title: Household income is associated with the p53 mutation frequency in human breast tumors.
abstract: BACKGROUND
  A study from Scotland reported that the p53 mutation frequency in breast tumors is associated with socio-economic deprivation.
  
  
  METHODS
  We analyzed the association of the tumor p53 mutational status with tumor characteristics, education, and self-reported annual household income (HI) among 173 breast cancer patients from the greater Baltimore area, United States.
  
  
  RESULTS
  p53 mutational frequency was significantly associated with HI. Patients with < $15,000 HI had the highest p53 mutation frequency (21%), followed by the income group between $15,000 and $60,000 (18%), while those above $60,000 HI had the fewest mutations (5%). When dichotomized at $60,000, 26 out of 135 patients in the low income category had acquired a p53 mutation, while only 2 out of 38 with a high income carried a mutation (P < 0.05). In the adjusted logistic regression analysis with 3 income categories (trend test), the association between HI and p53 mutational status was independent of tumor characteristics, age, race/ethnicity, tobacco smoking and body mass. Further analyses revealed that HI may impact the p53 mutational frequency preferentially in patients who develop an estrogen receptor (ER)-negative disease. Within this group, 42% of the low income patients (< $15,000 HI) carried a mutation, followed by the middle income group (21%), while those above $60,000 HI did not carry mutations (Ptrend < 0.05).
  
  
  CONCLUSIONS
  HI is associated with the p53 mutational frequency in patients who develop an ER-negative disease. Furthermore, high income patients may acquire fewer p53 mutations than other patients, suggesting that lifetime exposures associated with socio-economic status may impact breast cancer biology.
authors.affiliation: Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: Adrienne M
authors.initials: AM
authors.lastname: Starks
authors.forename: Damali N
authors.initials: DN
authors.lastname: Martin
authors.forename: Tiffany H
authors.initials: TH
authors.lastname: Dorsey
authors.forename: Brenda J
authors.initials: BJ
authors.lastname: Boersma
authors.forename: Tiffany A
authors.initials: TA
authors.lastname: Wallace
authors.forename: Stefan
authors.initials: S
authors.lastname: Ambs
mesh_terms: D000328:Adult; D000368:Aged; D015142:Baltimore / Q000453:epidemiology; D044383:Black People; D015992:Body Mass Index; D001943:Breast Neoplasms / Q000208:ethnology / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D004522:Educational Status; D005260:Female; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D008875:Middle Aged; D059645:Mutation Rate; D011960:Receptors, Estrogen / Q000172:deficiency / Q000235:genetics; D012044:Regression Analysis; D012307:Risk Factors; D012907:Smoking; D016019:Survival Analysis; D016159:Tumor Suppressor Protein p53 / Q000235:genetics*; D044465:White People; D001741:Black or African American
chemical_list: D011960:Receptors, Estrogen; D016159:Tumor Suppressor Protein p53