Cargando…
Revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mLSR-3D and STAPL-3D
Despite advances in three-dimensional (3D) imaging, it remains challenging to profile all the cells within a large 3D tissue, including the morphology and organization of the many cell types present. Here, we introduce eight-color, multispectral, large-scale single-cell resolution 3D (mLSR-3D) imagi...
Autores principales: | , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611791/ https://www.ncbi.nlm.nih.gov/pubmed/34083793 http://dx.doi.org/10.1038/s41587-021-00926-3 |
_version_ | 1783605305396953088 |
---|---|
author | van Ineveld, Ravian L. Kleinnijenhuis, Michiel Alieva, Maria de Blank, Sam Roman, Mario Barrera van Vliet, Esmée J. Mir, Clara Martínez Johnson, Hannah R. Bos, Frank L. Heukers, Raimond Chuva de Sousa Lopes, Susana M. Drost, Jarno Dekkers, Johanna F. Wehrens, Ellen J. Rios, Anne C. |
author_facet | van Ineveld, Ravian L. Kleinnijenhuis, Michiel Alieva, Maria de Blank, Sam Roman, Mario Barrera van Vliet, Esmée J. Mir, Clara Martínez Johnson, Hannah R. Bos, Frank L. Heukers, Raimond Chuva de Sousa Lopes, Susana M. Drost, Jarno Dekkers, Johanna F. Wehrens, Ellen J. Rios, Anne C. |
author_sort | van Ineveld, Ravian L. |
collection | PubMed |
description | Despite advances in three-dimensional (3D) imaging, it remains challenging to profile all the cells within a large 3D tissue, including the morphology and organization of the many cell types present. Here, we introduce eight-color, multispectral, large-scale single-cell resolution 3D (mLSR-3D) imaging and image analysis software for the parallelized, deep learning-based segmentation of large numbers of single cells in tissues, called segmentation analysis by parallelization of 3D datasets (STAPL-3D). Applying the method to pediatric Wilms tumor, we extract molecular, spatial and morphological features of millions of cells and reconstruct the tumor’s spatio-phenotypic patterning. In situ population profiling and pseudotime ordering reveals a highly disorganized spatial pattern in Wilms tumor compared to healthy fetal kidney, yet cellular profiles closely resembling human fetal kidney cells could be observed. In addition, we identify previously unreported tumor-specific populations, uniquely characterized by their spatial embedding or morphological attributes. Our results demonstrate the use of combining mLSR-3D and STAPL-3D to generate a comprehensive cellular map of human tumors. |
format | Online Article Text |
id | pubmed-7611791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76117912021-10-10 Revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mLSR-3D and STAPL-3D van Ineveld, Ravian L. Kleinnijenhuis, Michiel Alieva, Maria de Blank, Sam Roman, Mario Barrera van Vliet, Esmée J. Mir, Clara Martínez Johnson, Hannah R. Bos, Frank L. Heukers, Raimond Chuva de Sousa Lopes, Susana M. Drost, Jarno Dekkers, Johanna F. Wehrens, Ellen J. Rios, Anne C. Nat Biotechnol Article Despite advances in three-dimensional (3D) imaging, it remains challenging to profile all the cells within a large 3D tissue, including the morphology and organization of the many cell types present. Here, we introduce eight-color, multispectral, large-scale single-cell resolution 3D (mLSR-3D) imaging and image analysis software for the parallelized, deep learning-based segmentation of large numbers of single cells in tissues, called segmentation analysis by parallelization of 3D datasets (STAPL-3D). Applying the method to pediatric Wilms tumor, we extract molecular, spatial and morphological features of millions of cells and reconstruct the tumor’s spatio-phenotypic patterning. In situ population profiling and pseudotime ordering reveals a highly disorganized spatial pattern in Wilms tumor compared to healthy fetal kidney, yet cellular profiles closely resembling human fetal kidney cells could be observed. In addition, we identify previously unreported tumor-specific populations, uniquely characterized by their spatial embedding or morphological attributes. Our results demonstrate the use of combining mLSR-3D and STAPL-3D to generate a comprehensive cellular map of human tumors. 2021-10-01 2021-06-03 /pmc/articles/PMC7611791/ /pubmed/34083793 http://dx.doi.org/10.1038/s41587-021-00926-3 Text en http://www.nature.com/authors/editorial_policies/license.html#termsUsers may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article van Ineveld, Ravian L. Kleinnijenhuis, Michiel Alieva, Maria de Blank, Sam Roman, Mario Barrera van Vliet, Esmée J. Mir, Clara Martínez Johnson, Hannah R. Bos, Frank L. Heukers, Raimond Chuva de Sousa Lopes, Susana M. Drost, Jarno Dekkers, Johanna F. Wehrens, Ellen J. Rios, Anne C. Revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mLSR-3D and STAPL-3D |
title | Revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mLSR-3D and STAPL-3D |
title_full | Revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mLSR-3D and STAPL-3D |
title_fullStr | Revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mLSR-3D and STAPL-3D |
title_full_unstemmed | Revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mLSR-3D and STAPL-3D |
title_short | Revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mLSR-3D and STAPL-3D |
title_sort | revealing the spatio-phenotypic patterning of cells in healthy and tumor tissues with mlsr-3d and stapl-3d |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611791/ https://www.ncbi.nlm.nih.gov/pubmed/34083793 http://dx.doi.org/10.1038/s41587-021-00926-3 |
work_keys_str_mv | AT vanineveldravianl revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT kleinnijenhuismichiel revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT alievamaria revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT deblanksam revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT romanmariobarrera revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT vanvlietesmeej revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT mirclaramartinez revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT johnsonhannahr revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT bosfrankl revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT heukersraimond revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT chuvadesousalopessusanam revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT drostjarno revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT dekkersjohannaf revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT wehrensellenj revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d AT riosannec revealingthespatiophenotypicpatterningofcellsinhealthyandtumortissueswithmlsr3dandstapl3d |