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Acquired CYP19A1 amplification is an early specific mechanism of aromatase inhibitor resistance in ERα metastatic breast cancer

Nature Genetics volume 49, pages 444–450 (2017)Cite this article

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A Corrigendum to this article was published on 26 May 2017

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Abstract

Tumor evolution is shaped by many variables, potentially involving external selective pressures induced by therapies1. After surgery, patients with estrogen receptor (ERα)-positive breast cancer are treated with adjuvant endocrine therapy2, including selective estrogen receptor modulators (SERMs) and/or aromatase inhibitors (AIs)3. However, more than 20% of patients relapse within 10 years and eventually progress to incurable metastatic disease4. Here we demonstrate that the choice of therapy has a fundamental influence on the genetic landscape of relapsed diseases. We found that 21.5% of AI-treated, relapsed patients had acquired CYP19A1 (encoding aromatase) amplification (CYP19A1amp). Relapsed patients also developed numerous mutations targeting key breast cancer–associated genes, including ESR1 and CYP19A1. Notably, CYP19A1amp cells also emerged in vitro, but only in AI-resistant models. CYP19A1 amplification caused increased aromatase activity and estrogen-independent ERα binding to target genes, resulting in CYP19A1amp cells showing decreased sensitivity to AI treatment. These data suggest that AI treatment itself selects for acquired CYP19A1amp and promotes local autocrine estrogen signaling in AI-resistant metastatic patients.

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Figure 1: Clinical treatments shape cancer genetic evolution.
Figure 2: AI-resistant metastases develop cluster amplification of CYP19A1.
Figure 3: CYP19A1 amplification leads to increased aromatase activity.
Figure 4: CYP19A1amp cells endogenously activate ERα and develop tolerance to AI.

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  • 31 January 2017

    In the version of this article initially published online, the names of authors Hermannus Kempe and Pernette J. Verschure were spelled incorrectly. These errors have been corrected in the print, PDF and HTML versions of this article.

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Acknowledgements

We thank all participants and their families. We thank A. Bardelli for his comments. We thank D. Patten for help with the exemestane study. We thank L. Watson for her help with the manuscript. We thank J.Bean for support. For these studies, S.M. and G.P. were supported by Associazione Italiana Ricerca sul Cancro (AIRC) (5x1000 campaign). L.M. was supported by the Imperial College Junior Research Fellowship. S.-P.H. was supported by Cancer Research UK (CRUK) grant C37/A18784. Y.P. was supported by CRUK PhD studentship P55374. G.C. was supported by the EpiPredict project (European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement 642691).

Author information

Author notes

  1. Luca Magnani and Gianmaria Frigè: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Surgery and Cancer, Imperial College London, London, UK

    Luca Magnani, Raffaella Maria Gadaleta, Giacomo Corleone, Sung-Pil Hong, Ylenia Perone & Simak Ali

  2. Department of Experimental Oncology, European Institute of Oncology, Milan, Italy

    Gianmaria Frigè & Saverio Minucci

  3. Hematology Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy

    Sonia Fabris & Antonino Neri

  4. Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands

    Hermannus Kempe & Pernette J Verschure

  5. Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Iros Barozzi

  6. Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Arcavacata di Rende, Italy

    Valentina Vircillo

  7. Division of Stem Cells and Cancer, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany

    Massimo Saini & Andreas Trumpp

  8. Institute for Stem Cell Technology and Experimental Medicine GmbH, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany

    Massimo Saini, Andreas Trumpp & Giancarlo Pruneri

  9. Division of Pathology, European Institute of Oncology and University of Milan, School of Medicine, Milan, Italy

    Giuseppe Viale

  10. Department of Oncology and Hemato-oncology, University of Milano, Milan, Italy

    Antonino Neri

  11. Division of Medical Senology, European Institute of Oncology (IEO), Milan, Italy

    Marco Angelo Colleoni

  12. Department of Biosciences, University of Milano, Milan, Italy

    Saverio Minucci

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  1. Luca Magnani
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Contributions

L.M. conceived the study and wrote the manuscript. L.M., S.M. and G.P. planned and supervised all experiments. L.M., G.F., S.-P.H., Y.P., R.M.G., S.F., H.K., and V.V. performed experiments. G.C. and I.B. performed bioinformatics analyses. P.J.V., G.V., A.N., M.S., A.T., S.A. and M.A.C. provided reagents, samples and intellectual contribution. All authors discussed the results and commented on the manuscript.

