Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Chronic p53-independent p21 expression causes genomic instability by deregulating replication licensing

Nature Cell Biology volume 18, pages 777–789 (2016)Cite this article

Subjects

Abstract

The cyclin-dependent kinase inhibitor p21WAF1/CIP1 (p21) is a cell-cycle checkpoint effector and inducer of senescence, regulated by p53. Yet, evidence suggests that p21 could also be oncogenic, through a mechanism that has so far remained obscure. We report that a subset of atypical cancerous cells strongly expressing p21 showed proliferation features. This occurred predominantly in p53-mutant human cancers, suggesting p53-independent upregulation of p21 selectively in more aggressive tumour cells. Multifaceted phenotypic and genomic analyses of p21-inducible, p53-null, cancerous and near-normal cellular models showed that after an initial senescence-like phase, a subpopulation of p21-expressing proliferating cells emerged, featuring increased genomic instability, aggressiveness and chemoresistance. Mechanistically, sustained p21 accumulation inhibited mainly the CRL4–CDT2 ubiquitin ligase, leading to deregulated origin licensing and replication stress. Collectively, our data reveal the tumour-promoting ability of p21 through deregulation of DNA replication licensing machinery—an unorthodox role to be considered in cancer treatment, since p21 responds to various stimuli including some chemotherapy drugs.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: p21 and Ki67 are co-expressed in a subset of atypical cells of high-grade/poorly differentiated, advanced human carcinomas and precancerous lesions.
Figure 2: Prolonged stimulation of p21 upregulates and stabilizes the RLFs CDC6 and CDT1 at the protein level.
Figure 3: The status of p53 defines the ability of p21 to regulate the levels of CDT1 and CDC6.
Figure 4: Sustained p21 expression triggers replication stress and DNA damage accumulation in a CDT1/CDC6-dependent manner in S phase.
Figure 5: Extended p21 overexpression mediates accumulation of replication intermediate lesions that are processed by MUS81–EME1 and repaired by a Rad52-dependent mechanism.
Figure 6: Deregulated upregulation of CDC6/CDT1 links p53-independent activation of p21 with senescence.
Figure 7: Prolonged p21 expression, in cells with p53 loss of function, overrides the senescence barrier.
Figure 8: p21-expressing cells that have overridden (escaped) the senescence barrier demonstrate genomic instability and aggressive behaviour.

Similar content being viewed by others

Accession codes

Accessions

Gene Expression Omnibus

Proteomics Identifications Database

Sequence Read Archive

References

  1. Abbas, T. & Dutta, A. p21 in cancer: intricate networks and multiple activities. Nat. Rev. Cancer 9, 400–414 (2009).

    Article  CAS  Google Scholar 

  2. Roninson, I. B. Oncogenic functions of tumour suppressor p21(Waf1/Cip1/Sdi1): association with cell senescence and tumour-promoting activities of stromal fibroblasts. Cancer Lett. 179, 1–14 (2002).

    Article  CAS  Google Scholar 

  3. Pateras, I. S., Apostolopoulou, K., Niforou, K., Kotsinas, A. & Gorgoulis, V. G. p57KIP2: “Kip”ing the cell under control. Mol. Cancer Res. 7, 1902–1919 (2009).

    Article  CAS  Google Scholar 

  4. Rivlin, N., Brosh, R., Oren, M. & Rotter, V. Mutations in the p53 tumor suppressor gene: important milestones at the various steps of tumorigenesis. Genes Cancer 2, 466–474 (2011).

    Article  CAS  Google Scholar 

  5. Warfel, N. A. & El-Deiry, W. S. p21WAF1 and tumourigenesis: 20 years after. Curr. Opin. Oncol. 25, 52–58 (2013).

    Article  CAS  Google Scholar 

  6. Abbas, T., Keaton, M. A. & Dutta, A. Genomic instability in cancer. Cold Spring Harb. Perspect. Biol. 5, a012914 (2013).

    Article  Google Scholar 

  7. Blow, J. J. & Dutta, A. Preventing re-replication of chromosomal DNA. Nat. Rev. Mol. Cell Biol. 6, 476–486 (2005).

    Article  CAS  Google Scholar 

  8. Petrakis, T. G. et al. Exploring and exploiting the systemic effects of deregulated replication licensing. Semin. Cancer Biol. 37–38, 3–15 (2016).

    Article  Google Scholar 

  9. Blow, J. J. & Gillespie, P. J. Replication licensing and cancer—a fatal entanglement? Nat. Rev. Cancer 8, 799–806 (2008).

    Article  CAS  Google Scholar 

  10. Negrini, S., Gorgoulis, V. G. & Halazonetis, T. D. Genomic instability—an evolving hallmark of cancer. Nat. Rev. Mol. Cell Biol. 11, 220–228 (2010).

    Article  CAS  Google Scholar 

  11. Halazonetis, T. D., Gorgoulis, V. G. & Bartek, J. An oncogene-induced DNA damage model for cancer development. Science 319, 1352–1355 (2008).

    Article  CAS  Google Scholar 

  12. Sideridou, M. et al. Cdc6 expression represses E-cadherin transcription and activates adjacent replication origins. J. Cell Biol. 195, 1123–1140 (2011).

    Article  CAS  Google Scholar 

  13. Karakaidos, P. et al. Overexpression of the replication licensing regulators hCdt1 and hCdc6 characterizes a subset of non-small-cell lung carcinomas: synergistic effect with mutant p53 on tumor growth and chromosomal instability-evidence of E2F-1 transcriptional control over hCdt1. Am. J. Pathol. 165, 1351–1365 (2004).

    Article  CAS  Google Scholar 

  14. Liontos, M. et al. Deregulated overexpression of hCdt1 and hCdc6 promotes malignant behavior. Cancer Res. 67, 10899–10909 (2007).

    Article  CAS  Google Scholar 

  15. Rosai, J. R. Ackerman’s Surgical Pathology (Elsevier, 2011).

    Google Scholar 

  16. Velimezi, G. et al. Functional interplay between the DNA-damage-response kinase ATM and ARF tumour suppressor protein in human cancer. Nat. Cell Biol. 15, 967–977 (2013).

