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TP53-based interaction analysis identifies cis-eQTL variants for TP53BP2, FBXO28, and FAM53A that associate with survival and treatment outcome in breast cancer

Rainer Fagerholm, Sofia Khan, Marjanka K. Schmidt, Montserrat García-Closas, Päivi Heikkilä, Jani Saarela, Jonathan Beesley, Maral Jamshidi, Kristiina Aittomäki, Jianjun Liu, H. Raza Ali, Irene L. Andrulis, Matthias W. Beckmann, Sabine Behrens, Fiona M. Blows, Hermann Brenner, Jenny Chang-Claude, Fergus J. Couch, Kamila Czene, Peter A. Fasching, Jonine Figueroa, Giuseppe Floris, Gord Glendon, Qi Guo, Per Hall, Emily Hallberg, Ute Hamann, Bernd Holleczek, Maartje J. Hooning, John L. Hopper, Agnes Jager, Maria Kabisch, kConFab/AOCS Investigators, Renske Keeman, Veli-Matti Kosma, Diether Lambrechts, Annika Lindblom, Arto Mannermaa, Sara Margolin, Elena Provenzano, Mitul Shah, Melissa C. Southey, Joe Dennis, Michael Lush, Kyriaki Michailidou, Qin Wang, Manjeet K. Bolla, Alison M. Dunning, Douglas F. Easton, Paul D.P. Pharoah, Georgia Chenevix-Trench, Carl Blomqvist and Heli Nevanlinna _

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Oncotarget. 2017; 8:18381-18398. https://doi.org/10.18632/oncotarget.15110

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Abstract

Rainer Fagerholm1, Sofia Khan1, Marjanka K. Schmidt2, Montserrat García-Closas3, Päivi Heikkilä4, Jani Saarela5, Jonathan Beesley6, Maral Jamshidi1, Kristiina Aittomäki7, Jianjun Liu8, H. Raza Ali9,10, Irene L. Andrulis11,12, Matthias W. Beckmann13, Sabine Behrens14, Fiona M. Blows15, Hermann Brenner16,17,18, Jenny Chang-Claude14,19, Fergus J. Couch20, Kamila Czene21, Peter A. Fasching13,22, Jonine Figueroa23,3, Giuseppe Floris24, Gord Glendon11, Qi Guo15, Per Hall21, Emily Hallberg25, Ute Hamann26, Bernd Holleczek27, Maartje J. Hooning28, John L. Hopper29, Agnes Jager28, Maria Kabisch26, kConFab/AOCS Investigators30, Renske Keeman2, Veli-Matti Kosma31,32,33, Diether Lambrechts34,35, Annika Lindblom36, Arto Mannermaa31,32,33, Sara Margolin37, Elena Provenzano38,39,40, Mitul Shah15, Melissa C. Southey41, Joe Dennis42, Michael Lush42, Kyriaki Michailidou42,43, Qin Wang42, Manjeet K. Bolla42, Alison M. Dunning15, Douglas F. Easton15,42, Paul D.P. Pharoah15,42, Georgia Chenevix-Trench6, Carl Blomqvist44,45 and Heli Nevanlinna1

1 Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland

2 Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands

3 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA

4 Department of Pathology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland

5 Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland.

6 Department of Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia

7 Department of Clinical Genetics, Helsinki University Hospital, University of Helsinki, Helsinki, Finland

8 Human Genetics Division, Genome Institute of Singapore, Singapore, Singapore

9 Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK

10 Department of Pathology, University of Cambridge, Cambridge, UK.

11 Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Canada

12 Department of Molecular Genetics, University of Toronto, Toronto, Canada

13 Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany

14 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany

15 Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK

16 Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany

17 German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany

18 Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany

19 University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany

20 Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA

21 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

22 David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, CA, USA

23 Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Edinburgh, UK

24 Leuven Multidisciplinary Breast Center, Department of Oncology, KULeuven, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium

25 Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA

26 Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany

27 Saarland Cancer Registry, Saarbrücken, Germany

28 Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam, The Netherlands

29 Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global health, The University of Melbourne, Melbourne, Australia

30 Peter MacCallum Cancer Center, The University of Melbourne, Melbourne, Australia

31 Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland

32 Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland

33 Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland

34 Vesalius Research Center, VIB, Leuven, Belgium

35 Laboratory for Translational Genetics, Department of Oncology, University of Leuven, Leuven, Belgium

36 Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden

37 Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden

38 Department of Oncology, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK

39 Department of Histopathology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK

40 Cambridge Experimental Cancer Medicine Centre and NIHR Cambridge Biomedical Research Centre, Cambridge, UK

41 Department of Pathology, The University of Melbourne, Melbourne, Australia

42 Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK

43 Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus

44 Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland

45 Department of Oncology, University of Örebro, Örebro, Sweden

Correspondence to:

Heli Nevanlinna, email:

Keywords: breast cancer, TP53, survival, anthracycline, SNP

Received: December 21, 2016 Accepted: January 01, 2017 Published: February 05, 2017

Abstract

TP53 overexpression is indicative of somatic TP53 mutations and associates with aggressive tumors and poor prognosis in breast cancer. We utilized a two-stage SNP association study to detect variants associated with breast cancer survival in a TP53-dependent manner. Initially, a genome-wide study (n = 575 cases) was conducted to discover candidate SNPs for genotyping and validation in the Breast Cancer Association Consortium (BCAC). The SNPs were then tested for interaction with tumor TP53 status (n = 4,610) and anthracycline treatment (n = 17,828). For SNPs interacting with anthracycline treatment, siRNA knockdown experiments were carried out to validate candidate genes.

In the test for interaction between SNP genotype and TP53 status, we identified one locus, represented by rs10916264 (p(interaction) = 3.44 × 10-5; FDR-adjusted p = 0.0011) in estrogen receptor (ER) positive cases. The rs10916264 AA genotype associated with worse survival among cases with ER-positive, TP53-positive tumors (hazard ratio [HR] 2.36, 95% confidence interval [C.I] 1.45 - 3.82). This is a cis-eQTL locus for FBXO28 and TP53BP2; expression levels of these genes were associated with patient survival specifically in ER-positive, TP53-mutated tumors. Additionally, the SNP rs798755 was associated with survival in interaction with anthracycline treatment (p(interaction) = 9.57 × 10-5, FDR-adjusted p = 0.0130). RNAi-based depletion of a predicted regulatory target gene, FAM53A, indicated that this gene can modulate doxorubicin sensitivity in breast cancer cell lines.

If confirmed in independent data sets, these results may be of clinical relevance in the development of prognostic and predictive marker panels for breast cancer.


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