1
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Jain P, Kizhuttil R, Nair MB, Bhatia S, Thompson EW, George JT, Jolly MK. Cell-state transitions and density-dependent interactions together explain the dynamics of spontaneous epithelial-mesenchymal heterogeneity. iScience 2024; 27:110310. [PMID: 39055927 PMCID: PMC11269952 DOI: 10.1016/j.isci.2024.110310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 04/21/2024] [Accepted: 06/17/2024] [Indexed: 07/28/2024] Open
Abstract
Cancer cell populations comprise phenotypes distributed among the epithelial-mesenchymal (E-M) spectrum. However, it remains unclear which population-level processes give rise to the observed experimental distribution and dynamical changes in E-M heterogeneity, including (1) differential growth, (2) cell-state switching, and (3) population density-dependent growth or state-transition rates. Here, we analyze the necessity of these three processes in explaining the dynamics of E-M population distributions as observed in PMC42-LA and HCC38 breast cancer cells. We find that, while cell-state transition is necessary to reproduce experimental observations of dynamical changes in E-M fractions, including density-dependent growth interactions (cooperation or suppression) better explains the data. Further, our models predict that treatment of HCC38 cells with transforming growth factor β (TGF-β) signaling and Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/3) inhibitors enhances the rate of mesenchymal-epithelial transition (MET) instead of lowering that of E-M transition (EMT). Overall, our study identifies the population-level processes shaping the dynamics of spontaneous E-M heterogeneity in breast cancer cells.
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Affiliation(s)
- Paras Jain
- Department of Bioengineering, Indian Institute of Science, Bangalore, India
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA
| | | | - Madhav B. Nair
- Indian Institute of Science Education and Research, Kolkata, India
| | - Sugandha Bhatia
- School of Biomedical Science, Queensland University of Technology (QUT) at Translational Research Institute, Woolloongabba QLD 4102, Australia
| | - Erik W. Thompson
- Diamantina Institute, The University of Queensland, Brisbane QLD, Australia
| | - Jason T. George
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
| | - Mohit Kumar Jolly
- Department of Bioengineering, Indian Institute of Science, Bangalore, India
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2
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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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3
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Quinsgaard EMB, Korsnes MS, Korsnes R, Moestue SA. Single-cell tracking as a tool for studying EMT-phenotypes. Exp Cell Res 2024; 437:113993. [PMID: 38485079 DOI: 10.1016/j.yexcr.2024.113993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 02/28/2024] [Accepted: 03/06/2024] [Indexed: 03/24/2024]
Abstract
This article demonstrates that label-free single-cell video tracking is a useful approach for in vitro studies of Epithelial-Mesenchymal Transition (EMT). EMT is a highly heterogeneous process, involved in wound healing, embryogenesis and cancer. The process promotes metastasis, and increased understanding can aid development of novel therapeutic strategies. The role of EMT-associated biomarkers depends on biological context, making it challenging to compare and interpret data from different studies. We demonstrate single-cell video tracking for comprehensive phenotype analysis. In this study we performed single-cell video tracking on 72-h long recordings. We quantified several behaviours at a single-cell level during induced EMT in MDA-MB-468 cells. This revealed notable variations in migration speed, with different dose-response patterns and varying distributions of speed. By registering cell morphologies during the recording, we determined preferred paths of morphological transitions. We also found a clear association between migration speed and cell morphology. We found elevated rates of cell death, diminished proliferation, and an increase in mitotic failures followed by re-fusion of sister-cells. The method allows tracking of phenotypes in cell lineages, which can be particularly useful in epigenetic studies. Sister-cells were found to have significant similarities in their speeds and morphologies, illustrating the heritability of these traits.
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Affiliation(s)
- Ellen Marie Botne Quinsgaard
- Norwegian University of Science and Technology (NTNU), Department of Clinical and Molecular Medicine, NO-7491 Trondheim, Norway.
| | - Mónica Suárez Korsnes
- Norwegian University of Science and Technology (NTNU), Department of Clinical and Molecular Medicine, NO-7491 Trondheim, Norway; Korsnes Biocomputing (KoBio), Trondheim, Norway
| | | | - Siver Andreas Moestue
- Norwegian University of Science and Technology (NTNU), Department of Clinical and Molecular Medicine, NO-7491 Trondheim, Norway; Department of Pharmacy, Nord University, Bodø, Norway
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4
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Li T, Xing S, Liu Y. Simultaneous Proximity DNAzyme-Activated Duplexed Protein-Specific Glycosylation Imaging on Cell Surface via Bioorthogonal Chemistry. Anal Chem 2023; 95:17790-17797. [PMID: 37994926 DOI: 10.1021/acs.analchem.3c03869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Due to the scarcity of strategies to evaluate the multiple subtype monosaccharides in one specific protein simultaneously within a single assay, understanding the glycosylation mechanisms and revealing their roles in disease development become extremely challenging. Herein, a strategy of proximity DNAzyme-activated fluorescence imaging of multiplex saccharides in a protein on the cell surface via bio-orthogonal chemistry is reported. The multichannel proximity DNAzyme-activated fluorescence recovery enabled the highly selective and effective imaging analysis of multiplexed protein-specific glycosylation in situ and has been demonstrated. This strategy is successfully applied to visualize the sialylation and fucosylation in four specific proteins on different cell lines and evaluate the variations of protein-specific glycosylation in response to the alterations of the cellular physiological status. More importantly, the quantitative tracking of the terminal sialyation and fucosylation changes at the single-protein level is realized by assigning the target protein as the native reference, which has the potential to be a versatile platform for glycobiology research and clinical diagnosis.
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Affiliation(s)
- Ting Li
- Department of Chemistry, Beijing Key Laboratory for Analytical Methods and Instrumentation, Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology of Ministry of Education, Tsinghua University, Beijing 100084, P. R. China
| | - Simin Xing
- Department of Chemistry, Beijing Key Laboratory for Analytical Methods and Instrumentation, Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology of Ministry of Education, Tsinghua University, Beijing 100084, P. R. China
| | - Yang Liu
- Department of Chemistry, Beijing Key Laboratory for Analytical Methods and Instrumentation, Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology of Ministry of Education, Tsinghua University, Beijing 100084, P. R. China
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5
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Gunnarsson EB, Foo J, Leder K. Statistical inference of the rates of cell proliferation and phenotypic switching in cancer. J Theor Biol 2023; 568:111497. [PMID: 37087049 PMCID: PMC10372878 DOI: 10.1016/j.jtbi.2023.111497] [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: 09/26/2022] [Revised: 02/21/2023] [Accepted: 04/12/2023] [Indexed: 04/24/2023]
Abstract
Recent evidence suggests that nongenetic (epigenetic) mechanisms play an important role at all stages of cancer evolution. In many cancers, these mechanisms have been observed to induce dynamic switching between two or more cell states, which commonly show differential responses to drug treatments. To understand how these cancers evolve over time, and how they respond to treatment, we need to understand the state-dependent rates of cell proliferation and phenotypic switching. In this work, we propose a rigorous statistical framework for estimating these parameters, using data from commonly performed cell line experiments, where phenotypes are sorted and expanded in culture. The framework explicitly models the stochastic dynamics of cell division, cell death and phenotypic switching, and it provides likelihood-based confidence intervals for the model parameters. The input data can be either the fraction of cells or the number of cells in each state at one or more time points. Through a combination of theoretical analysis and numerical simulations, we show that when cell fraction data is used, the rates of switching may be the only parameters that can be estimated accurately. On the other hand, using cell number data enables accurate estimation of the net division rate for each phenotype, and it can even enable estimation of the state-dependent rates of cell division and cell death. We conclude by applying our framework to a publicly available dataset.