    Article  CAS  Google Scholar 

  17. Cooks, T. et al. Mutant p53 prolongs NF-κB activation and promotes chronic inflammation and inflammation-associated colorectal cancer. Cancer Cell 23, 634–646 (2013).

    Article  CAS  Google Scholar 

  18. Agarwal, M. L., Agarwal, A., Taylor, W. R. & Stark, G. R. p53 controls both the G2/M and the G1 cell cycle checkpoints and mediates reversible growth arrest in human fibroblasts. Proc. Natl Acad. Sci. USA 92, 8493–8497 (1995).

    Article  CAS  Google Scholar 

  19. Bates, S., Ryan, K. M., Phillips, A. C. & Vousden, K. H. Cell cycle arrest and DNA endoreduplication following p21Waf1/Cip1 expression. Oncogene 17, 1691–1703 (1998).

    Article  CAS  Google Scholar 

  20. Havens, C. G. & Walter, J. C. Mechanism of CRL4(Cdt2), a PCNA-dependent E3 ubiquitin ligase. Genes Dev. 25, 1568–1582 (2011).

    Article  CAS  Google Scholar 

  21. Jørgensen, S. et al. SET8 is degraded via PCNA-coupled CRL4(CDT2) ubiquitylation in S phase and after UV irradiation. J. Cell Biol. 192, 43–54 (2011).

    Article  Google Scholar 

  22. Gibbs, E. et al. The influence of the proliferating cell nuclear antigen-interacting domain of p21(CIP1) on DNA synthesis catalyzed by the human and Saccharomyces cerevisiae polymerase delta holoenzymes. J. Biol. Chem. 272, 2373–2381 (1997).

    Article  CAS  Google Scholar 

  23. Duursma, A. & Agami, R. p53-dependent regulation of Cdc6 protein stability controls cellular proliferation. Mol. Cell. Biol. 25, 6937–6947 (2005).

    Article  CAS  Google Scholar 

  24. Peart, M. J. et al. APC/C(Cdc20) targets E2F1 for degradation in prometaphase. Cell Cycle 9, 3956–3964 (2010).

    Article  CAS  Google Scholar 

  25. Budhavarapu, V. N. et al. Regulation of E2F1 by APC/C Cdh1 via K11 linkage-specific ubiquitin chain formation. Cell Cycle 11, 2030–2038 (2012).

    Article  CAS  Google Scholar 

  26. Vaziri, C. et al. A p53-dependent checkpoint pathway prevents rereplication. Mol. Cell 11, 997–1008 (2003).

    Article  CAS  Google Scholar 

  27. Gorgoulis, V. G. et al. p53 activates ICAM-1 (CD54) expression in an NF-κB-independent manner. EMBO J. 22, 1567–1578 (2003).

    Article  CAS  Google Scholar 

  28. Bester, A. C. et al. Nucleotide deficiency promotes genomic instability in early stages of cancer development. Cell 145, 435–446 (2011).

    Article  CAS  Google Scholar 

  29. Essers, J. et al. Nuclear dynamics of PCNA in DNA replication and repair. Mol. Cell. Biol. 25, 9350–9359 (2005).

    Article  CAS  Google Scholar 

  30. Barlow, J. H. et al. Identification of early replicating fragile sites that contribute to genome instability. Cell 152, 620–632 (2013).

    Article  CAS  Google Scholar 

  31. Beck, H. et al. Regulators of cyclin-dependent kinases are crucial for maintaining genome integrity in S phase. J. Cell Biol. 188, 629–638 (2010).

    Article  CAS  Google Scholar 

  32. Petermann, E. & Helleday, T. Pathways of mammalian replication fork restart. Nat. Rev. Mol. Cell Biol. 11, 683–687 (2010).

    Article  CAS  Google Scholar 

  33. Neelsen, K. J. et al. Deregulated origin licensing leads to chromosomal breaks by rereplication of a gapped DNA template. Genes Dev. 27, 2537–2542 (2013).

    Article  CAS  Google Scholar 

  34. Couch, F. B. et al. ATR phosphorylates SMARCAL1 to prevent replication fork collapse. Genes Dev. 27, 1610–1623 (2013).

    Article  CAS  Google Scholar 

  35. Neelsen, K. J. et al. Visualization and interpretation of eukaryotic DNA replication intermediates in vivo by electron microscopy. Methods Mol. Biol. 1094, 177–208 (2014).

    Article  CAS  Google Scholar 

  36. Zellweger, R. et al. Rad51-mediated replication fork reversal is a global response to genotoxic treatments in human cells. J. Cell Biol. 208, 563–579 (2015).

    Article  CAS  Google Scholar 

  37. Neelsen, K. J. & Lopes, M. Replication fork reversal in eukaryotes: from dead end to dynamic response. Nat. Rev. Mol. Cell Biol. 16, 207–220 (2015).

    Article  CAS  Google Scholar 

  38. Hanada, K. et al. The structure-specific endonuclease Mus81 contributes to replication restart by generating double-strand DNA breaks. Nat. Struct. Mol. Biol. 14, 1096–1104 (2007).

    Article  CAS  Google Scholar 

  39. Neelsen, K. J., Zanini, I. M., Herrador, R. & Lopes, M. Oncogenes induce genotoxic stress by mitotic processing of unusual replication intermediates. J. Cell Biol. 200, 699–708 (2013).

    Article  CAS  Google Scholar 

  40. Murfuni, I. et al. The WRN and MUS81 proteins limit cell death and genome instability following oncogene activation. Oncogene 32, 610–620 (2013).

    Article  CAS  Google Scholar 

  41. Wu, Y., Kantake, N., Sugiyama, T. & Kowalczykowski, S. C. Rad51 protein controls Rad52-mediated DNA annealing. J. Biol. Chem. 283, 14883–14892 (2008).

