Article | Published:

Translation from unconventional 5′ start sites drives tumour initiation

Nature volume 541, pages 494499 (26 January 2017) | Download Citation


We are just beginning to understand how translational control affects tumour initiation and malignancy. Here we use an epidermis-specific, in vivo ribosome profiling strategy to investigate the translational landscape during the transition from normal homeostasis to malignancy. Using a mouse model of inducible SOX2, which is broadly expressed in oncogenic RAS-associated cancers, we show that despite widespread reductions in translation and protein synthesis, certain oncogenic mRNAs are spared. During tumour initiation, the translational apparatus is redirected towards unconventional upstream initiation sites, enhancing the translational efficiency of oncogenic mRNAs. An in vivo RNA interference screen of translational regulators revealed that depletion of conventional eIF2 complexes has adverse effects on normal but not oncogenic growth. Conversely, the alternative initiation factor eIF2A is essential for cancer progression, during which it mediates initiation at these upstream sites, differentially skewing translation and protein expression. Our findings unveil a role for the translation of 5′ untranslated regions in cancer, and expose new targets for therapeutic intervention.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


Primary accessions

Gene Expression Omnibus


  1. 1.

    et al. Global quantification of mammalian gene expression control. Nature 473, 337–342 (2011)

  2. 2.

    et al. Proteogenomic characterization of human colon and rectal cancer. Nature 513, 382–387 (2014)

  3. 3.

    , , & mTOR, translation initiation and cancer. Oncogene 25, 6416–6422 (2006)

  4. 4.

    , , & Targeting the eIF4F translation initiation complex: a critical nexus for cancer development. Cancer Res. 75, 250–263 (2015)

  5. 5.

    & Regulation of translation initiation in eukaryotes: mechanisms and biological targets. Cell 136, 731–745 (2009)

  6. 6.

    et al. The translational landscape of mTOR signalling steers cancer initiation and metastasis. Nature 485, 55–61 (2012)

  7. 7.

    & Modeling cutaneous squamous carcinoma development in the mouse. Cold Spring Harb. Perspect. Med. 4, a013623 (2014)

  8. 8.

    , & Sox2 is required for development of taste bud sensory cells. Genes Dev. 20, 2654–2659 (2006)

  9. 9.

    et al. Multiple dose-dependent roles for Sox2 in the patterning and differentiation of anterior foregut endoderm. Development 134, 2521–2531 (2007)

  10. 10.

    et al. SOX2 controls tumour initiation and cancer stem-cell functions in squamous-cell carcinoma. Nature 511, 246–250 (2014)

  11. 11.

    et al. Comprehensive genomic analysis identifies SOX2 as a frequently amplified gene in small-cell lung cancer. Nat. Genet. 44, 1111–1116 (2012)

  12. 12.

    et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 6, pl1 (2013)

  13. 13.

    et al. RNAi screens in mice identify physiological regulators of oncogenic growth. Nature 501, 185–190 (2013)

  14. 14.

    , , & Rapid functional dissection of genetic networks via tissue-specific transduction and RNAi in mouse embryos. Nat. Med. 16, 821–827 (2010)

  15. 15.

    et al. Sox2 cooperates with inflammation-mediated Stat3 activation in the malignant transformation of foregut basal progenitor cells. Cell Stem Cell 12, 304–315 (2013)

  16. 16.

    , , & Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324, 218–223 (2009)

  17. 17.

    et al. High-resolution view of the yeast meiotic program revealed by ribosome profiling. Science 335, 552–557 (2012)

  18. 18.

    , & Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes. Cell 147, 789–802 (2011)

  19. 19.

    & Evidence for posttranscriptional regulation of the keratins expressed during hyperproliferation and malignant transformation in human epidermis. J. Cell Biol. 103, 1945–1955 (1986)

  20. 20.

