HER2 expression identifies dynamic functional states within circulating breast cancer cells

Abstract

Circulating tumour cells in women with advanced oestrogen-receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative breast cancer acquire a HER2-positive subpopulation after multiple courses of therapy1,2. In contrast to HER2-amplified primary breast cancer, which is highly sensitive to HER2-targeted therapy, the clinical significance of acquired HER2 heterogeneity during the evolution of metastatic breast cancer is unknown. Here we analyse circulating tumour cells from 19 women with ER+/HER2 primary tumours, 84% of whom had acquired circulating tumour cells expressing HER2. Cultured circulating tumour cells maintain discrete HER2+ and HER2 subpopulations: HER2+ circulating tumour cells are more proliferative but not addicted to HER2, consistent with activation of multiple signalling pathways; HER2 circulating tumour cells show activation of Notch and DNA damage pathways, exhibiting resistance to cytotoxic chemotherapy, but sensitivity to Notch inhibition. HER2+ and HER2 circulating tumour cells interconvert spontaneously, with cells of one phenotype producing daughters of the opposite within four cell doublings. Although HER2+ and HER2 circulating tumour cells have comparable tumour initiating potential, differential proliferation favours the HER2+ state, while oxidative stress or cytotoxic chemotherapy enhances transition to the HER2 phenotype. Simultaneous treatment with paclitaxel and Notch inhibitors achieves sustained suppression of tumorigenesis in orthotopic circulating tumour cell-derived tumour models. Together, these results point to distinct yet interconverting phenotypes within patient-derived circulating tumour cells, contributing to progression of breast cancer and acquisition of drug resistance.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Distinct properties of HER2+ and HER2 CTC subpopulations from patients with advanced ER+/HER2 breast cancer.
Figure 2: Interconversion of HER2+ and HER2 phenotypes.
Figure 3: Molecular pathways differentially activated in HER2 versus HER2+ cultured CTCs.
Figure 4: Cooperative targeting of HER2+ and HER2 CTC subpopulations suppresses tumour growth.

Accession codes

Primary accessions

Gene Expression Omnibus

Data deposits

Single-cell RNA-seq data have been deposited in the Gene Expression Omnibus under accession number GSE75367. Mass spectrometry raw data have been deposited in the MassIVE proteomics data repository under accession number MSV000079419 (https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp).

References

  1. 1

    Arteaga, C. L. & Engelman, J. A. ERBB receptors: from oncogene discovery to basic science to mechanism-based cancer therapeutics. Cancer Cell 25, 282–303 (2014)

    CAS  Article  Google Scholar 

  2. 2

    Houssami, N., Macaskill, P., Balleine, R. L., Bilous, M. & Pegram, M. D. HER2 discordance between primary breast cancer and its paired metastasis: tumor biology or test artefact? Insights through meta-analysis. Breast Cancer Res. Treat. 129, 659–674 (2011)

    CAS  Article  Google Scholar 

  3. 3

    Ozkumur, E. et al. Inertial focusing for tumor antigen-dependent and -independent sorting of rare circulating tumor cells. Sci. Translat. Med. 5, 179ra47 (2013)

    Article  Google Scholar 

  4. 4

    Yu, M. et al. Ex vivo culture of circulating breast tumor cells for individualized testing of drug susceptibility. Science 345, 216–220 (2014)

    ADS  CAS  Article  Google Scholar 

  5. 5

    Ting, L., Rad, R., Gygi, S. P. & Haas, W. MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics. Nature Methods 8, 937–940 (2011)

    CAS  Article  Google Scholar 

  6. 6

    Osipo, C. et al. ErbB-2 inhibition activates Notch-1 and sensitizes breast cancer cells to a γ-secretase inhibitor. Oncogene 27, 5019–5032 (2008)

    CAS  Article  Google Scholar 

  7. 7

    Abravanel, D. L. et al. Notch promotes recurrence of dormant tumor cells following HER2/neu-targeted therapy. J. Clin. Invest. 125, 2484–2496 (2015)