    Article  CAS  Google Scholar 

  42. Ottaviani, D., LeCain, M. & Sheer, D. The role of microhomology in genomic structural variation. Trends Genet. 30, 85–94 (2014).

    Article  CAS  Google Scholar 

  43. Iraqui, I. et al. Recovery of arrested replication forks by homologous recombination is error-prone. PLoS Genet. 8, e1002976 (2012).

    Article  CAS  Google Scholar 

  44. Benson, E. K. et al. p53-dependent gene repression through p21 is mediated by recruitment of E2F4 repression complexes. Oncogene 33, 3959–3969 (2014).

    Article  CAS  Google Scholar 

  45. Bartkova, J. et al. Oncogene-induced senescence is part of the tumorigenesis barrier imposed by DNA damage checkpoints. Nature 444, 633–637 (2006).

    Article  CAS  Google Scholar 

  46. Liontos, M. et al. Modulation of the E2F1-driven cancer cell fate by the DNA damage response machinery and potential novel E2F1 targets in osteosarcomas. Am. J. Pathol. 175, 376–391 (2009).

    Article  CAS  Google Scholar 

  47. Gonzalez, S. et al. Oncogenic activity of Cdc6 through repression of the INK4/ARF locus. Nature 440, 702–706 (2006).

    Article  CAS  Google Scholar 

  48. Beauséjour, C. M. et al. Reversal of human cellular senescence: roles of the p53 and p16 pathways. EMBO J. 22, 4212–4222 (2003).

    Article  Google Scholar 

  49. Woo, R. A. & Poon, R. Y. Cyclin-dependent kinases and S phase control in mammalian cells. Cell Cycle 2, 316–324 (2003).

    Article  CAS  Google Scholar 

  50. Pines, J. & Hunter, T. Human cyclins A and B1 are differentially located in the cell and undergo cell cycle-dependent nuclear transport. J. Cell Biol. 115, 1–17 (1991).

    Article  CAS  Google Scholar 

  51. Yu, J. et al. A network of p73, p53 and Egr1 is required for efficient apoptosis in tumor cells. Cell Death Differ. 14, 436–446 (2007).

    Article  CAS  Google Scholar 

  52. Terradas, M., Martín, M., Tusell, L. & Genescà, A. DNA lesions sequestered in micronuclei induce a local defective-damage response. DNA Repair (Amst) 8, 1225–1234 (2009).

    Article  CAS  Google Scholar 

  53. Holland, A. J. & Cleveland, D. W. Chromoanagenesis and cancer: mechanisms and consequences of localized, complex chromosomal rearrangements. Nat. Med. 18, 1630–1638 (2012).

    Article  CAS  Google Scholar 

  54. Perkins, N. D. et al. Regulation of NF-κB by cyclin-dependent kinases associated with the p300 coactivator. Science 275, 523–527 (1997).

    Article  CAS  Google Scholar 

  55. Viale, A. et al. Cell-cycle restriction limits DNA damage and maintains self-renewal of leukaemia stem cells. Nature 457, 51–56 (2009).

    Article  CAS  Google Scholar 

  56. Shay, J. W. & Roninson, I. B. Hallmarks of senescence in carcinogenesis and cancer therapy. Oncogene 23, 2919–2933 (2004).

    Article  CAS  Google Scholar 

  57. Nishitani, H. et al. Two E3 ubiquitin ligases, SCF-Skp2 and DDB1-Cul4, target human Cdt1 for proteolysis. EMBO J. 25, 1126–1136 (2006).

    Article  CAS  Google Scholar 

  58. Niculescu, A. B. et al. Effects of p21(Cip1/Waf1) at both the G1/S and the G2/M cell cycle transitions: pRb is a critical determinant in blocking DNA replication and in preventing endoreduplication. Mol. Cell. Biol. 18, 629–643 (1998).

    Article  CAS  Google Scholar 

  59. Porter, A. C. Preventing DNA over-replication: a Cdk perspective. Cell Div. 3, 3 (2008).

    Article  Google Scholar 

  60. Hastings, P. J., Ira, G. & Lupski, J. R. A microhomology-mediated break-induced replication model for the origin of human copy number variation. PLoS Genet. 5, e1000327 (2009).

    Article  CAS  Google Scholar 

  61. Zhang, C. Z., Leibowitz, M. L. & Pellman, D. Chromothripsis and beyond: rapid genome evolution from complex chromosomal rearrangements. Genes Dev. 27, 2513–2530 (2013).

    Article  CAS  Google Scholar 

  62. Stephens, P. J. et al. Massive genomic rearrangement acquired in a single catastrophic event during cancer development. Cell 144, 27–40 (2011).

    Article  CAS  Google Scholar 

  63. Sikder, H. A., Devlin, M. K., Dunlap, S., Ryu, B. & Alani, R. M. Id proteins in cell growth and tumorigenesis. Cancer Cell 3, 525–530 (2003).

    Article  CAS  Google Scholar 

  64. Burrell, R. A., McGranahan, N., Bartek, J. & Swanton, C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature 501, 338–345 (2013).

    Article  CAS  Google Scholar 

  65. Cha, H. H. et al. Glucocorticoids stimulate p21 gene expression by targeting multiple transcriptional elements within a steroid responsive region of the p21waf1/cip1 promoter in rat hepatoma cells. J. Biol. Chem. 273, 1998–2007 (1998).

    Article  CAS  Google Scholar 

  66. Georgakopoulou, E. A. et al. Specific lipofuscin staining as a novel biomarker to detect replicative and stress-induced senescence. A method applicable in cryo-preserved and archival tissues. Aging 5, 37–50 (2013).

    Article  CAS  Google Scholar 

  67. Evangelou, K. et al. The DNA damage checkpoint precedes activation of ARF in response to escalating oncogenic stress during tumorigenesis. Cell Death Differ. 20, 1485–1497 (2013).

    Article  CAS  Google Scholar 

  68. Delehouzé, C. et al. CDK/CK1 inhibitors roscovitine and CR8 downregulate amplified MYCN in neuroblastoma cells. Oncogene 33, 5675–5687 (2014).