    , , & Haematopoietic stem cells require a highly regulated protein synthesis rate. Nature 509, 49–54 (2014)

  21. 21.

    et al. Stem cell function and stress response are controlled by protein synthesis. Nature 534, 335–340 (2016)

  22. 22.

    et al.. Detecting actively translated open reading frames in ribosome profiling data. Nat. Methods 13, 165–170 (2016)

  23. 23.

    et al. Peptidomic discovery of short open reading frame-encoded peptides in human cells. Nat. Chem. Biol. 9, 59–64 (2013)

  24. 24.

    et al. Translocations and mutations involving the nucleophosmin (NPM1) gene in lymphomas and leukemias. Haematologica 92, 519–532 (2007)

  25. 25.

    et al. ETS family transcriptional regulators drive chromatin dynamics and malignancy in squamous cell carcinomas. eLife 4, e10870 (2015)

  26. 26.

    & Upstream open reading frames as regulators of mRNA translation. Mol. Cell. Biol. 20, 8635–8642 (2000)

  27. 27.

    et al. Highly parallel identification of essential genes in cancer cells. Proc. Natl Acad. Sci. USA 105, 20380–20385 (2008)

  28. 28.

    The scanning mechanism of eukaryotic translation initiation. Annu. Rev. Biochem. 83, 779–812 (2014)

  29. 29.

    et al. Regulated translation initiation controls stress-induced gene expression in mammalian cells. Mol. Cell 6, 1099–1108 (2000)

  30. 30.

    et al. Activities of Ligatin and MCT-1/DENR in eukaryotic translation initiation and ribosomal recycling. Genes Dev. 24, 1787–1801 (2010)

  31. 31.

    et al. GTP-independent tRNA delivery to the ribosomal P-site by a novel eukaryotic translation factor. J. Biol. Chem. 285, 26779–26787 (2010)

  32. 32.

    , , , & Characterization of mammalian eIF2A and identification of the yeast homolog. J. Biol. Chem. 277, 37079–37087 (2002)

  33. 33.

    , , & Eukaryotic translation initiation machinery can operate in a bacterial-like mode without eIF2. Nat. Struct. Mol. Biol. 15, 836–841 (2008)

  34. 34.

    et al. Leucine-tRNA initiates at CUG start codons for protein synthesis and presentation by MHC class I. Science 336, 1719–1723 (2012)

  35. 35.

    et al. Translation from the 5′ untranslated region shapes the integrated stress response. Science 351, aad3867 (2016)

  36. 36.

    Cancer Genome Atlas Network. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517, 576–582 (2015)

  37. 37.

    & Translational reprogramming in cellular stress response. WIREs RNA 5, 301–315 (2014)

  38. 38.

    Roles of the translation initiation factor eIF2α serine 51 phosphorylation in cancer formation and treatment. Biochim. Biophys. Acta 1849, 871–880 (2015)

  39. 39.

    et al. Novel characteristics of the biological properties of the yeast Saccharomyces cerevisiae eukaryotic initiation factor 2A. J. Biol. Chem. 280, 15601–15611 (2005)

  40. 40.

    , , , & Insights into the role of yeast eIF2A in IRES-mediated translation. PLoS One 6, e24492 (2011)

  41. 41.

    Could the eIF2α-independent translation be the achilles heel of cancer? Front. Oncol. 5, 264 (2015)

  42. 42.

    et al.. PTENα, a PTEN isoform translated through alternative initiation, regulates mitochondrial function and energy metabolism. Cell Metab. 19, 836–848 (2014)

  43. 43.

    , & Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014)

  44. 44.

    & Translation inhibitors cause abnormalities in ribosome profiling experiments. Nucleic Acids Res. 42, e134 (2014)

  45. 45.

    , , , & The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosome-protected mRNA fragments. Nat. Protocols 7, 1534–1550 (2012)

  46. 46.

    & Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012)

  47. 47.

    et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013)

  48. 48.

    & Plastid: nucleotide-resolution analysis of next-generation sequencing and genomics data. BMC Genomics 17, 958 (2016)

  49. 49.

    & RNAi-mediated gene function analysis in skin. Methods Mol. Biol. 961, 351–361 (2013)

  50. 50.

    et al. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell 159, 440–455 (2014)

  51. 51.

    , , & Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav. Res. Methods 41, 1149–1160 (2009)

  52. 52.

    & ELDA: extreme limiting dilution analysis for comparing depleted and enriched populations in stem cell and other assays. J. Immunol. Methods 347, 70–78 (2009)

  53. 53.

    , , , & Self-renewal, multipotency, and the existence of two cell populations within an epithelial stem cell niche. Cell 118, 635–648 (2004)

  54. 54.

