Understanding the organ tropism of metastatic breast cancer through the combination of liquid biopsy tools
Understanding the organ tropism of metastatic breast cancer through the combination of liquid biopsy tools
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DOI：
10.1016/j.ejca.2020.11.005
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发表时间：
2021-01-01
影响因子：
8.4
通讯作者：
Cristofanilli, Massimo
中科院分区：
文献类型：
--
作者：
Gerratana, Lorenzo;Davis, Andrew A.;Cristofanilli, Massimo
背景：液体活检提供了关于转移性乳腺癌（MBC）预后和可操作突变的实时数据。本研究的目的是探讨结合循环肿瘤DNA（ctDNA）分析和循环肿瘤细胞（CTC）计数估计靶器官更容易MBC involvement.Methods：这项回顾性研究分析了88 MBC患者的特点，为CTC和ctDNA在基线。通过CellSearch试剂盒分离CTC，同时使用基于Guardant360 NGS的测定分析ctDNA。根据成像收集疾病部位。通过单因素和多因素Logistic回归和Fisher精确检验以及随机森林机器学习算法探讨了相关性。结果：多因素Logistic回归后，ESR1突变是与肝转移相关的唯一显著因素（OR 8.10），而PIK3CA与肺定位相关（OR 3.74）。CTC计数与骨转移独立相关（OR 10.41），TP 53与淋巴结定位相关（OR 2.98）。通过随机森林机器学习算法进一步研究了转移行为。通过CTC计数和ESR1、GATA3、KIT、CDK4和ERBB2的改变描述骨受累，而亚型、CTC计数、炎性BC诊断、ESR1和KIT畸变描述肝转移。PIK3CA、MET、AR、CTC计数和TP 53与肺嗜器官性相关。此外，该模型表明，AR，CCNE1，ESR1，MYC和CTC计数是HR阳性MBC转移pattern.Conclusions的主要驱动因素：这些结果表明，ctDNA和CTC计数可以提供有用的见解MBC器官嗜性，这表明未来的监测策略，动态地集中在高风险器官的肿瘤生物学定义的可能的作用。(C)2020作者（S）爱思唯尔有限公司出版
Background: Liquid biopsy provides real-time data about prognosis and actionable mutations in metastatic breast cancer (MBC). The aim of this study was to explore the combination of circulating tumour DNA (ctDNA) analysis and circulating tumour cells (CTCs) enumeration in estimating target organs more susceptible to MBC involvement.Methods: This retrospective study analysed 88 MBC patients characterised for both CTCs and ctDNA at baseline. CTCs were isolated through the CellSearch kit, while ctDNA was analysed using the Guardant360 NGS-based assay. Sites of disease were collected on the basis of imaging. Associations were explored both through uni- and multivariate logistic regression and Fisher's exact test and the random forest machine learning algorithm.Results: After multivariate logistic regression, ESR1 mutation was the only significant factor associated with liver metastases (OR 8.10), while PIK3CA was associated with lung localisations (OR 3.74). CTC enumeration was independently associated with bone metastases (OR 10.41) and TP53 was associated with lymph node localisations (OR 2.98). The metastatic behaviour was further investigated through a random forest machine learning algorithm. Bone involvement was described by CTC enumeration and alterations in ESR1, GATA3, KIT, CDK4 and ERBB2, while subtype, CTC enumeration, inflammatory BC diagnosis, ESR1 and KIT aberrations described liver metastases. PIK3CA, MET, AR, CTC enumeration and TP53 were associated with lung organotropism. The model, moreover, showed that AR, CCNE1, ESR1, MYC and CTC enumeration were the main drivers in HR positive MBC metastatic pattern.Conclusions: These results indicate that ctDNA and CTCs enumeration could provide useful insights regarding MBC organotropism, suggesting a possible role for future monitoring strategies that dynamically focus on high-risk organs defined by tumourbiology. (C) 2020 The Author(s). Published by Elsevier Ltd.