Association of Breast Cancer Risk loci with Breast Cancer Survival Myrto Barrdahl [1], Federico Canzian [2], Sara Lindström [3], Irene Shui [4], Amanda Black [5], Robert N. Hoover [5], Regina G. Ziegler [5], Julie E. Buring [6,7], Stephen J. Chanock [5,8], W. Ryan Diver [9], Susan M. Gapstur [9], Mia M. Gaudet [9], Graham G. Giles [10,11], Christopher Haiman [12], Brian E. Henderson [12], Susan Hankinson [4,13,14], David J. Hunter [3], Amit D. Joshi [4], Peter Kraft [4], I-Min Lee [4,15], Loic Le Marchand [16], Roger L. Milne [10,11], Melissa C. Southey [17], Walter Willett [18], Marc Gunter [19], Salvatore Panico [20], Malin Sund [21], Elisabete Weiderpass [22-25], María-José Sánchez [26,27], Kim Overvad [28], Laure Dossus [29-31], Petra H Peeters [32,33], Kay-Tee Khaw [34], Dimitrios Trichopoulos [4,35,36], Rudolf Kaaks [1], Daniele Campa [1] 1.
Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581 Heidelberg D-69120, Germany
2.
Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581 Heidelberg D-69120, Germany
3.
Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue Boston MA-02115, USA
4.
Department of Epidemiology, Harvard School of Public Health , 677 Huntington Avenue Boston MA-02115, USA
5.
Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9000 Rockville Pike Bethesda MD20892, USA
6.
Department of Ambulatory Care and Prevention, Harvard Medical School, 677 Huntington Avenue Boston MA02115, USA
7.
Divisions of Preventive Medicine and Aging, Department of Medicine, Brigham and women’s Hospital and Harvard Medical School, 677 Huntington Avenue Boston MA-02115, USA
8.
Core Genotyping Facility Frederick National Laboratory for Cancer Research, 8717 Grovemont Circle Gaithersburg MD-20877, USA
9.
Epidemiology Research Program, American Cancer Society, 250 Williams St NW Atlanta GA-30303, USA
10. Cancer Epidemiology Centre, Cancer Council Victoria, 615 St Kilda Rd VIC-3004 Melbourne, Australia 11. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health,University of Melbourne, Parkville VIC-3010 Victoria, Australia
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as an ‘Accepted Article’, doi: 10.1002/ijc.29446 This article is protected by copyright. All rights reserved.
Page 3 of 27
International Journal of Cancer
12. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, 1975 Zonal Avenue Los Angeles CA-90033, USA 13. Department of Epidemiology, University of Massachusetts-Amherst School of Public Health and Health Sciences,402 Arnold Amherst MA-01003-9304, USA 14. Cancer Research Center, Brigham and Women’s Hospital, 75 Francis Street Boston MA-02115, USA 15. Department of Medicine, Harvard Medical School, 677 Huntington Avenue Boston MA-02115, USA 16. Cancer Research Center of Hawaii, University of Hawaii, 2777 Kalakaua Avenue Honolulu HI-96813, USA 17. Department of Pathology, University of Melbourne, Parkville VIC-3010 Melbourne, Australia 18. Department of Nutrition, Harvard School of Public Health, 677 Huntington Avenue Boston MA-02115, USA 19. Department of Epidemiology Biostatistics, School of Public Health, Imperial College, South Kensington Campus London UK-SW7 2AZ, UK 20. Dipartimento di Medicina Clinica e Chirurgia, Via Sergio Pancini 5 Naples I-80131, Italy 21. Department of Surgical and Perioperative Sciences, Surgery, Umeå University, Universitetstorget 16 S-90185, Sweden 22. Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø N-9037, Norway 23. Department of Research, Cancer Registry of Norway, Fridtjof Nansens vei 19 Oslo N-0304, Norway 24. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A Stockholm SE17177, Sweden 25. Samfundet Folkhälsan, Topeliusgatan 20 Helsinki FI-00250, Finland. 26. Escuela Andaluza de Salud Pública. Instituto de Investigación Biosanitaria ibs.GRANADA. Hospitales Universitarios de Granada/Universidad de Granada, Calle Real de Cartuja 36 Granada ES-18012, Spain 27. CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona ESP-08036, Spain 28. Department of Public Health, Section for Epidemiology, Aarhus University, Norrebrogade 44 Aarhus DK-8000, Denmark 29. INSERM, Centre for Research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women’s Health team, 16 Avenue Paul Vaillant Couturier F-94805, Villejuif, France 30. Univ Paris Sud, UMRS 1018, F-94805, Villejuif, France 31. IGR, F-94805, Villejuif, France 32. Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht Stratenum 6 NL-3508, The Netherlands
John Wiley 2& Sons, Inc. This article is protected by copyright. All rights reserved.