    Article  Google Scholar 

  8. 8

    DeNicola, G. M. et al. Oncogene-induced Nrf2 transcription promotes ROS detoxification and tumorigenesis. Nature 475, 106–109 (2011)

    CAS  Article  Google Scholar 

  9. 9

    Wakabayashi, N. et al. Notch-Nrf2 axis: regulation of Nrf2 gene expression and cytoprotection by notch signaling. Mol. Cell. Biol. 34, 653–663 (2014)

    Article  Google Scholar 

  10. 10

    Korkaya, H. & Wicha, M. S. HER-2, notch, and breast cancer stem cells: targeting an axis of evil. Clin. Cancer Res. 15, 1845–1847 (2009)

    CAS  Article  Google Scholar 

  11. 11

    Ithimakin, S. et al. HER2 drives luminal breast cancer stem cells in the absence of HER2 amplification: implications for efficacy of adjuvant trastuzumab. Cancer Res. 73, 1635–1646 (2013)

    CAS  Article  Google Scholar 

  12. 12

    Korkaya, H., Paulson, A., Iovino, F. & Wicha, M. S. HER2 regulates the mammary stem/progenitor cell population driving tumorigenesis and invasion. Oncogene 27, 6120–6130 (2008)

    CAS  Article  Google Scholar 

  13. 13

    Ginestier, C. et al. ALDH1 is a marker of normal and malignant human mammary stem cells and a predictor of poor clinical outcome. Cell Stem Cell 1, 555–567 (2007)

    CAS  Article  Google Scholar 

  14. 14

    Martz, C. A. et al. Systematic identification of signaling pathways with potential to confer anticancer drug resistance. Sci. Signal. 7, ra121 (2014)

    Article  Google Scholar 

  15. 15

    Pandya, K. et al. Targeting both Notch and ErbB-2 signalling pathways is required for prevention of ErbB-2-positive breast tumour recurrence. Br. J. Cancer 105, 796–806 (2011)

    CAS  Article  Google Scholar 

  16. 16

    Takebe, N., Harris, P. J., Warren, R. Q. & Ivy, S. P. Targeting cancer stem cells by inhibiting Wnt, Notch, and Hedgehog pathways. Nature Rev. Clin. Oncol. 8, 97–106 (2011)

    CAS  Article  Google Scholar 

  17. 17

    Vanharanta, S. & Massagué, J. Origins of metastatic traits. Cancer Cell 24, 410–421 (2013)

    CAS  Article  Google Scholar 

  18. 18

    Lawson, D. A. et al. Single-cell analysis reveals a stem-cell program in human metastatic breast cancer cells. Nature 526, 131–135 (2015)

    ADS  CAS  Article  Google Scholar 

  19. 19

    Bidard, F. C. & Pierga, J. Y. Clinical utility of circulating tumor cells in metastatic breast cancer. J. Clin. Oncol. 33, 1622 (2015)

    Article  Google Scholar 

  20. 20

    Schramm, A. et al. The DETECT Study Program: personalized treatment in advanced breast cancer based on circulating tumor cells (CTCs). ASCO Meet. Abstr. 33, TPS11109 (2015)

    Google Scholar 

  21. 21

    Ignatiadis, M. et al. Abstract OT1-2-02: trastuzumab in HER2-negative early breast cancer as adjuvant treatment for circulating tumor cells (CTCs) (Treat CTC). Cancer Res. 75, OT1–2–02 (2015)

    Google Scholar 

  22. 22

    Amakye, D., Jagani, Z. & Dorsch, M. Unraveling the therapeutic potential of the Hedgehog pathway in cancer. Nature Med. 19, 1410–1422 (2013)

    CAS  Article  Google Scholar 

  23. 23

    Kim, E. J. et al. Pilot clinical trial of hedgehog pathway inhibitor GDC-0449 (vismodegib) in combination with gemcitabine in patients with metastatic pancreatic adenocarcinoma. Clin. Cancer Res. 20, 5937–5945 (2014)

