Abstract
Seventy percent of breast cancers express the estrogen receptor (ER), and agents that target the ER are the mainstay of treatment. However, virtually all people with ER+ breast cancer develop resistance to ER-directed agents in the metastatic setting. Beyond mutations in the ER itself, which occur in 25–30% of people treated with aromatase inhibitors1–4, knowledge about clinical resistance mechanisms remains incomplete. We identified activating HER2 mutations in metastatic biopsies from eight patients with ER+ metastatic breast cancer who had developed resistance to aromatase inhibitors, tamoxifen or fulvestrant. Examination of treatment-naive primary tumors in five patients showed no evidence of pre-existing mutations in four of five patients, suggesting that these mutations were acquired under the selective pressure of ER-directed therapy. The HER2 mutations and ER mutations were mutually exclusive, suggesting a distinct mechanism of acquired resistance to ER-directed therapies. In vitro analysis confirmed that the HER2 mutations conferred estrogen independence as well as—in contrast to ER mutations—resistance to tamoxifen, fulvestrant and the CDK4 and CDK6 inhibitor palbociclib. Resistance was overcome by combining ER-directed therapy with the irreversible HER2 kinase inhibitor neratinib.
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Data availability
Tumor and germline whole-exome sequencing data generated and analyzed for this study have been deposited in the access-controlled public repository dbGaP with accession code phs001285. RNA-seq data are available through GEO under accession GSE121411. Additional data generated in this study, including tumor exome analysis, are available within the paper and in the supplementary information.
References
Merenbakh-Lamin, K. et al. D538G mutation in estrogen receptor-alpha: A novel mechanism for acquired endocrine resistance in breast cancer. Cancer Res. 73, 6856–6864 (2013).
Robinson, D. R. et al. Activating ESR1 mutations in hormone-resistant metastatic breast cancer. Nat. Genet. 45, 1446–1451 (2013).
Toy, W. et al. ESR1 ligand-binding domain mutations in hormone-resistant breast cancer. Nat. Genet. 45, 1439–1445 (2013).
Jeselsohn, R. et al. Emergence of constitutively active estrogen receptor-alpha mutations in pretreated advanced estrogen receptor-positive breast cancer. Clin. Cancer Res. 20, 1757–1767 (2014).
Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 490, 61–70 (2012).
Giuliano, M., Trivedi, M. V. & Schiff, R. Bidirectional crosstalk between the estrogen receptor and human epidermal growth factor receptor 2 signaling pathways in breast cancer: molecular basis and clinical implications. Breast Care (Basel) 8, 256–262 (2013).
Osborne, C. K. & Schiff, R. Mechanisms of endocrine resistance in breast cancer. Annu. Rev. Med. 62, 233–247 (2011).
Hurtado, A. et al. Regulation of ERBB2 by oestrogen receptor-PAX2 determines response to tamoxifen. Nature 456, 663–666 (2008).
Liu, S. et al. Targeting tyrosine-kinases and estrogen receptor abrogates resistance to endocrine therapy in breast cancer. Oncotarget 5, 9049–9064 (2014).
Knowlden, J. M. et al. Elevated levels of epidermal growth factor receptor/c-erbB2 heterodimers mediate an autocrine growth regulatory pathway in tamoxifen-resistant MCF-7 cells. Endocrinology 144, 1032–1044 (2003).
Frogne, T. et al. Activation of ErbB3, EGFR and Erk is essential for growth of human breast cancer cell lines with acquired resistance to fulvestrant. Breast Cancer Res. Treat. 114, 263–275 (2009).
Benz, C. C. et al. Estrogen-dependent, tamoxifen-resistant tumorigenic growth of MCF-7 cells transfected with HER2/neu. Breast Cancer Res. Treat. 24, 85–95 (1992).
Elledge, R. M. et al. HER-2 expression and response to tamoxifen in estrogen receptor-positive breast cancer: a Southwest Oncology Group study. Clin. Cancer Res. 4, 7–12 (1998).
Bose, R. et al. Activating HER2 mutations in HER2 gene amplification negative breast cancer. Cancer Discov. 3, 224–237 (2013).
