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Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation
Cancer patients often harbor occult metastases, a potential source of relapse that is targetable only through systemic therapy. Studies of this occult fraction have been limited by a lack of tools with which to isolate discrete cells on spatial grounds. We developed PIC-IT, a photoconversion-based i...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7929558/ https://www.ncbi.nlm.nih.gov/pubmed/33620315 http://dx.doi.org/10.7554/eLife.63270 |
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author | Sela, Yogev Li, Jinyang Kuri, Paola Merrell, Allyson J Li, Ning Lengner, Chris Rompolas, Pantelis Stanger, Ben Z |
author_facet | Sela, Yogev Li, Jinyang Kuri, Paola Merrell, Allyson J Li, Ning Lengner, Chris Rompolas, Pantelis Stanger, Ben Z |
author_sort | Sela, Yogev |
collection | PubMed |
description | Cancer patients often harbor occult metastases, a potential source of relapse that is targetable only through systemic therapy. Studies of this occult fraction have been limited by a lack of tools with which to isolate discrete cells on spatial grounds. We developed PIC-IT, a photoconversion-based isolation technique allowing efficient recovery of cell clusters of any size – including single-metastatic cells – which are largely inaccessible otherwise. In a murine pancreatic cancer model, transcriptional profiling of spontaneously arising microcolonies revealed phenotypic heterogeneity, functionally reduced propensity to proliferate and enrichment for an inflammatory-response phenotype associated with NF-κB/AP-1 signaling. Pharmacological inhibition of NF-κB depleted microcolonies but had no effect on macrometastases, suggesting microcolonies are particularly dependent on this pathway. PIC-IT thus enables systematic investigation of metastatic heterogeneity. Moreover, the technique can be applied to other biological systems in which isolation and characterization of spatially distinct cell populations is not currently feasible. |
format | Online Article Text |
id | pubmed-7929558 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-79295582021-03-04 Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation Sela, Yogev Li, Jinyang Kuri, Paola Merrell, Allyson J Li, Ning Lengner, Chris Rompolas, Pantelis Stanger, Ben Z eLife Cancer Biology Cancer patients often harbor occult metastases, a potential source of relapse that is targetable only through systemic therapy. Studies of this occult fraction have been limited by a lack of tools with which to isolate discrete cells on spatial grounds. We developed PIC-IT, a photoconversion-based isolation technique allowing efficient recovery of cell clusters of any size – including single-metastatic cells – which are largely inaccessible otherwise. In a murine pancreatic cancer model, transcriptional profiling of spontaneously arising microcolonies revealed phenotypic heterogeneity, functionally reduced propensity to proliferate and enrichment for an inflammatory-response phenotype associated with NF-κB/AP-1 signaling. Pharmacological inhibition of NF-κB depleted microcolonies but had no effect on macrometastases, suggesting microcolonies are particularly dependent on this pathway. PIC-IT thus enables systematic investigation of metastatic heterogeneity. Moreover, the technique can be applied to other biological systems in which isolation and characterization of spatially distinct cell populations is not currently feasible. eLife Sciences Publications, Ltd 2021-02-23 /pmc/articles/PMC7929558/ /pubmed/33620315 http://dx.doi.org/10.7554/eLife.63270 Text en © 2021, Sela et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Cancer Biology Sela, Yogev Li, Jinyang Kuri, Paola Merrell, Allyson J Li, Ning Lengner, Chris Rompolas, Pantelis Stanger, Ben Z Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation |
title | Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation |
title_full | Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation |
title_fullStr | Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation |
title_full_unstemmed | Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation |
title_short | Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation |
title_sort | dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation |
topic | Cancer Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7929558/ https://www.ncbi.nlm.nih.gov/pubmed/33620315 http://dx.doi.org/10.7554/eLife.63270 |
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