Predicting breast cancer response to neoadjuvant chemotherapy based on tumor vascular features in needle biopsies
Predicting breast cancer response to neoadjuvant chemotherapy based on tumor vascular features in needle biopsies
复制标题
DOI：
10.1172/jci.insight.126518
复制
发表时间：
2019-04-18
期刊：
影响因子：
8
通讯作者：
Cristin, Vittorio
中科院分区：
文献类型：
--
作者：
Brocato, Terisse A.;Brown-Glaberman, Ursa;Cristin, Vittorio
在临床乳腺癌干预中，基于预测性生物标志物选择最佳治疗方案仍然是一个难以实现的目标。在这里，我们提出了一个建模工具，预测乳腺癌的反应，新辅助化疗的可能性，使用患者特异性肿瘤血管生物标志物。对来自48名患者的3990张组织学图像进行了半自动分析，每位患者分析了10-208张图像。我们应用基于组织学的数学模型对30例切除的原发性乳腺癌肿瘤进行了评估，然后对18例接受新辅助化疗的患者进行了评估，收集了治疗前和治疗后的病理学标本和MRI数据。我们发现，空芯活检样本可以以可接受的准确度用于确定代表整个组织区域的组织学参数。对从肿瘤脉管系统测量获得的模型组织学参数的分析，特别是扩散距离除以药物递送血管的半径（L/r（B））和血容量分数（BVF），提供了获得病理完全缓解（pCR）的患者与未获得病理完全缓解的患者的统计学显著性分离。利用该模型，可以以患者特异性方式评估原发性乳腺肿瘤血管生物标志物，从而实现乳腺癌治疗的精确方法。
In clinical breast cancer intervention, selection of the optimal treatment protocol based on predictive biomarkers remains an elusive goal. Here, we present a modeling tool to predict the likelihood of breast cancer response to neoadjuvant chemotherapy using patient-specific tumor vasculature biomarkers. A semiautomated analysis was implemented and performed on 3990 histological images from 48 patients, with 10-208 images analyzed for each patient. We applied a histology-based mathematical model to 30 resected primary breast cancer tumors and then evaluated a cohort of 18 patients undergoing neoadjuvant chemotherapy, collecting pre- and posttreatment pathology specimens and MRI data. We found that core biopsy samples can be used with acceptable accuracy to determine histological parameters representative of the whole tissue region. Analysis of model histology parameters obtained from tumor vasculature measurements, specifically diffusion distance divided by the radius of the drug-delivering blood vessel (L/r(b)) and blood volume fraction (BVF), provides a statistically significant separation of patients obtaining a pathologic complete response (pCR) from those who do not. With this model, it is feasible to evaluate primary breast tumor vasculature biomarkers in a patient-specific manner, thereby allowing a precision approach to breast cancer treatment.