Hanker, A. B. et al. An acquired HER2 T798I gatekeeper mutation induces resistance to neratinib in a patient with HER2 mutant-driven breast cancer. Cancer Discov. 7, 575––585 (2017).
Greulich, H. et al. Functional analysis of receptor tyrosine kinase mutations in lung cancer identifies oncogenic extracellular domain mutations of ERBB2. Proc. Natl Acad. Sci. USA 109, 14476–14481 (2012).
Zabransky, D. J. et al. HER2 missense mutations have distinct effects on oncogenic signaling and migration. Proc. Natl Acad. Sci. USA 112, E6205–E6214 (2015).
Cohen, O. et al. Abstract S1-01: Whole exome and transcriptome sequencing of resistant ER+ metastatic breast cancer. Cancer Res. 77, S1-01–S1-01 (2017).
Imielinski, M. et al. Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing. Cell 150, 1107–1120 (2012).
Berger, A. H. et al. High-throughput phenotyping of lung cancer somatic mutations. Cancer Cell 30, 214–228 (2016).
de Martino, M. et al. Impact of ERBB2 mutations on in vitro sensitivity of bladder cancer to lapatinib. Cancer Biol. Ther. 15, 1239–1247 (2014).
Pereira, B. et al. The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nat. Commun. 7, 11479 (2016).
Yun, C. H. et al. Structures of lung cancer-derived EGFR mutants and inhibitor complexes: mechanism of activation and insights into differential inhibitor sensitivity. Cancer Cell 11, 217–227 (2007).
Kobayashi, S. et al. Compound EGFR mutations and response to EGFR tyrosine kinase inhibitors. J. Thorac. Oncol. 8, 45–51 (2013).
Curtis, C. et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486, 346–352 (2012).
Ciriello, G. et al. Comprehensive molecular portraits of invasive lobular breast cancer. Cancer Cell 163, 506–519 (2015).
Lefebvre, C. et al. Mutational profile of metastatic breast cancers: a retrospective analysis. PLoS Med. 13, e1002201 (2016).
Yates, L. R. et al. Genomic evolution of breast cancer metastasis and relapse. Cancer Cell 32, 169–184.e7 (2017).
Zehir, A. et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat. Med. 23, 703–713 (2017).
AACR Project GENIE Consortium. AACR Project GENIE: powering precision medicine through an international consortium. Cancer Discov. 7, 818–831 (2017).
Robinson, D. R. et al. Integrative clinical genomics of metastatic cancer. Nature 548, 297–303 (2017).
Lai, A. et al. Identification of gdc-0810 (arn-810), an orally bioavailable selective estrogen receptor degrader (serd) that demonstrates robust activity in tamoxifen-resistant breast cancer xenografts. J. Med. Chem. 58, 4888–4904 (2015).
Massarweh, S. et al. Tamoxifen resistance in breast tumors is driven by growth factor receptor signaling with repression of classic estrogen receptor genomic function. Cancer Res. 68, 826–833 (2008).
Sergushichev, A. An algorithm for fast preranked gene set enrichment analysis using cumulative statistic calculation. Preprint at https://www.biorxiv.org/content/early/2016/06/20/060012 (2016).
Lupien, M. et al. Growth factor stimulation induces a distinct ER(alpha) cistrome underlying breast cancer endocrine resistance. Genes Dev. 24, 2219–2227 (2010).
Jiang, J. et al. Epidermal growth factor-independent transformation of Ba/F3 cells with cancer-derived epidermal growth factor receptor mutants induces gefitinib-sensitive cell cycle progression. Cancer Res. 65, 8968–8974 (2005).
Burke, C. L., Lemmon, M. A., Coren, B. A., Engelman, D. M. & Stern, D. F. Dimerization of the p185neu transmembrane domain is necessary but not sufficient for transformation. Oncogene 14, 687–696 (1997).
Chen, L. I., Webster, M. K., Meyer, A. N. & Donoghue, D. J. Transmembrane domain sequence requirements for activation of the p185c-neu receptor tyrosine kinase. J. Cell. Biol. 137, 619–631 (1997).
Ma, C. X. et al. Neratinib efficacy and circulating tumor DNA detection of HER2 mutations in HER2 nonamplified metastatic breast cancer. Clin. Cancer Res. 23, 5687–5695 (2017).