    Article  Google Scholar 

  69. Papachristou, E. K. et al. The shotgun proteomic study of the human ThinPrep cervical smear using iTRAQ mass-tagging and 2D LC-FT-Orbitrap-MS: the detection of the human papillomavirus at the protein level. J. Proteome Res. 12, 2078–2089 (2013).

    Article  CAS  Google Scholar 

  70. Ramirez-Gonzalez, R. H. et al. StatsDB: platform-agnostic storage and understanding of next generation sequencing run metrics. F1000Res. 2, 248 (2013).

    Article  Google Scholar 

  71. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    Article  CAS  Google Scholar 

  72. Li, H. et al. 1000 genome project data processing subgroup. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  Google Scholar 

  73. Chen, K. et al. BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat. Methods 6, 677–681 (2009).

    Article  CAS  Google Scholar 

  74. de Winter, J. C. F. Using the Student’s t-test with extremely small sample sizes. Pract. Assess. Res. Eval. 18, 10 (2013).

    Google Scholar 

  75. Venkatraman, E. S. & Olshen, A. B. A faster circular binary segmentation algorithm for the analysis of array CGH data. Bioinformatics 23, 657–663 (2007).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We would like to thank A. Kotsinas, K. Evangelou, T. Liloglou and A. Georgakilas for their valuable support to this work. We would like to thank A. Dutta for providing the vectors with the wt and PIP mutated domain of p21, G. Blandino for the H1299 p21–Ponasterone-ON cells and Z. Lygerou for the secondary antibodies employed in the IF analyses. We thank R. Allsopp, D. Coates, the Wessex Cancer Trust and Medical Research, UK, and the University of Southampton ‘Annual Adventures in Research’ fund for their support of the proteomics infrastructure and its use for this study. We are also indebted to the PRIDE team for the proteomics data processing–repository assistance. This work received funding from the European Union’s Seventh Framework Programmes ‘INsPiRE’ and ‘INTEGER’, the Greek GSRT programmes of Excellence I (Aristeia I - ‘STOCHAGEN’), the Greek GSRT programmes of Excellence II (Aristeia II - ‘TransProFeat CDC6’), the Greek GSRT Cooperation programme (‘NoisePlus’), the Hellenic Association for Molecular Cancer Research (HAMCR), and partial funding from the Research Institute for the Study of Genetic and Malignant Diseases in Childhood, ‘Aghia Sophia’ Children’s Hospital, Athens, Greece, the Danish National Research Foundation (Center of excellence project CARD), the Lundbeck Foundation and the Danish Council for Independent Research.

Author information

Author notes

  1. Panagiotis Galanos and Konstantinos Vougas: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Histology and Embryology, Molecular Carcinogenesis Group, School of Medicine, University of Athens, 75 Mikras Asias Str, Athens GR-11527, Greece

    Panagiotis Galanos, Sofia Havaki & Vassilis G. Gorgoulis

  2. Biomedical Research Foundation of the Academy of Athens, 4 Soranou Ephessiou St., Athens GR-11527, Greece

    Konstantinos Vougas, Alexander Polyzos, Antonis Kokkalis, Fani-Marlen Roumelioti, Sarantis Gagos, Dimitris Thanos & Vassilis G. Gorgoulis

  3. Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaloes Vej 5, Copenhagen DK-2200, Denmark

    David Walter & Claus Storgaard Sørensen

  4. Genome Integrity Unit, Danish Cancer Society Research Centre, Strandboulevarden 49, Copenhagen DK-2100, Denmark

    Apolinar Maya-Mendoza & Jiri Bartek

  5. Centre for Gene Regulation & Expression, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK

    Emma J. Haagensen & J. Julian Blow

  6. Department of Medical Genetics, Medical School, University of Athens, Thivon & Levadias Str., Athens GR-11527, Greece

    Maria Tzetis & Emanuel Kanavakis

  7. Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology, 08028 Barcelona, Spain

    Begoña Canovas, Ana Igea & Angel Nebreda

  8. Institute of Molecular Cancer Research, University of Zurich, Winterthurerstrasse 190, Zurich CH-8057, Switzerland

    Akshay K. Ahuja, Ralph Zellweger & Massimo Lopes

  9. Research Institute for the Study of Genetic and Malignant Disorders in Childhood, Aghia Sophia Children’s Hospital, Thivon Str., Athens GR-11527, Greece

    Emanuel Kanavakis

  10. Laboratory of Cell Proliferation and Ageing, Institute of Biosciences and Applications, National Centre for Scientific Research ‘Demokritos’, Agia Paraskevi Attikis, PO Box 60228, Athens GR-153 10, Greece

    Dimitris Kletsas

  11. Department of Drug Discovery and Biomedical Sciences, Center for Targeted Therapeutics, South Carolina College of Pharmacy, University of South Carolina, Coker Life Science Building, 715 Sumter Street, Columbia, South Carolina 29208, USA

    Igor B. Roninson

  12. Cancer and Clinical Experimental Science Units, Faculty of Medicine, Institute for Life Sciences, Center for Proteome Research, University of Southampton, University Road Southampton, Southampton SO17 1BJ, UK

    Spiros D. Garbis

  13. Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain

    Angel Nebreda

  14. Faculty Institute of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Wilmslow Road, Manchester M20 4QL, UK

    Paul Townsend & Vassilis G. Gorgoulis

  15. Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University, Hněvotínská, Olomouc 1333/5 779 00, Czech Republic

    Jiri Bartek

  16. Division of Translational Medicine and Chemical Biology, Department of Medical Biochemistry and Biophysics, Science for Life Laboratory, Karolinska Institute, Stockholm SE-171 77, Sweden

