HER kinase inhibition in patients with HER2- and HER3-mutant cancers


Somatic mutations of ERBB2 and ERBB3 (which encode HER2 and HER3, respectively) are found in a wide range of cancers. Preclinical modelling suggests that a subset of these mutations lead to constitutive HER2 activation, but most remain biologically uncharacterized. Here we define the biological and therapeutic importance of known oncogenic HER2 and HER3 mutations and variants of unknown biological importance by conducting a multi-histology, genomically selected, ‘basket’ trial using the pan-HER kinase inhibitor neratinib (SUMMIT; clinicaltrials.gov identifier NCT01953926). Efficacy in HER2-mutant cancers varied as a function of both tumour type and mutant allele to a degree not predicted by preclinical models, with the greatest activity seen in breast, cervical and biliary cancers and with tumours that contain kinase domain missense mutations. This study demonstrates how a molecularly driven clinical trial can be used to refine our biological understanding of both characterized and new genomic alterations with potential broad applicability for advancing the paradigm of genome-driven oncology.

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Figure 1: Individual treatment outcome and response for 141 patients grouped by tumour cohort and mutant allele/domain.
Figure 2: Integrated efficacy by tumour type and HER2 allele/domain.
Figure 3: Genomic modifiers of response and outcome by treatment duration.


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We thank patients and their families for participating in this study. Editorial support, not including writing, was provided by L. Miller. This work was funded by Puma Biotechnology, and supported by grants from the National Institutes of Health (grants P30 CA008748, P30 CA016672, P30 CA014089, R01 CA204749, R01 CA80195, T32 CA009207, 1U01 CA180964 and UL1 TR000371), the National Institutes of Health/National Cancer Institute (Breast SPORE grant P50 CA098131), Cycle for Survival, Marie-Josée and Henry R. Kravis Center for Molecular Oncology, The Cancer Prevention and Research Institute of Texas (RP1100584), the Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, Nellie B. Connally Breast Cancer Research Endowment, and the Breast Cancer Research Foundation.

Author information




D.M.H., H.W., M.F.B., R.E.C, F.X., A.B., L.D.E., G.M., C.F., A.S.L., R.P.B., J.B. and D.B.S. designed the study and supervised the analyses. R.E.C., F.X., L.D.E., G.M., C.F., A.S.L. and R.P.B. helped to collect and monitor the clinical outcome data. D.M.H., S.A.P., J.R., C.S., G.I.S., D.J., D.I.Q., V.M., B.D., I.A.M., V.B., E.C., S.L., A.C.L., J.P.E., B.T.L., A.J.H., R.M., A.M.S., A.D., L.M.S., K.J., G.I., J.J.H., C.L.A., F.M.B., J.B. and D.B.D. enrolled patients and provided patient samples. G.U. developed the PET response criteria and performed radiographic response assessments. B.S.T., J.P., J.T., S.D.S., N.B., M.M., M.F.B., J.B. and D.B.S. performed the tumour and plasma sequencing, provided computational infrastructure, and made final variant calls. D.M.H., H.W., M.S., B.S.T., J.P., J.T., H.B., M.F.B. and D.B.S. analysed clinical and genomic data and performed the integrated efficacy analyses. F.X. performed biostatistical analyses of the clinical efficacy data. D.M.H., H.W., B.S.T., C.L.A., F.M.B. and D.B.S. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to David M. Hyman.

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Competing interests

R.E.C., F.X., L.D.E., G.M., C.F., A.S.L. and R.P.B. are employees of Puma Biotechnology. D.M.H., M.S. and J.B. receive research support from Puma Biotechnology, B.T.L. and M.S. receive research funding from Diachi, A.D. receives personal fees from Roche, and D.S. received personal fees from Loxo Oncology and Pfizer.

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Reviewer Information Nature thanks E. Mardis and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Figure 1 Design of SUMMIT study.

Five tumour-specific HER2 (ERBB2)-mutant cohorts were pre-specified (endometrial, gastroesophageal, ovarian, colorectal and bladder/urinary tract). In addition, a sixth ‘solid tumour (not otherwise specified, NOS)’ HER2-mutant cohort allowed for the enrolment of patients with any other cancer types. A sufficient number of patients with breast, cervical, biliary and lung cancer were enrolled in the solid tumours (NOS) cohort to permit independent efficacy analysis using the same design as the pre-specified cohorts. Patients with HER3 (ERBB3)-mutant tumours were enrolled in a HER3-specific cohort regardless of tumour type. CBR, clinical benefit rate; cfDNA, cell-free (tumour) DNA; CI, confidence interval.

Extended Data Figure 2 Distribution of HER2 and HER3 mutations positioned by their amino acid coordinates across the respective protein domains.

a, b, HER2 (a) and HER3 (b) mutations (125 and 16 mutations, respectively). Each unique mutation is represented by a circle, with the circle size and number representing the frequency, and coloured to show the mutation class as indicated in the legend. The corresponding amino acid change and common hotspot mutations (shown in pink) are labelled next to the circles. Source data

Extended Data Figure 3 Spectrum of HER2 and HER3 mutations observed in the neratinib study versus TCGA, ICGC and other public datasets.

a, b, Distribution of HER2 (a) and HER3 (b) mutations observed across our cohort in comparison to the spectrum of HER2 and HER3 mutations (reflected lollipop) from publically available datasets (TCGA, ICGC and other published studies). Source data

Extended Data Figure 4 Distribution and outcome of 28 HER2 exon 20 insertions.

a, Percentage best change and PFS plots corresponding to each type of exon 20 insertion (colour coded by synonymous amino acid change). Three cases with no change are indicated in colour-coded circles above the x axis. b, Zoomed-in schematic of all exon 20 insertions positioned by their amino acid coordinates and frequencies. c, Five unique types of exon 20 insertions observed in the study with the resulting full amino acid sequences (insertion indicated in red). Source data

Extended Data Figure 5 Genomic modifiers of response and outcome by treatment duration.

a, Cancer cell fractions with 95% confidence intervals and clonality status of all HER2 mutations in 74 patients with sufficient sequencing data ordered by increasing clinical benefit (weeks on therapy). b, Comparison of the percentage activation of known oncogenic alterations in the three pathways between the patients of clinical benefit (n = 20, biologically independent samples) and no benefit (n = 66, biologically independent samples). Nominal Fisher’s P values are shown. Source data

Extended Data Figure 6 SUMMIT CONSORT diagram.

Extended Data Table 1 Patient demographics and efficacy by cohort
Extended Data Table 2 Treatment-emergent adverse events (occurring in ≥ 10% of patients)
Extended Data Table 3 PET response criteria
Extended Data Table 4 Patient disposition by cohort

Supplementary information

Life Sciences Reporting Summary (PDF 72 kb)

Supplementary Information

This file contains: 1 - list of genes covered in the MSK-IMPACT panel along with the HGNC ID, short gene description, chromosomal location, and panel version, 2 - list of all somatic mutations within the MSK-IMPACT genes for patient tumour samples with sequencing data and 3 - list of all somatic copy number alterations within the MSK-IMPACT genes for patient tumour samples with sequencing data. (PDF 745 kb)

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Hyman, D., Piha-Paul, S., Won, H. et al. HER kinase inhibition in patients with HER2- and HER3-mutant cancers. Nature 554, 189–194 (2018). https://doi.org/10.1038/nature25475

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