Janssen L M, de Vries B B L Penning, Janse M H A, van der Wall E, Elias S G, Salgado R, van Diest P J, Gilhuijs K G A
Image Sciences Institute, University Medical Centre Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands.
Breast Cancer Res Treat. 2025 Jan;209(1):167-175. doi: 10.1007/s10549-024-07484-7. Epub 2024 Sep 16.
In this study, we aimed to explore if the combination of tumor infiltrating lymphocytes (TILs) and change in tumor load on dynamic contrast-enhanced magnetic resonance imaging leads to better assessment of response to neoadjuvant chemotherapy (NAC) in patients with breast cancer, compared to either alone.
In 190 NAC treated patients, MRI scans were performed before and at the end of treatment. The percentage of stromal TILs (%TILs) was assessed in pre-NAC biopsies according to established criteria. Prediction models were developed with linear regression by least absolute shrinkage and selection operator and cross validation (CV), with residual cancer burden as the dependent variable. Discrimination for pathological complete response (pCR) was evaluated using area under the receiver operating characteristic curves (AUC). We used Cox regression analysis for exploring the association between %TILs and recurrence-free survival (RFS).
Fifty-one patients reached pCR. In all patients, the %TILs model and change in MRI tumor load model had an estimated CV AUC of 0.69 (95% confidence interval (CI) 0.53-0.78) and 0.69 (95% CI 0.61-0.79), respectively, whereas a model combining the variables resulted in an estimated CV AUC of 0.75 (95% CI 0.66-0.83). In the group with tumors that were ER positive and HER2 negative (ER+/HER2-) and in the group with tumors that were either triple negative or HER2 positive (TN&HER2+) separately, the combined model reached an estimated CV AUC of 0.72 (95% CI 0.60-0.88) and 0.70(95% CI 0.59-0.82), respectively. A significant association was observed between pre-treatment %TILS and RFS (hazard ratio (HR) 0.72 (95% CI 0.53-0.98), for every standard deviation increase in %TILS, p = 0.038).
The combination of TILs and MRI is informative of response to NAC in patients with both ER+/HER2- and TN&HER2+ tumors.
在本研究中,我们旨在探讨与单独使用肿瘤浸润淋巴细胞(TILs)或动态对比增强磁共振成像上肿瘤负荷变化相比,两者联合使用是否能更好地评估乳腺癌患者新辅助化疗(NAC)的疗效。
对190例接受NAC治疗的患者在治疗前和治疗结束时进行了MRI扫描。根据既定标准,在NAC治疗前的活检中评估基质TILs的百分比(%TILs)。采用最小绝对收缩和选择算子及交叉验证(CV)的线性回归方法建立预测模型,以残余癌负担作为因变量。使用受试者工作特征曲线下面积(AUC)评估病理完全缓解(pCR)的辨别能力。我们使用Cox回归分析来探讨%TILs与无复发生存期(RFS)之间的关联。
51例患者达到pCR。在所有患者中,%TILs模型和MRI肿瘤负荷变化模型的估计CV AUC分别为0.69(95%置信区间(CI)0.53 - 0.78)和0.69(95% CI 0.61 - 0.79),而将这两个变量结合的模型估计CV AUC为0.75(95% CI 0.66 - 0.83)。在雌激素受体阳性且人表皮生长因子受体2阴性(ER+/HER2-)的肿瘤组和三阴性或人表皮生长因子受体2阳性(TN&HER2+)的肿瘤组中,联合模型的估计CV AUC分别为0.72(95% CI 0.60 - 0.88)和0.70(95% CI 0.59 - 0.82)。观察到治疗前%TILS与RFS之间存在显著关联(风险比(HR)0.72(95% CI 0.53 - 0.98),%TILS每增加一个标准差,p = 0.038)。
TILs与MRI的联合使用有助于评估ER+/HER2-和TN&HER2+肿瘤患者对NAC的反应。