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p53 induces formation of NEAT1 lncRNA-containing paraspeckles that modulate replication stress response and chemosensitivity

Nature Medicine volume 22, pages 861–868 (2016)Cite this article

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Abstract

In a search for mediators of the p53 tumor suppressor pathway, which induces pleiotropic and often antagonistic cellular responses, we identified the long noncoding RNA (lncRNA) NEAT1. NEAT1 is an essential architectural component of paraspeckle nuclear bodies, whose pathophysiological relevance remains unclear. Activation of p53, pharmacologically or by oncogene-induced replication stress, stimulated the formation of paraspeckles in mouse and human cells. Silencing Neat1 expression in mice, which prevents paraspeckle formation, sensitized preneoplastic cells to DNA-damage-induced cell death and impaired skin tumorigenesis. We provide mechanistic evidence that NEAT1 promotes ATR signaling in response to replication stress and is thereby engaged in a negative feedback loop that attenuates oncogene-dependent activation of p53. NEAT1 targeting in established human cancer cell lines induced synthetic lethality with genotoxic chemotherapeutics, including PARP inhibitors, and nongenotoxic activation of p53. This study establishes a key genetic link between NEAT1 paraspeckles, p53 biology and tumorigenesis and identifies NEAT1 as a promising target to enhance sensitivity of cancer cells to both chemotherapy and p53 reactivation therapy.

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Figure 1: p53 induces NEAT1 expression and paraspeckle formation.
Figure 2: DNA damage induces NEAT1 paraspeckle formation.
Figure 3: Neat1 KO mice are resistant to chemically induced skin cancer formation.
Figure 4: Neat1 prevents accumulation of DNA damage and p53.
Figure 5: NEAT1 paraspeckles modulate ATR signaling and chemosensitivity.
Figure 6: Detection of NEAT1 paraspeckles in human cancers and correlation of NEAT1_2 levels with response to platinum-based therapy.

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References

  1. Vogelstein, B., Lane, D. & Levine, A.J. Surfing the p53 network. Nature 408, 307–310 (2000).

    Google Scholar 

  2. Sharpless, N.E. & DePinho, R.A. How stem cells age and why this makes us grow old. Nat. Rev. Mol. Cell Biol. 8, 703–713 (2007).

    Google Scholar 

  3. Vassilev, L.T. et al. In vivo activation of the p53 pathway by small-molecule antagonists of MDM2. Science 303, 844–848 (2004).

    Google Scholar 

  4. Khoo, K.H., Verma, C.S. & Lane, D.P. Drugging the p53 pathway: understanding the route to clinical efficacy. Nat. Rev. Drug Discov. 13, 217–236 (2014).

    Google Scholar 

  5. Carvajal, L.A. & Manfredi, J.J. Another fork in the road–life or death decisions by the tumour suppressor p53. EMBO Rep. 14, 414–421 (2013).

    Google Scholar 

  6. Huang, B., Deo, D., Xia, M. & Vassilev, L.T. Pharmacologic p53 activation blocks cell cycle progression but fails to induce senescence in epithelial cancer cells. Mol. Cancer Res. 7, 1497–1509 (2009).

    Google Scholar 

  7. Derrien, T. et al. The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression. Genome Res. 22, 1775–1789 (2012).

    Google Scholar 

  8. Yildirim, E. et al. Xist RNA is a potent suppressor of hematologic cancer in mice. Cell 152, 727–742 (2013).

    Google Scholar 

  9. Arun, G. et al. Differentiation of mammary tumors and reduction in metastasis upon Malat1 lncRNA loss. Genes Dev. 30, 34–51 (2016).

    Google Scholar 

  10. Huarte, M. et al. A large intergenic noncoding RNA induced by p53 mediates global gene repression in the p53 response. Cell 142, 409–419 (2010).

    Google Scholar 

  11. Hung, T. et al. Extensive and coordinated transcription of noncoding RNAs within cell-cycle promoters. Nat. Genet. 43, 621–629 (2011).

