A survey of chromosomal instability measures across mechanistic models

• 成果类型: Article
• 署名作者: Lynch, Andrew R.; Bradford, Shermineh; Zhou, Amber S.; Oxendine, Kim; Henderson, Les; Horner, Vanessa L.; Weaver, Beth A.; Burkard, Mark E.
• 署名单位: University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-10035
• DOI: 10.1073/pnas.2309621121
• 发表日期: 2024-04-16
• 关键词: mis-segregation; aneuploidy; EVOLUTION; cancer; cells; metastasis; signature

摘要

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, six- centromere FISH, bulk transcriptomics, and single - cell DNA sequencing (scDNAseq). As expected, microscopy of tumor cells in live and fixed samples significantly correlated (R = 0.72; P < 0.001) and sensitively detect CIN. Cytogenetics approaches include chromosome spreads and 6- centromere FISH, which also significantly correlate (R = 0.76; P < 0.001) 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, scDNAseq detects CIN with high sensitivity, and significantly correlates with imaging methods (R = 0.82; P < 0.001). 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 the comparison of CIN rates between phenotypes and methods, we propose a standardized unit of CIN: Mis- segregations per Diploid Division. This systematic analysis of common CIN measures highlights the superiority of single - cell methods and provides guidance for measuring CIN in the clinical setting.