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Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration
SIMPLE SUMMARY: In this study, we normalized trajectories containing both mesenchymal and epithelial cells to remove the effect of cell location on clustering, and performed a dimensionality reduction on the time series data before clustering. When the clustering results were superimposed on the tra...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559181/ https://www.ncbi.nlm.nih.gov/pubmed/36230509 http://dx.doi.org/10.3390/cancers14194587 |
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author | Xin, Zhuohan Kajita, Masashi K. Deguchi, Keiko Suye, Shin-ichiro Fujita, Satoshi |
author_facet | Xin, Zhuohan Kajita, Masashi K. Deguchi, Keiko Suye, Shin-ichiro Fujita, Satoshi |
author_sort | Xin, Zhuohan |
collection | PubMed |
description | SIMPLE SUMMARY: In this study, we normalized trajectories containing both mesenchymal and epithelial cells to remove the effect of cell location on clustering, and performed a dimensionality reduction on the time series data before clustering. When the clustering results were superimposed on the trajectories prior to normalization, the results still showed similarities in location, indicating that this method can find cells with similar migration patterns. These data highlight the reliability of this method in identifying consistent migration patterns in collective cell migration. ABSTRACT: Collective invasion drives multicellular cancer cells to spread to surrounding normal tissues. To fully comprehend metastasis, the methodology of analysis of individual cell migration in tissue should be well developed. Extracting and classifying cells with similar migratory characteristics in a colony would facilitate an understanding of complex cell migration patterns. Here, we used electrospun fibers as the extracellular matrix for the in vitro modeling of collective cell migration, clustering of mesenchymal and epithelial cells based on trajectories, and analysis of collective migration patterns based on trajectory similarity. We normalized the trajectories to eliminate the effect of cell location on clustering and used uniform manifold approximation and projection to perform dimensionality reduction on the time-series data before clustering. When the clustering results were superimposed on the trajectories before normalization, the results still exhibited positional similarity, thereby demonstrating that this method can identify cells with similar migration patterns. The same cluster contained both mesenchymal and epithelial cells, and this result was related to cell location and cell division. These data highlight the reliability of this method in identifying consistent migration patterns during collective cell migration. This provides new insights into the epithelial–mesenchymal interactions that affect migration patterns. |
format | Online Article Text |
id | pubmed-9559181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95591812022-10-14 Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration Xin, Zhuohan Kajita, Masashi K. Deguchi, Keiko Suye, Shin-ichiro Fujita, Satoshi Cancers (Basel) Article SIMPLE SUMMARY: In this study, we normalized trajectories containing both mesenchymal and epithelial cells to remove the effect of cell location on clustering, and performed a dimensionality reduction on the time series data before clustering. When the clustering results were superimposed on the trajectories prior to normalization, the results still showed similarities in location, indicating that this method can find cells with similar migration patterns. These data highlight the reliability of this method in identifying consistent migration patterns in collective cell migration. ABSTRACT: Collective invasion drives multicellular cancer cells to spread to surrounding normal tissues. To fully comprehend metastasis, the methodology of analysis of individual cell migration in tissue should be well developed. Extracting and classifying cells with similar migratory characteristics in a colony would facilitate an understanding of complex cell migration patterns. Here, we used electrospun fibers as the extracellular matrix for the in vitro modeling of collective cell migration, clustering of mesenchymal and epithelial cells based on trajectories, and analysis of collective migration patterns based on trajectory similarity. We normalized the trajectories to eliminate the effect of cell location on clustering and used uniform manifold approximation and projection to perform dimensionality reduction on the time-series data before clustering. When the clustering results were superimposed on the trajectories before normalization, the results still exhibited positional similarity, thereby demonstrating that this method can identify cells with similar migration patterns. The same cluster contained both mesenchymal and epithelial cells, and this result was related to cell location and cell division. These data highlight the reliability of this method in identifying consistent migration patterns during collective cell migration. This provides new insights into the epithelial–mesenchymal interactions that affect migration patterns. MDPI 2022-09-22 /pmc/articles/PMC9559181/ /pubmed/36230509 http://dx.doi.org/10.3390/cancers14194587 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xin, Zhuohan Kajita, Masashi K. Deguchi, Keiko Suye, Shin-ichiro Fujita, Satoshi Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration |
title | Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration |
title_full | Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration |
title_fullStr | Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration |
title_full_unstemmed | Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration |
title_short | Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration |
title_sort | time-series clustering of single-cell trajectories in collective cell migration |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559181/ https://www.ncbi.nlm.nih.gov/pubmed/36230509 http://dx.doi.org/10.3390/cancers14194587 |
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