    CAS  Article  Google Scholar 

  24. 24

    LoRusso, P. M. et al. Phase I trial of hedgehog pathway inhibitor vismodegib (GDC-0449) in patients with refractory, locally advanced or metastatic solid tumors. Clin. Cancer Res. 17, 2502–2511 (2011)

    CAS  Article  Google Scholar 

  25. 25

    Krop, I. et al. Phase I pharmacologic and pharmacodynamic study of the gamma secretase (Notch) inhibitor MK-0752 in adult patients with advanced solid tumors. J. Clin. Oncol. 30, 2307–2313 (2012)

    CAS  Article  Google Scholar 

  26. 26

    Miyamoto, D. T. et al. RNA-Seq of single prostate CTCs implicates noncanonical Wnt signaling in antiandrogen resistance. Science 349, 1351–1356 (2015)

    ADS  CAS  Article  Google Scholar 

  27. 27

    Mohapatra, G. et al. Glioma test array for use with formalin-fixed, paraffin-embedded tissue: array comparative genomic hybridization correlates with loss of heterozygosity and fluorescence in situ hybridization. J. Mol. Diagn. 8, 268–276 (2006)

    CAS  Article  Google Scholar 

  28. 28

    Snuderl, M. et al. Polysomy for chromosomes 1 and 19 predicts earlier recurrence in anaplastic oligodendrogliomas with concurrent 1p/19q loss. Clin. Cancer Res. 15, 6430–6437 (2009)

    CAS  Article  Google Scholar 

  29. 29

    Wolff, A. C. et al. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J. Clin. Oncol. 25, 118–145 (2007)

    CAS  Article  Google Scholar 

  30. 30

    Zheng, Z. et al. Anchored multiplex PCR for targeted next-generation sequencing. Nature Med. 20, 1479–1484 (2014)

    CAS  Article  Google Scholar 

  31. 31

    Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009)

    CAS  Article  Google Scholar 

  32. 32

    Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nature Biotechnol. 31, 213–219 (2013)

    CAS  Article  Google Scholar 

  33. 33

    McAlister, G. C. et al. Increasing the multiplexing capacity of TMTs using reporter ion isotopologues with isobaric masses. Anal. Chem. 84, 7469–7478 (2012)

    CAS  Article  Google Scholar 

  34. 34

    McAlister, G. C. et al. MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal. Chem. 86, 7150–7158 (2014)

    CAS  Article  Google Scholar 

  35. 35

    Huttlin, E. L. et al. A tissue-specific atlas of mouse protein phosphorylation and expression. Cell 143, 1174–1189 (2010)

    CAS  Article  Google Scholar 

  36. 36

    Elias, J. E. & Gygi, S. P. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nature Methods 4, 207–214 (2007)

    CAS  Article  Google Scholar 

  37. 37

    Szklarczyk, D. et al. The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res. 39, D561–D568 (2011)

    CAS  Article  Google Scholar 

  38. 38

    Garnett, M. J. et al. Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature 483, 570–575 (2012)

    ADS  CAS  Article  Google Scholar 

Download references

Acknowledgements

We thank the patients who participated in this study. This work was supported by National Institutes of Health (NIH) 2RO1CA129933, the Howard Hughes Medical Institute, the Breast Cancer Research Foundation, the National Foundation for Cancer Research (DAH) and Wellcome Trust 102696 (C.B.), NIH Quantum 2U01EB012493 (M.T., D.A.H.), T32 CA009361, Susan G. Komen Foundation PDF16376429 (N.V.J.), K12 5K12CA087723 (A.B.) and T32GM007753 (R.Y.E.). We thank D. Dombrowski (NIH 1S100D1016372-01) for expert flow cytometry.

