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

Starks AM, Martin DN, Dorsey TH, Boersma BJ, Wallace TA, Ambs S - PLoS ONE (2013)

Bottom Line: 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).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.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America.

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.

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Related in: MedlinePlus

Kaplan-Meier survival curves for 5-year breast cancer-specific survival by annual household income (HI) of the patients.Log-rank test: P < 0.05. Within this follow-up period, 38 of the 173 patients (22%) died from breast cancer.
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pone-0057361-g001: Kaplan-Meier survival curves for 5-year breast cancer-specific survival by annual household income (HI) of the patients.Log-rank test: P < 0.05. Within this follow-up period, 38 of the 173 patients (22%) died from breast cancer.

Mentions: In an exploratory approach, we also examined the association of HI and the tumor p53 status with disease-specific survival using Cox regression modeling. Both HI (hazard ratio (HR)  =  0.64, 95% CI: 0.44 to 0.94 for dying from breast cancer with increasing HI) and the tumor p53 mutation status (HR  =  1.66, 95% CI: 1.02 to 2.7 for a p53 mutation carrier vs. non-carrier) were significantly associated with survival in the univariable analysis, but not education (HR  =  0.76, 95% CI: 0.45 to 1.26). Figure 1 shows a Kaplan-Meier plot of the relationship between HI and breast cancer-specific survival. In an analysis that included both HI and tumor p53 mutation status as covariates, only HI was a significant predictor of survival. The inclusion of other covariates to the model that were associated with survival in the univariable analysis (age, TNM stage, ER status in addition to HI and p53 mutation status) yielded a borderline significant association for both HI (HR  =  0.62, 95% CI: 0.38 to 1.02 for dying from breast cancer with increasing HI) and tumor p53 status (HR  =  1.95, 95% CI: 0.93 to 4.1 for a p53 mutation carrier vs. non-carrier) with disease-specific survival, suggesting that these two variables are likely independent predictors of survival in larger studies. Additional analyses did not find that the two variables may affect survival through an interaction.


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

Starks AM, Martin DN, Dorsey TH, Boersma BJ, Wallace TA, Ambs S - PLoS ONE (2013)

Kaplan-Meier survival curves for 5-year breast cancer-specific survival by annual household income (HI) of the patients.Log-rank test: P < 0.05. Within this follow-up period, 38 of the 173 patients (22%) died from breast cancer.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3585937&req=5

pone-0057361-g001: Kaplan-Meier survival curves for 5-year breast cancer-specific survival by annual household income (HI) of the patients.Log-rank test: P < 0.05. Within this follow-up period, 38 of the 173 patients (22%) died from breast cancer.
Mentions: In an exploratory approach, we also examined the association of HI and the tumor p53 status with disease-specific survival using Cox regression modeling. Both HI (hazard ratio (HR)  =  0.64, 95% CI: 0.44 to 0.94 for dying from breast cancer with increasing HI) and the tumor p53 mutation status (HR  =  1.66, 95% CI: 1.02 to 2.7 for a p53 mutation carrier vs. non-carrier) were significantly associated with survival in the univariable analysis, but not education (HR  =  0.76, 95% CI: 0.45 to 1.26). Figure 1 shows a Kaplan-Meier plot of the relationship between HI and breast cancer-specific survival. In an analysis that included both HI and tumor p53 mutation status as covariates, only HI was a significant predictor of survival. The inclusion of other covariates to the model that were associated with survival in the univariable analysis (age, TNM stage, ER status in addition to HI and p53 mutation status) yielded a borderline significant association for both HI (HR  =  0.62, 95% CI: 0.38 to 1.02 for dying from breast cancer with increasing HI) and tumor p53 status (HR  =  1.95, 95% CI: 0.93 to 4.1 for a p53 mutation carrier vs. non-carrier) with disease-specific survival, suggesting that these two variables are likely independent predictors of survival in larger studies. Additional analyses did not find that the two variables may affect survival through an interaction.

Bottom Line: 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).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.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America.

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.

Show MeSH
Related in: MedlinePlus