . Prospective evaluation in independent cohorts and correlation of these outcomes with more recognized efficacy endpoints is now warranted for model confirmation and tailoring of escalated/de-escalated therapeutic strategies for early-TNBC patients.
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