    Google Scholar 

  12. Marín-Béjar, O. et al. Pint lincRNA connects the p53 pathway with epigenetic silencing by the Polycomb repressive complex 2. Genome Biol. 14, R104 (2013).

    Google Scholar 

  13. Blume, C.J. et al. p53-dependent non-coding RNA networks in chronic lymphocytic leukemia. Leukemia 29, 2015–2023 (2015).

    Google Scholar 

  14. Janky, R. et al. iRegulon: from a gene list to a gene regulatory network using large motif and track collections. PLoS Comput. Biol. 10, e1003731 (2014).

    Google Scholar 

  15. Herrmann, C., Van de Sande, B., Potier, D. & Aerts, S. i-cisTarget: an integrative genomics method for the prediction of regulatory features and cis-regulatory modules. Nucleic Acids Res. 40, e114 (2012).

    Google Scholar 

  16. Clemson, C.M. et al. An architectural role for a nuclear noncoding RNA: NEAT1 RNA is essential for the structure of paraspeckles. Mol. Cell 33, 717–726 (2009).

    Google Scholar 

  17. Wilusz, J.E. et al. A triple helix stabilizes the 3′ ends of long noncoding RNAs that lack poly(A) tails. Genes Dev. 26, 2392–2407 (2012).

    Google Scholar 

  18. Chen, L.-L. & Carmichael, G.G. Altered nuclear retention of mRNAs containing inverted repeats in human embryonic stem cells: functional role of a nuclear noncoding RNA. Mol. Cell 35, 467–478 (2009).

    Google Scholar 

  19. Sasaki, Y.T.F., Ideue, T., Sano, M., Mituyama, T. & Hirose, T. MENepsilon/beta noncoding RNAs are essential for structural integrity of nuclear paraspeckles. Proc. Natl. Acad. Sci. USA 106, 2525–2530 (2009).

    Google Scholar 

  20. Sunwoo, H. et al. MEN-ɛ/β nuclear-retained non-coding RNAs are up-regulated upon muscle differentiation and are essential components of paraspeckles. Genome Res. 19, 347–359 (2009).

    Google Scholar 

  21. Yamazaki, T. & Hirose, T. The building process of the functional paraspeckle with long non-coding RNAs. Front. Biosci. (Elite Ed.) 7, 1–41 (2015).

    Google Scholar 

  22. Reinhardt, H.C. & Schumacher, B. The p53 network: cellular and systemic DNA damage responses in aging and cancer. Trends Genet. 28, 128–136 (2012).

    Google Scholar 

  23. Nassar, D., Latil, M., Boeckx, B., Lambrechts, D. & Blanpain, C. Genomic landscape of carcinogen-induced and genetically induced mouse skin squamous cell carcinoma. Nat. Med. 21, 946–954 (2015).

    Google Scholar 

  24. Lapouge, G. et al. Identifying the cellular origin of squamous skin tumors. Proc. Natl. Acad. Sci. USA 108, 7431–7436 (2011).

    Google Scholar 

  25. Nakagawa, S., Naganuma, T., Shioi, G. & Hirose, T. Paraspeckles are subpopulation-specific nuclear bodies that are not essential in mice. J. Cell Biol. 193, 31–39 (2011).

    Google Scholar 

  26. Gaillard, H., García-Muse, T. & Aguilera, A. Replication stress and cancer. Nat. Rev. Cancer 15, 276–289 (2015).

    Google Scholar 

  27. Llopis, A. et al. The stress-activated protein kinases p38α/β and JNK1/2 cooperate with Chk1 to inhibit mitotic entry upon DNA replication arrest. Cell Cycle 11, 3627–3637 (2012).

    Google Scholar 

  28. Branzei, D. & Foiani, M. Maintaining genome stability at the replication fork. Nat. Rev. Mol. Cell Biol. 11, 208–219 (2010).

    Google Scholar 

  29. Dobbelstein, M. & Sørensen, C.S. Exploiting replicative stress to treat cancer. Nat. Rev. Drug Discov. 14, 405–423 (2015).