Author information

Affiliations

Authors

Contributions

N.V.J., D.A.H. and S.M. conceived the project and provided project leadership. A.B. enrolled patients and provided clinical guidance. B.S.W. and S.R. performed the bioinformatics analyses. M.L. and Y.Z. assisted with animal experiments. T.K.S., M.L.O. and A.J.I. performed the mutational analysis and fluorescence in situ hybridization. J.A.L., R.D., R.O. and R.Y.E. picked micromanipulated CTCs for scRNA-seq and assisted with molecular biology experiments. D.S. analysed pathology specimens. C.B. and M.Y. helped with drug screens. S.R. and D.T.T. provided scRNA-seq support. W.H. and M.B. performed MS experiments and analysis. R.V. and M.T. collaboratively developed the CTC-iChip isolation of viable CTCs.

Corresponding authors

Correspondence to Shyamala Maheswaran or Daniel A. Haber.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information

Nature thanks J. P. Medema and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Patients with advanced ER+/HER2 breast cancer harbour discrete HER2+ and HER2 subpopulations.

a, CTCs freshly isolated from 19 patients with ER+/HER2 breast cancer were stained with HER2 (green) and EpCAM (yellow) and imaged using imaging flow cytometry. Bar graph shows the number of HER2+ (black) and HER2 (white) CTCs (median 22% HER2+ CTCs, range 4–58%). Supplementary Table 1 provides HER2+/HER2 ratios and each patient’s clinical history. b, scRNA-seq for ERBB2 expression at multiple time-points showing acquisition of HER2+ CTCs (Brx-82, Brx-42) over the course of progressive disease. Single asterisk (*) denotes patient expiration. Rx, sacituzumab (IMMU-132); Rx1, vinorelbine + trastuzumab; Rx2, eribulin. c, Distinct HER2+ and HER2 CTCs from 13 patients with triple-negative breast cancer (TNBC) determined by scRNA-seq (HER2 ≤ 0 RPM; HER2+ > 153, range 33–463). d, HER2 fluorescence in situ hybridization (FISH) analysis of metastatic tumours from patients, Brx-42, Brx-82 and Brx-142, shows no amplification of ERBB2 compared with HER2-amplified control (Supplementary Table 1 for tumour source data). HER2 (red); chromosome enumeration probe 17 (CEP17) (cyan); scale bar, 10 μm. Representative images from five independent fields are shown. e, Bright field and immunofluorescence (DAPI, blue; HER2, green) images of CTC lines, Brx-42, Brx-82 and Brx-142, demonstrate heterogeneity in HER2 expression. Scale bar, 100 μm (bright field); 20 μm (immunofluorescence). Representative images from three independent fields are shown. f, FACS analysis shows two distinct HER2+ and HER2 subpopulations in the CTC line Brx-42 (at initiation) compared with HER2 control. Representative data of two independent experiments are shown. g, HER2 FISH analysis of the HER2+ and HER2 subpopulations from CTC lines Brx-42, Brx-82 and Brx-142 shows that ERBB2 is not amplified. HER2-amplified SKBR3 cells shown as control. HER2 (red); CEP17 (green); scale bar, 10 μm. Representative images from five independent fields are shown.

Extended Data Figure 2 HER2+ and HER2 subpopulations exhibit distinct functional properties.

a, Increased expression of the proliferation marker Ki67 (red) in the HER2+ subpopulation of CTC line Brx-142 (t-test, P < 0.0001), compared with the HER2 subpopulation, with no change in cleaved-caspase 3 (red). HER2+ cells (green); scale bar, 20 μm. Representative images from five independent fields are shown. b, FACS analysis for the apoptotic marker Annexin V-FITC shows no difference in apoptosis between the HER2+ and HER2 subpopulations of FACS-purified CTC line Brx-142. Representative data from two independent experiments are shown. c, Tumours initiated by HER2+ or HER2 CTCs (Brx-82: 200,000 cells) orthotopically injected into the mammary fat pad show differential growth rates; n = 8. d, Metastatic frequency of HER2+ and HER2 cultured CTCs (Brx-82: P = 0.05; Brx-142: P = 0.009) following orthotopic injection; n = 8. e, Limiting dilution experiments demonstrate comparable tumour initiating ability from 200 HER2+ and HER2 cultured CTCs (Brx-82, Brx-142); n = 8.

