Meta-Analysis

. 2015 Apr 18;107(5):djv081.

doi: 10.1093/jnci/djv081. Print 2015 May.

Identification of novel genetic markers of breast cancer survival

Qi Guo¹, Marjanka K Schmidt¹, Peter Kraft¹, Sander Canisius¹, Constance Chen¹, Sofia Khan¹, Jonathan Tyrer¹, Manjeet K Bolla¹, Qin Wang¹, Joe Dennis¹, Kyriaki Michailidou¹, Michael Lush¹, Siddhartha Kar¹, Jonathan Beesley¹, Alison M Dunning¹, Mitul Shah¹, Kamila Czene¹, Hatef Darabi¹, Mikael Eriksson¹, Diether Lambrechts¹, Caroline Weltens¹, Karin Leunen¹, Stig E Bojesen¹, Børge G Nordestgaard¹, Sune F Nielsen¹, Henrik Flyger¹, Jenny Chang-Claude¹, Anja Rudolph¹, Petra Seibold¹, Dieter Flesch-Janys¹, Carl Blomqvist¹, Kristiina Aittomäki¹, Rainer Fagerholm¹, Taru A Muranen¹, Fergus J Couch¹, Janet E Olson¹, Celine Vachon¹, Irene L Andrulis¹, Julia A Knight¹, Gord Glendon¹, Anna Marie Mulligan¹, Annegien Broeks¹, Frans B Hogervorst¹, Christopher A Haiman¹, Brian E Henderson¹, Fredrick Schumacher¹, Loic Le Marchand¹, John L Hopper¹, Helen Tsimiklis¹, Carmel Apicella¹, Melissa C Southey¹, Angela Cox¹, Simon S Cross¹, Malcolm W R Reed¹, Graham G Giles¹, Roger L Milne¹, Catriona McLean¹, Robert Winqvist¹, Katri Pylkäs¹, Arja Jukkola-Vuorinen¹, Mervi Grip¹, Maartje J Hooning¹, Antoinette Hollestelle¹, John W M Martens¹, Ans M W van den Ouweland¹, Federik Marme¹, Andreas Schneeweiss¹, Rongxi Yang¹, Barbara Burwinkel¹, Jonine Figueroa¹, Stephen J Chanock¹, Jolanta Lissowska¹, Elinor J Sawyer¹, Ian Tomlinson¹, Michael J Kerin¹, Nicola Miller¹, Hermann Brenner¹, Aida Karina Dieffenbach¹, Volker Arndt¹, Bernd Holleczek¹, Arto Mannermaa¹, Vesa Kataja¹, Veli-Matti Kosma¹, Jaana M Hartikainen¹, Jingmei Li¹, Judith S Brand¹, Keith Humphreys¹, Peter Devilee¹, Rob A E M Tollenaar¹, Caroline Seynaeve¹, Paolo Radice¹, Paolo Peterlongo¹, Bernardo Bonanni¹, Paolo Mariani¹, Peter A Fasching¹, Matthias W Beckmann¹, Alexander Hein¹, Arif B Ekici¹, Georgia Chenevix-Trench¹, Rosemary Balleine¹; kConFab Investigators; Kelly-Anne Phillips¹, Javier Benitez¹, M Pilar Zamora¹, Jose Ignacio Arias Perez¹, Primitiva Menéndez¹, Anna Jakubowska¹, Jan Lubinski¹, Katarzyna Jaworska-Bieniek¹, Katarzyna Durda¹, Ute Hamann¹, Maria Kabisch¹, Hans Ulrich Ulmer¹, Thomas Rüdiger¹, Sara Margolin¹, Vessela Kristensen¹, Silje Nord¹, D Gareth Evans¹, Jean E Abraham¹, Helena M Earl¹, Louise Hiller¹, Janet A Dunn¹, Sarah Bowden¹, Christine Berg¹, Daniele Campa¹, W Ryan Diver¹, Susan M Gapstur¹, Mia M Gaudet¹, Susan E Hankinson¹, Robert N Hoover¹, Anika Hüsing¹, Rudolf Kaaks¹, Mitchell J Machiela¹, Walter Willett¹, Myrto Barrdahl¹, Federico Canzian¹, Suet-Feung Chin¹, Carlos Caldas¹, David J Hunter¹, Sara Lindstrom¹, Montserrat García-Closas¹, Per Hall¹, Douglas F Easton¹, Diana M Eccles¹, Nazneen Rahman¹, Heli Nevanlinna¹, Paul D P Pharoah¹