Hyman, D. M. et al. HER kinase inhibition in patients with HER2- and HER3-mutant cancers. Nature 554, 189–194 (2018).
Ma, C. X. B. R. et al. Phase II trial of neratinib for HER2 mutated, non-amplified metastatic breast cancer (HER2mut MBC). J. Clin. Oncol. 34, abstr 516 (2016).
Hyman, D. et al. Abstract PD2-08: Neratinib + fulvestrant in ERBB2-mutant, HER2–non-amplified, estrogen receptor (ER)-positive, metastatic breast cancer (MBC): Preliminary analysis from the phase II SUMMIT trial. Cancer Res. 77, https://doi.org/10.1158/1538-7445.SABCS16-PD2-08 (2017).
Wagle, N. et al. High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing. Cancer Discov. 2, 82–93 (2012).
MacConaill, L. E. et al. Prospective enterprise-level molecular genotyping of a cohort of cancer patients. J. Mol. Diagn. 16, 660–672 (2014).
Sholl, L. M. et al. Institutional implementation of clinical tumor profiling on an unselected cancer population. JCI Insight 1, e87062 (2016).
Liberzon, A. et al. The molecular signatures database (MSigDB) hallmark gene set collection. Cell Syst. 1, 417–425 (2015).
Bild, A. H. et al. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 439, 353–357 (2006).
He, M. et al. EGFR exon 19 insertions: a new family of sensitizing EGFR mutations in lung adenocarcinoma. Clin. Cancer Res. 18, 1790–1797 (2012).
Wang, S. E. et al. HER2 kinase domain mutation results in constitutive phosphorylation and activation of HER2 and EGFR and resistance to EGFR tyrosine kinase inhibitors. Cancer Cell 10, 25–38 (2006).
Kancha, R. K., von Bubnoff, N., Peschel, C. & Duyster, J. Functional analysis of epidermal growth factor receptor (EGFR) mutations and potential implications for EGFR targeted therapy. Clin. Cancer Res. 15, 460–467 (2009).
Fisher, S. et al. A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries. Genome. Biol. 12, R1 (2011).
Reich, M. et al. GenePattern 2.0. Nat. Genet. 38, 500–501 (2006).
Cibulskis, K. et al. ContEst: estimating cross-contamination of human samples in next-generation sequencing data. Bioinformatics 27, 2601–2602 (2011).
Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol. 31, 213–219 (2013).
Saunders, C. T. et al. Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs. Bioinformatics 28, 1811–1817 (2012).
Costello, M. et al. Discovery and characterization of artifactual mutations in deep coverage targeted capture sequencing data due to oxidative DNA damage during sample preparation. Nucleic Acids Res. 41, e67 (2013).
Van Allen, E. M. et al. Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine. Nat. Med. 20, 682–688 (2014).
Ramos, A. H. et al. Oncotator: cancer variant annotation tool. Hum. Mutat. 36, E2423–E2429 (2015).
Olshen, A. B., Venkatraman, E. S., Lucito, R. & Wigler, M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 5, 557–572 (2004).
DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).
Carter, S. L. et al. Absolute quantification of somatic DNA alterations in human cancer. Nat. Biotechnol. 30, 413–421 (2012).
Brastianos, P. K. et al. Genomic characterization of brain metastases reveals branched evolution and potential therapeutic targets. Cancer Discov. 5, 1164–1177 (2015).
Stachler, M. D. et al. Paired exome analysis of Barrett’s esophagus and adenocarcinoma. Nat. Genet. 47, 1047–1055 (2015).
Lawrence, M. S. et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature 505, 495–501 (2014).
Futreal, P. A. et al. A census of human cancer genes. Nat. Rev. Cancer 4, 177–183 (2004).
Picelli, S. et al. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat. Methods 10, 1096–1098 (2013).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
DeLuca, D. S. et al. RNA-SeQC: RNA-seq metrics for quality control and process optimization. Bioinformatics 28, 1530–1532 (2012).
Leek, J. T., Johnson, W. E., Parker, H. S., Jaffe, A. E. & Storey, J. D. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics 28, 882–883 (2012).
