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Oncotarget. 2015 Nov 10;6(35):37979-94. doi: 10.18632/oncotarget.4991.

SNP-SNP interaction analysis of NF-κB signaling pathway on breast cancer survival.

Author information

1
Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, HUS, Finland.
2
Department of Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, HUS, Finland.
3
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
4
Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, ON, Canada.
5
Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
6
Department of Obstetrics and Gynecology, University of Ulm, Ulm, Germany.
7
Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
8
Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands.
9
Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
10
Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany.
11
Department of Medicine, Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, CA, USA.
12
Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
13
Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
14
Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
15
Prosserman Centre for Health Research, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, ON, Canada.
16
Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
17
Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany.
18
Molecular Epidemiology Group, German Cancer Research Center, Heidelberg, Germany.
19
Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg, Germany.
20
National Center for Tumor Diseases, University of Heidelberg, Heidelberg, Germany.
21
Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia.
22
Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia.
23
Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
24
Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark.
25
Department of Breast Surgery, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark.
26
Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany.
27
Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany.
28
German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.
29
Saarland Cancer Registry, Saarbrücken, Germany.
30
Department of Oncology - Pathology, Karolinska Institutet, Stockholm, Sweden.
31
School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland.
32
Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland.
33
Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland.
34
Vesalius Research Center (VRC), VIB, Leuven, Belgium.
35
Laboratory for Translational Genetics, Department of Oncology, University of Leuven, Leuven, Belgium.
36
Multidisciplinary Breast Center, Medical Oncology, University Hospital Leuven, Leuven, Belgium.
37
Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
38
Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
39
Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.
40
Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
41
Anatomical Pathology, The Alfred Hospital, Melbourne, Australia.
42
Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
43
Laboratory of Cancer Genetics and Tumor Biology, Cancer Research and Translational Medicine, Biocenter Oulu, University of Oulu, Oulu, Finland.
44
Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre NordLab, Oulu, Finland.
45
Department of Surgical Oncology, Leiden University Medical Center, Leiden, The Netherlands.
46
Division of Genetics and Epidemiology, Institute of Cancer Research, Sutton, UK.
47
Breakthrough Breast Cancer Research Centre, Division of Breast Cancer Research, The Institute of Cancer Research, London, UK.
48
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
49
Department of Medical Oncology, Erasmus MC Cancer Institute, AE Rotterdam, The Netherlands.
50
Sheffield Cancer Research, Department of Oncology, University of Sheffield, Sheffield, UK.
51
Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK.
52
Centre Hospitalier Universitaire de Québec Research Center, Laval University, Québec City, QC, Canada.
53
Department of Oncology, University of Helsinki and Helsinki University Central Hospital, Helsinki, HUS, Finland.

Abstract

In breast cancer, constitutive activation of NF-κB has been reported, however, the impact of genetic variation of the pathway on patient prognosis has been little studied. Furthermore, a combination of genetic variants, rather than single polymorphisms, may affect disease prognosis. Here, in an extensive dataset (n = 30,431) from the Breast Cancer Association Consortium, we investigated the association of 917 SNPs in 75 genes in the NF-κB pathway with breast cancer prognosis. We explored SNP-SNP interactions on survival using the likelihood-ratio test comparing multivariate Cox' regression models of SNP pairs without and with an interaction term. We found two interacting pairs associating with prognosis: patients simultaneously homozygous for the rare alleles of rs5996080 and rs7973914 had worse survival (HRinteraction 6.98, 95% CI=3.3-14.4, P=1.42E-07), and patients carrying at least one rare allele for rs17243893 and rs57890595 had better survival (HRinteraction 0.51, 95% CI=0.3-0.6, P = 2.19E-05). Based on in silico functional analyses and literature, we speculate that the rs5996080 and rs7973914 loci may affect the BAFFR and TNFR1/TNFR3 receptors and breast cancer survival, possibly by disturbing both the canonical and non-canonical NF-κB pathways or their dynamics, whereas, rs17243893-rs57890595 interaction on survival may be mediated through TRAF2-TRAIL-R4 interplay. These results warrant further validation and functional analyses.

KEYWORDS:

NF-κB pathway; SNP-SNP interaction; breast cancer; survival analysis

PMID:
26317411
PMCID:
PMC4741978
DOI:
10.18632/oncotarget.4991
[Indexed for MEDLINE]
Free PMC Article

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