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机器学习揭示了间质型乳腺癌细胞对基质硬度的适应。

Machine learning reveals mesenchymal breast carcinoma cell adaptation in response to matrix stiffness.

机构信息

ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, Australia.

Institute for Biology and Biomedicine, Lobachevsky State University, Nizhny Novgorod, Russia.

出版信息

PLoS Comput Biol. 2021 Jul 23;17(7):e1009193. doi: 10.1371/journal.pcbi.1009193. eCollection 2021 Jul.

Abstract

Epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition (MET), are believed to play key roles in facilitating the metastatic cascade. Metastatic lesions often exhibit a similar epithelial-like state to that of the primary tumour, in particular, by forming carcinoma cell clusters via E-cadherin-mediated junctional complexes. However, the factors enabling mesenchymal-like micrometastatic cells to resume growth and reacquire an epithelial phenotype in the target organ microenvironment remain elusive. In this study, we developed a workflow using image-based cell profiling and machine learning to examine morphological, contextual and molecular states of individual breast carcinoma cells (MDA-MB-231). MDA-MB-231 heterogeneous response to the host organ microenvironment was modelled by substrates with controllable stiffness varying from 0.2kPa (soft tissues) to 64kPa (bone tissues). We identified 3 distinct morphological cell types (morphs) varying from compact round-shaped to flattened irregular-shaped cells with lamellipodia, predominantly populating 2-kPa and >16kPa substrates, respectively. These observations were accompanied by significant changes in E-cadherin and vimentin expression. Furthermore, we demonstrate that the bone-mimicking substrate (64kPa) induced multicellular cluster formation accompanied by E-cadherin cell surface localisation. MDA-MB-231 cells responded to different substrate stiffness by morphological adaptation, changes in proliferation rate and cytoskeleton markers, and cluster formation on bone-mimicking substrate. Our results suggest that the stiffest microenvironment can induce MET.

摘要

上皮-间充质转化(EMT)及其逆转过程,间充质-上皮转化(MET),被认为在促进转移级联中发挥关键作用。转移病变通常表现出类似于原发性肿瘤的上皮样状态,特别是通过 E-钙粘蛋白介导的连接复合物形成癌细簇。然而,使间充质样微转移细胞在靶器官微环境中恢复生长并重新获得上皮表型的因素仍然难以捉摸。在这项研究中,我们使用基于图像的细胞分析和机器学习开发了一种工作流程,以检查单个乳腺癌细胞(MDA-MB-231)的形态、上下文和分子状态。MDA-MB-231 对宿主器官微环境的异质反应通过从 0.2kPa(软组织)到 64kPa(骨骼组织)的可控硬度的基质来模拟。我们确定了 3 种不同的形态细胞类型(形态),从紧凑的圆形到扁平的不规则形状的细胞,带有片状伪足,主要分别填充在 2kPa 和>16kPa 的基质上。这些观察结果伴随着 E-钙粘蛋白和波形蛋白表达的显著变化。此外,我们证明,类似于骨骼的基质(64kPa)诱导了细胞表面定位的多细胞簇形成。MDA-MB-231 细胞通过形态适应、增殖率和细胞骨架标志物的变化以及在骨骼模拟基质上的簇形成对不同的基质硬度做出反应。我们的结果表明,最硬的微环境可以诱导 MET。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e99/8336795/52556e59bc63/pcbi.1009193.g001.jpg

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