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).
Stover, D. G. et al. The role of proliferation in determining response to neoadjuvant chemotherapy in breast cancer: a gene expression-based meta-analysis. Clin. Cancer Res. 22, 6039–6050 (2016).
Creighton, C. J. et al. Development of resistance to targeted therapies transforms the clinically associated molecular profile subtype of breast tumor xenografts. Cancer Res. 68, 7493–7501 (2008).
Hanzelmann, S., Castelo, R. & Guinney, J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics 14, 7 (2013).
Acknowledgements
We thank Q. Quartey and P. Ram for technical assistance, F. Luo, R. Jeselsohn, C. Strathdee, I. Leshchiner, D. Rosebrock, D. Livitz and G. Getz for technical advice, and B. Kaplan, H. Greulich, C. Strathdee, F. Luo, E. Goetz and L. Garraway for providing reagents. We thank C. Johannessen, M. Brown, M. Meyerson and R. Bose for helpful discussions and comments on the manuscript. We are grateful to all the patients who volunteered for our tumor biopsy protocol and generously provided the tissue analyzed in this study. This work was supported by the Department of Defense W81XWH-13-1-0032 (N.W.), AACR Landon Foundation 13-60-27-WAGL (N.W.), National Cancer Institute Breast Cancer SPORE at DF/HCC P50CA168504 (N.W.), Susan G. Komen CCR15333343 (N.W.), the V Foundation (N.W.), the Breast Cancer Alliance (N.W.), the Cancer Couch Foundation (N.W.), the MBC Collective (N.W.), Breast Cancer Research Foundation (N.U.L. and E.P.W.), ACT NOW (to Dana-Farber Cancer Institute Breast Oncology Program), Fashion Footwear Association of New York (to Dana-Farber Cancer Institute Breast Oncology Program), Friends of Dana-Farber Cancer Institute (to N.U.L.), the Klarman Family Foundation and HHMI (to A.R.) and Dana-Farber/Harvard Cancer Center SPORE grant P50CA168504.
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Contributions
U.N., O.C. and N.W. conceived and designed the study; U.N., C.K. and M.S.C. performed experiments; O.C. performed the computational analyses; O.C. and S.F. evaluated the evolutionary trajectories; A.G.W., S.A.W. and N.W. performed clinical data abstraction and annotation; C.P. and N.S.P. performed kinase structural modeling; O.R. and A.R. supervised the RNA-seq experiment; L.M., K.H. and N.O. assisted with acquisition and annotation of clinical samples; C.X.M. is the principal investigator on the clinical trial of fulvestrant/neratinib on which patient 315 was treated; E.P.W., N.U.L. and N.W. oversaw patient enrollment and sample collection on the metastatic biopsy protocol; U.N., O.C. and N.W. wrote the manuscript with input from all authors; N.W. supervised the study.
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Competing interests
N.W. was previously a stockholder in Foundation Medicine, was previously a consultant for Novartis, and has received sponsored research support from Novartis and Puma Biotechnology. N.U.L. has received research funding from Genentech, Cascadian Therapeutics, Array Biopharma, Novartis and Pfizer. C.X.M. receives consulting fees from Puma Biotechnology, Novartis and Pfizer, and research funding from Puma Biotechnology and Pfizer. S.A.W. is a consultant for Foundation Medicine and InfiniteMD. E.P.W. is a consultant for InfiniteMD, Genentech and Eli Lilly. A.R. is a scientific advisory board member of ThermoFisher Scientific, Syros Pharmaceuticals and Driver Group and a founder of Celsius Therapeutics. None of these entities had any role in the conceptualization, design, data collection, analysis, decision to publish or preparation of the manuscript.
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Integrated supplementary information
Supplementary Figure 1 Spectrum of HER2 mutations observed in MBC across several studies.
