Short-term molecular consequences of chromosome mis-segregation for genome stability

  1. Lorenza Garribba
  2. Giuseppina De Feudis
  3. Valentino Martis
  4. Martina Galli
  5. Marie Dumont
  6. Yonatan Eliezer
  7. René Wardenaar
  8. Marica Rosaria Ippolito
  9. Divya Ramalingam Iyer
  10. Andréa E. Tijhuis
  11. Diana C. J. Spierings
  12. Michael Schubert
  13. Silvia Taglietti
  14. Chiara Soriani
  15. Simon Gemble
  16. Renata Basto
  17. Nick Rhind
  18. Floris Foijer
  19. Uri Ben-David
  20. Daniele Fachinetti
  21. Ylli Doksani
  22. Stefano Santaguida

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Abstract

Chromosome instability (CIN) is the most common form of genome instability and is a hallmark of cancer. CIN invariably leads to aneuploidy, a state of karyotype imbalance. Here, we show that aneuploidy can also trigger CIN. We found that aneuploid cells experience DNA replication stress in their first S-phase and precipitate in a state of continuous CIN. This generates a repertoire of genetically diverse cells with structural chromosomal abnormalities that can either continue proliferating or stop dividing. Cycling aneuploid cells display lower karyotype complexity compared to the arrested ones and increased expression of DNA repair signatures. Interestingly, the same signatures are upregulated in highly-proliferative cancer cells, which might enable them to proliferate despite the disadvantage conferred by aneuploidy-induced CIN. Altogether, our study reveals the short-term origins of CIN following aneuploidy and indicates the aneuploid state of cancer cells as a point mutation-independent source of genome instability, providing an explanation for aneuploidy occurrence in tumors.

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  1. Version published to 10.1038/s41467-023-37095-7
  2. Version published to 10.1101/2022.06.19.496702v2 on bioRxiv
  3. ASAPbio crowd review

    Review coordinated via ASAPbio’s crowd preprint review

    This review reflects comments and contributions by Ashley Albright, Samuel Lord, Arthur Molines and Sónia Gomes Pereira. Review synthesized by Iratxe Puebla.

    The paper studies the involvement of aneuploidy in promoting chromosomal instability and suggests the aneuploid state of cancer cells as a point-mutation independent source of genome instability. The paper reports a considerable amount of data. We outline below some suggestions regarding presentation and the analyses reported:

    ‘mis-segregation in otherwise pseudo-diploid human cells’ - Please provide some explanation for the term ‘pseudo-diploid’.

    ‘suggesting that dormant replication origins’ - Please provide a sentence clarifying the meaning of ‘dormant replication’.

    ‘Cells activate dormant origins in response to reduced fork rate and stalled forks to ensure that the genome gets fully replicated in time’ - Please provide a reference to support this statement.

    Figure 3

    • Recommend re-arranging the order and position of the panels for greater clarity.
    • ‘Interestingly, we found a positive correlation between S phase length and frequency of abnormal mitoses (mean S phase length in control: 603,3 ± 55,4; aneuploid: 728,7 ± 46,2) (Fig. 3c).’ - Figure 3C shows that the cells that have an abnormal mitosis had a slightly longer S phase on average, however there is no correlation analysis done or an analysis around "frequency of abnormal mitosis", recommend revising the sentence.
    • Figure 3C - Cells with a longer S phase (or cell cycle in general) will receive more light before reaching mitosis. Is it possible that the correlation mentioned is due to photo-toxicity? Longer S phase -> more photo-toxicity -> abnormal mitosis. Recommend adding a control to account for the potential phototoxicity of the imaging.

    Figure 4 - Panels C and D show that, among the cells that have foci, the number of foci is increased, either by aneuploidy or by the drugs. However, it is unclear from the data if the number of cells with foci also increases. Would it be possible to plot the % of cells with more than 1 foci for each condition? (as in Figure 4G). Also, C and D are aggregates of multiple experiments, it would be good to show the data per replicates.

    ‘there was a sub-population of senescent cells in the aneuploid sample (Fig. 5a)’ - Was senescence tested in the normal (euploid) population too (at the same passage)? Is that the sample named as "control" in the figure legend?

    ‘in aneuploid cycling cells was comparable to that of the controls for at least 3 generations by live-cell imaging (Fig. 6a-c)’ - Suggest clarifying here what the control is, in addition to naming it in the figure legend.

    Comments on analyses/reporting

    • In various figures (including Figures 1H,J,L,N,O; 2C,G,E; 3I; 4C,D; 5H,I; 6H,I,J), there is a concern about the statistical approach to calculate p-values based on multiple measurements or cells within each sample. The t-test assumes that each measurement is independent, and multiple cells within the same sample are not independent. Recommend either not reporting p-values or averaging together the values from each sample and calculating the p-value using those sample-level means. For more information, see https://doi.org/10.1371/journal.pbio.2005282 and https://doi.org/10.1083/jcb.202001064
    • For each bar graph throughout the paper, recommend reporting the value of n, in the figure itself, the figure legend, or in the text. Using Figure 1C as an example, this reports a doubling in the number of cells with greater than 10 errors, but the significance of that would vary depending on the number of cells analyzed. Some plots in panels c and f have no error bars, and it would be useful to report the number of experiments.
    • Almost every figure features representative images. The manuscript includes a massive amount of data already, but it may be relevant to show additional images in the supplement in cases where representative images are used in figures.
    • Data analysis for RNAseq ‘results were filtered only based on p-value’ - Please clarify why the False Discovery Rate was not taken into the filtering step.
  4. Version published to 10.1101/2022.06.19.496702v1 on bioRxiv