    , & Improved vectors and genome-wide libraries for CRISPR screening. Nat. Methods 11, 783–784 (2014)

  55. 55.

    , & Modular stop and go extraction tips with stacked disks for parallel and multidimensional peptide fractionation in proteomics. J. Proteome Res. 5, 988–994 (2006)

  56. 56.

    et al. Identifying and quantifying proteolytic events and the natural N terminome by terminal amine isotopic labeling of substrates. Nat. Protocols 6, 1578–1611 (2011)

  57. 57.

    RNA secondary structure analysis using the Vienna RNA package. Curr. Protoc. Bioinformatics Chapter 12, Unit12.2 (2009)

Download references


We thank J. Que for the R26-Sox2-IRES-eGFP mice, D. Xu and the Cornell Genomics Facility for sequencing support, the Rockefeller Proteomics Facility for protein/peptide analyses, members of the Fuchs’ laboratory for discussions, and L. Polak and M. Sribour for their support with tumorigenesis studies. We thank E. Heller for bioinformatics support, L. Calviello for support with RiboTaper, and F. Garcia-Quiroz and M. Jovanovic for critical reading of the manuscript. The Rockefeller University Proteomics Resource Center acknowledges funding from the Leona M. and Harry B. Helmsley Charitable Trust and Sohn Conferences Foundation for mass spectrometer instrumentation. The results published here are in part based upon data generated by the TCGA Research Network ( A.S. was supported by the Human Frontier Science Program Organization (HFSP, LT000639-2013) and is currently supported by the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7 under REA grant agreement no. 629861. S.N. is a Damon Runyon Fellow (DRG-2183-14). B.H. was supported by a Medical Scientist Training Program grant from the National Institute of General Medical Sciences of the National Institutes of Health under award number T32GM007739 to the Weill Cornell/Rockefeller/Sloan-Kettering Tri-Institutional MD-PhD Program. E.F. and J.S.W. are Investigators of the Howard Hughes Medical institute. This work was supported by grants to E.F. from the National Institutes of Health (R37-AR27883) and NYSTEM CO29559.

Author information

Author notes

    • Daniel Schramek

    Present address: The Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto M5G 1X5, Canada.


  1. Robin Chemers Neustein Laboratory of Mammalian Development and Cell Biology, Howard Hughes Medical Institute, The Rockefeller University, New York, New York 10065, USA

    • Ataman Sendoel
    • , Shruti Naik
    • , Nicholas C. Gomez
    • , Brian Hurwitz
    • , John Levorse
    • , Daniel Schramek
    •  & Elaine Fuchs
  2. Department of Cellular and Molecular Pharmacology, Howard Hughes Medical Institute, University of California, San Francisco, California 94158, USA

    • Joshua G. Dunn
    • , Edwin H. Rodriguez
    •  & Jonathan S. Weissman
  3. Proteomics Resource Center, The Rockefeller University, New York, New York 10065, USA

    • Brian D. Dill
    •  & Henrik Molina


  1. Search for Ataman Sendoel in:

  2. Search for Joshua G. Dunn in:

  3. Search for Edwin H. Rodriguez in:

  4. Search for Shruti Naik in:

  5. Search for Nicholas C. Gomez in:

  6. Search for Brian Hurwitz in:

  7. Search for John Levorse in:

  8. Search for Brian D. Dill in:

  9. Search for Daniel Schramek in:

  10. Search for Henrik Molina in:

  11. Search for Jonathan S. Weissman in:

  12. Search for Elaine Fuchs in:


A.S. and E.F. conceived the project, designed the experiments and wrote the manuscript. A.S. and B.H. performed the experiments, and collected and analysed data. J.G.D., E.H.R., J.S.W. and N.C.G. contributed to ribosome profiling data analysis. D.S. contributed to control shRNA library generation and established HrasG12V; Tgfbr2-null cell lines. S.N. contributed to OPP experiments. J.L. carried out in utero lentiviral injections. H.M. and B.D.D. performed proteomics experiments and analysed proteomics data. E.F. supervised the project. All authors discussed the results and edited the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Elaine Fuchs.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Figure

    This file contains the raw data for Figures 4h and 5a,d.

About this article

Publication history





Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.