Intercellular signaling stabilizes single-cell level phenotypic transitions and accelerates the reestablishment of equilibrium of heterogeneous cancer cell populations

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. Our inference approach reveals that signaling interactions between cancerous cells in small cell lung cancer (SCLC) result in seemingly contradictory behaviors, reinforcing the cellular phenotypes and maintaining 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 reinforce its phenotype, further promoting the intratumoral heterogeneity. We use a mathematical model based on ordinary differential equations to show that inter-subtype communication accelerates the development of heterogeneous tumor populations. 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.