Reconstruction of single- cell lineage trajectories and identification of diversity in fates during the epithelial- to- mesenchymal transition

• 成果类型: Article
• 署名作者: Cheng, Yu - Chen; Zhang, Yun; Tripathi, Shubham; Harshavardhan, B. V.; Jolly, Mohit Kumar; Schiebinger, Geoffrey; Levine, Herbert; Mcdonald, Thomas O.; Michor, Franziska
• 署名单位: Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Chinese Academy of Medical Sciences - Peking Union Medical College; Peking Union Medical College; Cancer Institute & Hospital - CAMS; Yale University; Indian Institute of Science (IISC) - Bangalore; Indian Institute of Science (IISC) - Bangalore; University of British Columbia; Northeastern University; Northeastern University; Harvard University; Massachusetts Institute of Technology (MIT); Broad Institute
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-9080
• DOI: 10.1073/pnas.2406842121
• 发表日期: 2024-08-06
• 关键词: growth-factor-beta; tgf-beta; breast-cancer; emt; expression; hypoxia; resistance; signature; pathways; genomics

摘要

Exploring the complexity of the epithelial- to- mesenchymal transition (EMT) unveils a diversity of potential cell fates; however, the exact timing and mechanisms by which early cell states diverge into distinct EMT trajectories remain unclear. Studying these EMT trajectories through single- cell RNA sequencing is challenging due to the necessity of sacrificing cells for each measurement. In this study, we employed optimal- transport analysis to reconstruct the past trajectories of different cell fates during TGF- beta- induced EMT in the MCF10A cell line. Our analysis revealed three distinct trajectories leading to low EMT, partial EMT, and high EMT states. Cells along the partial EMT trajectory showed substantial variations in the EMT signature and exhibited pronounced stemness. Throughout this EMT trajectory, we observed a consistent downregulation of the EED and EZH2 genes. This finding was validated by recent inhibitor screens of EMT regulators and CRISPR screen studies. Moreover, we applied our analysis of early- phase differential gene expression to gene sets associated with stemness and proliferation, pinpointing ITGB4, LAMA3, and LAMB3 as genes differentially expressed in the initial stages of the partial versus high EMT trajectories. We also found that CENPF, CKS1B, and MKI67 showed significant upregulation in the high EMT trajectory. While the first group of genes aligns with findings from previous studies, our work uniquely pinpoints the precise timing of these upregulations. Finally, the identification of the latter group of genes sheds light on potential cell cycle targets for modulating EMT trajectories. Significance In our study, optimal- transport analysis was used to infer cell- to- cell connections from scRNAseq data, allowing us to predict cell linkages and overcome limitations of sequencing such as the need to sacrifice cells for each measurement. This approach led us to identify diverse EMT responses under uniform treatment, a significant advancement over previous studies limited by the static nature of scRNAseq data. Our analysis identified a broad set of genes involved in the EMT process, uncovering insights such as the upregulation of cell cycle genes in cells predisposed to a high EMT state and the enhancement of cell adhesion marker genes in cells veering toward a partial EMT state.