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Affiliation(s)
- Einar Bjarki Gunnarsson
- Department of Industrial and Systems Engineering, University of Minnesota, Twin Cities, MN 55455, USA; School of Mathematics, University of Minnesota, Twin Cities, MN 55455, USA.
| | - Jasmine Foo
- School of Mathematics, University of Minnesota, Twin Cities, MN 55455, USA
| | - Kevin Leder
- Department of Industrial and Systems Engineering, University of Minnesota, Twin Cities, MN 55455, USA
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6
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Subhadarshini S, Markus J, Sahoo S, Jolly MK. Dynamics of Epithelial-Mesenchymal Plasticity: What Have Single-Cell Investigations Elucidated So Far? ACS OMEGA 2023; 8:11665-11673. [PMID: 37033874 PMCID: PMC10077445 DOI: 10.1021/acsomega.2c07989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/06/2023] [Indexed: 06/19/2023]
Abstract
Epithelial-mesenchymal plasticity (EMP) is a key driver of cancer metastasis and therapeutic resistance, through which cancer cells can reversibly and dynamically alter their molecular and functional traits along the epithelial-mesenchymal spectrum. While cells in the epithelial phenotype are usually tightly adherent, less metastatic, and drug-sensitive, those in the hybrid epithelial/mesenchymal and/or mesenchymal state are more invasive, migratory, drug-resistant, and immune-evasive. Single-cell studies have emerged as a powerful tool in gaining new insights into the dynamics of EMP across various cancer types. Here, we review many recent studies that employ single-cell analysis techniques to better understand the dynamics of EMP in cancer both in vitro and in vivo. These single-cell studies have underlined the plurality of trajectories cells can traverse during EMP and the consequent heterogeneity of hybrid epithelial/mesenchymal phenotypes seen at both preclinical and clinical levels. They also demonstrate how diverse EMP trajectories may exhibit hysteretic behavior and how the rate of such cell-state transitions depends on the genetic/epigenetic background of recipient cells, as well as the dose and/or duration of EMP-inducing growth factors. Finally, we discuss the relationship between EMP and patient survival across many cancer types. We also present a next set of questions related to EMP that could benefit much from single-cell observations and pave the way to better tackle phenotypic switching and heterogeneity in clinic.
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Affiliation(s)
| | - Joel Markus
- Centre
for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Sarthak Sahoo
- Centre
for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Mohit Kumar Jolly
- Centre
for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
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7
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Mohan S, Wal P, Pathak K, Khandai M, Behl T, Alhazmi HA, Khuwaja G, Khalid A. Nanosilver-functionalized polysaccharides as a platform for wound dressing. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:54385-54406. [PMID: 36961636 DOI: 10.1007/s11356-023-26450-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 03/10/2023] [Indexed: 06/18/2023]
Abstract
Polysaccharides that are naturally sourced have enormous promise as wound dressings, due to their wider availability and reasonable cost and good biocompatibility. Furthermore, nanosilver extensively applied in wound treatment is attributed to its broad spectrum of antimicrobial effects and lesser drug resistance. Consequently, wound dressings in corporating nanosilver have attracted wide-scale interest in wound healing, and nanosilver-functionalized polysaccharide-based wound dressings present an affordable option for healing of chronic wounds. This review encompasses preparation methods, classification, and antibacterial performances of nanosilver wound dressings. The prospective research arenas of nanosilver-based wound polysaccharide dressings are also elaborated. The review attempts to include a summary of the most recent advancements in silver nanotechnology as well as guidance for the investigation of nanosilver-functionalized polysaccharide-based wound dressings.
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Affiliation(s)
- Syam Mohan
- School of Health Sciences, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India
- Substance Abuse and Toxicology Research Centre, Jazan University, Jazan, Saudi Arabia
- Center for Transdisciplinary Research, Department of Pharmacology, Saveetha Dental College, Saveetha Institute of Medical and Technical Science, Saveetha University, Chennai, India
| | - Pranay Wal
- Pharmacy, Pranveer Singh Institute of Technology, National Highway-2, Bhauti Road, Kanpur, India
| | - Kamla Pathak
- Faculty of Pharmacy, Uttar Pradesh University of Medical Sciences, Etawah, India
| | | | - Tapan Behl
- School of Health Sciences, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.
| | - Hassan A Alhazmi
- Substance Abuse and Toxicology Research Centre, Jazan University, Jazan, Saudi Arabia
- Department of Pharmaceutical Chemistry and Pharmacognosy, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
| | - Gulrana Khuwaja
- Department of Pharmaceutical Chemistry and Pharmacognosy, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
| | - Asaad Khalid
- Substance Abuse and Toxicology Research Centre, Jazan University, Jazan, Saudi Arabia
- Medicinal and Aromatic Plants and Traditional Medicine Research Institute, National Center for Research, P. O. Box 2404, Khartoum, Sudan
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8
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Li M, Wu S, Zhuang C, Shi C, Gu L, Wang P, Guo F, Wang Y, Liu Z. Metabolomic analysis of circulating tumor cells derived liver metastasis of colorectal cancer. Heliyon 2022; 9:e12515. [PMID: 36691542 PMCID: PMC9860459 DOI: 10.1016/j.heliyon.2022.e12515] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 08/17/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
Metabolic reprogramming is one of the essential features of tumor that may dramatically contribute to metastasis and collapse. The metabolic profiling is investigated on the patient derived tissue and cancer cell line derived mouse metastasis xenograft. As well-recognized "seeds" for remote metastasis of tumor, role of circulating tumor cells (CTCs) in the study of metabolic reprogramming feature of tumor is yet to be elucidated. More specifically, whether there is difference of metabolic features of liver metastasis in colorectal cancer (CRC) derived from either CTCs or cancer cell line is still unknown. In this study, comprehensive untargeted metabolomics was performed using high performance liquid chromatography-mass spectrometry (HPLC-MS) in liver metastasis tissues from CT26 cells and CTCs derived mouse models. We identified 288 differential metabolites associated with the pathways such as one carbon pool by folate, folate biosynthesis and histidine metabolism through bioinformation analysis. Multiple gene expression was upregulated in the CTCs derived liver metastasis, specifically some specific enzymes. These results indicated that the metabolite phenotype and corresponding gene expression in the CTCs derived liver metastasis tissues was different from the parental CT26 cells, displaying a specific up-regulation of mRNAs involved in the above metabolism-related pathways. The metabolic profile of CTCs was characterized on the liver metastatic process in colorectal cancer. The invasion ability and chemo drug tolerance of the CTCs derived tumor and metastasis was found to be overwhelming higher than cell line derived counterpart. Identification of the differential metabolites will lead to a better understanding of the hallmarks of the cancer progression and metastasis, which may suggest potential attractive target for treating metastatic CRC.
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Affiliation(s)
- Meng Li
- Department of General Surgery, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200092, PR China
| | - Shengming Wu
- The Institute for Translational Nanomedicine, Shanghai East Hospital, The Institute for Biomedical Engineering & Nano Science, School of Medicine, Tongji University, Shanghai 200092, PR China
| | - Chengle Zhuang
- Department of General Surgery, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200092, PR China
| | - Chenzhang Shi
- Department of General Surgery, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200092, PR China
| | - Lei Gu
- Department of General Surgery, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200092, PR China
| | - Peng Wang
- The Institute for Translational Nanomedicine, Shanghai East Hospital, The Institute for Biomedical Engineering & Nano Science, School of Medicine, Tongji University, Shanghai 200092, PR China
| | - Fangfang Guo
- The Institute for Translational Nanomedicine, Shanghai East Hospital, The Institute for Biomedical Engineering & Nano Science, School of Medicine, Tongji University, Shanghai 200092, PR China
| | - Yilong Wang
- The Institute for Translational Nanomedicine, Shanghai East Hospital, The Institute for Biomedical Engineering & Nano Science, School of Medicine, Tongji University, Shanghai 200092, PR China,Corresponding author.
| | - Zhongchen Liu
- Department of General Surgery, Shanghai Tenth People’s Hospital, School of Medicine, Tongji University, Shanghai 200092, PR China,Corresponding author.