HER2 mutations in MBC identified in this study as well as in several recent studies are depicted along the length of the protein. In addition to the current study, we aggregated HER2 mutations observed in MBC in Lefebvre et al. (PLoS Med. 2016) and Yates et al. (Cancer Cell 2017), as well as the MBC subset from the MET500 study of Robinson et al. (Nature 2017), the MBC subset from the MSK-IMPACT compendium of Zehir et al. (Nat. Med. 2017) and the MBC subset from the AACR Project GENIE Consortium V1.0.15 (Cancer Discov. 2017), excluding duplicate patients from MSK-IMPACT. The mutations identified in the current study are highlighted. Among these, P1074L, I628M, R143G, and S653C (seen in two patients) have not been previously described (colored in purple). G727A, Leu755Ser, V777L, L869R, and R1153L have been observed in MBC in other studies. A more detailed list of the mutations can be found in Supplementary Table 1.
Supplementary Figure 2 Clinical timelines for the four patients with uncharacterized HER2 mutations, as well as detailed clinicopathological features.
Patient histories are shown from breast cancer diagnosis until metastatic biopsy sequenced in this study; arrows represent distinct therapies and durations, described in the key (upper right). Asterisks demarcate the diagnosis of metastatic disease in each case.
Supplementary Figure 3 Clonal structure and evolutionary dynamics of uncharacterized HER2 (ERBB2) mutations.
Clonal dynamics are shown for three metastatic samples with uncharacterized HER2 (ERBB2) mutations by comparing the metastatic clonal cell fraction/CCF (y axis) to the matched primary CCF (x axis). ERBB2 mutations are mapped to metastatic acquired clones in all three patients (colored in red, upper left corner) while not detected in the matched primary (CCF ~ 0). 'Truncal’ mutations that are shared between metastatic and primary tumors are found in all patients, demonstrating that the primary and metastatic samples are clonally related (colored in gray, upper right corner; CCF ~ 1 in both primary and metastatic samples). Primary-specific mutations are found in clones that were dominant in the primary tumor but not observed in the metastatic tumor (colored in blue). The phylogenetic relationships among clones are reconstructed for each patient starting from the normal cell (white circle) connected to the ancestral cancer cells (gray trunk). The phylogenetic divergence of the primary clones and subclones is depicted with blue edges, and that of the metastatic clones and subclones in red. Selected mutations in cancer genes are marked on the corresponding branches of the cancer phylogeny.
Supplementary Figure 4 HER2 kinase domain mutants confer resistance to anti-estrogen agents in MCF7 cells.
MCF7 HER2-mutant and control cells were compared on the basis of sensitivity to estrogen deprivation and the anti-ER agents tamoxifen and fulvestrant. a, MCF7 cells expressing the indicated HER2 mutants were serum starved for 2 d, followed by treatment with vehicle or 10 nM estradiol (E2) as indicated. After a week, relative viability compared to cells grown in complete medium was analyzed by CellTiter-Glo. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of six independent experiments. b–d, MCF7 control or HER2-mutant cells were plated in complete medium containing several concentrations of tamoxifen (b), fulvestrant (c), or GDC-0810 (d). Viability was determined after a week and normalized to untreated wells. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of six independent experiments.
Supplementary Figure 5 HER2 extracellular and signaling domain mutations do not confer resistance to anti-estrogen agents.
a–d, T47D HER2-mutant and control cells were compared on the basis of sensitivity to estrogen deprivation and the anti-ER agents tamoxifen, fulvestrant, and GDC-0810. a, T47D cells expressing the indicated HER2 mutants or controls were serum starved for 2 d, followed by treatment with vehicle or 10 nM estradiol (E2) as indicated. After a week, relative viability compared to cells grown in complete medium was analyzed by CellTiter-Glo. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of eight independent experiments. b–d, Cells were plated as in a and switched to full medium containing several concentrations of tamoxifen (b), fulvestrant (c), or GDC-0810 (d) after 2 d. Cells were retreated after 3 d. Viability was determined by CellTiter-Glo assay after a week and normalized to untreated wells. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of eight independent experiments. e,f, Levels of the HER2 activation markers phospho-ERK and phospho-AKT were examined by western blotting in T47D HER2-mutant and control cells. T47D HER2-mutant and control cells were plated in estrogen-deprived medium for 48 h and then switched to fresh medium supplemented with CSS (e) or complete medium containing DMSO or 1 μM fulvestrant (f) for 24 h. Whole-cell extracts were analyzed by western blotting using the indicated antibodies. Results shown are representative of five independent experiments. g, Levels of ER downstream target transcripts were examined by qPCR in T47D HER2-mutant and control cells. T47D HER2-mutant and control cells were plated in estrogen-deprived medium for 48 h, followed by RNA extraction and qRT–PCR using primers for ESR1, PGR, GREB1, or TFF1. Results shown are the mean +/− s.e.m. of three independent experiments.