Affiliations

Affiliation

¹ Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, UK (QG, JT, AMD, MS, JEA, DFE, PDPP); Netherlands Cancer Institute, Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands (MKS, SC, AB, FBH); Department of Epidemiology, Harvard School of Public Health, Boston, MA (PK, SH, DJH, SL); Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard School of Public Health, Boston, MA (PK, CCh, DJH, SL); Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland (SK, RF, TAM, HN); Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK (MKB, QW, JD, KM, ML, SK, DFE, PDPP); Department of Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia (JBee, GCT); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden (KC, HD, ME, JiL, JBr, KH, PH); Laboratory for Translational Genetics, Department of Oncology, University of Leuven, Leuven, Belgium (DL); Vesalius Research Center, VIB, Leuven, Belgium (DL); Oncology Department, University Hospital Gasthuisberg, Leuven, Belgium (CW, KL); Copenhagen General Population Study, Herlev Hospital, Copenhagen, Denmark (SEB, BGN, SFN); Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Denmark (SEB, BGN, SFN); Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark (SEB, BGN); Department of Breast Surgery, Herlev Hospital, Copenhagen University Hospital, Denmark (HF); Division of Cancer Epidemiology, German Cancer Research Center (Deutsches Krebsforschungszentrum), Heidelberg, Germany (JCC, AR, PS, DC, AHü, RK, MB); Department of Cancer Epidemiology/Clinical Cancer Registry and Institute for Medical Biometrics and Epidemiology, University Clinic Hamburg-Eppendorf, Hamburg, Germany (DFJ); Department of Oncology

PMID: 25890600
PMCID: PMC4555642
DOI: 10.1093/jnci/djv081

Meta-Analysis

Identification of novel genetic markers of breast cancer survival

Qi Guo et al. J Natl Cancer Inst. 2015.

. 2015 Apr 18;107(5):djv081.

doi: 10.1093/jnci/djv081. Print 2015 May.

Authors

Affiliation

¹ Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, UK (QG, JT, AMD, MS, JEA, DFE, PDPP); Netherlands Cancer Institute, Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands (MKS, SC, AB, FBH); Department of Epidemiology, Harvard School of Public Health, Boston, MA (PK, SH, DJH, SL); Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard School of Public Health, Boston, MA (PK, CCh, DJH, SL); Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland (SK, RF, TAM, HN); Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK (MKB, QW, JD, KM, ML, SK, DFE, PDPP); Department of Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia (JBee, GCT); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden (KC, HD, ME, JiL, JBr, KH, PH); Laboratory for Translational Genetics, Department of Oncology, University of Leuven, Leuven, Belgium (DL); Vesalius Research Center, VIB, Leuven, Belgium (DL); Oncology Department, University Hospital Gasthuisberg, Leuven, Belgium (CW, KL); Copenhagen General Population Study, Herlev Hospital, Copenhagen, Denmark (SEB, BGN, SFN); Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Denmark (SEB, BGN, SFN); Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark (SEB, BGN); Department of Breast Surgery, Herlev Hospital, Copenhagen University Hospital, Denmark (HF); Division of Cancer Epidemiology, German Cancer Research Center (Deutsches Krebsforschungszentrum), Heidelberg, Germany (JCC, AR, PS, DC, AHü, RK, MB); Department of Cancer Epidemiology/Clinical Cancer Registry and Institute for Medical Biometrics and Epidemiology, University Clinic Hamburg-Eppendorf, Hamburg, Germany (DFJ); Department of Oncology

PMID: 25890600
PMCID: PMC4555642
DOI: 10.1093/jnci/djv081

Abstract

Background: Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival.

Methods: We conducted a large meta-analysis of studies in populations of European ancestry, including 37954 patients with 2900 deaths from breast cancer. Each study had been genotyped for between 200000 and 900000 single nucleotide polymorphisms (SNPs) across the genome; genotypes for nine million common variants were imputed using a common reference panel from the 1000 Genomes Project. We also carried out subtype-specific analyses based on 6881 estrogen receptor (ER)-negative patients (920 events) and 23059 ER-positive patients (1333 events). All statistical tests were two-sided.

Results: We identified one new locus (rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases (hazard ratio [HR] = 1.95, 95% confidence interval [CI] = 1.55 to 2.47, P = 1.91 x 10(-8)). Genotyping a subset of 2113 case patients, of which 300 were ER negative, provided supporting evidence for the quality of the imputation. The association in this set of case patients was stronger for the observed genotypes than for the imputed genotypes. A second locus (rs148760487 at 2q24.2) was associated at genome-wide statistical significance in initial analyses; the association was similar in ER-positive and ER-negative case patients. Here the results of genotyping suggested that the finding was less robust.

Conclusions: This is currently the largest study investigating genetic variation associated with breast cancer survival. Our results have potential clinical implications, as they confirm that germline genotype can provide prognostic information in addition to standard tumor prognostic factors.

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Figures

**Figure 1.**
Association plot for combined GWAS and COGS analyses for estrogen receptor (ER)–negative cases. The P values of the association between each single nucleotide polymorphism (SNP) and breast cancer survival were obtained by cox regression analyses with adjustment for principle components for each study and then combined. The y-axis shows the -log₁₀ P values of each SNP analyzed, and the x-axis shows their chromosome position. The **red horizontal line** represents P = 5x10^-8. All statistical tests were two-sided.

**Figure 2.**
Quantile-Quantile (Q-Q) plot for the combined GWAS and COGS analyses for estrogen receptor (ER)–negative cases. The y-axis represents the observed -log₁₀ P value, and the x-axis represents the expected -log₁₀ P value. The **red line** represents the expected distribution under the null hypothesis of no association. All statistical tests were two-sided.

See this image and copyright information in PMC

References

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Identification of novel genetic markers of breast cancer survival

Affiliation

Identification of novel genetic markers of breast cancer survival

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LinkOut - more resources

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Medical

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