Abstract

The translational control of oncoprotein expression is implicated in many cancers. Here we report an eIF4A RNA helicase-dependent mechanism of translational control that contributes to oncogenesis and underlies the anticancer effects of silvestrol and related compounds. For example, eIF4A promotes T-cell acute lymphoblastic leukaemia development in vivo and is required for leukaemia maintenance. Accordingly, inhibition of eIF4A with silvestrol has powerful therapeutic effects against murine and human leukaemic cells in vitro and in vivo. We use transcriptome-scale ribosome footprinting to identify the hallmarks of eIF4A-dependent transcripts. These include 5′ untranslated region (UTR) sequences such as the 12-nucleotide guanine quartet (CGG)4 motif that can form RNA G-quadruplex structures. Notably, among the most eIF4A-dependent and silvestrol-sensitive transcripts are a number of oncogenes, superenhancer-associated transcription factors, and epigenetic regulators. Hence, the 5′ UTRs of select cancer genes harbour a targetable requirement for the eIF4A RNA helicase.

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Primary accessions

Gene Expression Omnibus

Data deposits

The ribosome footprinting and total mRNA sequencing data have been deposited in the Gene Expression Omnibus database under accession number GSE56887.

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Acknowledgements

We thank the members of A.L.W.’s thesis committee: N. Rosen, A. M. Brown and S. W. Lowe. For reagents and advice we thank J. T. Barata, W. S. Pear, R. Cencic, S. Shuman, J. Cools, A. A. Ferrando, C. S. Fraser, N. J. Lajkiewicz, A. Luz, J. F. Glickman, C. Y. Park, P. Yellen, A. Heguy, K. Huberman and A. Viale. H.-G.W. is a Scholar of the Leukemia and Lymphoma Society. This research was supported by National Cancer Institute R01-CA142798-01 (H.-G.W.), the Leukemia Research Foundation (H.-G.W.), the Experimental Therapeutics Center (H.-G.W.), the American Cancer Society 10284 (H.-G.W.), European Union grant no. PITN-GA-2012-316861 (Y.Z.), the Fund for Scientific Research FWO Flanders (J.V.d.M. and P.R.), grants G.0198.08 and G.0869.10N (F.S.), the GOA-UGent 12051203 (F.S.), Stichting tegen Kanker (F.S.), the Belgian Program of Interuniversity Poles of Attraction (F.S.), the Belgian Foundation Against Cancer (F.S.), the American Cancer Society PF-11-077-01-CDD (C.M.R.), the Lymphoma Research Foundation (J.H.S.), National Institutes of Health grants GM-067041 and GM-073855 (J.A.P.), and the Canadian Institutes of Health Research MOP-10653 (J.P.).

Author information

Author notes

    • Andrew L. Wolfe
    •  & Kamini Singh

    These authors contributed equally to this work.

    • Konstantinos J. Mavrakis
    •  & Jonathan H. Schatz

    Present addresses: Novartis, Cambridge, Massachusetts 02139, USA (K.J.M.); The University of Arizona Cancer Center, Tucson, Arizona 85719, USA (J.H.S.).

Affiliations

  1. Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA

    • Andrew L. Wolfe
    • , Kamini Singh
    • , Viraj R. Sanghvi
    • , Konstantinos J. Mavrakis
    • , Man Jiang
    • , Joni Van der Meulen
    • , Jonathan H. Schatz
    • , Chunying Zhao
    •  & Hans-Guido Wendel
  2. Weill Cornell Graduate School of Medical Sciences, New York, New York 10065, USA

    • Andrew L. Wolfe
  3. Computational Biology Department, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA

    • Yi Zhong
    • , Philipp Drewe
    •  & Gunnar Rätsch
  4. Stem Cell Center and Developmental Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA

    • Vinagolu K. Rajasekhar
  5. Department of Cancer Biology, University of Massachusetts Medical School, Worcester, Massachusetts 01605 USA

