Lopez Daniel, Tyson Darren R, Hong Tian
Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville. Knoxville, Tennessee 37916, USA.
Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Durham, North Carolina 27710, USA.
bioRxiv. 2025 Mar 26:2025.01.03.631250. doi: 10.1101/2025.01.03.631250.
Cancer cells within tumors exhibit a wide range of phenotypic states driven by non-genetic mechanisms in addition to extensively studied genetic alterations. Conversions among cancer cell states can result in intratumoral heterogeneity which contributes to metastasis and development of drug resistance. However, mechanisms underlying the initiation and/or maintenance of such phenotypic plasticity are poorly understood. In particular, the role of intercellular communications in phenotypic plasticity remains elusive.
In this study, we employ a multiscale inference-based approach using single-cell RNA sequencing (scRNA-seq) data to explore how intercellular interactions influence phenotypic dynamics of cancer cells, particularly cancers undergoing epithelial-mesenchymal transition. In addition, we use mathematical models based on our data-driven findings to interrogate the roles of intercellular communications at the cell populations from the viewpoint of dynamical systems.
Our inference approach reveals that signaling interactions between cancerous cells in small cell lung cancer (SCLC) result in the reinforcement of the phenotypic transition in single cells and the maintenance of population-level intratumoral heterogeneity. Additionally, we find a recurring signaling pattern across multiple types of cancer in which the mesenchymal-like subtypes utilize signals from other subtypes to support its new phenotype, further promoting the intratumoral heterogeneity. Our models show that inter-subtype communication both accelerates the development of heterogeneous tumor populations and confers robustness to their steady state phenotypic compositions.
Our work highlights the critical role of intercellular signaling in sustaining intratumoral heterogeneity, and our approach of computational analysis of scRNA-seq data can infer inter- and intra-cellular signaling networks in a holistic manner.
肿瘤内的癌细胞除了具有广泛研究的基因改变外，还表现出由非遗传机制驱动的多种表型状态。癌细胞状态之间的转换可导致肿瘤内异质性，这有助于转移和耐药性的发展。然而，这种表型可塑性的起始和/或维持机制仍知之甚少。特别是，细胞间通讯在表型可塑性中的作用仍然难以捉摸。
在本研究中，我们采用基于多尺度推断的方法，利用单细胞RNA测序（scRNA-seq）数据来探索细胞间相互作用如何影响癌细胞的表型动态，特别是经历上皮-间质转化的癌症。此外，我们基于数据驱动的发现使用数学模型，从动态系统的角度探讨细胞间通讯在细胞群体中的作用。
我们的推断方法表明，小细胞肺癌（SCLC）中癌细胞之间的信号相互作用导致单细胞中表型转变的加强和群体水平肿瘤内异质性的维持。此外，我们在多种类型的癌症中发现了一种反复出现的信号模式，其中间充质样亚型利用来自其他亚型的信号来支持其新表型，进一步促进肿瘤内异质性。我们的模型表明，亚型间通讯既加速了异质性肿瘤群体的发展，又赋予其稳态表型组成以稳健性。
我们的工作强调了细胞间信号在维持肿瘤内异质性中的关键作用，并且我们对scRNA-seq数据的计算分析方法可以整体推断细胞间和细胞内信号网络。
