Image-based Identification of Chemical Compounds Capable of Trapping FOXO in the Cell Nucleus

  • Susana Machado
  • Catarina Raposo
  • Bibiana I. Ferreira
  • Wolfgang LinkEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1890)


Forkhead box O (FOXO) factors are tumor suppressor proteins commonly inactivated in human tumors. Furthermore, genetic variation within the FOXO3a gene is consistently associated with human longevity. FOXO proteins are usually inactivated by posttranslational modifications leading to cytoplasmic mislocalization. Therefore, the pharmacological activation by promoting nuclear localization of FOXOs is considered an attractive therapeutic approach to treat cancer and age-related diseases. We developed a cell-based imaging assay to screen for chemical agents capable of inhibiting the nuclear export and in turn trapping proteins that contain a nuclear export sequence including FOXO factors in the nucleus. The fluorescent signal of untreated assay cells localizes predominantly to the cytoplasm. Upon treatment with the nuclear export inhibitors the fluorescent-tagged reporter proteins appear as speckles in the nucleus. In a personalized medicine context, drugs capable of reactivating FOXO factors might be of enormous clinical value in human tumors in which these proteins are inactivated. Here, we describe the procedures for monitoring nuclear export which is suitable for high-throughput screening of compound collections.

Key words

FOXO Nuclear export High-content screening CMR1 



This work was supported by Fundação para a Ciência e a Tecnologia (FCT) Research Center Grant UID/BIM/04773/2013 Centre for Biomedical Research 1334. Work in the laboratory of WL was funded by a research grant from Liga Portuguesa Contra o Cancro – Núcleo Regional do Sul (LPCC/NRS), Terry Fox. B. I. Ferreira is the recipient of a FCT 2014 research grant SFRH/BPD/100434/2014. S. Machado is the recipient of a ProRegem grant PD/BD/114258/2016.


  1. 1.
    Hung MC, Link W (2011) Protein localization in disease and therapy. J Cell Sci 124(Pt 20):3381–3392. [pii]CrossRefPubMedGoogle Scholar
  2. 2.
    Hill R, Cautain B, de Pedro N, Link W (2014) Targeting nucleocytoplasmic transport in cancer therapy. Oncotarget 5(1):11–28. 1457[pii]CrossRefPubMedGoogle Scholar
  3. 3.
    Zanella F, Link W, Carnero A (2010) Understanding FOXO, new views on old transcription factors. Curr Cancer Drug Targets 10(2):135–146 doi:EPub-Abstract-CCDT-02 [pii]CrossRefGoogle Scholar
  4. 4.
    Link W, Fernandez-Marcos PJ (2017) FOXO transcription factors at the interface of metabolism and cancer. Int J Cancer 141(12):2379–2391. CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Martins R, Lithgow GJ, Link W (2016) Long live FOXO: unraveling the role of FOXO proteins in aging and longevity. Aging Cell 15(2):196–207. CrossRefGoogle Scholar
  6. 6.
    Zanella F, Dos Santos NR, Link W (2013) Moving to the core: spatiotemporal analysis of Forkhead box O (FOXO) and nuclear factor-kappaB (NF-kappaB) nuclear translocation. Traffic 14(3):247–258. CrossRefPubMedGoogle Scholar
  7. 7.
    Kau TR, Way JC, Silver PA (2004) Nuclear transport and cancer: from mechanism to intervention. Nat Rev Cancer 4(2):106–117. CrossRefPubMedGoogle Scholar
  8. 8.
    Zanella F, Rosado A, Blanco F, Henderson BR, Carnero A, Link W (2007) An HTS approach to screen for antagonists of the nuclear export machinery using high content cell-based assays. Assay Drug Dev Technol 5(3):333–341. CrossRefPubMedGoogle Scholar
  9. 9.
    Zanella F, Rosado A, Garcia B, Carnero A, Link W (2009) Using multiplexed regulation of luciferase activity and GFP translocation to screen for FOXO modulators. BMC Cell Biol 10(14):1471–2121Google Scholar
  10. 10.
    Kauselmann G, Dopazo A, Link W (2012) Identification of disease-relevant genes for molecularly-targeted drug discovery. Curr Cancer Drug Targets 12(1):1–13 doi:BSP/CCDT/E-Pub/00174 [pii]CrossRefGoogle Scholar
  11. 11.
    Zhang JH, Chung TD, Oldenburg KR (1999) A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J Biomol Screen 4(2):67–73. CrossRefPubMedGoogle Scholar
  12. 12.
    Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 46(1–3):3–26 doi:S0169-409X(00)00129-0 [pii]CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Susana Machado
    • 1
  • Catarina Raposo
    • 1
  • Bibiana I. Ferreira
    • 1
    • 2
  • Wolfgang Link
    • 3
    Email author
  1. 1.Centre for Biomedical Research (CBMR)University of AlgarveFaroPortugal
  2. 2.Regenerative Medicine Program, Department of Biomedical Sciences and MedicineUniversity of AlgarveFaroPortugal
  3. 3.Instituto de Investigaciones BiomeÇdicas “Alberto Sols” (CSIC-UAM)Arturo DuperierMadridSpain

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