    • Justine E. Roderick
    •  & Michelle A. Kelliher
  6. Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, B-9000 Ghent, Belgium

    • Joni Van der Meulen
    • , Pieter Rondou
    •  & Frank Speleman
  7. Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA

    • Jonathan H. Schatz
  8. Department of Chemistry, Center for Chemical Methodology and Library Development, Boston University, Boston, Massachusetts 02215, USA

    • Christina M. Rodrigo
    •  & John A. Porco
  9. Molecular Pharmacology Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA

    • Elisa de Stanchina
  10. Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA

    • Julie Teruya-Feldstein
  11. Department of Biochemistry, McGill University, Montreal, Quebec H3G 1Y6, Canada

    • Jerry Pelletier
  12. Department of Oncology, McGill University, Montreal, Quebec H3G 1Y6, Canada

    • Jerry Pelletier
  13. The Rosalind and Morris Goodman Cancer Research Center, McGill University, Montreal, Quebec H3G 1Y6, Canada

    • Jerry Pelletier

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Contributions

A.L.W. performed in vivo and treatment studies; K.S. performed ribosome footprinting and RNA structure studies; Y.Z. and P.D. analysed footprint data; V.K.R., V.R.S., K.J.M., M.J., J.E.R., J.H.S., C.Z., J.T.-F. and M.A.K. contributed to experiments; C.M.R. prepared (±)-CR-31-B; E.d.S. directed murine drug toxicity experiments; J.V.d.M., P.R. and F.S. generated genomic data on T-ALL; J.A.P. Jr and J.P. advised on all aspects of the study; G.R. supervised computational analyses; H.-G.W. designed the study and wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Gunnar Rätsch or Hans-Guido Wendel.

Extended data

Supplementary information

Excel files

  1. 1.

    Supplementary Table 1

    Summary of re-sequencing data showing mutation data observed in 36 T-ALL samples.

  2. 2.

    Supplementary Table 2

    The multi-panel table provides results of a detailed analysis of the toxic effects of CR treatment in non-tumour bearing c57/B6 mice. a) Body and organ weights; b) Individual haematology; c) Bone marrow and spleen cytology; d) Individual chemistry.

  3. 3.

    Supplementary Table 3

    a) Genes with decreased Translational Efficiency (TE down); b) Genes with increased Translational Efficiency (TE up); c) Background genes with no change in Translational Efficiency (TE background); d) Complete list of genes that showed a significant change in RF distribution across the length of their transcript (rDiff positive gene set); e) Genes that are both TE down and rDiff positive.

  4. 4.

    Supplementary Table 4

    a-b) Complete lists of TE Down genes that harbour the 12-mer (a) or 9-mer (b) in their 5’UTRs; c-d) Complete lists of rDiff genes that harbour the 12-mer (c) or 9-mer (d) in their 5’UTRs; Prevalence of the TE Down 12-mer motif; e) TE Down genes with one or more predicted G-quadruplex structures; f) rDiff genes with one or more predicted G-quadruplex structures; g-h) Overlap of TE Down 12-mer motif (g) or 9-mer motif (h) with predicted G-quadruplexes. i-j) Overlap of rDiff 12-mer motif (i) or 9-mer motif (j) with predicted G-quadruplexes; k) Nucleotide-level depiction of the overlap between 9-mer motifs and G-quadruplexes. The motif is located at the positions marked X in the sequence. The middle row shows the structure. + represents that it is part of a G-quadruplex, ) ( represents a bond with another nucleotide.

  5. 5.

    Supplementary Table 5

    RNA oligos used for Circular Dichroism (CD) and thermal denaturation analysis. Note: 12-mers or 9-mers are shown in red.

  6. 6.

    Supplementary Table 6

    Overlap of TE down or rDiff genes with reported super-enhancer associated genes in the T-ALL cell lines DND41, JURKAT, or RPMI-840234. '+' indicates presence of one or more 12-mers, 9-mers, or predicted G-quadruplexes in the 5’UTR.

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DOI

https://doi.org/10.1038/nature13485

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