Supplementary Figure 6 HER2 kinase domain mutant I628M does not confer resistance to anti-estrogen agents.
T47D HER2-mutant and control cells were compared on the basis of sensitivity to estrogen deprivation and the anti-ER agents tamoxifen and fulvestrant. a, T47D cells expressing the indicated HER2 mutants were serum starved for 2 d, followed by treatment with vehicle or 10 nM estradiol (E2) as indicated. After a week, relative viability compared to cells grown in complete medium was analyzed by CellTiter-Glo. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of four independent experiments. b–d, T47D control or HER2-mutant cells were plated in complete medium containing several concentrations of tamoxifen (b), fulvestrant (c), or GDC-0810 (d). Viability was determined after a week and normalized to untreated wells. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of four independent experiments.
Supplementary Figure 7 HER2 kinase domain compound mutant G727A/V777L confers resistance to anti-estrogen agents.
T47D HER2-mutant and control cells were compared on the basis of sensitivity to estrogen deprivation and the anti-ER agents tamoxifen and fulvestrant. a, T47D cells expressing the indicated HER2 mutants were serum starved for 2 d, followed by treatment with vehicle or 10 nM estradiol (E2) as indicated. After a week, relative viability compared to cells grown in complete medium was analyzed by CellTiter-Glo. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of four independent experiments. b–d, T47D control or HER2-mutant cells were plated in complete medium containing several concentrations of tamoxifen (b), fulvestrant (c), or GDC-0810 (d). Viability was determined after a week and normalized to untreated wells. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of four independent experiments.
Supplementary Figure 8 Activating HER2 mutants confer resistance to anti-estrogen agents at low-level expression in T47D cells.
T47D cells stably expressing GFP, wild-type HER2 or HER2 mutants under the control of a tet-on promoter were generated as described in the supplementary methods. a, Inducible T47D cells were treated with vehicle or 250 ng/mL doxycycline, and western blotting was performed to compare HER2 construct expression levels across cell lines. T47D cells expressing HER2 mutants constitutively under the EF-1α promoter (pLX307 vector) are included for comparison. Results shown are representative of five independent experiments. b, Inducible T47D cells were serum starved for 2 d in medium containing 250 ng/mL doxycycline, followed by vehicle or 10 nM estradiol (E2) as indicated. After a week, relative viability compared to cells grown in complete medium was analyzed by CellTiter-Glo. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of two independent experiments. c,d, Inducible cell lines were serum starved for 2 d in medium containing 250 ng/mL (c) or 100 ng/mL (d) doxycycline, followed by treatment with complete medium containing several concentrations of fulvestrant along with the appropriate concentration of doxycycline. After a week, relative viability compared to cells grown in complete medium with doxycycline was analyzed by CellTiter-Glo assay. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of three independent experiments.
Supplementary Figure 9 ERBB1/2 signatures and growth factor-driven ER signatures among HER2 activating mutants and controls.
Gene expression analysis by RNA sequencing of T47D cells expressing the indicated mutants or controls was performed after 2 d of serum starvation followed by treatment with DMSO or 1 μM fulvestrant for 24 h. Six replicates were performed for each specific construct and drug condition. ERBB1/2 signaling (left panels) and growth factor−driven ER signaling (right panels) signature strengths are shown for each of the HER2 mutants and the controls, across all replicates, in cells treated with DMSO (a), fulvestrant (b), and palbociclib (c).
