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Kiranjit K Dhillon Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

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Ilirjana Bajrami The CRUK Gene Function Laboratory and Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK

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Toshiyasu Taniguchi Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

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Christopher J Lord The CRUK Gene Function Laboratory and Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK

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BRCA1 and BRCA2: discovery, genetics and biology Globally, breast cancer is the most common cancer in women. Its familial form constitutes 5–10% of all breast cancers and has a dominant mode of inheritance and is characterised by earlier onset

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E Thomas The University of Texas MD Anderson Cancer Center, Breast Medical Oncology, 1515 Holcombe Boulevard, Box 424, Houston, Texas 77030, USA. ethomas@mdanderson.org

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G N Hortobagyi The University of Texas MD Anderson Cancer Center, Breast Medical Oncology, 1515 Holcombe Boulevard, Box 424, Houston, Texas 77030, USA. ethomas@mdanderson.org

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Since the initial studies of adjuvant therapy in the 1970s, it has become increasingly clear that chemotherapy and hormone therapy have had a substantial effect on the survival of women with early breast cancer. It was originally assumed that only women with high-risk features would derive benefit from adjuvant therapy, but it is now apparent from numerous studies that adjuvant therapy improves survival in all subgroups of women with invasive breast cancer, although the absolute benefit varies depending on tumor stage and other prognostic features. Considerable progress has been made in elucidating effective adjuvant therapy regimens, but there continue to be many unanswered questions that are being addressed in ongoing clinical trials of adjuvant hormone therapy and chemotherapy. This paper reviews the current paradigms in adjuvant therapy, the published data that have affected current practice patterns, and the current controversies.

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Barbara Kuske
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Catherine Naughton
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Kate Moore
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Kenneth G MacLeod
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William R Miller
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Robert Clarke
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Simon P Langdon
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David A Cameron
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Introduction Estrogen receptor α (ERα) is a major growth regulator for many breast cancers and has provided an exploitable target for therapy ( Ali & Coombes 2002 ). Estrogen binding to ERα promotes conformational changes in the

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Philippe L Bedard
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Sandeep K Singhal Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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Michail Ignatiadis Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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Ian Bradbury Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada
Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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Benjamin Haibe-Kains Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada
Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada
Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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Christine Desmedt Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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Sherene Loi Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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Dean B Evans Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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Stefan Michiels Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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J Michael Dixon Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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William R Miller Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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Martine J Piccart Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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Christos Sotiriou Division of Medical Oncology and Hematology, Breast Cancer Translational Research Laboratory JC Heuson, Frontier Science (Scotland) Ltd, School of Medicine, Machine Learning Group, Novartis Institutes for BioMedical Research, Breakthrough Breast Research Group, University of Edinburgh, Department of Biostatistics and Computational Biology, Department of Medicine, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada

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Introduction Histological grade is a powerful prognostic factor for early-stage breast cancer ( Rakha et al . 2008 ). The gene expression grade index (GGI) is a 97-gene algorithm that separates intermediate histological grade tumors into low

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Daniele Generali
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Stephen B Fox
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Alfredo Berruti
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Maria P Brizzi
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Leticia Campo
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Simone Bonardi
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Simon M Wigfield
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Paolo Bruzzi
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Alessandra Bersiga
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Giovanni Allevi
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Manuela Milani
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Sergio Aguggini
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Luigi Dogliotti
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Alberto Bottini
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Adrian L Harris
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, estrogen receptor (ER), and c-erbB2 expression in breast cancer patients ( Chia et al. 2001 , Bartosova et al. 2002 , Span et al. 2003 ). All these studies involved heterogeneous patient populations submitted postoperatively to different treatment

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Elgene Lim Garvan Institute of Medical Research and St Vincent’s Hospital, University of New South Wales, Sydney, New South Wales, Australia

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Gerard Tarulli Dame Roma Mitchell Cancer Research Laboratories and Adelaide Prostate Cancer Research Centre, University of Adelaide, Adelaide, South Australia, Australia

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Neil Portman Garvan Institute of Medical Research and St Vincent’s Hospital, University of New South Wales, Sydney, New South Wales, Australia

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Theresa E Hickey Dame Roma Mitchell Cancer Research Laboratories and Adelaide Prostate Cancer Research Centre, University of Adelaide, Adelaide, South Australia, Australia

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Wayne D Tilley Dame Roma Mitchell Cancer Research Laboratories and Adelaide Prostate Cancer Research Centre, University of Adelaide, Adelaide, South Australia, Australia

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Carlo Palmieri Institute of Translational Medicine, University of Liverpool, Clatterbridge Cancer Centre, NHS Foundation Trust, and Royal Liverpool University Hospital, Liverpool, Merseyside, UK