    Google Scholar 

  30. Sullivan, K.D. et al. ATM and MET kinases are synthetic lethal with nongenotoxic activation of p53. Nat. Chem. Biol. 8, 646–654 (2012).

    Google Scholar 

  31. Ferriss, J.S. et al. Multi-gene expression predictors of single drug responses to adjuvant chemotherapy in ovarian carcinoma: predicting platinum resistance. PLoS One 7, e30550 (2012).

    Google Scholar 

  32. The Cancer Genome Atlas Research Network (TCGA). Integrated genomic analyses of ovarian carcinoma. Nature 474, 609–615 (2011).

  33. Chakravarty, D. et al. The oestrogen receptor-α-regulated lncRNA NEAT1 is a critical modulator of prostate cancer. Nat. Commun. 5, 5383 (2014).

    Google Scholar 

  34. Choudhry, H. et al. Tumor hypoxia induces nuclear paraspeckle formation through HIF-2α dependent transcriptional activation of NEAT1 leading to cancer cell survival. Oncogene 34, 4482–4490 (2015).

    Google Scholar 

  35. Zhen, L. et al. Long noncoding RNA NEAT1 promotes glioma pathogenesis by regulating miR-449b-5p/c-Met axis. Tumour Biol. 37, 673–683 (2016).

    Google Scholar 

  36. Guo, S. et al. Clinical implication of long non-coding RNA NEAT1 expression in hepatocellular carcinoma patients. Int. J. Clin. Exp. Pathol. 8, 5395–5402 (2015).

    Google Scholar 

  37. Pan, L.-J. et al. Upregulation and clinicopathological significance of long non-coding NEAT1 RNA in NSCLC tissues. Asian Pac. J. Cancer Prev. 16, 2851–2855 (2015).

    Google Scholar 

  38. Sengupta, S. & Harris, C.C. p53: traffic cop at the crossroads of DNA repair and recombination. Nat. Rev. Mol. Cell Biol. 6, 44–55 (2005).

    Google Scholar 

  39. Harris, S.L. & Levine, A.J. The p53 pathway: positive and negative feedback loops. Oncogene 24, 2899–2908 (2005).

    Google Scholar 

  40. Cha, H. et al. Wip1 directly dephosphorylates γ-H2AX and attenuates the DNA damage response. Cancer Res. 70, 4112–4122 (2010).

    Google Scholar 

  41. Moon, S.-H. et al. Wild-type p53-induced phosphatase 1 dephosphorylates histone variant γ-H2AX and suppresses DNA double strand break repair. J. Biol. Chem. 285, 12935–12947 (2010).

    Google Scholar 

  42. Chowdhury, D. et al. γ-H2AX dephosphorylation by protein phosphatase 2A facilitates DNA double-strand break repair. Mol. Cell 20, 801–809 (2005).

    Google Scholar 

  43. Rulten, S.L. et al. PARP-1 dependent recruitment of the amyotrophic lateral sclerosis-associated protein FUS/TLS to sites of oxidative DNA damage. Nucleic Acids Res. 42, 307–314 (2014).

    Google Scholar 

  44. Krietsch, J. et al. PARP activation regulates the RNA-binding protein NONO in the DNA damage response to DNA double-strand breaks. Nucleic Acids Res. 40, 10287–10301 (2012).

    Google Scholar 

  45. Ha, K., Takeda, Y. & Dynan, W.S. Sequences in PSF/SFPQ mediate radioresistance and recruitment of PSF/SFPQ-containing complexes to DNA damage sites in human cells. DNA Repair (Amst.) 10, 252–259 (2011).

    Google Scholar 

  46. Salton, M., Lerenthal, Y., Wang, S.Y., Chen, D.J. & Shiloh, Y. Involvement of Matrin 3 and SFPQ/NONO in the DNA damage response. Cell Cycle 9, 1568–1576 (2010).