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9
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Xing J. Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology. Phys Biol 2022; 19:10.1088/1478-3975/ac8c16. [PMID: 35998617 PMCID: PMC9585661 DOI: 10.1088/1478-3975/ac8c16] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 08/23/2022] [Indexed: 11/11/2022]
Abstract
Cells with the same genome can exist in different phenotypes and can change between distinct phenotypes when subject to specific stimuli and microenvironments. Some examples include cell differentiation during development, reprogramming for induced pluripotent stem cells and transdifferentiation, cancer metastasis and fibrosis progression. The regulation and dynamics of cell phenotypic conversion is a fundamental problem in biology, and has a long history of being studied within the formalism of dynamical systems. A main challenge for mechanism-driven modeling studies is acquiring sufficient amount of quantitative information for constraining model parameters. Advances in quantitative experimental approaches, especially high throughput single-cell techniques, have accelerated the emergence of a new direction for reconstructing the governing dynamical equations of a cellular system from quantitative single-cell data, beyond the dominant statistical approaches. Here I review a selected number of recent studies using live- and fixed-cell data and provide my perspective on future development.
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Affiliation(s)
- Jianhua Xing
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15232, USA
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15232, USA
- UPMC-Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
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10
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Xing J. Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology. Phys Biol 2022. [PMID: 35998617 DOI: 10.48550/arxiv.2203.14964] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Cells with the same genome can exist in different phenotypes and can change between distinct phenotypes when subject to specific stimuli and microenvironments. Some examples include cell differentiation during development, reprogramming for induced pluripotent stem cells and transdifferentiation, cancer metastasis and fibrosis progression. The regulation and dynamics of cell phenotypic conversion is a fundamental problem in biology, and has a long history of being studied within the formalism of dynamical systems. A main challenge for mechanism-driven modeling studies is acquiring sufficient amount of quantitative information for constraining model parameters. Advances in quantitative experimental approaches, especially high throughput single-cell techniques, have accelerated the emergence of a new direction for reconstructing the governing dynamical equations of a cellular system from quantitative single-cell data, beyond the dominant statistical approaches. Here I review a selected number of recent studies using live- and fixed-cell data and provide my perspective on future development.
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Affiliation(s)
- Jianhua Xing
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15232, United States of America.,Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15232, United States of America.,UPMC-Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, United States of America
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11
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Cancer: More than a geneticist’s Pandora’s box. J Biosci 2022. [DOI: 10.1007/s12038-022-00254-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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12
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Hirway SU, Weinberg SH. A review of computational modeling, machine learning and image analysis in cancer metastasis dynamics. COMPUTATIONAL AND SYSTEMS ONCOLOGY 2022. [DOI: 10.1002/cso2.1044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Affiliation(s)
- Shreyas U. Hirway
- Department of Biomedical Engineering The Ohio State University Columbus Ohio USA
| | - Seth H. Weinberg
- Department of Biomedical Engineering The Ohio State University Columbus Ohio USA
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13
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Minin A, Blatov I, Lebedeva V, Tuchai M, Pozdina V, Byzov I, Zubarev I. Novel cost-efficient protein-membrane basedsystem for cells co-cultivation and modeling theintercellular communication. Biotechnol Bioeng 2022; 119:1033-1042. [PMID: 35000190 DOI: 10.1002/bit.28031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 12/23/2021] [Accepted: 12/26/2021] [Indexed: 11/11/2022]
Abstract
In vitro systems serve as compact and manipulate models to investigate interactions between different cell types. A homogeneous population of cells predictably and uniformly responds to external factors. In a heterogeneous cell population, the effect of external growth factors is perceived in the context of intercellular interactions. Indirect cell cocultivation allows one to observe the paracrine effects of cells and separately analyze cell populations. The article describes an application of custom-made cell co-cultivation systems based on protein membranes separated from the bottom of the vessel by the 3d printed holder or kept afloat by a magnetic field. Using the proposed co-cultivation system, we analyzed the interaction of A549 cells and fibroblasts, in the presence and absence of growth factors. During co-cultivation of cells, the expression of genes of the activation for epithelial and mesenchymal transitions decreases. The article proposes the application of a newly available system for the co-cultivation of different cell types. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- A Minin
- M. N. Mikheev Institute of Metal Physics, Yekaterinburg, Russian Federation.,Ural Federal University, Yekaterinburg, Russian Federation
| | - I Blatov
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
| | - V Lebedeva
- Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
| | - M Tuchai
- Ural Research Center for Radiation Medicine, Chelyabinsk, Russian Federation
| | - V Pozdina
- Institute of Immunology and Physiology, Yekaterinburg, Russian Federation
| | - I Byzov
- M. N. Mikheev Institute of Metal Physics, Yekaterinburg, Russian Federation
| | - I Zubarev
- Ural Federal University, Yekaterinburg, Russian Federation.,Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation.,Lomonosov Moscow State University, Moscow, Russian Federation
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14
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Sahoo S, Ashraf B, Duddu AS, Biddle A, Jolly MK. Interconnected high-dimensional landscapes of epithelial-mesenchymal plasticity and stemness in cancer. Clin Exp Metastasis 2022; 39:279-290. [PMID: 34993766 DOI: 10.1007/s10585-021-10139-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 11/09/2021] [Indexed: 02/06/2023]
Abstract
Establishing macrometastases at distant organs is a highly challenging process for cancer cells, with extremely high attrition rates. A very small percentage of disseminated cells have the ability to dynamically adapt to their changing micro-environments through reversibly switching to another phenotype, aiding metastasis. Such plasticity can be exhibited along one or more axes-epithelial-mesenchymal plasticity (EMP) and cancer stem cells (CSCs) being the two most studied, and often tacitly assumed to be synonymous. Here, we review the emerging concepts related to EMP and CSCs across multiple cancers. Both processes are multi-dimensional in nature; for instance, EMP can be defined on morphological, molecular and functional changes, which may or may not be synchronized. Similarly, self-renewal, multi-lineage potential, and resistance to anoikis and/or therapy may not all occur simultaneously in CSCs. Thus, understanding the complexity in defining EMP and CSCs is essential if we are to understand their contribution to cancer metastasis. This will require a more comprehensive understanding of the non-linearity of these processes. These processes are dynamic, reversible, and semi-independent in nature; cells traverse the inter-connected high-dimensional EMP and CSC landscapes in diverse paths, each of which may exhibit a distinct EMP-CSC coupling. Our proposed model offers a potential unifying framework for elucidating the coupled decision-making along these dimensions and highlights a key set of open questions to be answered.
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Affiliation(s)
- Sarthak Sahoo
- Centre for BioSystems Science and Engineering (BSSE), Indian Institute of Science, Bangalore, 560012, India.,UG Programme, Indian Institute of Science, Bangalore, 560012, India
| | - Bazella Ashraf
- Department of Biotechnology, Central University of Kashmir, Ganderbal, India
| | - Atchuta Srinivas Duddu
- Centre for BioSystems Science and Engineering (BSSE), Indian Institute of Science, Bangalore, 560012, India
| | - Adrian Biddle
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering (BSSE), Indian Institute of Science, Bangalore, 560012, India.
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15
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Subbalakshmi AR, Ashraf B, Jolly MK. Biophysical and biochemical attributes of hybrid epithelial/mesenchymal phenotypes. Phys Biol 2022; 19. [PMID: 34986465 DOI: 10.1088/1478-3975/ac482c] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 01/05/2022] [Indexed: 11/11/2022]
Abstract
The Epithelial-Mesenchymal Transition (EMT) is a biological phenomenon associated with explicit phenotypic and molecular changes in cellular traits. Unlike the earlier-held popular belief of it being a binary process, EMT is now thought of as a landscape including diverse hybrid E/M phenotypes manifested by varying degrees of the transition. These hybrid cells can co-express both epithelial and mesenchymal markers and/or functional traits, and can possess the property of collective cell migration, enhanced tumor-initiating ability, and immune/targeted therapy-evasive features, all of which are often associated with worse patient outcomes. These characteristics of the hybrid E/M cells have led to a surge in studies that map their biophysical and biochemical hallmarks that can be helpful in exploiting their therapeutic vulnerabilities. This review discusses recent advances made in investigating hybrid E/M phenotype(s) from diverse biophysical and biochemical aspects by integrating live cell-imaging, cellular morphology quantification and mathematical modelling, and highlights a set of questions that remain unanswered about the dynamics of hybrid E/M states.