    Jiri Bartek

Authors
  1. Panagiotis Galanos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Konstantinos Vougas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. David Walter
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alexander Polyzos
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Apolinar Maya-Mendoza
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Emma J. Haagensen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Antonis Kokkalis
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Fani-Marlen Roumelioti
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Sarantis Gagos
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Maria Tzetis
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Begoña Canovas
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Ana Igea
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Akshay K. Ahuja
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Ralph Zellweger
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Sofia Havaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Emanuel Kanavakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Dimitris Kletsas
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Igor B. Roninson
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Spiros D. Garbis
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Massimo Lopes
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Angel Nebreda
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Dimitris Thanos
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. J. Julian Blow
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Paul Townsend
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. Claus Storgaard Sørensen
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Jiri Bartek
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Vassilis G. Gorgoulis
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

P.G., K.V. and D.W.: cell culture and manipulations, siRNA/plasmid/viral transfections/transductions/infections, immunoblots, cell growth, RT–PCR, ChIP, comet, IHC and IF assays. D.W. and C.S.S.: PFGE analysis. A.M.-M. and J.B.: DNA fibre spreading assay. A.K.A., R.Z., S.H. and M.L.: electron microscopy and cell culture for electron microscopy. E.J.H. and J.J.B.: FACS analyses. B.C., A.I. and A.N.: time-lapse video analyses. D.K.: MTT, soft agar, invasion and kinase assays. F.-M.R. and S.G.: molecular cytogenetic analyses. A.P., A.K. and D.T.: whole-genome and RNA sequencing. M.T. and E.K.: aCGH analyses. K.V., S.D.G. and P.T.: proteomic analysis. I.B.R.: data analysis and cell line production. K.V. and A.P.: transcriptomic and bioinformatic analyses. J.J.B., C.S.S., A.N. and J.B.: data analysis and interpretation, and assistance in manuscript preparation. V.G.G.: experimental design, guidance, manuscript preparation and writing.

Corresponding authors

Correspondence to Jiri Bartek or Vassilis G. Gorgoulis.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1

(a) Representative factors affected by p21WAF1/Cip1 induction at transcriptional and translational level. Representative real-time RT-PCR analyses to validate the high-throughput expression results (see also Fig. 2) (p < 0.01, t-test, error bars indicate mean ± SDs, n = 3 experiments). i. Mitotic factors: PLK1, AURKB, BUB1, BUB1B, KIF23 and the pro-apoptotic factor GLIPR1 along with the suppressor of the p21WAF1/Cip1 mediated effects ID1 are transcriptionally downregulated at the indicated time points in Saos2 p21WAF1/Cip1 Tet-ON induced cells. Growth factor IGFBP5, the ion channel encoding gene TRPM8 and the poly-A binding protein PABPC1L are upregulated. PBGD: Porphobilinogen deaminase (house-keeping gene) ii. Representative immunoblots that validate the proteome. Actin serves as a loading control. (PLK1: Polo-like kinase-1; AURKB: Aurora kinase B; BUB1: budding uninhibited by benzimidazoles 1 homolog; KIF23: kinesin family member 23; GLIPR1: Glioma pathogenesis related 1; ID1: inhibitor of DNA binding 1; IGFBP5: insulin-like growth factor binding protein 5; TRPM8: transient receptor potential cation channel subfamily M member 8; PABPC1L: poly(A) binding protein, cytoplasmic 1-like; TOP2A: topoisomerase 2A). (b) Timeline of senescence appearance in Saos2 p21WAF1/Cip1 Tet-ON and Li–Fraumeni p21WAF1/Cip1 Tet-ON induced cells. Activation of the senescence barrier occurs at approximately day 3 of induction in both cellular systems and increases gradually, reaching its highest value at around day 10, while no signs of senescence are evident in untreated cells grown for the same time period (as corresponding graphs depict). p21WAF1/Cip1 was confirmed by western blot (upper right panel). (c) i. E2F1 is upregulated while Chk1 is activated upon prolonged p21WAF1/Cip1 induction. Lysates from Saos2 p21WAF1/Cip1 Tet-ON cells, after treatment with 1 μg ml−1 Doxycycline for the depicted time points, were separated by SDS-PAGE and immunoblotted to detect the indicated proteins. ii. Silencing of Cdh-1/FZR-1 leads to increase in E2F1 expression in the p53 null H1299 cells. iii. A decline of Cdk2 activity is observed following p21WAF1/Cip1 induction. Histogram depicting decreased Cdk2 activity at days 4 after p21WAF1/Cip1 induction. (d) MCM2-7 chromatin loading is increased following p21WAF1/Cip1 induction in Saos2 and Li–Fraumeni cells. i. Diagram describing cell fractionation experimental algorithm. ii–iii. All fractions were separated by SDS-PAGE and were analyzed by IB in Saos2 cells (ii) and Li–Fraumeni cells (iii). Lamin-B serves as fractionation control, while β-tubulin as loading control (n = 3 experiments). iv. FACS analysis of MCM2 chromatin loading in induced Saos2 p21WAF1/Cip1 Tet-ON cells versus non-induced (red dots, -ve: control experiment with no MCM2 antibody; blue dots, + ve: experiment with MCM2 antibody) (∗P < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.005, t-test, error bars indicate mean ± SDs, n = 3 experiments). (e) Re-replication and DNA damage was significantly lesser in Saos2 cells infected with p21PCNA mutant. i. Comet assays showed DNA breaks in cells infected with the indicated constructs (see also Fig. 4b, d, f) (p < 0.0001, ANOVA, error bars indicate mean ± SDs, n = 3 experiments). Red lines in magnifications of insets label comet (moment) tails for length comparison. ii. FACS analysis of the corresponding treatments. iii. DNA damage is p21WAF1/Cip1 dependent in Saos2 cells treated with TGF-β (n = 3 experiments). iv. p21WAF1/Cip1 dependent DNA damage, in Saos2 cells treated with TGF-β, is exerted via Cdc6/Cdt1 mediated replication stress. (Empty vector: pMSCV, p21PCNA: mutant p21WAF1/Cip1 harboring Q144, M147, F150 substitutions to A in its PIP degron motif). Source data can be found in Supplementary Table 25.