Extended Data Figure 3 Dynamics of HER2+ and HER2 interconversion.

a, FACS-purified HER2+ and HER2 subpopulations from CTC line Brx-82 were monitored over 28 days to determine shifts in the composition of sorted populations. Representative data of two independent experiments are shown. b, Growth curves for HER2+ (red) and HER2 (blue) FACS-purified single cell clones from CTC line Brx-142; two-way ANOVA, P < 0.0001; n = 20. c, IHC HER2 staining of tumour xenografts derived from unlabelled HER2 and HER2+ CTCs showing acquisition/loss of HER2 (brown), respectively. Arrows indicate regions of HER2 acquisition/loss. Representative image from at least five independent fields; n = 8. ER+/HER2 and HER2-amplified breast cancers are shown below as controls. d, Low-magnification (landscape) view of HER2 IHC staining of tumour xenografts derived from mixed HER2+ and HER2 CTC cultures containing either GFP-tagged HER2+/HER2 cells (high magnification images are shown in Fig. 2f). Top: representative GFP-tagged HER2 cells give rise to GFP+/HER2+ cells (GFP: cytoplasmic red stain, HER2: cell surface brown stain). Bottom: GFP-tagged HER2+ cells produce GFP+/HER2 cells. Scale bar, 100 μm.

Extended Data Figure 4 Proteomic and scRNA-seq analysis of HER2+ versus HER2 cells.

a, b, MS-based whole cell proteome profiles (6,349 proteins) comparing HER2+ and HER2 populations from CTC lines (Brx-42, Brx-82, Brx-142). Matched HER2+ versus HER2 proteomic differences show significant linear correlation (Pearson correlation coefficient = 0.71 between Brx-82 and Brx-42; Pearson correlation coefficient = 0.64 between Brx-142 and Brx-42); NI, normalized intensity; n = 2 per cell line are shown. c, Phospho-RTK array of HER2+ and HER2 populations of CTC cell lines Brx-142 and Brx-82 show increased phosphorylation of RTKs in the HER2+ population. Numbers denote the following: 1, HER2; 2, HER3; 3, HER4; 4, INSR; 5, EPHA1; 6, EPHA2; 7, EPHA10. Representative data from two independent experiments are shown. d, Volcano plot depicts genes enriched in HER2+ (red) and HER2 (blue) individual CTCs isolated from patients Brx-42 and Brx-82 and analysed by scRNA-seq; n = 22. e, Venn diagram showing PID pathway overlap of genes and proteins derived from scRNA-seq (Brx-42, Brx-82) and quantitative proteomics of HER2+ CTCs, respectively.

Extended Data Figure 5 Fifty-five panel drug screen shows differential drug sensitivities exhibited by HER2+ versus HER2 subpopulations.

a, Heat map showing percentage cell viability (represented as decimal) after 6 days of drug treatment of the HER2+ and HER2 subpopulations derived from CTC lines Brx-142 and Brx-82. Red and blue represent high and low drug sensitivities, respectively; n = 6. b, Lapatinib sensitivity of HER2+ (red) and HER2 (blue) subpopulations of CTC line Brx-82. MDA-231 (TNBC) and SKBR3 (HER2-amplified) are shown as controls. c, Chemosensitivity of HER2+ (red) and HER2 (blue) subpopulations of CTC line Brx-142. MDA-231 (blue) and SKBR3 (red) are shown as controls. d, Sensitivity of HER2+ (red) and HER2 (blue) subpopulations of CTC line Brx-142 to Notch inhibition with Notchi1 (BMS-708163) and Notchi2 (RO4929097). MDA-231 and SKBR3 cells are shown as controls. ad, Representative of at least two independent experiments for each condition; n = 6.