Supplementary Figure 10 Combination therapeutic approaches in HER2-mutant cells.
a,b, T47D HER2-mutant and control cells were compared on the basis of sensitivity to pan-HER kinase inhibitor neratinib alone or in combination with fulvestrant. a, T47D HER2-mutant or control cells serum starved for 2 d were switched to complete medium containing 100 nM fulvestrant, 32 nM neratinib, or the combination. Cells were retreated after 3 d, and viability was determined by CellTiter-Glo assay 1 week after the start of treatment. Results shown are the mean +/− s.e.m. of technical replicates and are representative of 13 independent experiments. b, Levels of the HER2 activation markers phospho-ERK and phospho-AKT were examined by western blotting in T47D HER2-mutant and control cells treated with neratinib. T47D HER-mutant and control cells serum starved for 2 d were switched to complete medium containing DMSO or 1 μM neratinib for 24 h. Whole-cell extracts were analyzed for the indicated proteins by immunoblotting. Results shown are representative of three independent experiments. c, T47D HER2-mutant and control cells serum starved for 2 d were switched to complete medium containing 320 nM neratinib. Cells were retreated after 3 d, and viability was determined by CellTiter-Glo assay a week after the start of treatment. Results shown are the mean +/− s.e.m. and are representative of 15 independent experiments. d–i, The effectiveness of inhibitors against CDK4 and CDK6 or the downstream HER2 targets MEK, ERK, PI3K, AKT or mTOR were examined in T47D HER2-mutant and control cells. Inhibitor monotherapy was compared to combination therapy with fulvestrant. Cells plated as in b were treated with 100 nM fulvestrant, 1 μM palbociclib (CDK4 and CDK6 inhibitor; d), 1 µM trametinib (MEK inhibitor; e), 3.2 μM VX-11e (ERK inhibitor; f), 320 nM BYL719 (PI3K inhibitor; g), 320 nM AZD5363 (AKT inhibitor; h), 10 nM everolimus (mTOR inhibitor; i), or the combination. Cells were retreated after 3 d, and viability was determined by CellTiter-Glo assay 1 week after the start of treatment. Results shown are the mean +/− s.e.m. of three technical replicates and are representative of six, four, six, two, nine, and two independent experiments, respectively.
Supplementary Figure 11 ERBB1/2 signaling and growth factor-driven ER signaling signatures for HER2 activating mutants across multiple drugs.
Gene expression analysis by RNA sequencing performed as described in Fig. 4 included T47D cells expressing the four activating HER2 mutants as indicated. Cells were serum starved then treated with 1 μM fulvestrant, 1 μM neratinib, 10 μM palbociclib, or combinations (1 µM fulvestrant + 1 µM neratinib, 1 µM fulvestrant + 10 µM palbociclib). Six replicates were performed for each specific construct and drug condition, as shown. ERBB1/2 signaling (a) and growth factor−driven ER signaling (b) signature strengths were compared in mutant cell lines under various treatment conditions.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–11 and Supplementary Note
Supplementary Table 1
HER2 mutations observed in MBC across several studies
Supplementary Tables 2–4
Clinicopathological data for 12 patients with HER2 mutations
Supplementary Table 5
All SNVs from 12 patients with HER2 mutations
Supplementary Table 6
All CNAs from 12 patients with HER2 mutations
Supplementary Table 7
Differentially expressed genes comparing all mutant and control cell lines versus GFP under all drugs
Supplementary Table 8
Differentially expressed genes comparing activating HER2 mutants versus wild-type HER2 under all drugs
Supplementary Table 9
Gene set enrichment analysis for activating HER2 mutants versus GFP, under treatment with fulvestrant
Supplementary Table 10
Gene set enrichment analysis for activating HER2 mutants versus GFP, under treatment with DMSO
Supplementary Table 11
Gene set enrichment analysis for activating HER2 mutants versus wild-type HER2, under treatment with fulvestrant
Supplementary Table 12
Gene set enrichment analysis for activating HER2 mutants versus wild-type HER2, under treatment with fulvestrant
Supplementary Table 13
Primer sequences for qPCR
Supplementary Data
Uncropped western blots
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Nayar, U., Cohen, O., Kapstad, C. et al. Acquired HER2 mutations in ER+ metastatic breast cancer confer resistance to estrogen receptor–directed therapies. Nat Genet 51, 207–216 (2019). https://doi.org/10.1038/s41588-018-0287-5
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DOI: https://doi.org/10.1038/s41588-018-0287-5
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