Preprint
A survey of CIN measures across mechanistic models
bioRxiv : the preprint server for biology
06/15/2023
PMCID: PMC10312700
PMID: 37398147
Abstract
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.
Details
- Title: Subtitle
- A survey of CIN measures across mechanistic models
- Creators
- Andrew R Lynch - University of Wisconsin–MadisonShermineh Bradford - University of Wisconsin–MadisonAmber S Zhou - University of Wisconsin–MadisonKim Oxendine - University of Wisconsin–MadisonLes Henderson - University of Wisconsin–MadisonVanessa L Horner - University of Wisconsin–MadisonBeth A Weaver - University of Wisconsin–MadisonMark E Burkard - University of Wisconsin–Madison
- Resource Type
- Preprint
- Publication Details
- bioRxiv : the preprint server for biology
- Publisher
- United States
- PMID
- 37398147
- PMCID
- PMC10312700
- Grant note
- F31 CA254247 / NCI NIH HHS S10 RR025483 / NCRR NIH HHS T32 HG002760 / NHGRI NIH HHS T32 GM008688 / NIGMS NIH HHS P30 CA014520 / NCI NIH HHS R01 CA234904 / NCI NIH HHS
- Language
- English
- Date posted
- 06/15/2023
- Academic Unit
- Internal Medicine
- Record Identifier
- 9984700648902771
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