Computationally Derived Spatial Immune Signature Identifies Trastuzumab Responders in HER2+ Breast Cancer: NSABP B-41 Clinical Trial Validation.

Predictive signatures are needed to identify patients most likely to respond to these therapies.

需要预测性标志物来识别最有可能对这些治疗产生反应的患者。

experimental_design

We developed Density and Spatial architecture of Tumor-Infiltrating Lymphocytes (DeSTIL), a computational signature derived from hematoxylin and eosin slides.

我们开发了基于苏木精和伊红染色切片的肿瘤浸润淋巴细胞密度和空间结构（DeSTIL）计算签名。

The signature captures spatial organization of immune cells and interactions with nonimmune cells.

该签名捕捉了免疫细胞的空间组织以及与非免疫细胞的相互作用。

DeSTIL was trained on HER2+ breast cancer slides from The Cancer Genome Atlas (n = 250) and validated in a phase III National Surgical Adjuvant Breast and Bowel Project (NSABP) B-41 randomized clinical trial (n = 221), which compared chemotherapy plus trastuzumab, lapatinib, or combination.

DeSTIL 在癌症基因组图谱（The Cancer Genome Atlas）的 HER2 阳性乳腺癌切片（n = 250）上进行了训练，并在一项 III 期的国家外科辅助乳腺和肠道项目（NSABP）B-41 随机临床试验（n = 221）中进行了验证，该试验比较了化疗联合曲妥珠单抗、拉帕替尼或联合治疗。

The DeSTIL scores were dichotomized into positive and negative groups, and event-free survival (EFS) was assessed using Cox proportional hazards with interaction terms.

DeSTIL 评分被二分化为阳性组和阴性组，并使用包含交互项的Cox比例风险模型评估了无事件生存（EFS）。

Results

In NSABP B-41, DeSTIL-positive patients (n = 61) showed significantly improved event-free survival (EFS) with trastuzumab compared with the combination arm [hazard ratio(HR) = 0.09; 95% confidence interval(CI) = 0.01-0.77; P = 0.006] and a significant signature-treatment interaction (P = 0.024).

在NSABP B-41研究中，DeSTIL阳性患者（n = 61）在接受曲妥珠单抗治疗后，与联合治疗组相比，无事件生存期（EFS）显著改善[风险比（HR）= 0.09；95%置信区间（CI）= 0.01-0.77；P = 0.006]，并且存在显著的特征-治疗相互作用（P = 0.024）。

No EFS difference was observed in DeSTIL-negative patients (n = 160).

在DeSTIL阴性患者（n = 160）中，未观察到EFS的差异。

Gene expression analysis supported the image-derived signature stratifying DeSTIL-positive and DeSTIL-negative tumors.

基因表达分析支持了基于图像派生的签名，该签名能够区分DeSTIL阳性与DeSTIL阴性肿瘤。

In an exploratory pathologic complete response analysis, a classifier trained on University Hospitals Cleveland slides achieved AUCs of 0.70 in the training cohort and 0.63 in the trastuzumab arm of the NSABP B-41 validation cohort.

在一项探索性的病理完全缓解分析中，基于克利夫兰大学医院幻灯片训练的分类器，在训练队列中实现了0.70的AUC，在NSABP B-41验证队列的曲妥珠单抗组中实现了0.63的AUC。

Conclusions

DeSTIL identifies a subset of HER2+ patients who derive greater benefit from trastuzumab.

DeSTIL识别出一组HER2+患者，他们从曲妥珠单抗中获得更大的益处。

These findings support the potential of computationally derived immune architecture to inform selection of standard HER2-targeted therapies.

这些发现支持了通过计算方法得到的免疫结构在指导选择标准HER2靶向治疗方面的潜力。