Supplementary Figure 2

(a) Silencing of p21WAF1/Cip1 in induced (ii.) Saos2- and (iii.) Li Fraumeni- p21WAF1/Cip1 Tet-ON cells alleviates replication stress, DNA damage, senescence induction and enhanced resistance to chemotherapeutic drugs. Timeline of the experimental procedure is also depicted (i.). cells (p = NS, t-test or ANOVA, error bars indicate mean ± SDs, n = 3 experiments). Bars: 20 μm (IF), 30 μm (comet). (b) PCNA staining patterns reveal that sustained p21WAF1/Cip1 expression, in cells with non-functional p53, “traps” cells mainly in early S-phase. IF analysis for assessing PCNA staining patterns in non-induced and 96 h induced cells. Histograms depict average of observed patterns in the induction conditions employed (mean ± SDs, n = 3 experiments). Scale bars: 10 μm. (c) Absence of nascent ssDNA in Saos2 p21WAF1/Cip1 Tet-ON expressing cells. p21WAF1/Cip1 expression was induced for 96 h with 1 μg ml−1 doxycycline. The newly synthesized DNA was labeled for 20 min with 10 μM BrdU. 2 mM HU and 5 μM ATRi were added after the BrdU pulse as indicated for 2 h. After the indicated treatments, cells were fixed and stained with antibodies against BrdU without DNA denaturation to selectively detect nascent-strand ssDNA. Bars: 40 μm. (d) P21WAF1/Cip1 mediated DNA damage is processed by MUS81 resolvase. i. IF staining of DDR markers (53BP1 and γH2AX) in Saos2 p21WAF1 Tet-ON induced cells for 96 h, with or without anti-MUS81 siRNA targeting. Histogram depicts quantification of 53BP1 and γH2AX foci/cell (p < 0.01, t-test, error bars indicate mean ± SDs, n = 3 experiments). Bars: 20 μm. ii. DNA damage assessed by comet assay after prolonged expression in Li–Fraumeni p21WAF1 Tet-ON cells (p < 0.01, t-test, error bars indicate mean ± SDs, n = 3 experiments). Bars: 50 μm. iii. Silencing of the homologous repair recombinase Rad51 resulted in decreased γH2AX levels in Li–Fraumeni p21WAF1 Tet-ON cells (p < 0.0001, ANOVA, error bars indicate mean ± SDs, n = 3 experiments). (e) Sustained expression of p21WAF1/Cip1 in cells with non-functional p53 leads to restoration of Cdk2 activity in “escaped” cells. i. Following an initial decline (days 2-12) Cdk2 activity is increased in “escaped” cells (after day 20) (p < 0.01, t-test, error bars indicate mean ± SDs, n = 3 experiments). ii. Expression levels of p21WAF1/Cip1 in the “escaped” (i) Saos2 and (ii) Li–Fraumeni p21WAF1 Tet-ON cells were similar or even higher sometimes (see Fig. 7g) to those observed in the initial phase of p21WAF1/Cip1 induction. (f) Potential mechanisms involved in p73 down regulation in the “escaped” Saos2- and Li–Fraumeni-p21 cells. (see Fig. 7g) i. Absence of p73 promoter methylation and genetic loss at TP73 locus (1p36.33) (see Supplementary Fig. S5, S6; Supplementary Table 4). Representative result from real-time PCR followed by high resolution melting (HRM) analysis is depicted (n = 3 experiments). Ctl DNA: SssI methylated and unmethylated control DNA. ii. Bioinformatic analysis employing Ingenuity software revealed potential factors that regulate p73 expression and activity. EGR-1 (Early Growth Response-1) is a potent transcriptional up-regulator of p7351. In turn, p73 can also transcriptionally induce EGR-1exprresion, forming a positive feed-back loop. HECW2 (HECT, C2 and WW Domain Containing E3 Ubiquitin Protein Ligase 2) expression stabilizes p73 protein levels via mono-ubiquitination1, while PRKACB (Protein Kinase A Catalytic Subunit β) decreases p73 transactivation and intramolecular interaction capacity2. iii. TP73 gene locus organization and structure of p73 protein with HECW2 and PRKACB interacting domains. Yellow rectangles: transcribed non translated TP73 exons; Blue rectangles: transcribed TP73 exons; Green rectangle: P1 promoter of TP73 gene; Blue ovals: EGR-1 biding sites. TDA: transactivation domain; DBD: DNA binding domain; OD: oligomerization domain; SAM: sterile alpha-motif domain. iv–v. Analysis of EGR-1, HECW2 and PRKACB expression status in “escaped” Saos2 p21WAF1/Cip1 cells at mRNA (iv.) and protein (v.) level validated results obtained from high-throughput transcriptome analysis (Supplementary Fig. S3). CREB phosphorylation was examined as a proof-of-concept for PRKACB activity. vi. Analysis of EGR-1 at mRNA and protein level in “escaped” Li–Fraumeni p21WAF1/Cip1 cells (fold difference mean ± SDs, n = 3 experiments). vii. Potential mechanism for p73 downregulation in “escaped” cells. Decreased levels of EGR-1 possibly represent the main reason for low p73 expression49. Additionally, high levels of PRKACB decreases p73 transactivation and intramolecular interaction abilities2, counteracting the ability of high HECW2 expression to stabilize p73 via mono-ubiquitination1. High PRKACB levels may contribute further to p73 down-regulation by interfering with the positive feed-back loop between ERG-1 and p732. (g) Serial-section immunohistochemical (IHC) analysis showed co-expression of p21WAF1/Cip1, Ki67 and Cdc6/Cdt1 in atypical cancer cells in head and neck carcinomas, urothelial carcinomas and precancerous lesions. Actin serves as a loading control. Source data can be found in Supplementary Table 25.

Supplementary Figure 3 Differentially expressed genes whose expression status affects cancer according to literature in Saos2- and Li–Fraumeni-p21 cells.

