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Modeling cancer progression using human pluripotent stem cell-derived cells and organoids
Conventional cancer cell lines and animal models have been mainstays of cancer research. More recently, human pluripotent stem cells (hPSCs) and hPSC-derived organoid technologies, together with genome engineering approaches, have provided a complementary platform to model cancer progression. Here,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7849931/ https://www.ncbi.nlm.nih.gov/pubmed/33137568 http://dx.doi.org/10.1016/j.scr.2020.102063 |
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author | Zhang, Meili Vandana, J. Jeya Lacko, Lauretta Chen, Shuibing |
author_facet | Zhang, Meili Vandana, J. Jeya Lacko, Lauretta Chen, Shuibing |
author_sort | Zhang, Meili |
collection | PubMed |
description | Conventional cancer cell lines and animal models have been mainstays of cancer research. More recently, human pluripotent stem cells (hPSCs) and hPSC-derived organoid technologies, together with genome engineering approaches, have provided a complementary platform to model cancer progression. Here, we review the application of these technologies in cancer modeling with respect to the cell-of-origin, cancer propagation, and metastasis. We further discuss the benefits and challenges accompanying the use of hPSC models for cancer research and discuss their broad applicability in drug discovery, biomarker identification, decoding molecular mechanisms, and the deconstruction of clonal and intra-tumoral heterogeneity. In summary, hPSC-derived organoids provide powerful models to recapitulate the pathogenic states in cancer and to perform drug discovery. |
format | Online Article Text |
id | pubmed-7849931 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-78499312021-02-01 Modeling cancer progression using human pluripotent stem cell-derived cells and organoids Zhang, Meili Vandana, J. Jeya Lacko, Lauretta Chen, Shuibing Stem Cell Res Article Conventional cancer cell lines and animal models have been mainstays of cancer research. More recently, human pluripotent stem cells (hPSCs) and hPSC-derived organoid technologies, together with genome engineering approaches, have provided a complementary platform to model cancer progression. Here, we review the application of these technologies in cancer modeling with respect to the cell-of-origin, cancer propagation, and metastasis. We further discuss the benefits and challenges accompanying the use of hPSC models for cancer research and discuss their broad applicability in drug discovery, biomarker identification, decoding molecular mechanisms, and the deconstruction of clonal and intra-tumoral heterogeneity. In summary, hPSC-derived organoids provide powerful models to recapitulate the pathogenic states in cancer and to perform drug discovery. 2020-10-27 2020-12 /pmc/articles/PMC7849931/ /pubmed/33137568 http://dx.doi.org/10.1016/j.scr.2020.102063 Text en This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Zhang, Meili Vandana, J. Jeya Lacko, Lauretta Chen, Shuibing Modeling cancer progression using human pluripotent stem cell-derived cells and organoids |
title | Modeling cancer progression using human pluripotent stem cell-derived cells and organoids |
title_full | Modeling cancer progression using human pluripotent stem cell-derived cells and organoids |
title_fullStr | Modeling cancer progression using human pluripotent stem cell-derived cells and organoids |
title_full_unstemmed | Modeling cancer progression using human pluripotent stem cell-derived cells and organoids |
title_short | Modeling cancer progression using human pluripotent stem cell-derived cells and organoids |
title_sort | modeling cancer progression using human pluripotent stem cell-derived cells and organoids |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7849931/ https://www.ncbi.nlm.nih.gov/pubmed/33137568 http://dx.doi.org/10.1016/j.scr.2020.102063 |
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