{"doi":"10.1073/pnas.2406842121","title":"Reconstruction of single-cell lineage trajectories and identification of diversity in fates during the epithelial-to-mesenchymal transition","abstract":"<jats:p>\n                    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\n                    <jats:italic>EED</jats:italic>\n                    and\n                    <jats:italic>EZH2</jats:italic>\n                    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\n                    <jats:italic>ITGB4</jats:italic>\n                    ,\n                    <jats:italic>LAMA3</jats:italic>\n                    , and\n                    <jats:italic>LAMB3</jats:italic>\n                    as genes differentially expressed in the initial stages of the partial versus high EMT trajectories. We also found that\n                    <jats:italic>CENPF</jats:italic>\n                    ,\n                    <jats:italic>CKS1B</jats:italic>\n                    , and\n                    <jats:italic>MKI67</jats:italic>\n                    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.\n                  </jats:p>","journal":"Proceedings of the National Academy of Sciences","year":2024,"id":640217,"datarank":0.4636563680037475,"base_score":3.091042453358316,"endowment":3.091042453358316,"self_citation_contribution":0.4636563680037475,"citation_network_contribution":0.0,"self_endowment_contribution":0.4636563680037475,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":21,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":753259,"name":"Yun Zhang","orcid":"0000-0002-9837-1365","position":1,"is_corresponding":false},{"id":267403,"name":"Shubham Tripathi","orcid":"0000-0002-0141-987X","position":2,"is_corresponding":false},{"id":1663836,"name":"B. V. Harshavardhan","orcid":null,"position":3,"is_corresponding":false},{"id":243172,"name":"Mohit Kumar Jolly","orcid":"0000-0002-6631-2109","position":4,"is_corresponding":false},{"id":48123,"name":"Geoffrey Schiebinger","orcid":"0000-0002-8290-7997","position":5,"is_corresponding":false},{"id":267404,"name":"Herbert Levine","orcid":"0000-0002-8819-9055","position":6,"is_corresponding":false},{"id":444986,"name":"Thomas O. McDonald","orcid":"0000-0002-5272-0187","position":7,"is_corresponding":false},{"id":565018,"name":"Franziska Michor","orcid":"0000-0003-4869-8842","position":8,"is_corresponding":false},{"id":1091293,"name":"Yu-Chen Cheng","orcid":"0000-0003-1869-4760","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Reconstruction of single-cell lineage trajectories and identification of diversity in fates during the epithelial-to-mesenchymal transition","abstract":"<jats:p>\n                    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\n                    <jats:italic>EED</jats:italic>\n                    and\n                    <jats:italic>EZH2</jats:italic>\n                    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\n                    <jats:italic>ITGB4</jats:italic>\n                    ,\n                    <jats:italic>LAMA3</jats:italic>\n                    , and\n                    <jats:italic>LAMB3</jats:italic>\n                    as genes differentially expressed in the initial stages of the partial versus high EMT trajectories. We also found that\n                    <jats:italic>CENPF</jats:italic>\n                    ,\n                    <jats:italic>CKS1B</jats:italic>\n                    , and\n                    <jats:italic>MKI67</jats:italic>\n                    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.\n                  </jats:p>","is_dataset_classified":null,"base_score":3.091042453358316,"endowment":3.091042453358316,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"39093947","pmcid":"PMC11317558","openalex_id":"https://openalex.org/W4401246969","authors":[],"funders":[{"funder_name":"National Science Foundation","grant_id":"PHY-2019745","title":null}],"total_grants":1,"fwci":3.3711,"citation_percentile":0.93532957,"influential_citations":0,"citation_trend":[{"year":2024,"count":5},{"year":2025,"count":12},{"year":2026,"count":4}],"oa_status":"hybrid","license":"cc-by-nc-nd","oa_locations":[{"url":"https://www.pnas.org/doi/pdf/10.1073/pnas.2406842121","host_type":"journal"},{"url":"https://www.pnas.org/doi/pdf/10.1073/pnas.2406842121","host_type":"publisher"},{"url":"https://pnas.org/doi/pdf/10.1073/pnas.2406842121","host_type":"publisher"},{"url":"https://doi.org/10.1073/pnas.2406842121","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/39093947","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11317558","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11317558/pdf/pnas.202406842.pdf","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC11317558","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC11317558?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Single-cell and spatial transcriptomics","Cancer Cells and Metastasis","Cancer Genomics and Diagnostics"],"mesh_terms":["Enhancer of Zeste Homolog 2 Protein","Humans","Transforming Growth Factor beta","Cell Lineage","Epithelial-Mesenchymal Transition","Single-Cell Analysis"],"keywords":["Epithelial–mesenchymal transition","Biology","Downregulation and upregulation","Transcriptome","Gene","Computational biology","Cell","Cell cycle","Cell biology","Gene expression","Genetics","Cell Fate","Emt","Scrna-seq"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Life below water"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"bioproject"},{"name":"geo"},{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-07T08:06:03.761528Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}