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Reconstruction of single-cell lineage trajectories and identification of diversity in fates during the epithelial-to-mesenchymal transition.
Cheng, Yu-Chen; Zhang, Yun; Tripathi, Shubham; Harshavardhan, B V; Jolly, Mohit Kumar; Schiebinger, Geoffrey; Levine, Herbert; McDonald, Thomas O; Michor, Franziska.
Afiliación
  • Cheng YC; Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215.
  • Zhang Y; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02215.
  • Tripathi S; Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA 02215.
  • Harshavardhan BV; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138.
  • Jolly MK; State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
  • Schiebinger G; Yale Center for Systems and Engineering Immunology and Department of Immunobiology, Yale School of Medicine, New Haven, CT 06510.
  • Levine H; Interdisciplinary Mathematics Initiative, Indian Institute of Science, Bangalore 560012, India.
  • McDonald TO; Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.
  • Michor F; Department of Mathematics, University of British Columbia, Vancouver, BC V6T 1Z2, Canada.
Proc Natl Acad Sci U S A ; 121(32): e2406842121, 2024 Aug 06.
Article en En | MEDLINE | ID: mdl-39093947
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Análisis de la Célula Individual / Transición Epitelial-Mesenquimal Límite: Humans Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Análisis de la Célula Individual / Transición Epitelial-Mesenquimal Límite: Humans Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2024 Tipo del documento: Article