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Hong T, Xing J. Data- and theory-driven approaches for understanding paths of epithelial-mesenchymal transition. Genesis 2024; 62:e23591. [PMID: 38553870 PMCID: PMC11017362 DOI: 10.1002/dvg.23591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 02/16/2024] [Accepted: 03/16/2024] [Indexed: 04/02/2024]
Abstract
Reversible transitions between epithelial and mesenchymal cell states are a crucial form of epithelial plasticity for development and disease progression. Recent experimental data and mechanistic models showed multiple intermediate epithelial-mesenchymal transition (EMT) states as well as trajectories of EMT underpinned by complex gene regulatory networks. In this review, we summarize recent progress in quantifying EMT and characterizing EMT paths with computational methods and quantitative experiments including omics-level measurements. We provide perspectives on how these studies can help relating fundamental cell biology to physiological and pathological outcomes of EMT.
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Affiliation(s)
- Tian Hong
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, Knoxville TN, USA
| | - Jianhua Xing
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
- UPMC-Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA, USA
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Groves SM, Panchy N, Tyson DR, Harris LA, Quaranta V, Hong T. Involvement of Epithelial-Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity. Cancers (Basel) 2023; 15:1477. [PMID: 36900269 PMCID: PMC10001072 DOI: 10.3390/cancers15051477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 02/16/2023] [Accepted: 02/20/2023] [Indexed: 03/03/2023] Open
Abstract
Small cell lung cancer (SCLC) is an aggressive cancer recalcitrant to treatment, arising predominantly from epithelial pulmonary neuroendocrine (NE) cells. Intratumor heterogeneity plays critical roles in SCLC disease progression, metastasis, and treatment resistance. At least five transcriptional SCLC NE and non-NE cell subtypes were recently defined by gene expression signatures. Transition from NE to non-NE cell states and cooperation between subtypes within a tumor likely contribute to SCLC progression by mechanisms of adaptation to perturbations. Therefore, gene regulatory programs distinguishing SCLC subtypes or promoting transitions are of great interest. Here, we systematically analyze the relationship between SCLC NE/non-NE transition and epithelial to mesenchymal transition (EMT)-a well-studied cellular process contributing to cancer invasiveness and resistance-using multiple transcriptome datasets from SCLC mouse tumor models, human cancer cell lines, and tumor samples. The NE SCLC-A2 subtype maps to the epithelial state. In contrast, SCLC-A and SCLC-N (NE) map to a partial mesenchymal state (M1) that is distinct from the non-NE, partial mesenchymal state (M2). The correspondence between SCLC subtypes and the EMT program paves the way for further work to understand gene regulatory mechanisms of SCLC tumor plasticity with applicability to other cancer types.
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Affiliation(s)
- Sarah M. Groves
- Department of Biochemistry, Vanderbilt University, Nashville, TN 37235, USA
| | - Nicholas Panchy
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, TN 37996, USA
| | - Darren R. Tyson
- Department of Biochemistry, Vanderbilt University, Nashville, TN 37235, USA
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37235, USA
| | - Leonard A. Harris
- Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA
- Interdisciplinary Graduate Program in Cell and Molecular Biology, University of Arkansas, Fayetteville, AR 72701, USA
- Cancer Biology Program, Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Vito Quaranta
- Department of Biochemistry, Vanderbilt University, Nashville, TN 37235, USA
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37235, USA
| | - Tian Hong
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, TN 37996, USA
- National Institute for Mathematical and Biological Synthesis, Knoxville, TN 37996, USA
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Panchy N, Watanabe K, Takahashi M, Willems A, Hong T. Comparative single-cell transcriptomes of dose and time dependent epithelial–mesenchymal spectrums. NAR Genom Bioinform 2022; 4:lqac072. [PMID: 36159174 PMCID: PMC9492285 DOI: 10.1093/nargab/lqac072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 08/17/2022] [Accepted: 08/31/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
Epithelial–mesenchymal transition (EMT) is a cellular process involved in development and disease progression. Intermediate EMT states were observed in tumors and fibrotic tissues, but previous in vitro studies focused on time-dependent responses with single doses of signals; it was unclear whether single-cell transcriptomes support stable intermediates observed in diseases. Here, we performed single-cell RNA-sequencing with human mammary epithelial cells treated with multiple doses of TGF-β. We found that dose-dependent EMT harbors multiple intermediate states at nearly steady state. Comparisons of dose- and time-dependent EMT transcriptomes revealed that the dose-dependent data enable higher sensitivity to detect genes associated with EMT. We identified cell clusters unique to time-dependent EMT, reflecting cells en route to stable states. Combining dose- and time-dependent cell clusters gave rise to accurate prognosis for cancer patients. Our transcriptomic data and analyses uncover a stable EMT continuum at the single-cell resolution, and complementary information of two types of single-cell experiments.
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Affiliation(s)
- Nicholas Panchy
- Department of Biochemistry & Cellular and Molecular Biology. The University of Tennessee , Knoxville, Knoxville, TN 37996, USA
| | - Kazuhide Watanabe
- RIKEN Center for Integrative Medical Sciences , 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Masataka Takahashi
- RIKEN Center for Integrative Medical Sciences , 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Andrew Willems
- School of Genome Science and Technology, The University of Tennessee , Knoxville, Knoxville, TN 37916, USA
| | - Tian Hong
- Department of Biochemistry & Cellular and Molecular Biology. The University of Tennessee , Knoxville, Knoxville, TN 37996, USA
- National Institute for Mathematical and Biological Synthesis , Knoxville, TN 37996, USA
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