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approximately 75% of all breast cancers. When present, ER drives neoplasia and is a bona fide therapeutic target. The underlying aim of current endocrine therapy is to either reduce ER activity or reduce receptor levels within breast cancer cells. Despite the

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D M Barnes Hedley Atkins/Cancer Research UK Breast Pathology Laboratory, Guy's Hospital, London SE1 9RT, UK. diana.barnes@cancer.org.uk

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R R Millis Hedley Atkins/Cancer Research UK Breast Pathology Laboratory, Guy's Hospital, London SE1 9RT, UK. diana.barnes@cancer.org.uk

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C E Gillett Hedley Atkins/Cancer Research UK Breast Pathology Laboratory, Guy's Hospital, London SE1 9RT, UK. diana.barnes@cancer.org.uk

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K Ryder Hedley Atkins/Cancer Research UK Breast Pathology Laboratory, Guy's Hospital, London SE1 9RT, UK. diana.barnes@cancer.org.uk

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D Skilton Hedley Atkins/Cancer Research UK Breast Pathology Laboratory, Guy's Hospital, London SE1 9RT, UK. diana.barnes@cancer.org.uk

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I S Fentiman Hedley Atkins/Cancer Research UK Breast Pathology Laboratory, Guy's Hospital, London SE1 9RT, UK. diana.barnes@cancer.org.uk

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R D Rubens Hedley Atkins/Cancer Research UK Breast Pathology Laboratory, Guy's Hospital, London SE1 9RT, UK. diana.barnes@cancer.org.uk

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The oestrogen receptor (ER) status of 2660 patients with primary breast cancer has been related to the effect of different adjuvant systemic therapies on survival. However, as patients in the various treatment groups also had different prognostic features comparison between treatments was difficult. Over 90% of patients receiving tamoxifen (Tam) were postmenopausal compared with <20% of those receiving chemotherapy (CT). The latter had more positive nodes (85% vs 54%) and grade III tumours (54% vs 30%) than the Tam group. The combined CT and Tam group had similar characteristics to the CT alone group. The current reported increase in the proportion of women with ER+ tumours is explained by immunohistochemical analysis of ER and screening programmes. ER status was unrelated to survival in patients with small, low grade, node-negative tumours which was no different from that expected for age-matched women taken from the general population. The value of adjuvant treatment in these patients is therefore questionable. In those given any adjuvant treatment, survival of women with ER+ tumours was prolonged, with the greatest effect being seen in those receiving Tam. Patients with ER- tumours benefited from CT but the addition of Tam to CT improved survival only in those with ER+ tumours. ER status is now established as a major predictive factor for treatment selection in primary disease. Studies of prognostic and predictive markers may be invalidated by use of adjuvant therapy and selection criteria for different treatments. Survival will be influenced by both tumour biology and therapy. This important consideration must be remembered when analysing new markers, particularly in small studies.

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John P Wiebe Department of Biology, Hormonal Regulatory Mechanisms Laboratory, University of Western Ontario, London, Ontario, Canada N6A 5B7

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as a means of decreasing the local P concentrations. PR has long been linked to the proliferative changes in the normal breast, but its role in breast cancer is unclear. Recent studies have provided evidence that P metabolites formed in breast

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Erin E Swinstead Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, NIH, Bethesda, Maryland, USA

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Ville Paakinaho Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, NIH, Bethesda, Maryland, USA
Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland

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Gordon L Hager Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, NIH, Bethesda, Maryland, USA

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chromatin accessibility occurs in cancers ( Denny et al . 2016 , Qu et al . 2017 ). Breast cancer is no exception, with alterations occurring in chromatin accessibility, TF action and regulation ( Jeselsohn et al . 2015 , D’Antonio et al . 2017

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Keely M McNamara
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Nicole L Moore Department of Pathology Tohoku University School of Medicine, Miyagi, Sendai, Japan

Dame Roma Mitchell Cancer Research Laboratories Discipline of Medicine, The University of Adelaide and Hanson Institute, DX 650801, Adelaide, South Australia 5005, Australia

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Theresa E Hickey Department of Pathology Tohoku University School of Medicine, Miyagi, Sendai, Japan

Dame Roma Mitchell Cancer Research Laboratories Discipline of Medicine, The University of Adelaide and Hanson Institute, DX 650801, Adelaide, South Australia 5005, Australia

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Hironobu Sasano
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Wayne D Tilley Department of Pathology Tohoku University School of Medicine, Miyagi, Sendai, Japan

Dame Roma Mitchell Cancer Research Laboratories Discipline of Medicine, The University of Adelaide and Hanson Institute, DX 650801, Adelaide, South Australia 5005, Australia

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Introduction The importance of androgenic hormones in breast cancer has been recognised for much of the last century. Despite little understanding of their cellular actions in breast tissue at the time, androgenic compounds were used as breast

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