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Affiliation(s)
- Ayalur Raghu Subbalakshmi
- Indian Institute of Science, Centre for BioSystems Science and Engineering, Bangalore, 560012, INDIA
| | - Bazella Ashraf
- Central University of Kashmir, Department of Biotechnology, Ganderbal, Jammu and Kashmir, 191201, INDIA
| | - Mohit Kumar Jolly
- Indian Institute of Science, Centre for BioSystems Science and Engineering, Bangalore, 560012, INDIA
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16
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Mandal S, Tejaswi T, Janivara R, Srikrishnan S, Thakur P, Sahoo S, Chakraborty P, Sohal SS, Levine H, George JT, Jolly MK. Transcriptomic-Based Quantification of the Epithelial-Hybrid-Mesenchymal Spectrum across Biological Contexts. Biomolecules 2021; 12:29. [PMID: 35053177 PMCID: PMC8773604 DOI: 10.3390/biom12010029] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 12/20/2021] [Accepted: 12/21/2021] [Indexed: 12/12/2022] Open
Abstract
Epithelial-mesenchymal plasticity (EMP) underlies embryonic development, wound healing, and cancer metastasis and fibrosis. Cancer cells exhibiting EMP often have more aggressive behavior, characterized by drug resistance, and tumor-initiating and immuno-evasive traits. Thus, the EMP status of cancer cells can be a critical indicator of patient prognosis. Here, we compare three distinct transcriptomic-based metrics-each derived using a different gene list and algorithm-that quantify the EMP spectrum. Our results for over 80 cancer-related RNA-seq datasets reveal a high degree of concordance among these metrics in quantifying the extent of EMP. Moreover, each metric, despite being trained on cancer expression profiles, recapitulates the expected changes in EMP scores for non-cancer contexts such as lung fibrosis and cellular reprogramming into induced pluripotent stem cells. Thus, we offer a scoring platform to quantify the extent of EMP in vitro and in vivo for diverse biological applications including cancer.
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Affiliation(s)
- Susmita Mandal
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India; (S.M.); (T.T.); (S.S.); (P.C.)
| | - Tanishq Tejaswi
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India; (S.M.); (T.T.); (S.S.); (P.C.)
- Undergraduate Programme, Indian Institute of Science, Bangalore 560012, India
| | - Rohini Janivara
- Department of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA;
| | - Syamanthak Srikrishnan
- Department of Biotechnology, Indian Institute of Technology, Kharagpur 721302, India; (S.S.); (P.T.)
| | - Pradipti Thakur
- Department of Biotechnology, Indian Institute of Technology, Kharagpur 721302, India; (S.S.); (P.T.)
| | - Sarthak Sahoo
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India; (S.M.); (T.T.); (S.S.); (P.C.)
| | - Priyanka Chakraborty
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India; (S.M.); (T.T.); (S.S.); (P.C.)
| | - Sukhwinder Singh Sohal
- Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston 7248, Australia;
| | - Herbert Levine
- Departments of Physics and Bioengineering, Northeastern University, Boston, MA 02115, USA;
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
| | - Jason T. George
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77030, USA
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India; (S.M.); (T.T.); (S.S.); (P.C.)
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17
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Hirway SU, Hassan NT, Sofroniou M, Lemmon CA, Weinberg SH. Immunofluorescence Image Feature Analysis and Phenotype Scoring Pipeline for Distinguishing Epithelial-Mesenchymal Transition. MICROSCOPY AND MICROANALYSIS : THE OFFICIAL JOURNAL OF MICROSCOPY SOCIETY OF AMERICA, MICROBEAM ANALYSIS SOCIETY, MICROSCOPICAL SOCIETY OF CANADA 2021; 27:849-859. [PMID: 34011419 PMCID: PMC8349798 DOI: 10.1017/s1431927621000428] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Epithelial–mesenchymal transition (EMT) is an essential biological process, also implicated in pathological settings such as cancer metastasis, in which epithelial cells transdifferentiate into mesenchymal cells. We devised an image analysis pipeline to distinguish between tissues comprised of epithelial and mesenchymal cells, based on extracted features from immunofluorescence images of differing biochemical markers. Mammary epithelial cells were cultured with 0 (control), 2, 4, or 10 ng/mL TGF-β1, a well-established EMT-inducer. Cells were fixed, stained, and imaged for E-cadherin, actin, fibronectin, and nuclei via immunofluorescence microscopy. Feature selection was performed on different combinations of individual cell markers using a Bag-of-Features extraction. Control and high-dose images comprised the training data set, and the intermediate dose images comprised the testing data set. A feature distance analysis was performed to quantify differences between the treatment groups. The pipeline was successful in distinguishing between control (epithelial) and the high-dose (mesenchymal) groups, as well as demonstrating progress along the EMT process in the intermediate dose groups. Validation using quantitative PCR (qPCR) demonstrated that biomarker expression measurements were well-correlated with the feature distance analysis. Overall, we identified image pipeline characteristics for feature extraction and quantification of immunofluorescence images to distinguish progression of EMT.
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Affiliation(s)
- Shreyas U. Hirway
- Biomedical Engineering Department, The Ohio State University, Columbus, OH, USA
| | - Nadiah T. Hassan
- Biomedical Engineering Department, Virginia Commonwealth University, Richmond, VA, USA
| | - Michael Sofroniou
- Biomedical Engineering Department, Virginia Commonwealth University, Richmond, VA, USA
| | - Christopher A. Lemmon
- Biomedical Engineering Department, Virginia Commonwealth University, Richmond, VA, USA
| | - Seth H. Weinberg
- Biomedical Engineering Department, The Ohio State University, Columbus, OH, USA
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18
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Rozova VS, Anwer AG, Guller AE, Es HA, Khabir Z, Sokolova AI, Gavrilov MU, Goldys EM, Warkiani ME, Thiery JP, Zvyagin AV. Machine learning reveals mesenchymal breast carcinoma cell adaptation in response to matrix stiffness. PLoS Comput Biol 2021; 17:e1009193. [PMID: 34297718 PMCID: PMC8336795 DOI: 10.1371/journal.pcbi.1009193] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 08/04/2021] [Accepted: 06/17/2021] [Indexed: 12/31/2022] Open
Abstract
Epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition (MET), are believed to play key roles in facilitating the metastatic cascade. Metastatic lesions often exhibit a similar epithelial-like state to that of the primary tumour, in particular, by forming carcinoma cell clusters via E-cadherin-mediated junctional complexes. However, the factors enabling mesenchymal-like micrometastatic cells to resume growth and reacquire an epithelial phenotype in the target organ microenvironment remain elusive. In this study, we developed a workflow using image-based cell profiling and machine learning to examine morphological, contextual and molecular states of individual breast carcinoma cells (MDA-MB-231). MDA-MB-231 heterogeneous response to the host organ microenvironment was modelled by substrates with controllable stiffness varying from 0.2kPa (soft tissues) to 64kPa (bone tissues). We identified 3 distinct morphological cell types (morphs) varying from compact round-shaped to flattened irregular-shaped cells with lamellipodia, predominantly populating 2-kPa and >16kPa substrates, respectively. These observations were accompanied by significant changes in E-cadherin and vimentin expression. Furthermore, we demonstrate that the bone-mimicking substrate (64kPa) induced multicellular cluster formation accompanied by E-cadherin cell surface localisation. MDA-MB-231 cells responded to different substrate stiffness by morphological adaptation, changes in proliferation rate and cytoskeleton markers, and cluster formation on bone-mimicking substrate. Our results suggest that the stiffest microenvironment can induce MET.