    Google Scholar 

  47. Mastrocola, A.S., Kim, S.H., Trinh, A.T., Rodenkirch, L.A. & Tibbetts, R.S. The RNA-binding protein fused in sarcoma (FUS) functions downstream of poly(ADP-ribose) polymerase (PARP) in response to DNA damage. J. Biol. Chem. 288, 24731–24741 (2013).

    Google Scholar 

  48. Altmeyer, M. et al. Liquid demixing of intrinsically disordered proteins is seeded by poly(ADP-ribose). Nat. Commun. 6, 8088 (2015).

    Google Scholar 

  49. Wickramasinghe, V.O. & Venkitaraman, A.R. RNA processing and genome stability: cause and consequence. Mol. Cell 61, 496–505 (2016).

    Google Scholar 

  50. Britton, S. et al. DNA damage triggers SAF-A and RNA biogenesis factors exclusion from chromatin coupled to R-loops removal. Nucleic Acids Res. 42, 9047–9062 (2014).

    Google Scholar 

  51. Shanbhag, N.M., Rafalska-Metcalf, I.U., Balane-Bolivar, C., Janicki, S.M. & Greenberg, R.A. ATM-dependent chromatin changes silence transcription in cis to DNA double-strand breaks. Cell 141, 970–981 (2010).

    Google Scholar 

  52. Specks, J., Lecona, E., Lopez-Contreras, A.J. & Fernandez-Capetillo, O. A single conserved residue mediates binding of the ribonucleotide reductase catalytic subunit RRM1 to RRM2 and is essential for mouse development. Mol. Cell. Biol. 35, 2910–2917 (2015).

    Google Scholar 

  53. Nakagawa, S. et al. The lncRNA Neat1 is required for corpus luteum formation and the establishment of pregnancy in a subpopulation of mice. Development 141, 4618–4627 (2014).

    Google Scholar 

  54. Standaert, L. et al. The long noncoding RNA Neat1 is required for mammary gland development and lactation. RNA 20, 1844–1849 (2014).

    Google Scholar 

  55. Jacks, T. et al. Tumor spectrum analysis in p53-mutant mice. Curr. Biol. 4, 1–7 (1994).

    Google Scholar 

  56. Vasioukhin, V. et al. The magical touch: genome targeting in epidermal stem cells induced by tamoxifen application to mouse skin. Proc. Natl. Acad. Sci. USA 96, 8551–8556 (1999).

    Google Scholar 

  57. Abel, E.L., Angel, J.M., Kiguchi, K. & DiGiovanni, J. Multi-stage chemical carcinogenesis in mouse skin: fundamentals and applications. Nat. Protoc. 4, 1350–1362 (2009).

    Google Scholar 

  58. Trapnell, C., Pachter, L. & Salzberg, S.L. TopHat: discovering splice junctions with RNA-seq. Bioinformatics 25, 1105–1111 (2009).

    Google Scholar 

  59. Anders, S., Pyl, P.T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

    Google Scholar 

  60. Harrow, J. et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 22, 1760–1774 (2012).

    Google Scholar 

  61. Anders, S. & Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11, R106 (2010).

    Google Scholar 

  62. Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).

    Google Scholar 

  63. Smoot, M.E., Ono, K., Ruscheinski, J., Wang, P.L. & Ideker, T. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27, 431–432 (2011).

    Google Scholar 

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Acknowledgements

We thank O. Van Goethem, G. Bervoets and S. Peeters for excellent technical assistance; E. Bonomi and M. Bugatti (Fondazione Beretta) for ISH analysis of human cancer samples; and S. Jackson for helpful comments on the manuscript and for imaging facility access. Imaging was done on a Nikon A1 confocal microscope acquired through a Hercules grant type 1 (AKUL/09/037) to W. Annaert. This work was supported by Interuniversitaire Attractiepolen (IUAP), an Institute for Science, Innovation and Technology (IWT) scholarship to C.A. and a Fund for Scientific Research Flanders (FWO) scholarship to L.S. W.V. is supported by Associazione Italiana per la Ricerca sul Cancro (AIRC, IG 15378) and by Ministero Salute (RF-2010-2315888).