Corresponding authors

Correspondence to Luca Magnani, Giancarlo Pruneri or Saverio Minucci.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Treatment histories of patients with CYP19A1 amplification in the discovery cohort.

Treatment history for the six patients from the AI discovery cohort with acquired CYP19A1 amplification. PD, progressive disease; PR, partial response (according to Response Evaluation Criteria in Solid Tumors: RECIST standards).

Supplementary Figure 2 Treatment histories of patients with CYP19A1 amplification in the validation cohort.

Treatment history for the six patients from the AI validation cohort with acquired CYP19A1 amplification. PD, progressive disease; PR, partial response (according to Response Evaluation Criteria in Solid Tumors: RECIST standards).

Supplementary Figure 3 CYP19A1 locus CNAs in primary cancers.

CNA meta-analysis of primary breast cancers. (a) CYP19A1 locus. (b) ESR1 locus. Figures were generated using cBioPortal. Only datasets with potential CNA data are presented. Cancers are grouped and color-coded based on tissue of origin. CNA analysis was obtained using GISTIC.

Supplementary Figure 4 ESR1 locus CNAs in metastatic breast cancers and PDX models.

(a) CNA TaqMan analysis for potential ESR1 amplification in the validation cohort. Copy number values are normalized to the adjacent normal tissue and to an internal normalizer (either TERT or RNASEP). (b) CNA TaqMan analysis for potential ESR1 amplifications in the PDX cohort (obtained from patients treated with SERM/AI as indicated by the lower panel).

Supplementary Figure 5 CYP19A1 CNAs can be due to focal amplification as assayed by TaqMan.

(a) Graphical representation of GABRB3 locus, and its position with respect to the CYP19A1 locus. Normalization to the GABRB3 locus can help to identify focal (signal at the CYP19A1 locus > GABRB3) vs. whole chromosome amplification (signal at the CYP19A1 locus ≍ GABRB3). (b) Combined plot of all clinical datasets.

Supplementary Figure 6 CYP19A1 CNAs can be due to focal amplification as assayed by FISH.

Representative FISH images for the validation dataset. One case of CYP19A1 amplified and one case of CYP19A1 wild type are shown. The summary of TaqMan results and FISH ratio (CYP19A1/ 15 alpha satellite) is reported in the table.

Supplementary Figure 7 Mutational landscape of breast cancer drivers in patients with primary breast cancer.

SNV meta-analysis of primary breast cancers. (a) Cumulative frequency of CNA and SNV mapping at the PIK3CA, MAP3K1, GATA3, TP53, ESR1 and CYP19A1 loci in primary breast cancers. These genes were profiled in our targeted sequencing panel. (b) SNVs for the sequenced genes in a recent TCGA dataset including all breast cancer subtypes. (c) SNVs for the sequenced genes in the 2012 TCGA dataset restricted to luminal A/B (ERα-positive) patients. Mutational frequencies for the Luminal A and Luminal B subsets are included in the bottom panel (from two different TCGA datasets).

Supplementary Figure 8 Mutational landscape of breast cancer drivers in patients with metastatic breast cancer.

(a) Total depth of sequencing coverage and statistics for activating ESR1 mutations in Tamoxifen and AI patient samples. Allele frequencies (AF) are also reported as a fraction of the total number of sequenced and aligned reads. SNVs were called against adjacent matched normal tissue. (b) Boxplots for individual patient/mutations in the AI cohorts. DNA was re-extracted from patients included in Figure 2d and re-analyzed on a separate experiment using an Ampliseq custom panel. Patients’ identifiers from CYP19A1-amplified samples are highlighted in green boxes; ESR1-amplified patients are highlighted in bold. A summary of the mutation frequencies is shown in the table below.