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Affiliation(s)
- Vlada S. Rozova
- ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, Australia
- Institute for Biology and Biomedicine, Lobachevsky State University, Nizhny Novgorod, Russia
| | - Ayad G. Anwer
- ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, Australia
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Australia
| | - Anna E. Guller
- ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, Australia
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Australia
- Institute for Regenerative Medicine, Sechenov University, Moscow, Russia
| | | | - Zahra Khabir
- ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, Australia
| | - Anastasiya I. Sokolova
- Centre of Biomedical Engineering, Sechenov University, Moscow, Russia
- Laboratory of Medical Nanotechnologies, Federal Biomedical Agency, Moscow, Russia
| | - Maxim U. Gavrilov
- Centre of Biomedical Engineering, Sechenov University, Moscow, Russia
| | - Ewa M. Goldys
- ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, Australia
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, Australia
| | | | - Jean Paul Thiery
- Centre of Biomedical Engineering, Sechenov University, Moscow, Russia
- Bioland Laboratory, Guangzhou Regenerative Medicine and Health, Guangdong Laboratory, Guangzhou, China
| | - Andrei V. Zvyagin
- ARC Centre of Excellence for Nanoscale Biophotonics, Macquarie University, Sydney, Australia
- Centre of Biomedical Engineering, Sechenov University, Moscow, Russia
- Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia
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19
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Chakraborty P, Chen EL, McMullen I, Armstrong AJ, Kumar Jolly M, Somarelli JA. Analysis of immune subtypes across the epithelial-mesenchymal plasticity spectrum. Comput Struct Biotechnol J 2021; 19:3842-3851. [PMID: 34306571 PMCID: PMC8283019 DOI: 10.1016/j.csbj.2021.06.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 06/14/2021] [Accepted: 06/15/2021] [Indexed: 12/13/2022] Open
Abstract
Epithelial-mesenchymal plasticity plays a critical role in many solid tumor types as a mediator of metastatic dissemination and treatment resistance. In addition, there is also a growing appreciation that the epithelial/mesenchymal status of a tumor plays a role in immune evasion and immune suppression. A deeper understanding of the immunological features of different tumor types has been facilitated by the availability of large gene expression datasets and the development of methods to deconvolute bulk RNA-Seq data. These resources have generated powerful new ways of characterizing tumors, including classification of immune subtypes based on differential expression of immunological genes. In the present work, we combine scoring algorithms to quantify epithelial-mesenchymal plasticity with immune subtype analysis to understand the relationship between epithelial plasticity and immune subtype across cancers. We find heterogeneity of epithelial-mesenchymal transition (EMT) status both within and between cancer types, with greater heterogeneity in the expression of EMT-related factors than of MET-related factors. We also find that specific immune subtypes have associated EMT scores and differential expression of immune checkpoint markers.
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Affiliation(s)
- Priyanka Chakraborty
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | | | | | - Andrew J. Armstrong
- Department of Medicine, Durham, NC, United Kingdom
- Duke Cancer Institute Center for Prostate and Urologic Cancers, Durham, NC, United Kingdom
- Department of Pharmacology and Cancer Biology, Duke University, Durham, NC, United Kingdom
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Jason A. Somarelli
- Department of Medicine, Durham, NC, United Kingdom
- Duke Cancer Institute Center for Prostate and Urologic Cancers, Durham, NC, United Kingdom
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20
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Jolly MK, Murphy RJ, Bhatia S, Whitfield HJ, Redfern A, Davis MJ, Thompson EW. Measuring and Modelling the Epithelial- Mesenchymal Hybrid State in Cancer: Clinical Implications. Cells Tissues Organs 2021; 211:110-133. [PMID: 33902034 DOI: 10.1159/000515289] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 01/25/2021] [Indexed: 11/19/2022] Open
Abstract
The epithelial-mesenchymal (E/M) hybrid state has emerged as an important mediator of elements of cancer progression, facilitated by epithelial mesenchymal plasticity (EMP). We review here evidence for the presence, prognostic significance, and therapeutic potential of the E/M hybrid state in carcinoma. We further assess modelling predictions and validation studies to demonstrate stabilised E/M hybrid states along the spectrum of EMP, as well as computational approaches for characterising and quantifying EMP phenotypes, with particular attention to the emerging realm of single-cell approaches through RNA sequencing and protein-based techniques.
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Affiliation(s)
- Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | - Ryan J Murphy
- Queensland University of Technology, School of Mathematical Sciences, Brisbane, Queensland, Australia
| | - Sugandha Bhatia
- Queensland University of Technology, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Brisbane, Queensland, Australia.,Queensland University of Technology, Translational Research Institute, Brisbane, Queensland, Australia.,The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Holly J Whitfield
- Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia
| | - Andrew Redfern
- Department of Medicine, School of Medicine, University of Western Australia, Fiona Stanley Hospital Campus, Perth, Washington, Australia
| | - Melissa J Davis
- Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia.,Department of Clinical Pathology, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria, Australia
| | - Erik W Thompson
- Queensland University of Technology, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Brisbane, Queensland, Australia.,Queensland University of Technology, Translational Research Institute, Brisbane, Queensland, Australia
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21
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A Theoretical Approach to Coupling the Epithelial-Mesenchymal Transition (EMT) to Extracellular Matrix (ECM) Stiffness via LOXL2. Cancers (Basel) 2021; 13:cancers13071609. [PMID: 33807227 PMCID: PMC8037024 DOI: 10.3390/cancers13071609] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 03/12/2021] [Accepted: 03/22/2021] [Indexed: 02/06/2023] Open
Abstract
Simple Summary Epithelial-mesenchymal transition (EMT) is a key process in cancer progression through which cells weaken their cell-cell adhesion and gain mobility and invasive traits. Besides chemical signaling, recent studies have established the connection of EMT to mechanical microenvironment, such as the stiffness of extracellular matrix (ECM). LOXL2 is representative of a family of enzymes that promotes fiber cross-linking in ECM. With increased cross-linking comes increased stiffness, which induces EMT that can, in turn, elevate LOXL2 levels. As such, a positive feedback loop among EMT, LOXL2, and ECM stiffness can be formed. We built a mathematical model on a core biochemical reaction network featuring this feedback loop, and showed how strongly it drives EMT. We also illustrated mechanistically how cross-linking connects with stiffness, using a mechanical model of collagen (a major component of ECM). Using this theoretical framework, we demonstrated the heterogeneity of LOXL2/stiffness and its implications on migrating cancer cells that could seed metastasis, the growth of secondary malignant tumors. This framework can inspire experimental studies of more fine-grained mechanotransduction and biomechanical heterogeneity in cancers. Abstract The epithelial-mesenchymal transition (EMT) plays a critical role in cancer progression, being responsible in many cases for the onset of the metastatic cascade and being integral in the ability of cells to resist drug treatment. Most studies of EMT focus on its induction via chemical signals such as TGF-β or Notch ligands, but it has become increasingly clear that biomechanical features of the microenvironment such as extracellular matrix (ECM) stiffness can be equally important. Here, we introduce a coupled feedback loop connecting stiffness to the EMT transcription factor ZEB1, which acts via increasing the secretion of LOXL2 that leads to increased cross-linking of collagen fibers in the ECM. This increased cross-linking can effectively increase ECM stiffness and increase ZEB1 levels, thus setting a positive feedback loop between ZEB1 and ECM stiffness. To investigate the impact of this non-cell-autonomous effect, we introduce a computational approach capable of connecting LOXL2 concentration to increased stiffness and thereby to higher ZEB1 levels. Our results indicate that this positive feedback loop, once activated, can effectively lock the cells in a mesenchymal state. The spatial-temporal heterogeneity of the LOXL2 concentration and thus the mechanical stiffness also has direct implications for migrating cells that attempt to escape the primary tumor.