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Author notes

  1. Carmen Adriaens and Laura Standaert: These authors contributed equally to this work.

Authors and Affiliations

  1. Laboratory for Molecular Cancer Biology, Center for the Biology of Disease, VIB, KU Leuven, Leuven, Belgium

    Carmen Adriaens, Laura Standaert, Jasmine Barra, Eleonora Leucci & Jean-Christophe Marine

  2. Laboratory for Molecular Cancer Biology, Center for Human Genetics, KU Leuven, Leuven, Belgium

    Carmen Adriaens, Laura Standaert, Jasmine Barra, Eleonora Leucci & Jean-Christophe Marine

  3. Université Libre de Bruxelles, Institut de Recherche Interdisciplinaire en Biologie Humaine et Moléculaire, Bruxelles, Belgium

    Mathilde Latil, Gaëlle Lapouge, Benjamin Beck & Cédric Blanpain

  4. Laboratory of Computational Biology, Center for Human Genetics, KU Leuven, Leuven, Belgium

    Annelien Verfaillie & Stein Aerts

  5. Laboratory for Mechanisms of Cell Transformation, Center for the Biology of Disease, VIB, KU Leuven, Leuven, Belgium

    Peter Kalev & Anna A Sablina

  6. Laboratory for Mechanisms of Cell Transformation, Center for Human Genetics, KU Leuven, Leuven, Belgium

    Peter Kalev & Anna A Sablina

  7. Vesalius Research Center, VIB, KU Leuven, Leuven, Belgium

    Bram Boeckx & Diether Lambrechts

  8. Department of Oncology, Laboratory for Translational Genetics, KU Leuven, Leuven, Belgium

    Bram Boeckx & Diether Lambrechts

  9. The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK

    Paul W G Wijnhoven

  10. Mouse Histopathology Core Facility, Center for the Biology of Disease, VIB, KU Leuven, Leuven, Belgium

    Enrico Radaelli

  11. Department of Molecular and Translational Medicine, Section of Pathology, University of Brescia, Brescia, Italy

    William Vermi

  12. Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA

    William Vermi

  13. Department of Pathology, Laboratory of Translational Cell and Tissue Research, KU Leuven and UZ Leuven, Leuven, Belgium

    Joost van den Oord

  14. RNA Biology Laboratory, RIKEN, Wako, Japan

    Shinichi Nakagawa

  15. Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan

    Shinichi Nakagawa

  16. Institute for Genetic Medicine, Hokkaido University, Sapporo, Japan

    Tetsuro Hirose

  17. WELBIO, Université Libre de Bruxelles, Bruxelles, Belgium

    Cédric Blanpain

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  1. Carmen Adriaens
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Contributions

C.A., L.S. and J.B. designed and conducted experiments and acquired, analyzed and interpreted the data. M.L. performed DMBA and TPA treatments and monitored tumor development. A.V. and S.A. performed p53 ChIP-seq and RNA-seq experiments and data analysis. P.K. assessed DNA damage repair efficacy with bleomycin. B. Boeckx and D.L. analyzed expression data and constructed KM curves. E.R. and J.v.d.O. provided mouse and human pathology support. J.v.d.O. provided clinical samples. A.A.S., C.B. and E.L. designed research studies and contributed to interpretation of the data. G.L. and B. Beck provided reagents from mouse skin tumors. S.N. and T.H. provided Neat1 KO mice. W.V. performed the TMA. P.W.G.W. provided reagents and contributed to interpretation of the data. All authors read and edited the manuscript. J.-C.M. designed research studies and wrote the manuscript.

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Correspondence to Jean-Christophe Marine.

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Adriaens, C., Standaert, L., Barra, J. et al. p53 induces formation of NEAT1 lncRNA-containing paraspeckles that modulate replication stress response and chemosensitivity. Nat Med 22, 861–868 (2016). https://doi.org/10.1038/nm.4135

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