Extended Data Figure 6 NOTCH1 expression and activity in HER2 CTCs.

a, Western blot analysis of HER2+ and HER2 subpopulations from CTC lines Brx-142 and Brx-82 show increased NOTCH1 in HER2 cells. β-Actin is shown as control. Immunofluorescence analysis and scRNA-seq of NOTCH1 (red) and HER2 (green) shows inversely correlated expression in CTC lines (Brx-142, Brx-82). b, Ectopic expression of constitutively active Notch intracellular domain (ICD) or NRF2 results in increased expression of the Notch1 ligand JAG1 but does not alter HER2 expression. Representative data of two independent experiments are shown; s.e.m. (error bars). c, siRNA-mediated inhibition of HER2 in Brx-42 HER2+ CTCs, and lapatinib-mediated inhibition of HER2 in SKBR3 cells results in dose-dependent increases in the expression of genes involved in Notch signalling (NOTCH1, JAG1, DLL1, HES1, HEY1, HEY2). Representative data of two independent experiments are shown; s.e.m. (error bars). d, Inhibition of HER2 using lapatinib or siRNA knockdown in Brx-82 HER2+ CTCs increases the expression of NRF2-driven cytoprotective genes downstream of the Notch pathway. Representative data of two independent experiments are shown; s.e.m. (error bars). e, Quantitation of the interconversion of HER2+ cells from single-cell clones into 5- to 9-cell and >10-cell clusters following treatment with 10mM H2O2; t-test, P < 0.05; n = 10. f, Paclitaxel treatment of mice with tumours derived from Brx-142 FACS-purified HER2+ CTCs, demonstrating a reduction in CTCs, and HER2 CTCs with no change in counts; t-test P < 0.05; NS, not significant. g, Paclitaxel treatment of mice with mammary xenografts derived from parental CTC line Brx-142 showing initial tumour response, followed by recurrent tumour growth. IHC analysis and quantitation of the recurrent tumour shows greatly reduced HER2+ (brown stain) cell composition in the Paclitaxel drug treated (T, 3 weeks post-treatment) tumour compared with the untreated tumour U, and the recovered tumour (R, 5 weeks post-treatment). Bar indicates duration of drug treatment (Rx). Scale bar, 100 μm; two-way ANOVA, P < 0.0001; n = 6. Representative images from five independent fields per tumour are shown and quantified; t-test, P < 0.001. h, Dual GFP (red, cytoplasmic stain) and HER2 (brown, cell surface stain) IHC of tumour xenografts derived from mixed GFP-tagged HER2+ and untagged HER2 CTC cultures demonstrating enhanced conversion from GFP+/HER2+ to GFP+/HER2 after 4 weeks of paclitaxel treatment; t-test, P < 0.0001; n = 6. Scale bar, 100 μm. Arrows indicate interconverting cells. Representative images from five independent fields per tumour are shown. i, Mouse tumour xenografts derived from the CTC line Brx-142 treated with a combination of the Notchi3 (LY-414575) and paclitaxel shows diminished tumour relapse; n = 6. Bar indicates treatment duration.

Supplementary information

Supplementary Data

This file contains Supplementary Table 1. (XLSX 15 kb)

Supplementary Data

This file contains Supplementary Table 2. (XLSX 9 kb)

Supplementary Data

This file contains Supplementary Table 3. (XLSX 2589 kb)

Supplementary Data

This file contains Supplementary Table 4. (XLSX 23 kb)

Supplementary Data

This file contains Supplementary Table 5. (XLSX 360 kb)

Supplementary Data

This file contains Supplementary Table 6. (XLSX 42 kb)

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Jordan, N., Bardia, A., Wittner, B. et al. HER2 expression identifies dynamic functional states within circulating breast cancer cells. Nature 537, 102–106 (2016). https://doi.org/10.1038/nature19328

Download citation

Further reading

Comments

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.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing