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A survey of CIN measures across mechanistic models
Chromosomal instability (CIN) is the persistent reshuffling of cancer karyotypes via chromosome mis-segregation during cell division. In cancer, CIN exists at varying levels that have differential effects on tumor progression. However, mis-segregation rates remain challenging to assess in human canc...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312700/ https://www.ncbi.nlm.nih.gov/pubmed/37398147 http://dx.doi.org/10.1101/2023.06.15.544840 |
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author | Lynch, Andrew R. Bradford, Shermineh Zhou, Amber S. Oxendine, Kim Henderson, Les Horner, Vanessa L. Weaver, Beth A. Burkard, Mark E. |
author_facet | Lynch, Andrew R. Bradford, Shermineh Zhou, Amber S. Oxendine, Kim Henderson, Les Horner, Vanessa L. Weaver, Beth A. Burkard, Mark E. |
author_sort | Lynch, Andrew R. |
collection | PubMed |
description | Chromosomal instability (CIN) is the persistent reshuffling of cancer karyotypes via chromosome mis-segregation during cell division. In cancer, CIN exists at varying levels that have differential effects on tumor progression. However, mis-segregation rates remain challenging to assess in human cancer despite an array of available measures. We evaluated measures of CIN by comparing quantitative methods using specific, inducible phenotypic CIN models of chromosome bridges, pseudobipolar spindles, multipolar spindles, and polar chromosomes. For each, we measured CIN fixed and timelapse fluorescence microscopy, chromosome spreads, 6-centromere FISH, bulk transcriptomics, and single cell DNA sequencing (scDNAseq). As expected, microscopy of tumor cells in live and fixed samples correlated well (R=0.77; p<0.01) and sensitively detect CIN. Cytogenetics approaches include chromosome spreads and 6-centromere FISH, which also correlate well (R=0.77; p<0.01) but had limited sensitivity for lower rates of CIN. Bulk genomic DNA signatures and bulk transcriptomic scores, CIN70 and HET70, did not detect CIN. By contrast, single-cell DNA sequencing (scDNAseq) detects CIN with high sensitivity, and correlates very well with imaging methods (R=0.83; p<0.01). In summary, single-cell methods such as imaging, cytogenetics, and scDNAseq can measure CIN, with the latter being the most comprehensive method accessible to clinical samples. To facilitate comparison of CIN rates between phenotypes and methods, we propose a standardized unit of CIN: Mis-segregations per Diploid Division (MDD). This systematic analysis of common CIN measures highlights the superiority of single-cell methods and provides guidance for measuring CIN in the clinical setting. |
format | Online Article Text |
id | pubmed-10312700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-103127002023-07-01 A survey of CIN measures across mechanistic models Lynch, Andrew R. Bradford, Shermineh Zhou, Amber S. Oxendine, Kim Henderson, Les Horner, Vanessa L. Weaver, Beth A. Burkard, Mark E. bioRxiv Article Chromosomal instability (CIN) is the persistent reshuffling of cancer karyotypes via chromosome mis-segregation during cell division. In cancer, CIN exists at varying levels that have differential effects on tumor progression. However, mis-segregation rates remain challenging to assess in human cancer despite an array of available measures. We evaluated measures of CIN by comparing quantitative methods using specific, inducible phenotypic CIN models of chromosome bridges, pseudobipolar spindles, multipolar spindles, and polar chromosomes. For each, we measured CIN fixed and timelapse fluorescence microscopy, chromosome spreads, 6-centromere FISH, bulk transcriptomics, and single cell DNA sequencing (scDNAseq). As expected, microscopy of tumor cells in live and fixed samples correlated well (R=0.77; p<0.01) and sensitively detect CIN. Cytogenetics approaches include chromosome spreads and 6-centromere FISH, which also correlate well (R=0.77; p<0.01) but had limited sensitivity for lower rates of CIN. Bulk genomic DNA signatures and bulk transcriptomic scores, CIN70 and HET70, did not detect CIN. By contrast, single-cell DNA sequencing (scDNAseq) detects CIN with high sensitivity, and correlates very well with imaging methods (R=0.83; p<0.01). In summary, single-cell methods such as imaging, cytogenetics, and scDNAseq can measure CIN, with the latter being the most comprehensive method accessible to clinical samples. To facilitate comparison of CIN rates between phenotypes and methods, we propose a standardized unit of CIN: Mis-segregations per Diploid Division (MDD). This systematic analysis of common CIN measures highlights the superiority of single-cell methods and provides guidance for measuring CIN in the clinical setting. Cold Spring Harbor Laboratory 2023-06-15 /pmc/articles/PMC10312700/ /pubmed/37398147 http://dx.doi.org/10.1101/2023.06.15.544840 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Lynch, Andrew R. Bradford, Shermineh Zhou, Amber S. Oxendine, Kim Henderson, Les Horner, Vanessa L. Weaver, Beth A. Burkard, Mark E. A survey of CIN measures across mechanistic models |
title | A survey of CIN measures across mechanistic models |
title_full | A survey of CIN measures across mechanistic models |
title_fullStr | A survey of CIN measures across mechanistic models |
title_full_unstemmed | A survey of CIN measures across mechanistic models |
title_short | A survey of CIN measures across mechanistic models |
title_sort | survey of cin measures across mechanistic models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312700/ https://www.ncbi.nlm.nih.gov/pubmed/37398147 http://dx.doi.org/10.1101/2023.06.15.544840 |
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