International Journal of Cancer
33. MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, South Kensington Campus London UK-SW7 2AZ, UK 34. Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge Addenbrooke's Hospital, Hills Rd UK-CB2 0SP, UK 35. Bureau of Epidemiologic Research, Academy of Athens, Alexandropoulos Street Athens GR-10679, Greece 36. Hellenic Health Foundation, Kaisareas Street Athens GR-11527, Greece
Corresponding author: Daniele Campa Division of Cancer Epidemiology German Cancer Research Center (DKFZ) Im Neuenheimer Feld 280 D-69120 Heidelberg, Germany Tel. +49-6221-421814, Fax +49-6221-421810, E-mail [email protected]
John Wiley 3& Sons, Inc. This article is protected by copyright. All rights reserved.
Page 4 of 27
Page 5 of 27
International Journal of Cancer
Abstract The survival of breast cancer patients is largely influenced by tumor characteristics, such as TNM stage, tumor grade and hormone receptor status. However, there is growing evidence that inherited genetic variation might affect the disease prognosis and response to treatment. Several lines of evidence suggest that alleles influencing breast cancer risk might also be associated with breast cancer survival. We examined the associations between 35 breast cancer susceptibility loci and the disease over-all survival (OS) in 10,255 breast cancer patients from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) of which 1,379 died, including 754 of breast cancer. We also conducted a meta-analysis of almost 35,000 patients and 5,000 deaths, combining results from BPC3 and the Breast Cancer Association Consortium (BCAC) and performed in silico analyses of SNPs with significant associations. In BPC3, the C allele of LSP1-rs3817198 was significantly associated with improved OS (HRper-allele=0.70; 95% CI: 0.58-0.85; Ptrend=2.84×10-4; HRheterozygotes=0.71; 95% CI: 0.55-0.92; HRhomozygotes=0.48; 95% CI: 0.31-0.76; P2DF=1.45×10-3). In silico, the C allele of LSP1-rs3817198 was predicted to increase expression of the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C). In the meta-analysis, TNRC9-rs3803662 was significantly associated with increased death hazard (HRMETA =1.09; 95% CI: 1.04-1.15; Ptrend=6.6×10-4; HRheterozygotes=0.96 95% CI: 0.90-1.03; HRhomozygotes= 1.21; 95% CI: 1.09-1.35; P2DF=1.25×10-4). In conclusion, we show that there is little overlap between the breast cancer risk single nucleotide polymorphisms (SNPs) identified so far and the SNPs associated with breast cancer prognosis, with the possible exceptions of LSP1-rs3817198 and TNRC9-rs3803662.
Novelty and impact: Our results show that the investigated risk alleles are not associated with over-all survival of breast cancer cases.
Keywords: breast cancer, SNP, survival, BPC3, meta-analysis
John Wiley 4& Sons, Inc. This article is protected by copyright. All rights reserved.
International Journal of Cancer
Introduction Traditional prognostic factors, such as tumor size, lymph node metastasis [1], tumor grade and hormone receptor status are the most important markers of breast cancer survival [2,3]. There is, however, growing evidence that inherited genetic variation might influence the disease prognosis and the response to treatment [4]. For example, several genetic variants in xenobiotic metabolism, which might influence the effects of cancer treatments and oxidative stress related genes recently were found to be associated with survival of breast cancer patients [5-7]. Furthermore, there are reports suggesting that single nucleotide polymorphisms (SNPs) affecting breast cancer risk might also be associated with breast cancer mortality. For example, SNPs on chromosome 20q13 were reported to be related to both breast cancer risk and breast cancer clinical outcome [8] and the G870A (rs603965) polymorphic variant in the CCND1 gene was proposed to contribute to breast cancer risk and prognosis, especially in young women [9]. In a recent study by the Breast Cancer Association Consortium (BCAC), the T-allele of TNRC9-rs3803662, which has been reported to increase breast cancer risk, was shown to be associated with poor survival independent of traditional prognostic factors [10]. With the aim of further exploring the possibility that there exist genetic components common to breast cancer risk and prognosis, we selected 35 SNPs that had been associated with breast cancer risk at a significance level of p
Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581 Heidelberg D-69120, Germany
2.
Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581 Heidelberg D-69120, Germany
3.
Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue Boston MA-02115, USA
4.
Department of Epidemiology, Harvard School of Public Health , 677 Huntington Avenue Boston MA-02115, USA
5.
Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9000 Rockville Pike Bethesda MD20892, USA
6.
Department of Ambulatory Care and Prevention, Harvard Medical School, 677 Huntington Avenue Boston MA02115, USA
7.
Divisions of Preventive Medicine and Aging, Department of Medicine, Brigham and women’s Hospital and Harvard Medical School, 677 Huntington Avenue Boston MA-02115, USA
8.
Core Genotyping Facility Frederick National Laboratory for Cancer Research, 8717 Grovemont Circle Gaithersburg MD-20877, USA
9.
Epidemiology Research Program, American Cancer Society, 250 Williams St NW Atlanta GA-30303, USA
10. Cancer Epidemiology Centre, Cancer Council Victoria, 615 St Kilda Rd VIC-3004 Melbourne, Australia 11. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health,University of Melbourne, Parkville VIC-3010 Victoria, Australia
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as an ‘Accepted Article’, doi: 10.1002/ijc.29446 This article is protected by copyright. All rights reserved.
Page 3 of 27
International Journal of Cancer
12. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, 1975 Zonal Avenue Los Angeles CA-90033, USA 13. Department of Epidemiology, University of Massachusetts-Amherst School of Public Health and Health Sciences,402 Arnold Amherst MA-01003-9304, USA 14. Cancer Research Center, Brigham and Women’s Hospital, 75 Francis Street Boston MA-02115, USA 15. Department of Medicine, Harvard Medical School, 677 Huntington Avenue Boston MA-02115, USA 16. Cancer Research Center of Hawaii, University of Hawaii, 2777 Kalakaua Avenue Honolulu HI-96813, USA 17. Department of Pathology, University of Melbourne, Parkville VIC-3010 Melbourne, Australia 18. Department of Nutrition, Harvard School of Public Health, 677 Huntington Avenue Boston MA-02115, USA 19. Department of Epidemiology Biostatistics, School of Public Health, Imperial College, South Kensington Campus London UK-SW7 2AZ, UK 20. Dipartimento di Medicina Clinica e Chirurgia, Via Sergio Pancini 5 Naples I-80131, Italy 21. Department of Surgical and Perioperative Sciences, Surgery, Umeå University, Universitetstorget 16 S-90185, Sweden 22. Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, Tromsø N-9037, Norway 23. Department of Research, Cancer Registry of Norway, Fridtjof Nansens vei 19 Oslo N-0304, Norway 24. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A Stockholm SE17177, Sweden 25. Samfundet Folkhälsan, Topeliusgatan 20 Helsinki FI-00250, Finland. 26. Escuela Andaluza de Salud Pública. Instituto de Investigación Biosanitaria ibs.GRANADA. Hospitales Universitarios de Granada/Universidad de Granada, Calle Real de Cartuja 36 Granada ES-18012, Spain 27. CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona ESP-08036, Spain 28. Department of Public Health, Section for Epidemiology, Aarhus University, Norrebrogade 44 Aarhus DK-8000, Denmark 29. INSERM, Centre for Research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women’s Health team, 16 Avenue Paul Vaillant Couturier F-94805, Villejuif, France 30. Univ Paris Sud, UMRS 1018, F-94805, Villejuif, France 31. IGR, F-94805, Villejuif, France 32. Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht Stratenum 6 NL-3508, The Netherlands
John Wiley 2& Sons, Inc. This article is protected by copyright. All rights reserved.
