title: An investigation of the association of genetic susceptibility risk with somatic mutation burden in breast cancer.
abstract: BACKGROUND
  Genome-wide association studies have reported nearly 100 common germline susceptibility loci associated with the risk for breast cancer. Tumour sequencing studies have characterised somatic mutation profiles in breast cancer patients. The relationship between breast cancer susceptibility loci and somatic mutation patterns in breast cancer remains largely unexplored.
  
  
  METHODS
  We used single-nucleotide polymorphism (SNP) genotyping array data and tumour exome sequencing data available from 638 breast cancer patients of European ancestry from The Cancer Genome Atlas (TCGA) project. We analysed both genotype data and, when necessary, imputed genotypes for 90 known breast cancer susceptibility loci. We performed linear regression models to investigate possible associations between germline risk variants with total somatic mutation count (TSMC), as well as specific mutation types. We examined individual SNP genotypes, as well as a multi-SNP polygenic risk score (PRS). Models were statistically adjusted for age at diagnosis, stage, oestrogen-receptor (ER) and progesterone-receptor (PR) status of breast cancer. We also performed stratified analyses by ER and PR status.
  
  
  RESULTS
  We observed a significant inverse association (P=8.75 × 10(-6); FDR=0.001) between the risk allele in rs2588809 of the gene RAD51B and TSMC across all breast cancer patients, for both ER(+) and ER(-) tumours. This association was also evident for different types of mutations. The PRS analysis for all patients, with or without rs2588809, showed a significant inverse association (P=0.01 and 0.04, respectively) with TSMC. This inverse association was significant in ER(+) patients with the ER(+)-specific PRS (P=0.02), but not among ER(-) patients for the ER(-)-specific PRS (P=0.39).
  
  
  CONCLUSIONS
  We observed an inverse association between common germline risk variants and TSMC, which, if confirmed, could provide new insights into how germline variation informs our understanding of somatic mutation patterns in breast cancer.
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA.
authors.forename: Bin
authors.initials: B
authors.lastname: Zhu
authors.affiliation: Department of Statistics, Florida State University, Tallahassee, FL 32306, USA.
authors.forename: Anwesha
authors.initials: A
authors.lastname: Mukherjee
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA.
authors.forename: Mitchell J
authors.initials: MJ
authors.lastname: Machiela
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA.
authors.forename: Lei
authors.initials: L
authors.lastname: Song
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA.
authors.forename: Xing
authors.initials: X
authors.lastname: Hua
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA.
authors.forename: Jianxin
authors.initials: J
authors.lastname: Shi
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA.
authors.forename: Montserrat
authors.initials: M
authors.lastname: Garcia-Closas
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA.
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Chanock
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA.|Department of Biostatistics and Department of Oncology, Johns Hopkins University, Baltimore, MD 21205, USA.
authors.forename: Nilanjan
authors.initials: N
authors.lastname: Chatterjee
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000235:genetics*; D004967:Estrogens; D059472:Exome; D005260:Female; D020022:Genetic Predisposition to Disease; D005838:Genotype; D018095:Germ-Line Mutation; D006801:Humans; D008875:Middle Aged; D009154:Mutation; D009363:Neoplasm Proteins / Q000032:analysis; D009376:Neoplasms, Hormone-Dependent / Q000235:genetics; D020641:Polymorphism, Single Nucleotide; D011374:Progesterone; D011960:Receptors, Estrogen / Q000032:analysis; D011980:Receptors, Progesterone / Q000032:analysis; D012306:Risk; D044465:White People / Q000235:genetics
chemical_list: D004967:Estrogens; D009363:Neoplasm Proteins; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone; D011374:Progesterone