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22
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Chedere A, Hari K, Kumar S, Rangarajan A, Jolly MK. Multi-Stability and Consequent Phenotypic Plasticity in AMPK-Akt Double Negative Feedback Loop in Cancer Cells. J Clin Med 2021; 10:jcm10030472. [PMID: 33530625 PMCID: PMC7865639 DOI: 10.3390/jcm10030472] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 01/07/2021] [Accepted: 01/21/2021] [Indexed: 12/23/2022] Open
Abstract
Adaptation and survival of cancer cells to various stress and growth factor conditions is crucial for successful metastasis. A double-negative feedback loop between two serine/threonine kinases AMPK (AMP-activated protein kinase) and Akt can regulate the adaptation of breast cancer cells to matrix-deprivation stress. This feedback loop can significantly generate two phenotypes or cell states: matrix detachment-triggered pAMPKhigh/ pAktlow state, and matrix (re)attachment-triggered pAkthigh/ pAMPKlow state. However, whether these two cell states can exhibit phenotypic plasticity and heterogeneity in a given cell population, i.e., whether they can co-exist and undergo spontaneous switching to generate the other subpopulation, remains unclear. Here, we develop a mechanism-based mathematical model that captures the set of experimentally reported interactions among AMPK and Akt. Our simulations suggest that the AMPK-Akt feedback loop can give rise to two co-existing phenotypes (pAkthigh/ pAMPKlow and pAMPKhigh/pAktlow) in specific parameter regimes. Next, to test the model predictions, we segregated these two subpopulations in MDA-MB-231 cells and observed that each of them was capable of switching to another in adherent conditions. Finally, the predicted trends are supported by clinical data analysis of The Cancer Genome Atlas (TCGA) breast cancer and pan-cancer cohorts that revealed negatively correlated pAMPK and pAkt protein levels. Overall, our integrated computational-experimental approach unravels that AMPK-Akt feedback loop can generate multi-stability and drive phenotypic switching and heterogeneity in a cancer cell population.
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Affiliation(s)
- Adithya Chedere
- Department of Molecular Reproduction, Development, and Genetics, Indian Institute of Science, Bangalore 560012, India; (A.C.); (S.K.)
| | - Kishore Hari
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
| | - Saurav Kumar
- Department of Molecular Reproduction, Development, and Genetics, Indian Institute of Science, Bangalore 560012, India; (A.C.); (S.K.)
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Basic Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Annapoorni Rangarajan
- Department of Molecular Reproduction, Development, and Genetics, Indian Institute of Science, Bangalore 560012, India; (A.C.); (S.K.)
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Correspondence: (A.R.); (M.K.J.)
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India;
- Correspondence: (A.R.); (M.K.J.)
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23
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Pasani S, Sahoo S, Jolly MK. Hybrid E/M Phenotype(s) and Stemness: A Mechanistic Connection Embedded in Network Topology. J Clin Med 2020; 10:E60. [PMID: 33375334 PMCID: PMC7794989 DOI: 10.3390/jcm10010060] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 12/20/2020] [Accepted: 12/23/2020] [Indexed: 02/07/2023] Open
Abstract
Metastasis remains an unsolved clinical challenge. Two crucial features of metastasizing cancer cells are (a) their ability to dynamically move along the epithelial-hybrid-mesenchymal spectrum and (b) their tumor initiation potential or stemness. With increasing functional characterization of hybrid epithelial/mesenchymal (E/M) phenotypes along the spectrum, recent in vitro and in vivo studies have suggested an increasing association of hybrid E/M phenotypes with stemness. However, the mechanistic underpinnings enabling this association remain unclear. Here, we develop a mechanism-based mathematical modeling framework that interrogates the emergent nonlinear dynamics of the coupled network modules regulating E/M plasticity (miR-200/ZEB) and stemness (LIN28/let-7). Simulating the dynamics of this coupled network across a large ensemble of parameter sets, we observe that hybrid E/M phenotype(s) are more likely to acquire stemness relative to "pure" epithelial or mesenchymal states. We also integrate multiple "phenotypic stability factors" (PSFs) that have been shown to stabilize hybrid E/M phenotypes both in silico and in vitro-such as OVOL1/2, GRHL2, and NRF2-with this network, and demonstrate that the enrichment of hybrid E/M phenotype(s) with stemness is largely conserved in the presence of these PSFs. Thus, our results offer mechanistic insights into recent experimental observations of hybrid E/M phenotype(s) that are essential for tumor initiation and highlight how this feature is embedded in the underlying topology of interconnected EMT (Epithelial-Mesenchymal Transition) and stemness networks.
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Affiliation(s)
- Satwik Pasani
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India; (S.P.); (S.S.)
| | - Sarthak Sahoo
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India; (S.P.); (S.S.)
- Undergraduate Programme, Indian Institute of Science, Bangalore 560012, India
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India; (S.P.); (S.S.)
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24
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Saxena K, Jolly MK, Balamurugan K. Hypoxia, partial EMT and collective migration: Emerging culprits in metastasis. Transl Oncol 2020; 13:100845. [PMID: 32781367 PMCID: PMC7419667 DOI: 10.1016/j.tranon.2020.100845] [Citation(s) in RCA: 115] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Revised: 07/12/2020] [Accepted: 07/27/2020] [Indexed: 02/07/2023] Open
Abstract
Epithelial-mesenchymal transition (EMT) is a cellular biological process involved in migration of primary cancer cells to secondary sites facilitating metastasis. Besides, EMT also confers properties such as stemness, drug resistance and immune evasion which can aid a successful colonization at the distant site. EMT is not a binary process; recent evidence suggests that cells in partial EMT or hybrid E/M phenotype(s) can have enhanced stemness and drug resistance as compared to those undergoing a complete EMT. Moreover, partial EMT enables collective migration of cells as clusters of circulating tumor cells or emboli, further endorsing that cells in hybrid E/M phenotypes may be the 'fittest' for metastasis. Here, we review mechanisms and implications of hybrid E/M phenotypes, including their reported association with hypoxia. Hypoxia-driven activation of HIF-1α can drive EMT. In addition, cyclic hypoxia, as compared to acute or chronic hypoxia, shows the highest levels of active HIF-1α and can augment cancer aggressiveness to a greater extent, including enriching for a partial EMT phenotype. We also discuss how metastasis is influenced by hypoxia, partial EMT and collective cell migration, and call for a better understanding of interconnections among these mechanisms. We discuss the known regulators of hypoxia, hybrid EMT and collective cell migration and highlight the gaps which needs to be filled for connecting these three axes which will increase our understanding of dynamics of metastasis and help control it more effectively.
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Affiliation(s)
- Kritika Saxena
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.
| | - Kuppusamy Balamurugan
- Laboratory of Cell and Developmental Signaling, Center for Cancer Research, National Cancer Institute, Frederick, MD 21702, USA.
