Jain Paras, Kizhuttil Ramanarayanan, Nair Madhav B, Bhatia Sugandha, Thompson Erik W, George Jason T, Jolly Mohit Kumar
Department of Bioengineering, Indian Institute of Science, Bangalore, India.
Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA.
iScience. 2024 Jun 19;27(7):110310. doi: 10.1016/j.isci.2024.110310. eCollection 2024 Jul 19.
Cancer cell populations comprise phenotypes distributed among the epithelial-mesenchymal (E-M) spectrum. However, it remains unclear which population-level processes give rise to the observed experimental distribution and dynamical changes in E-M heterogeneity, including (1) differential growth, (2) cell-state switching, and (3) population density-dependent growth or state-transition rates. Here, we analyze the necessity of these three processes in explaining the dynamics of E-M population distributions as observed in PMC42-LA and HCC38 breast cancer cells. We find that, while cell-state transition is necessary to reproduce experimental observations of dynamical changes in E-M fractions, including density-dependent growth interactions (cooperation or suppression) better explains the data. Further, our models predict that treatment of HCC38 cells with transforming growth factor β (TGF-β) signaling and Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/3) inhibitors enhances the rate of mesenchymal-epithelial transition (MET) instead of lowering that of E-M transition (EMT). Overall, our study identifies the population-level processes shaping the dynamics of spontaneous E-M heterogeneity in breast cancer cells.
癌细胞群体包含分布于上皮-间质（E-M）谱系中的多种表型。然而，目前尚不清楚是哪些群体水平的过程导致了观察到的实验分布以及E-M异质性的动态变化，这些过程包括：（1）差异生长；（2）细胞状态转换；以及（3）群体密度依赖性生长或状态转换率。在此，我们分析了这三个过程对于解释在PMC42-LA和HCC38乳腺癌细胞中观察到的E-M群体分布动态的必要性。我们发现，虽然细胞状态转变对于重现E-M组分动态变化的实验观察结果是必要的，但包括密度依赖性生长相互作用（协同或抑制）在内的因素能更好地解释这些数据。此外，我们的模型预测，用转化生长因子β（TGF-β）信号传导抑制剂和Janus激酶2/信号转导及转录激活因子3（JAK2/3）抑制剂处理HCC38细胞会提高间质-上皮转变（MET）的速率，而不是降低上皮-间质转变（EMT）的速率。总体而言，我们的研究确定了塑造乳腺癌细胞中自发E-M异质性动态的群体水平过程。