Expression status of genes associated with cancer progression (see also Supplemental Table 8). (a) Timeline of experimental planning of transcriptome analyses. (b) Principal Component Analysis (PCA) of the differentially expressed genes depicting the majorly different gene expression signatures over the (19540 in Saos2- and 25376 in Li–Fraumeni cells) transcripts analysed. (c) Validation of representative factors in “escaped” (ON) cells versus non-induced (OFF) Saos2 and Li–Fraumeni cells. Representative real-time RT-PCR analyses, validating the high-throughput expression analysis (p < 0.01, t-test, error bars indicate mean ± SDs, n = 3 experiments). (d) Relative expression levels given as log-2-ratios of differentially expressed genes (p < 0.05) of the “escaped” vs OFF-cells, whose expression status (up or down-regulated) is reported to promote carcinogenesis. Arrow (←) denotes genes conferring cancer stemness (see also Supplemental Tables 8Aa, 8Ba). Lysates from non-induced and escaped Saos2 p21WAF1/Cip1 Tet-ON cells were immunoblotted to verify representatively the expression of the LGR5 cancer related stemness gene. (e) Differentially expressed genes whose expression status either promotes or suppresses cancer according to literature. Relative expression levels given as log-2-ratios of differentially expressed genes (p < 0.05) of the “escaped” vs OFF-cells. The lengths of the “encircled” lines depict the intensity of expression. Uncropped images of blots are shown in Supplementary Fig. S9. Source data can be found in Supplementary Table 25.

Supplementary Figure 4 “Escaped” Saos2 p21WAF1/Cip1 cells exhibit increased genomic instability relative to non-induced cells.

(a) Timeline of experimental planning of genomic analyses. (b) Overview of all array-CGH (aCGH) analyses results. In total 41 aberrations were found involving all chromosomes (except 9, 12, 14 and 15). The aberrations included 19 gains and 22 losses (Supplemental Table 5). The majority of aberrations were concentrated in chromosomes 3, 10 and X (Supplemental Table 5). [reference (Ref) genome is from un-induced (0 d) Saos2 p21WAF1/Cip1 cells]. (c) Novel clonal rearrangements distinguish the “escaped” Saos2 p21WAF1/Cip1 (ON) from OFF cells [arrows indicate lost (in OFF cells) or rearranged (in “escaped”-ON cells) chromosomes]. The p21WAF1/Cip1-OFF cells (control), were mainly hypotriploid (51-56 chromosomes) and shared most of the characteristic structural chromosome aberrations of the parental Saos2 cell line3. Compared to these cells, the “escaped” ones remained hypo-triploid but displayed at least 10 novel clonal structural or numerical aberrations affecting chromosomes 2, 3, 5, 8, 11, 13, 14, 20, 21 and X. Large portions of chromosomes X and 13 were lost in 90% of the “escaped” cells, confirming the aCGH findings. Furthermore, differential imbalances of chromosomes 5 and X between Saos2 p21WAF1/Cip1 ON cells and the controls were observed. In “escaped” (ON) cells, an additional inverted duplication of 5p was also present in 90% of the examined nuclei. (d) The Saos2 p21WAF1/Cip1 ON cells exert significantly higher rates (two fold) of random structural CIN/chromosome as compared to controls. (CIN:chromosomal instability). (e) Genomic distribution of breakpoints of random structural chromosome anomalies. Telomeric regions were found to be most frequently affected by fusions, translocations and tandem duplications of large chromosome segments. As unidentified ones were categorized the non-telomeric, non centromeric genomic rearrangements in which the cytogenetic bands of their breakpoints remained obscure. (f) “Escaped” Saos2 p21WAF1/Cip1 cells exhibit increased karyotypic aberrations relative to non-induced cells. Comparative pseudo-colored M-FISH/SKY karyograms of 10 non-induced (OFF) Saos2 p21WAF1/Cip1 cells (588 chromosomes) and 10 “escaped” (ON) ones (639 chromosomes), for the evaluation of whole genome structural CIN at the 350 chromosome band level. Arrows (and dashed rectangles) indicate representative non-clonal random structural rearrangements (unique anomalies encountered in a single cell). The “escaped” p21WAF1/Cip1 expressing cells (ON) displayed significantly higher rates of genome wide, random structural chromosomal rearrangements. ON cells (upper panel): Cells #1 and #7, from the Saos2 p21WAF1/Cip1 OFF panel, represent a minor subclone (20%) of this population because they share a distinctive clonal rearrangement affecting a derivative chromosome X and a deletion of 12p. Cells #3 and #5, belong to a second subclone of the control cells that is characterized by a deletion of a rearranged chromosome 19. The remaining non-induced (OFF) p21WAF1/Cip1 cells#2, #4, #6, #8 and #10, display a homogeneous karyotypic constitution and represent the major clone. Cell #9 is a polyploid product of whole genome endoreduplication of the major clone of Saos2 p21WAF1/Cip1 OFF cells. “Escaped”-OFF cells (lower panel): Cells #1 and #6 differ from the majority of the “escaped” (ON) population as they share a clonal inverted duplication of the long arm of chromosome 21. In addition, cells #2, #4 and #9, have lost a marker translocation der(9)t(5;9) that was replaced by a deletion 9p and acquired clonally an extra translocated der(22)t(20;22). A unique subclonal finding in Cells #3 and #10, of the “escaped” (ON) cells is the persistence of der(9)t(5;9). Cells #5 and #7 represent two different endoreduplicated ON subclones, characterized by unique structural abnormalities of chromosomes 7, 15 and 6 respectively. The karyotypic constitution of cell #8, resembles that of the control population and justifies the presence of an additional subclone that does not exceed the 10% of the “escaped” (ON) cells. (CIN:chromosomal instability).

Supplementary Figure 5 Correlation between aCGH replicates and corroboration with the cytogenetically detectable novel clonal alterations in Saos2 p21 cells (∗ see also Fig. 8f).

[reference (Ref) genome is from un-induced (0 d) Saos2 p21WAF1/Cip1 cells].

