PO.ET03.06 · 实验与分子治疗
戈沙妥珠单抗在乳腺癌模型中治疗反应的决定因素
Determinants of sacituzumab govitecan therapeutic response in breast cancer models
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
本研究确定了三阴性乳腺癌(TNBC)模型中戈沙妥珠单抗(SG)反应的标志物,并引入了新的SG获得性耐药患者来源异种移植(PDX),可作为患者获得性突变或基因调控改变的范例,这些改变赋予对该靶向疗法的耐药。SG是一种抗体药物偶联物(ADC),已获批用于治疗初始治疗后进展的TNBC和雌激素受体阳性乳腺癌。SG结合TROP2并递送SN-38作为其载荷;对SG的耐药可能由抗体内化效率低下或载荷疗效缺乏所致。我们假设个体的内在和获得性SG耐药机制将揭示可靶向以延长SG反应持续时间的特征。使用线性混合效应模型,我们将PDX在体内对SG的反应映射到其RNA表达,以确定区分SG反应的基因表达差异;在此过程中开发了初步的SG反应预测器。通过对先前SG敏感的PDX施用次优和持续的SG治疗,我们创建了获得性SG耐药(SGR)模型。然后,我们比较了这些同基因配对PDX之间的RNA表达,以确定获得性耐药机制和患者中常见的耐药通路。对配对组进行抗体内化实验使我们能够研究抗体或包封介导的耐药是否是肿瘤持续生长的原因。短期SN38测试用于界定配对模型中载荷耐药的程度。通过这些努力,我们确定了9个SG敏感和3个内在耐药的TNBC PDX,其差异表达使我们聚焦于13个预测SG反应的基因。三个最敏感的模型被用于创建获得性耐药模型,目前正在进行分析,利用bulk和单细胞RNA测序、蛋白质组学和细胞毒化合物筛选将它们与内在耐药模型进行比较。具有先天SG耐药的PDX的RNA测序界定了与细胞外基质、血管生成和金属离子转运相关的基因表达差异。相反,获得性耐药模型显示出耐药机制的多样性,其中显著包括细胞外基质蛋白合成增强。正在进行的研究旨在界定这些机制,以便优先考虑克服SG耐药的候选疗法。总之,已开发出初步的SG耐药特征,我们将对其进行完善以用于临床选择接受SG治疗的患者。此外,在获得性SG耐药过程中激活了若干生物学过程,可能可作为靶点。
查看英文原文 English abstract
This study identifies markers of Sacituzumab Govitecan (SG) response in triple-negative breast cancer (TNBC) models and introduces new SG acquired resistance patient derived xenografts (PDXs) that can serve as examples of patient-acquired mutations or gene regulation changes that confer resistance to this targeted therapy. SG is an antibody drug conjugate (ADC) that has been approved for treating TNBC and estrogen receptor positive breast cancers that have progressed on initial treatments. SG binds to TROP2 and delivers SN-38 as its payload; resistance to SG could be due to inefficient antibody internalization or lack of payload efficacy. We hypothesize that individual intrinsic and acquired SG resistance mechanisms will uncover features that can be targeted to extend the duration of response to SG. Using a linear mixed effects model, we mapped PDX responses to SG in vivo to their RNA expression in order to identify differences in gene expression that stratify SG response; developing an initial SG response predictor in this process. By administering suboptimal and continuous SG treatments to formerly SG-sensitive PDXs, we created acquired SG resistant (SGR) models. We then compared the RNA expression between these syngeneic pairs of PDXs to identify acquired resistance mechanisms and common pathways of resistance in patients. Performing antibody internalization assays on the paired sets allowed us to investigate if antibody or encapsulation mediated resistance was responsible for the continued tumor growth. Short-term SN38 testing was used to define the extent of payload resistance in paired models. Through these efforts, we identified 9 SG-sensitive and 3 intrinsically resistant TNBC PDXs whose differential expression led us to focus on 13 genes that predict SG response. Three of the most sensitive models were used to create acquired resistance models and analysis is underway to compare these to the intrinsic resistance models utilizing bulk and single-cell RNA-sequencing, proteomics, and cytotoxic compound screens. RNA sequencing of PDXs with innate SG resistance defined differences in gene expression related to extracellular matrix, angiogenesis, and metal ion trafficking. Conversely, acquired resistance models show diversity in resistance mechanisms including notably heightened extracellular matrix protein synthesis. Ongoing studies aim to define these mechanisms so that candidate therapeutics can be prioritized to overcome SG resistance. In conclusion, a preliminary SG resistance signature has been developed, which we will refine for clinical selection of patients to be treated with SG. Additionally, several biological processes are activated during acquired SG resistance and may be targetable.
利益披露 Disclosure
C. J. Walker, None..
N. Dashti-Gibson, None..
J. E. Altman, None..
R. K. Myrick, None..
E. K. Zboril, None..
O. M. Smith, None..
D. C. Boyd, None..
B. Hu, None..
M. G. Dozmorov, None..
J. C. Harrell, None.