International Journal of Cancer
33. MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, South Kensington Campus London UK-SW7 2AZ, UK 34. Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge Addenbrooke's Hospital, Hills Rd UK-CB2 0SP, UK 35. Bureau of Epidemiologic Research, Academy of Athens, Alexandropoulos Street Athens GR-10679, Greece 36. Hellenic Health Foundation, Kaisareas Street Athens GR-11527, Greece
Corresponding author: Daniele Campa Division of Cancer Epidemiology German Cancer Research Center (DKFZ) Im Neuenheimer Feld 280 D-69120 Heidelberg, Germany Tel. +49-6221-421814, Fax +49-6221-421810, E-mail [email protected]
John Wiley 3& Sons, Inc. This article is protected by copyright. All rights reserved.
Page 4 of 27
Page 5 of 27
International Journal of Cancer
Abstract The survival of breast cancer patients is largely influenced by tumor characteristics, such as TNM stage, tumor grade and hormone receptor status. However, there is growing evidence that inherited genetic variation might affect the disease prognosis and response to treatment. Several lines of evidence suggest that alleles influencing breast cancer risk might also be associated with breast cancer survival. We examined the associations between 35 breast cancer susceptibility loci and the disease over-all survival (OS) in 10,255 breast cancer patients from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) of which 1,379 died, including 754 of breast cancer. We also conducted a meta-analysis of almost 35,000 patients and 5,000 deaths, combining results from BPC3 and the Breast Cancer Association Consortium (BCAC) and performed in silico analyses of SNPs with significant associations. In BPC3, the C allele of LSP1-rs3817198 was significantly associated with improved OS (HRper-allele=0.70; 95% CI: 0.58-0.85; Ptrend=2.84×10-4; HRheterozygotes=0.71; 95% CI: 0.55-0.92; HRhomozygotes=0.48; 95% CI: 0.31-0.76; P2DF=1.45×10-3). In silico, the C allele of LSP1-rs3817198 was predicted to increase expression of the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C). In the meta-analysis, TNRC9-rs3803662 was significantly associated with increased death hazard (HRMETA =1.09; 95% CI: 1.04-1.15; Ptrend=6.6×10-4; HRheterozygotes=0.96 95% CI: 0.90-1.03; HRhomozygotes= 1.21; 95% CI: 1.09-1.35; P2DF=1.25×10-4). In conclusion, we show that there is little overlap between the breast cancer risk single nucleotide polymorphisms (SNPs) identified so far and the SNPs associated with breast cancer prognosis, with the possible exceptions of LSP1-rs3817198 and TNRC9-rs3803662.
Novelty and impact: Our results show that the investigated risk alleles are not associated with over-all survival of breast cancer cases.
Keywords: breast cancer, SNP, survival, BPC3, meta-analysis
John Wiley 4& Sons, Inc. This article is protected by copyright. All rights reserved.
International Journal of Cancer
Introduction Traditional prognostic factors, such as tumor size, lymph node metastasis [1], tumor grade and hormone receptor status are the most important markers of breast cancer survival [2,3]. There is, however, growing evidence that inherited genetic variation might influence the disease prognosis and the response to treatment [4]. For example, several genetic variants in xenobiotic metabolism, which might influence the effects of cancer treatments and oxidative stress related genes recently were found to be associated with survival of breast cancer patients [5-7]. Furthermore, there are reports suggesting that single nucleotide polymorphisms (SNPs) affecting breast cancer risk might also be associated with breast cancer mortality. For example, SNPs on chromosome 20q13 were reported to be related to both breast cancer risk and breast cancer clinical outcome [8] and the G870A (rs603965) polymorphic variant in the CCND1 gene was proposed to contribute to breast cancer risk and prognosis, especially in young women [9]. In a recent study by the Breast Cancer Association Consortium (BCAC), the T-allele of TNRC9-rs3803662, which has been reported to increase breast cancer risk, was shown to be associated with poor survival independent of traditional prognostic factors [10]. With the aim of further exploring the possibility that there exist genetic components common to breast cancer risk and prognosis, we selected 35 SNPs that had been associated with breast cancer risk at a significance level of p