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25
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Mandal M, Ghosh B, Rajput M, Chatterjee J. Impact of intercellular connectivity on epithelial mesenchymal transition plasticity. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR CELL RESEARCH 2020; 1867:118784. [DOI: 10.1016/j.bbamcr.2020.118784] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 06/14/2020] [Accepted: 06/18/2020] [Indexed: 12/14/2022]
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26
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Jia W, Tripathi S, Chakraborty P, Chedere A, Rangarajan A, Levine H, Jolly MK. Epigenetic feedback and stochastic partitioning during cell division can drive resistance to EMT. Oncotarget 2020; 11:2611-2624. [PMID: 32676163 PMCID: PMC7343638 DOI: 10.18632/oncotarget.27651] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Accepted: 06/01/2020] [Indexed: 12/12/2022] Open
Abstract
Epithelial-mesenchymal transition (EMT) and its reverse process mesenchymal-epithelial transition (MET) are central to metastatic aggressiveness and therapy resistance in solid tumors. While molecular determinants of both processes have been extensively characterized, the heterogeneity in the response of tumor cells to EMT and MET inducers has come into focus recently, and has been implicated in the failure of anti-cancer therapies. Recent experimental studies have shown that some cells can undergo an irreversible EMT depending on the duration of exposure to EMT-inducing signals. While the irreversibility of MET, or equivalently, resistance to EMT, has not been studied in as much detail, evidence supporting such behavior is slowly emerging. Here, we identify two possible mechanisms that can underlie resistance of cells to undergo EMT: epigenetic feedback in ZEB1/GRHL2 feedback loop and stochastic partitioning of biomolecules during cell division. Identifying the ZEB1/GRHL2 axis as a key determinant of epithelial-mesenchymal plasticity across many cancer types, we use mechanistic mathematical models to show how GRHL2 can be involved in both the abovementioned processes, thus driving an irreversible MET. Our study highlights how an isogenic population may contain subpopulation with varying degrees of susceptibility or resistance to EMT, and proposes a next set of questions for detailed experimental studies characterizing the irreversibility of MET/resistance to EMT.
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Affiliation(s)
- Wen Jia
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
- Department of Physics and Astronomy, Rice University, Houston, TX, USA
| | - Shubham Tripathi
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
- PhD Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, TX, USA
- Department of Physics, Northeastern University, Boston, MA, USA
| | - Priyanka Chakraborty
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
| | - Adithya Chedere
- Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, Bangalore, India
| | - Annapoorni Rangarajan
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
- Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, Bangalore, India
| | - Herbert Levine
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
- Department of Physics, Northeastern University, Boston, MA, USA
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore, India
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27
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Devaraj V, Bose B. DEBay: A computational tool for deconvolution of quantitative PCR data for estimation of cell type-specific gene expression in a mixed population. Heliyon 2020; 6:e04489. [PMID: 32728643 PMCID: PMC7381708 DOI: 10.1016/j.heliyon.2020.e04489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 07/12/2020] [Accepted: 07/14/2020] [Indexed: 11/30/2022] Open
Abstract
The expression of a gene is commonly estimated by quantitative PCR (qPCR) using RNA isolated from a large number of pooled cells. Such pooled samples often have subpopulations of cells with different levels of expression of the target gene. Estimation of gene expression from an ensemble of cells obscures the pattern of expression in different subpopulations. Physical separation of various subpopulations is a demanding task. We have developed a computational tool, Deconvolution of Ensemble through Bayes-approach (DEBay), to estimate cell type-specific gene expression from qPCR data of a mixed population. DEBay estimates Normalized Gene Expression Coefficient (NGEC), which is a relative measure of the expression of the target gene in each cell type in a population. NGEC has a direct algebraic correspondence with the normalized fold change in gene expression measured by qPCR. DEBay can deconvolute both time-dependent and -independent gene expression profiles. It uses the Bayesian method of model selection and parameter estimation. We have evaluated DEBay using synthetic and real experimental data. DEBay is implemented in Python. A GUI of DEBay and its source code are available for download at SourceForge (https://sourceforge.net/projects/debay).
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Affiliation(s)
- Vimalathithan Devaraj
- Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati, 781039, India
| | - Biplab Bose
- Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati, 781039, India
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Koshkin V, Bleker de Oliveira M, Peng C, Ailles LE, Liu G, Covens A, Krylov SN. Spheroid-Based Approach to Assess the Tissue Relevance of Analysis of Dispersed-Settled Tissue Cells by Cytometry of the Reaction Rate Constant. Anal Chem 2020; 92:9348-9355. [PMID: 32522000 DOI: 10.1021/acs.analchem.0c01667] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Cytometry of Reaction Rate Constant (CRRC) uses time-lapse fluorescence microscopy to measure a rate constant of a catalytic reaction in individual cells and, thus, facilitate accurate size determination for cell subpopulations with distinct efficiencies of this reaction. Reliable CRRC requires uniform exposure of cells to the reaction substrate followed by their uniform imaging, which in turn, requires that a tissue sample be disintegrated into a suspension of dispersed cells, and these cells settle on the support surface before being analyzed by CRRC. We call such cells "dispersed-settled" to distinguish them from cells cultured as a monolayer. Studies of the dispersed-settled cells can be tissue-relevant only if the cells maintain their 3D tissue state during the multi-hour CRRC procedure. Here, we propose an approach for assessing tissue relevance of the CRRC-based analysis of the dispersed-settled cells. Our approach utilizes cultured multicellular spheroids as a 3D cell model and cultured cell monolayers as a 2D cell model. The CRRC results of the dispersed-settled cells derived from spheroids are compared to those of spheroids and monolayers in order to find if the dispersed-settled cells are representative of the spheroids. To demonstrate its practical use, we applied this approach to a cellular reaction of multidrug resistance (MDR) transport, which was followed by extrusion of a fluorescent substrate from the cells. The approach proved to be reliable and revealed long-term maintenance of MDR transport in the dispersed-settled cells obtained from cultured ovarian cancer spheroids. Accordingly, CRRC can be used to determine accurately the size of a cell subpopulation with an elevated level of MDR transport in tumor samples, which makes CRRC a suitable method for the development of MDR-based predictors of chemoresistance. The proposed spheroid-based approach for validation of CRRC is applicable to other types of cellular reactions and, thus, will be an indispensable tool for transforming CRRC from an experimental technique into a practical analytical tool.
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Affiliation(s)
- Vasilij Koshkin
- Centre for Research on Biomolecular Interactions, York University, Toronto, Ontario M3J 1P3, Canada
| | | | - Chun Peng
- Centre for Research on Biomolecular Interactions, York University, Toronto, Ontario M3J 1P3, Canada
| | - Laurie E Ailles
- Princess Margaret Cancer Centre and Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario N5G 1L7, Canada
| | - Geoffrey Liu
- Department of Medicine, Medical Oncology, Princess Margaret Cancer Centre, Toronto, Ontario M5G 2M9, Canada
| | - Allan Covens
- Sunnybrook Odette Cancer Centre, Toronto, Ontario M4N 3M5, Canada
| | - Sergey N Krylov
- Centre for Research on Biomolecular Interactions, York University, Toronto, Ontario M3J 1P3, Canada
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Insights into the Multi-Dimensional Dynamic Landscape of Epithelial-Mesenchymal Plasticity through Inter-Disciplinary Approaches. J Clin Med 2020; 9:jcm9061624. [PMID: 32471235 PMCID: PMC7356048 DOI: 10.3390/jcm9061624] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 05/26/2020] [Indexed: 12/31/2022] Open
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Nordin A, Chowdhury SR, Saim AB, Bt Hj Idrus R. Effect of Kelulut Honey on the Cellular Dynamics of TGFβ-Induced Epithelial to Mesenchymal Transition in Primary Human Keratinocytes. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17093229. [PMID: 32384749 PMCID: PMC7246951 DOI: 10.3390/ijerph17093229] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 04/18/2020] [Accepted: 04/20/2020] [Indexed: 01/08/2023]
Abstract
Over-induction of epithelial to mesenchymal transition (EMT) by tumor growth factor beta (TGFβ) in keratinocytes is a key feature in keloid scar. The present work seeks to investigate the effect of Kelulut honey (KH) on TGFβ-induced EMT in human primary keratinocytes. Image analysis of the real time observation of TGFβ-induced keratinocytes revealed a faster wound closure and individual migration velocity compared to the untreated control. TGFβ-induced keratinocytes also have reduced circularity and display a classic EMT protein expression. Treatment of 0.0015% (v/v) KH reverses these effects. In untreated keratinocytes, KH resulted in slower initial wound closure and individual migration velocity, which sped up later on, resulting in greater wound closure at the final time point. KH treatment also led to greater directional migration compared to the control. KH treatment caused reduced circularity in keratinocytes but displayed a partial EMT protein expression. Taken together, the findings suggest the therapeutic potential of KH in preventing keloid scar by attenuating TGFβ-induced EMT.