Supplementary Figure 6

Correlation between aCGH and deep sequencing in Saos2 (a) and Li–Fraumeni (b) cells (Next Generation Sequencing: NGS) analyses. Data from all replicates for each application were averaged before comparison.

Supplementary Figure 7

Novel chromosomal rearrangements and microhomology regions related to breakpoints in (a) Saos2 and (b) Li–Fraumeni cells. Circos diagrams depicting novel chromosomal rearrangements in “escaped” Saos2 (a) and Li–Fraumeni (b) p21WAF1/Cip1 Tet-ON expressing cells, respectively, revealed by deep sequencing (human chromosomes are located at the perimeter). Data from two biological replicates are depicted. Circos in the middle show shared chromosomal rearrangements by the two Saos2 (a) and Li–Fraumeni (b) p21WAF1/Cip1 Tet-ON biological replicates. Breakpoints employing micro-homologies ≥4bp in Saos2 (a) and ≥3bp in Li–Fraumeni (b) p21WAF1/Cip1 Tet-ON cells, respectively, are also presented below each circus diagram. Cytogenetic analyses (see also Supplementary Fig S4) confirming NGS data on breakpoints in the “escaped” Saos2 p21WAF1/Cip1 Tet-ON expressing cells are also shown. Asterisk (a) denotes breakpoint that does not encompass a micro-homology. Continuous red line denotes position of breakpoints.

Supplementary Figure 8

Relative gene expression levels (log-2 ratios) at 12, 48, 96-hs after p21WAF1/Cip1 -induction as well as “escaped” versus OFF cells in (a) Saos2 and relative gene expression levels (log-2 ratios) at 10 days after p21WAF1/Cip1 -induction as well as “escaped” versus OFF in (b) Li–Fraumeni cells. (c) Proposed model. (a) A: Relative expression of all measured genes (19540) at each depicted time-point as compared to non-induced cells (OFF). The correlogram at the bottom which presents the Pearson correlation coefficient among the 4 datasets illustrates that the overall gene-expression of the “escaped” population is non-correlated (∼0 correlation coefficient) to the three prior time points, which amongst them present a high degree of correlation. B: Relative expression of genes presenting differential expression (p < 0.05) in the “escaped” cells in relation to OFF (553 genes). The correlogram at the bottom illustrates the absence of correlation between the “escaped” population with the three early time points (12, 48, 96 hs). C: Relative expression of commonly differentially expressed genes (42) (p < 0.05) at each time-point versus OFF. Special interest present the 16 out of 42 marked genes whose expression levels are reversed at the “escaped” population in comparison to the previous time-points. (b) The same heatmaps are presented for Li–Fraumeni cells. A: Relative expression of all measured genes (25367) at each depicted time-point as compared to non-induced cells (OFF). B: Relative expression of genes presenting differential expression (p < 0.05) in the “escaped” cells in relation to OFF (3507 genes). C: Relative expression of commonly differentially expressed genes (538) (p < 0.05) at each time-point versus OFF. Special interest present the 154 out of 538 marked genes whose expression levels are reversed at the “escaped” population in comparison to 10-days. (c) Proposed model depicting prolonged p53-independent p21 oncogenic action (for additional mechanistic explanations see discussion). Under “physiological” conditions, MDM2 degrades p534,10. Dashed lines depict ineffective pathway.

Supplementary Figure 9 Unprocessed blots/gels employed in the current manuscript.

Supplementary information

Supplementary Information

Supplementary Information (PDF 2480 kb)

Supplementary Table 1

Supplementary Information (XLS 51 kb)

Supplementary Table 2

Supplementary Information (XLS 2649 kb)

Supplementary Table 3

Supplementary Information (XLS 24 kb)

Supplementary Table 4

Supplementary Information (XLS 141 kb)

Supplementary Table 5

Supplementary Information (XLS 75 kb)

Supplementary Table 6

Supplementary Information (XLS 1822 kb)

Supplementary Table 7

Supplementary Information (XLS 23 kb)

Supplementary Table 8

Supplementary Information (XLS 48 kb)

Supplementary Table 9

Supplementary Information (XLS 33 kb)

Supplementary Table 10

Supplementary Information (XLS 29 kb)

Supplementary Table 11

Supplementary Information (XLS 70 kb)

Supplementary Table 12

Supplementary Information (XLS 19 kb)

Supplementary Table 13

Supplementary Information (XLS 44 kb)

Supplementary Table 14

Supplementary Information (XLS 27 kb)

Supplementary Table 15

Supplementary Information (XLS 27 kb)

Supplementary Table 16

Supplementary Information (PDF 2224 kb)

Supplementary Table 17

Supplementary Information (XLS 39 kb)

Supplementary Table 18

Supplementary Information (XLS 30 kb)

Supplementary Table 19

Supplementary Information (XLS 29 kb)

Supplementary Table 20

Supplementary Information (XLS 69 kb)

Supplementary Table 21

Supplementary Information (XLS 34 kb)

Supplementary Table 22

Supplementary Information (XLS 35 kb)

Supplementary Table 23

Supplementary Information (XLS 34 kb)

Supplementary Table 24

Supplementary Information (XLS 32 kb)

Supplementary Table 25

Supplementary Information (XLS 171 kb)

Dividing Saos2 p21WAF1/Cip1 Tet-OFF cells. (AVI 27738 kb)

Senescent Saos2 p21WAF1/Cip1 Tet-ON cells. (AVI 32065 kb)

Senescent and dying Saos2 p21WAF1/Cip1 Tet-ON cells. (AVI 22761 kb)

Re-replicating Saos2 p21WAF1/Cip1 Tet-ON cells. (AVI 15198 kb)

Escaped and diving Saos2 p21WAF1/Cip1 Tet-ON cells. (AVI 26181 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Galanos, P., Vougas, K., Walter, D. et al. Chronic p53-independent p21 expression causes genomic instability by deregulating replication licensing. Nat Cell Biol 18, 777–789 (2016). https://doi.org/10.1038/ncb3378

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ncb3378

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer