Household income is associated with the p53 mutation frequency in human breast tumors

PLoS One. 2013;8(3):e57361. doi: 10.1371/journal.pone.0057361. Epub 2013 Mar 1.

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.

Publication types

  • Research Support, N.I.H., Intramural

MeSH terms

  • Adult
  • Aged
  • Baltimore / epidemiology
  • Black People
  • Body Mass Index
  • Breast Neoplasms / ethnology
  • Breast Neoplasms / genetics*
  • Breast Neoplasms / mortality
  • Breast Neoplasms / pathology
  • Educational Status
  • Female
  • Humans
  • Income / statistics & numerical data*
  • Middle Aged
  • Mutation Rate*
  • Receptors, Estrogen / deficiency
  • Receptors, Estrogen / genetics
  • Regression Analysis
  • Risk Factors
  • Smoking
  • Survival Analysis
  • Tumor Suppressor Protein p53 / genetics*
  • White People

Substances

  • Receptors, Estrogen
  • Tumor Suppressor Protein p53