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Affiliation(s)
- Abid Nordin
- Department of Physiology, Faculty of Medicine, Cheras, Kuala Lumpur 56000, Malaysia;
- Tissue Engineering Centre, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur 56000, Malaysia;
| | - Shiplu Roy Chowdhury
- Tissue Engineering Centre, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur 56000, Malaysia;
| | - Aminuddin Bin Saim
- Ear, Nose & Throat Consultant Clinic, Ampang Puteri Specialist Hospital, Ampang, Selangor 68000, Malaysia;
| | - Ruszymah Bt Hj Idrus
- Department of Physiology, Faculty of Medicine, Cheras, Kuala Lumpur 56000, Malaysia;
- Tissue Engineering Centre, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur 56000, Malaysia;
- Correspondence: ; Tel.: +60-39-145-7669
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Chakraborty P, George JT, Tripathi S, Levine H, Jolly MK. Comparative Study of Transcriptomics-Based Scoring Metrics for the Epithelial-Hybrid-Mesenchymal Spectrum. Front Bioeng Biotechnol 2020; 8:220. [PMID: 32266244 PMCID: PMC7100584 DOI: 10.3389/fbioe.2020.00220] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 03/04/2020] [Indexed: 12/26/2022] Open
Abstract
The Epithelial-mesenchymal transition (EMT) is a cellular process implicated in embryonic development, wound healing, and pathological conditions such as cancer metastasis and fibrosis. Cancer cells undergoing EMT exhibit enhanced aggressive behavior characterized by drug resistance, tumor-initiation potential, and the ability to evade the immune system. Recent in silico, in vitro, and in vivo evidence indicates that EMT is not an all-or-none process; instead, cells can stably acquire one or more hybrid epithelial/mesenchymal (E/M) phenotypes which often can be more aggressive than purely E or M cell populations. Thus, the EMT status of cancer cells can prove to be a critical estimate of patient prognosis. Recent attempts have employed different transcriptomics signatures to quantify EMT status in cell lines and patient tumors. However, a comprehensive comparison of these methods, including their accuracy in identifying cells in the hybrid E/M phenotype(s), is lacking. Here, we compare three distinct metrics that score EMT on a continuum, based on the transcriptomics signature of individual samples. Our results demonstrate that these methods exhibit good concordance among themselves in quantifying the extent of EMT in a given sample. Moreover, scoring EMT using any of the three methods discerned that cells can undergo varying extents of EMT across tumor types. Separately, our analysis also identified tumor types with maximum variability in terms of EMT and associated an enrichment of hybrid E/M signatures in these samples. Moreover, we also found that the multinomial logistic regression (MLR)-based metric was capable of distinguishing between "pure" individual hybrid E/M vs. mixtures of E and M cells. Our results, thus, suggest that while any of the three methods can indicate a generic trend in the EMT status of a given cell, the MLR method has two additional advantages: (a) it uses a small number of predictors to calculate the EMT score and (b) it can predict from the transcriptomic signature of a population whether it is comprised of "pure" hybrid E/M cells at the single-cell level or is instead an ensemble of E and M cell subpopulations.
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Affiliation(s)
- Priyanka Chakraborty
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bengaluru, India
| | - Jason T. George
- Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, United States
| | - Shubham Tripathi
- Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
- Ph.D. Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, TX, United States
- Department of Physics, College of Science, Northeastern University, Boston, MA, United States
| | - Herbert Levine
- Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
- Department of Physics, College of Science, Northeastern University, Boston, MA, United States
- Department of Bioengineering, College of Engineering, Northeastern University, Boston, MA, United States
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bengaluru, India
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Chakraborty P, George JT, Tripathi S, Levine H, Jolly MK. Comparative Study of Transcriptomics-Based Scoring Metrics for the Epithelial-Hybrid-Mesenchymal Spectrum. Front Bioeng Biotechnol 2020; 8:220. [PMID: 32266244 DOI: 10.3389/fbioe.2020.00220/full] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 03/04/2020] [Indexed: 05/28/2023] Open
Abstract
The Epithelial-mesenchymal transition (EMT) is a cellular process implicated in embryonic development, wound healing, and pathological conditions such as cancer metastasis and fibrosis. Cancer cells undergoing EMT exhibit enhanced aggressive behavior characterized by drug resistance, tumor-initiation potential, and the ability to evade the immune system. Recent in silico, in vitro, and in vivo evidence indicates that EMT is not an all-or-none process; instead, cells can stably acquire one or more hybrid epithelial/mesenchymal (E/M) phenotypes which often can be more aggressive than purely E or M cell populations. Thus, the EMT status of cancer cells can prove to be a critical estimate of patient prognosis. Recent attempts have employed different transcriptomics signatures to quantify EMT status in cell lines and patient tumors. However, a comprehensive comparison of these methods, including their accuracy in identifying cells in the hybrid E/M phenotype(s), is lacking. Here, we compare three distinct metrics that score EMT on a continuum, based on the transcriptomics signature of individual samples. Our results demonstrate that these methods exhibit good concordance among themselves in quantifying the extent of EMT in a given sample. Moreover, scoring EMT using any of the three methods discerned that cells can undergo varying extents of EMT across tumor types. Separately, our analysis also identified tumor types with maximum variability in terms of EMT and associated an enrichment of hybrid E/M signatures in these samples. Moreover, we also found that the multinomial logistic regression (MLR)-based metric was capable of distinguishing between "pure" individual hybrid E/M vs. mixtures of E and M cells. Our results, thus, suggest that while any of the three methods can indicate a generic trend in the EMT status of a given cell, the MLR method has two additional advantages: (a) it uses a small number of predictors to calculate the EMT score and (b) it can predict from the transcriptomic signature of a population whether it is comprised of "pure" hybrid E/M cells at the single-cell level or is instead an ensemble of E and M cell subpopulations.
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Affiliation(s)
- Priyanka Chakraborty
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bengaluru, India
| | - Jason T George
- Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, United States
| | - Shubham Tripathi
- Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
- Ph.D. Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, TX, United States
- Department of Physics, College of Science, Northeastern University, Boston, MA, United States
| | - Herbert Levine
- Center for Theoretical Biological Physics, Rice University, Houston, TX, United States
- Department of Physics, College of Science, Northeastern University, Boston, MA, United States
- Department of Bioengineering, College of Engineering, Northeastern University, Boston, MA, United States
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bengaluru, India
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Jolly MK, Celià-Terrassa T. Dynamics of Phenotypic Heterogeneity Associated with EMT and Stemness during Cancer Progression. J Clin Med 2019; 8:E1542. [PMID: 31557977 PMCID: PMC6832750 DOI: 10.3390/jcm8101542] [Citation(s) in RCA: 82] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/20/2019] [Accepted: 09/23/2019] [Indexed: 12/15/2022] Open
Abstract
Genetic and phenotypic heterogeneity contribute to the generation of diverse tumor cell populations, thus enhancing cancer aggressiveness and therapy resistance. Compared to genetic heterogeneity, a consequence of mutational events, phenotypic heterogeneity arises from dynamic, reversible cell state transitions in response to varying intracellular/extracellular signals. Such phenotypic plasticity enables rapid adaptive responses to various stressful conditions and can have a strong impact on cancer progression. Herein, we have reviewed relevant literature on mechanisms associated with dynamic phenotypic changes and cellular plasticity, such as epithelial-mesenchymal transition (EMT) and cancer stemness, which have been reported to facilitate cancer metastasis. We also discuss how non-cell-autonomous mechanisms such as cell-cell communication can lead to an emergent population-level response in tumors. The molecular mechanisms underlying the complexity of tumor systems are crucial for comprehending cancer progression, and may provide new avenues for designing therapeutic strategies.
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Affiliation(s)
- Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India.
| | - Toni Celià-Terrassa
- Cancer Research Program, IMIM (Hospital del Mar Medical Research Institute), 08003 Barcelona, Spain.
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