249PD - Proteomic predictors of outcome after adjuvant anti-hormonal therapy for hormone receptor-positive breast cancer

Date 29 September 2012
Event ESMO Congress 2012
Session Breast cancer, early stage
Topics Anti-Cancer Agents & Biologic Therapy
Breast Cancer, Early Stage
Presenter Bryan Hennessy
Authors B. Hennessy1, D. Faratian2, Z. Ju3, A. Lluch-Hernandez4, S. Myhre5, A.M. Gonzalez-Angulo6, J. Overgaard7, J. Alsner8, A. Borresen-Dale5, G. Mills9
  • 1Medical Oncology, Beaumont Hospital, Dublin/IE
  • 2Division Of Pathology & Edinburgh Breakthrough Research Unit, University of Edinburgh, Edinburgh/UK
  • 3Biostatistics And Applied Mathematics, MD Anderson Cancer Center, Houston/US
  • 4Serv. Hematologia Y Oncologia Medica, Hospital Clinico Universitario de Valencia, ES-46010 - Valencia/ES
  • 5Department Of Genetics, Institute for Cancer Research, Norwegian Radium Hospital, Rikshospitalet University Hospital, Oslo, Norway, Oslo/NO
  • 6Department Of Breast Medical Oncology, MD Anderson Cancer Center, Houston/US
  • 7Dept. Experimental Clinical Oncology, Aarhus University Hospital, Aarhus/DK
  • 8Department Of Experimental Clinical Oncology, Aarhus University Hospital, Aarhus/DK
  • 9Systems Biology, MD Anderson Cancer Center, Houston/US



This study aimed to identify predictive proteomic biomarkers of outcome in women with estrogen and/or progesterone receptor-positive (ER/PR-positive) breast cancer after adjuvant tamoxifen, with sufficient power to alter patient management.


Using reverse phase protein arrays (RPPA), 140 antibodies were applied to a training set of 197 ER/PR-positive breast cancers to identify predictors. An algorithm was developed that predicted patient outcomes using a subset of antibodies. Since RPPA is a useful exploratory tool but does not lend itself as a practical clinical tool to assay validated biomarkers, quantitative immunofluorescence for selected proteins was applied to 313 ER/PR-positive breast cancers (test set) for validation. Seventy-seven other ER/PR-positive cancers with transcriptional profiling data were used to compare the performance of the proteomic biomarkers and established genomic predictors. All patients were treated with adjuvant tamoxifen after loco-regional therapy.


Two different combinations (4-protein/3-protein models) of four proteins (CCNB1/PAI1/PR/BCL2), subdivided lymph node-negative breast cancer patients into low-, medium- and high-risk groups with significantly different 10-year recurrence-free survival. The proteomic markers predicted 10-year distant metastasis-free survival in lymph node-negative patients in the test set in the low-, medium- and high-risk groups as follows: 0.9, 0.8, 0.7 (4-protein model (p = 0.05)), 0.91, 0.8, 0.74 (3-protein model (p = 0.004)), with 74%/64% patients in the low-risk groups, respectively. The proteomic models outperformed clinical variables and genomic predictors in multivariate analyses.


This study validates proteomic biomarkers that can be assayed in a practical inexpensive manner using immunofluorescence to identify lymph node-negative ER/PR-positive patients with excellent outcomes after adjuvant tamoxifen.


All authors have declared no conflicts of interest.