Oncotarget

Research Papers:

HER2-HER3 dimer quantification by FLIM-FRET predicts breast cancer metastatic relapse independently of HER2 IHC status

Gregory Weitsman, Paul R. Barber, Lan K. Nguyen, Katherine Lawler, Gargi Patel, Natalie Woodman, Muireann T. Kelleher, Sarah E. Pinder, Mark Rowley, Paul A. Ellis, Anand D. Purushotham, Anthonius C. Coolen, Boris N. Kholodenko, Borivoj Vojnovic, Cheryl Gillett and Tony Ng _

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Oncotarget. 2016; 7:51012-51026. https://doi.org/10.18632/oncotarget.9963

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Abstract

Gregory Weitsman1,*, Paul R. Barber2,3,*, Lan K. Nguyen7,10,*, Katherine Lawler3, Gargi Patel1,9, Natalie Woodman4,5, Muireann T. Kelleher8, Sarah E. Pinder4,5, Mark Rowley3, Paul A. Ellis4, Anand D. Purushotham4, Anthonius C. Coolen3, Boris N. Kholodenko7, Borivoj Vojnovic1,2, Cheryl Gillett4, Tony Ng1,5,6

1Richard Dimbleby Department of Cancer Research, Randall Division and Division of Cancer Studies, King’s College London, Guy’s Medical School Campus, London, UK

2Department of Oncology, Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, University of Oxford, Oxford, UK

3Institute for Mathematical and Molecular Biomedicine, King’s College London, Guy’s Medical School Campus, London, UK

4Research Oncology, Division of Cancer Studies, King’s College London, Guy’s Hospital, Great Maze Pond, London, UK

5Breakthrough Breast Cancer Research Unit, Department of Research Oncology, Guy’s Hospital King’s College London School of Medicine, London, UK

6UCL Cancer Institute, Paul O’Gorman Building, University College London, London, UK

7Systems Biology Ireland, University College Dublin, Belfield, Dublin, Ireland

8Department of Medical Oncology, St George’s Hospital NHS Foundation Trust, London, UK

9Sussex Cancer Centre, Brighton and Sussex University Hospitals, Royal Sussex County Hospital, Brighton, UK

10Department of Biochemistry and Molecular Biology, School of Biomedical Sciences and Biomedical Discovery Institute, Monash University, Melbourne, Australia

*These authors contributed equally to this work

Correspondence to:

Tony Ng, email: tony.ng@kcl.ac.uk, t.ng@ucl.ac.uk

Cheryl Gillett, email: cheryl.gillett@kcl.ac.uk

Keywords: breast cancer, HER2, HER3, FLIM-FRET, prognosis

Received: April 07, 2016     Accepted: May 23, 2016     Published: July 07, 2016

ABSTRACT

Overexpression of HER2 is an important prognostic marker, and the only predictive biomarker of response to HER2-targeted therapies in invasive breast cancer. HER2-HER3 dimer has been shown to drive proliferation and tumor progression, and targeting of this dimer with pertuzumab alongside chemotherapy and trastuzumab, has shown significant clinical utility. The purpose of this study was to accurately quantify HER2-HER3 dimerisation in formalin fixed paraffin embedded (FFPE) breast cancer tissue as a novel prognostic biomarker.

FFPE tissues were obtained from patients included in the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) study. HER2-HER3 dimerisation was quantified using an improved fluorescence lifetime imaging microscopy (FLIM) histology-based analysis. Analysis of 131 tissue microarray cores demonstrated that the extent of HER2-HER3 dimer formation as measured by Förster Resonance Energy Transfer (FRET) determined through FLIM predicts the likelihood of metastatic relapse up to 10 years after surgery (hazard ratio 3.91 (1.61–9.5), p = 0.003) independently of HER2 expression, in a multivariate model. Interestingly there was no correlation between the level of HER2 protein expressed and HER2-HER3 heterodimer formation. We used a mathematical model that takes into account the complex interactions in a network of all four HER proteins to explain this counterintuitive finding.

Future utility of this technique may highlight a group of patients who do not overexpress HER2 protein but are nevertheless dependent on the HER2-HER3 heterodimer as driver of proliferation. This assay could, if validated in a group of patients treated with, for instance pertuzumab, be used as a predictive biomarker to predict for response to such targeted therapies.


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