Supplementary Figure 9 CYP19A1 CNAs in breast cancer cell lines.

(a) ERα breast cancer cell lines treatment history and derivation. (b) Potential CNV called by MACS within chromosome 15. CYP19A1 is located at the center of the dense cluster (black box). (c) Close up of the CYP19A1 amplicon in the six cell lines. The panels show raw reads (SAM file) at the boundaries of the amplicon

Supplementary Figure 10 CYP19A1 activity and manipulation in breast cancer cell lines.

(a) Aromatase activity assay. Various breast cancer cell lines were assayed for aromatase enzyme activity. Aromatase activity is higher in LTED cells than in MCF7 cells, and it is significantly impaired by letrozole treatment. Columns and bars represent mean and s.e.m. from three independent experiments. Asterisks represent significant difference after one-way ANOVA with Tukey’s post-test. (b) CYP19A1 mRNA was depleted using two independent siRNA. Bar represent fold change in mRNA levels measured with qRT-PCR and compared to a control siRNA using two alternative intron-spanning primers. Columns and bars represent mean and s.e.m. from three independent experiments. Asterisks represent significant difference after one-way ANOVA with Dunnet’s post-test. (c) CYP19A1 was overexpressed using a CYP19A1 ORF. Bar represent fold change in mRNA levels measured with qRT-PCR and compared to a control plasmid using two alternative intron-spanning primers. Columns and bars represent mean and s.e.m. from three independent experiments. Asterisks represent significant difference after Student’s t-test. (d) Growth of CYP19A1amp LTED cells was tested in response to the SERM Tamoxifen and the SERD Fulvestrant. Data are reported as the ratio of SRB units between day 6 and day 1. Columns and bars represent mean and s.e.m. from three independent experiments. Asterisks represent significant difference after a ANOVA test. Significance levels are as follows: *P < 0.05, **P < 0.01, ****P < 0.0001.

Supplementary Figure 11 Uncropped western blot for analysis of CYP19A1 in breast cancer cell lines.

Top. Lane 1: MW marker. Lanes 2-7: MCF7, MCF7T, MCF7F, LTED, LTEDT and LTEDF. Antibody: CYP19A1.

Bottom. Lane1: MW marker. Lanes 2-7: MCF7, MCF7T, MCF7F, LTED, LTEDT and LTEDF. Antibody: β-actin

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–11 and Supplementary Note (PDF 1369 kb)

Supplementary Table 1

Estimation of CYP19A1 amplification in primary cancers using SNP arrays SNP array-based CNV analysis of several cancer studies has been performed using http://cistrome.org/CaSNP/ (see Online Methods). A summary of the results is shown. (XLSX 38 kb)

Supplementary Table 2

Probe lists for mutational profiling using Ion Torrent technology BEDFILE containing the genomic coordinates of the probes used for the AmpliSeq custom panel. (XLSX 53 kb)

Supplementary Data 1

Ion Torrent called mutations in patients treated with tamoxifen Report summaries for each patient treated with single adjuvant tamoxifen were generated using Ion Reporter (https://ionreporter.thermofisher.com/ir/). Each tab contains the results from paired analyses (normal-metastasis). Labeling of each patient is concordant with the labeling from the main text. (XLSX 178 kb)

Supplementary Data 2

Ion Torrent called mutations in patients treated with aromatase inhibitors Report summaries for each patient treated with single adjuvant aromatase inhibitors were generated using Ion Reporter (https://ionreporter.thermofisher.com/ir/). Each tab contains the results from paired analyses (normal-metastasis). Labeling of each patient is concordant with the labeling in the main text. (XLSX 500 kb)

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Magnani, L., Frigè, G., Gadaleta, R. et al. Acquired CYP19A1 amplification is an early specific mechanism of aromatase inhibitor resistance in ERα metastatic breast cancer. Nat Genet 49, 444–450 (2017). https://doi.org/10.1038/ng.3773

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