FAK overexpression and p53 mutations are highly correlated in human breast cancer

Focal Adhesion Kinase (FAK) is overexpressed in a number of tumors, including breast cancer. Another marker of breast cancer tumorigenesis is the tumor suppressor gene p53 that is frequently mutated in breast cancer. In the present study, our aim was to find a correlation between FAK overexpression, p53 expression and mutation status in a population-based series of invasive breast cancer tumors from the Carolina Breast Cancer Study. Immunohistochemical analyses of 622 breast cancer tumors revealed that expression of FAK and p53 were highly correlated (P = 0.0002) and FAK positive tumors were 1.8 times more likely to be p53 positive compared to FAK negative tumors [odds ratio (OR) = 1.8; 95% Confidence Interval (CI) 1.2 – 2.8, adjusted for age, race and stage at diagnosis]. Tumors positive for p53 expression showed higher intensity of FAK staining (P<0.0001) and higher percent of FAK positive staining (P<0.0005). From the same study, we evaluated 596 breast tumors for mutations in the p53 gene, using SSCP (single strand conformational polymorphism) and sequencing. Statistical analyses were performed to determine the correlation between p53 mutation status and FAK expression in these tumors. We found that FAK expression and p53 mutation were positively correlated (P<0.0001) and FAK positive tumors were 2.5 times more likely to be p53 mutation positive compared to FAK negative tumors [adjusted OR = 2.5, 95% CI 1.6–3.9]. This is the first analysis demonstrating a high correlation between FAK expression and p53 mutations in a population-based series of breast tumors

Associations between Polycyclic Aromatic Hydrocarbon–Related Exposures and p53 Mutations in Breast Tumors

Background: Previous studies have suggested that polycyclic aromatic hydrocarbons (PAHs) may be associated with breast cancer. However, the carcinogenicity of PAHs on the human breast remains unclear. Certain carcinogens may be associated with specific mutation patterns in the p53 tumor suppressor gene, thereby contributing information about disease etiology. Objectives: We hypothesized that associations of PAH-related exposures with breast cancer would differ according to tumor p53 mutation status, effect, type, and number. Methods: We examined this possibility in a population-based case–control study using polytomous logistic regression. As previously reported, 151 p53 mutations among 859 tumors were identified using Surveyor nuclease and confirmed by sequencing. Results: We found that participants with p53 mutations were less likely to be exposed to PAHs (assessed by smoking status in 859 cases and 1,556 controls, grilled/smoked meat intake in 822 cases and 1,475 controls, and PAH–DNA adducts in peripheral mononuclear cells in 487 cases and 941 controls) than participants without p53 mutations. For example, active and passive smoking was associated with p53 mutation–negative [odds ratio (OR) = 1.55; 95% confidence interval (CI), 1.11–2.15] but not p53 mutation–positive (OR = 0.77; 95% CI, 0.43–1.38) cancer (ratio of the ORs = 0.50, p < 0.05). However, frameshift mutations, mutation number, G:C→A:T transitions at CpG sites, and insertions/deletions were consistently elevated among exposed subjects. Conclusions: These findings suggest that PAHs may be associated with specific breast tumor p53 mutation subgroups rather than with overall p53 mutations and may also be related to breast cancer through mechanisms other than p53 mutation

Associations between Polycyclic Aromatic Hydrocarbon–Related Exposures and p53 Mutations in Breast Tumors

BackgroundPrevious studies have suggested that polycyclic aromatic hydrocarbons (PAHs) may be associated with breast cancer. However, the carcinogenicity of PAHs on the human breast remains unclear. Certain carcinogens may be associated with specific mutation patterns in the p53 tumor suppressor gene, thereby contributing information about disease etiology.ObjectivesWe hypothesized that associations of PAH-related exposures with breast cancer would differ according to tumor p53 mutation status, effect, type, and number.MethodsWe examined this possibility in a population-based case–control study using polytomous logistic regression. As previously reported, 151 p53 mutations among 859 tumors were identified using Surveyor nuclease and confirmed by sequencing.ResultsWe found that participants with p53 mutations were less likely to be exposed to PAHs (assessed by smoking status in 859 cases and 1,556 controls, grilled/smoked meat intake in 822 cases and 1,475 controls, and PAH–DNA adducts in peripheral mononuclear cells in 487 cases and 941 controls) than participants without p53 mutations. For example, active and passive smoking was associated with p53 mutation–negative [odds ratio (OR) = 1.55; 95% confidence interval (CI), 1.11–2.15] but not p53 mutation–positive (OR = 0.77; 95% CI, 0.43–1.38) cancer (ratio of the ORs = 0.50, p < 0.05). However, frameshift mutations, mutation number, G:C→A:T transitions at CpG sites, and insertions/deletions were consistently elevated among exposed subjects.ConclusionsThese findings suggest that PAHs may be associated with specific breast tumor p53 mutation subgroups rather than with overall p53 mutations and may also be related to breast cancer through mechanisms other than p53 mutation

Associations between Polycyclic Aromatic Hydrocarbon-Related Exposures and \u3cem\u3ep53\u3c/em\u3e Mutations in Breast Tumors

BACKGROUND: Previous studies have suggested that polycyclic aromatic hydrocarbons (PAHs) may be associated with breast cancer. However, the carcinogenicity of PAHs on the human breast remains unclear. Certain carcinogens may be associated with specific mutation patterns in the p53 tumor suppressor gene, thereby contributing information about disease etiology. OBJECTIVES: We hypothesized that associations of PAH-related exposures with breast cancer would differ according to tumor p53 mutation status, effect, type, and number. METHODS: We examined this possibility in a population-based case–control study using polytomous logistic regression. As previously reported, 151 p53 mutations among 859 tumors were identified using Surveyor nuclease and confirmed by sequencing. RESULTS: We found that participants with p53 mutations were less likely to be exposed to PAHs (assessed by smoking status in 859 cases and 1,556 controls, grilled/smoked meat intake in 822 cases and 1,475 controls, and PAH–DNA adducts in peripheral mononuclear cells in 487 cases and 941 controls) than participants without p53 mutations. For example, active and passive smoking was associated with p53 mutation–negative [odds ratio (OR) = 1.55; 95% confidence interval (CI), 1.11–2.15] but not p53 mutation–positive (OR = 0.77; 95% CI, 0.43–1.38) cancer (ratio of the ORs = 0.50, p \u3c 0.05). However, frameshift mutations, mutation number, G:C→A:T transitions at CpG sites, and insertions/deletions were consistently elevated among exposed subjects. CONCLUSIONS: These findings suggest that PAHs may be associated with specific breast tumor p53 mutation subgroups rather than with overall p53 mutations and may also be related to breast cancer through mechanisms other than p53 mutation

Chemotherapy response and recurrence-free survival in neoadjuvant breast cancer depends on biomarker profiles: results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657).

Neoadjuvant chemotherapy for breast cancer allows individual tumor response to be assessed depending on molecular subtype, and to judge the impact of response to therapy on recurrence-free survival (RFS). The multicenter I-SPY 1 TRIAL evaluated patients with ≥ 3 cm tumors by using early imaging and molecular signatures, with outcomes of pathologic complete response (pCR) and RFS. The current analysis was performed using data from patients who had molecular profiles and did not receive trastuzumab. The various molecular classifiers tested were highly correlated. Categorization of breast cancer by molecular signatures enhanced the ability of pCR to predict improvement in RFS compared to the population as a whole. In multivariate analysis, the molecular signatures that added to the ability of HR and HER2 receptors, clinical stage, and pCR in predicting RFS included 70-gene signature, wound healing signature, p53 mutation signature, and PAM50 risk of recurrence. The low risk signatures were associated with significantly better prognosis, and also identified additional patients with a good prognosis within the no pCR group, primarily in the hormone receptor positive, HER-2 negative subgroup. The I-SPY 1 population is enriched for tumors with a poor prognosis but is still heterogeneous in terms of rates of pCR and RFS. The ability of pCR to predict RFS is better by subset than it is for the whole group. Molecular markers improve prediction of RFS by identifying additional patients with excellent prognosis within the no pCR group

Chemotherapy response and recurrence-free survival in neoadjuvant breast cancer depends on biomarker profiles: results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657)

Neoadjuvant chemotherapy for breast cancer allows individual tumor response to be assessed depending on molecular subtype, and to judge the impact of response to therapy on recurrence-free survival (RFS). The multicenter I-SPY 1 TRIAL evaluated patients with ≥3 cm tumors by using early imaging and molecular signatures, with outcomes of pathologic complete response (pCR) and RFS. The current analysis was performed using data from patients who had molecular profiles and did not receive trastuzumab. The various molecular classifiers tested were highly correlated. Categorization of breast cancer by molecular signatures enhanced the ability of pCR to predict improvement in RFS compared to the population as a whole. In multivariate analysis, the molecular signatures that added to the ability of HR and HER2 receptors, clinical stage, and pCR in predicting RFS included 70-gene signature, wound healing signature, p53 mutation signature, and PAM50 risk of recurrence. The low risk signatures were associated with significantly better prognosis, and also identified additional patients with a good prognosis within the no pCR group, primarily in the hormone receptor positive, HER-2 negative subgroup. The I-SPY 1 population is enriched for tumors with a poor prognosis but is still heterogeneous in terms of rates of pCR and RFS. The ability of pCR to predict RFS is better by subset than it is for the whole group. Molecular markers improve prediction of RFS by identifying additional patients with excellent prognosis within the no pCR group