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Noncoding somatic and inherited single-nucleotide variants converge to promote ESR1 expression in breast cancer

Nature Genetics volume 48, pages 1260–1266 (2016)Cite this article

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Abstract

Sustained expression of the estrogen receptor-α (ESR1) drives two-thirds of breast cancer and defines the ESR1-positive subtype. ESR1 engages enhancers upon estrogen stimulation to establish an oncogenic expression program1. Somatic copy number alterations involving the ESR1 gene occur in approximately 1% of ESR1-positive breast cancers2,3,4,5, suggesting that other mechanisms underlie the persistent expression of ESR1. We report significant enrichment of somatic mutations within the set of regulatory elements (SRE) regulating ESR1 in 7% of ESR1-positive breast cancers. These mutations regulate ESR1 expression by modulating transcription factor binding to the DNA. The SRE includes a recurrently mutated enhancer whose activity is also affected by rs9383590, a functional inherited single-nucleotide variant (SNV) that accounts for several breast cancer risk–associated loci. Our work highlights the importance of considering the combinatorial activity of regulatory elements as a single unit to delineate the impact of noncoding genetic alterations on single genes in cancer.

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Figure 1: Identification of a functional risk-associated SNV shared between Europeans and East Asians.
Figure 2: The rs9383590 SNV interacts with the ESR1 promoter altering gene expression.
Figure 3: The SRE of ESR1 is targeted by acquired somatic mutations in breast cancer.
Figure 4: Noncoding somatic mutations targeting ESR1 increase gene expression.

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Acknowledgements

We thank A. Razak, C. Elser, D. Cescon, D. Warr, E. Amir, L. Siu, N. Leighl and S. Sridhar for their involvement in recruiting the IMPACT and COMPACT samples used in this study. We also thank M. Lemaire for helpful discussions. We thank R. Rottapel and O. Kent for use of and help with the Glomax Multi-Detection system. We acknowledge the ENCODE consortium and the ENCODE production laboratories that generated the data sets provided by the ENCODE Data Coordination Center used in the manuscript. We also acknowledge the Cancer Genome Project, for making all the breast cancer and liver cancer called mutations publicly available, and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), for making the genotyping and expression data from primary breast tumors data available. We acknowledge the Princess Margaret Genomics Centre and the Bioinformatics group for providing the infrastructure assisting us with the targeted sequencing and analysis of the ESR1 SRE. Supported by the National Cancer Institute (NCI) at the National Institute of Health (NIH) (R01CA155004 to M.L.), the Princess Margaret Cancer Foundation (T.J.P. and M.L.), The Canadian Cancer Society (CCSRI702922 to M.L.), the Susan G. Komen Foundation (CCR15332792 to T.J.P.) and the Gattuso-Slaight Personalized Cancer Medicine Fund/PMCF (B.H.-K.). M.L. is funded by a young investigator award from the Ontario Institute for Cancer Research (OICR), a new investigator salary award from the Canadian Institute of Health Research (CIHR) and a Movember Rising Star award from Prostate Cancer Canada (PCC) (RS2014-04). K.J.K. and R.C.P. are supported by Canadian Breast Cancer Foundation (CBCF) postdoctoral fellowships. S.D.B. is supported by a Knudson and CIHR postdoctoral fellowship.

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Author notes

  1. Xue Wu

    Present address: Present address: Geneseeq Technology, Inc., Toronto, Ontario, Canada.,

  2. Swneke D Bailey and Kinjal Desai: These authors contributed equally to this work.

Authors and Affiliations

  1. Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada

    Swneke D Bailey, Ken J Kron, Parisa Mazrooei, Aislinn E Treloar, Mark Dowar, David W Cescon, S Y Cindy Yang, Xue Wu, Rossanna C Pezo, Benjamin Haibe-Kains, Philippe L Bedard, Trevor J Pugh & Mathieu Lupien

  2. Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada

    Swneke D Bailey, Ken J Kron, Parisa Mazrooei, Aislinn E Treloar, S Y Cindy Yang, Benjamin Haibe-Kains, Tak W Mak, Trevor J Pugh & Mathieu Lupien

  3. Department of Genetics, Norris Cotton Cancer Center, Dartmouth Medical School, Lebanon, New Hampshire, USA

    Kinjal Desai

  4. Department of Genetics, Stanford University School of Medicine, Stanford, California, USA

    Nicholas A Sinnott-Armstrong

  5. Campbell Family Institute for Breast Cancer Research, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada

    Kelsie L Thu, David W Cescon, Jennifer Silvester & Tak W Mak

  6. Department of Computer Science, University of Toronto, Toronto, Ontario, Canada

    Benjamin Haibe-Kains

  7. Division of Medical Oncology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada

    Philippe L Bedard

  8. Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, USA

    Richard C Sallari

  9. Ontario Institute for Cancer Research, Toronto, Ontario, Canada

    Mathieu Lupien

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  1. Swneke D Bailey
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Contributions

The concept of interrogating the mutational load in regulatory elements converging on single genes arose through discussions between S.D.B., N.A.S.-A., R.C.S. and M.L. S.D.B. designed and/or implemented all the computational and statistical approaches except for IGR and analyzed the results under the supervision of M.L. Experimental assessment of the effect of SNVs on enhancer activity, transcription factor binding and gene expression was designed by K.D., S.D.B. and M.L. and conducted by K.D. with assistance from K.J.K., A.E.T. and X.W. The CRISPR–Cas9-based enhancer deletion was conducted by K.D., K.J.K., K.L.T., J.S. and D.W.C. under the supervision of T.W.M. and M.L. P.M. and N.A.S.-A. implemented the IGR approach to predict allele-bias binding of transcription factors on SNVs after improvements to IGR by N.A.S.-A. and R.C.S. R.C.P. and P.L.B. assessed the ESR1, PR and HER2 expression status on primary breast tumors included in our validation cohort. S.Y.C.Y. performed the alignment and gene expression quantification of the TCGA RNA-seq data. M.D. assisted in DNA capture sequencing of the primary breast tumor validation cohort under T.J.P.'s supervision. B.H.-K. oversaw the expression analysis of the METABRIC data set. M.L. oversaw the project. Figures were designed and prepared by S.D.B. and K.D. The manuscript was written by S.D.B., K.D. and M.L. with assistance from all other authors.

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Correspondence to Mathieu Lupien.

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Bailey, S., Desai, K., Kron, K. et al. Noncoding somatic and inherited single-nucleotide variants converge to promote ESR1 expression in breast cancer. Nat Genet 48, 1260–1266 (2016). https://doi.org/10.1038/ng.3650

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