In the present study, we observed a significant association between the presence of overexpression of p53 protein assessed by immunohistochemistry and p53 mutations, particularly missense mutations. However, in multivariate analysis, adjusting for age, ER/PR status, tumor stage and type of mutation, we failed to demonstrate a role for either mutations in p53 or protein overexpression in breast-cancer specific or all-cause mortality.
When compared with the IARC database, we observed a lower proportion of missense mutations (53.0% vs. 73.3%) and higher frequency of silent and frameshift/in frame mutations (19.2% vs. 4.7%; 17.2% vs. 10.5% for our study and the IARC database, respectively). For mutational screening, we selected a method based on the use of Surveyor nuclease previously shown to have a high sensitivity comparable with the ABI3100 capillary sequencer [17
]. The method has been successfully used in various applications, including detection of heteroplasmic mitochondrial DNA mutations [21
], detection of mutations in the hCDC4
gene in patients with acute myeloid leukemia [22
] and p53
mutations in exons 5–8 in patients with hematological malignancies [23
]. Due to the decreasing costs of sequencing, future studies will not be required to utilize this prescreening method because it is no longer cost effective.
Immunohistochemical staining for p53 protein provides information on the concentration and the localization of the protein. In our study, we detected p53 overexpression in 36% of tumor samples. This frequency is comparable with other studies that reported positive p53 immunostaining in 30–40% of samples [24
]. Immunohistochemical staining is widely used, however, the method is semiquantitative, subjective and results may depend on the threshold set during scoring. Moreover, a recent study [30
] reported that the results could be strongly affected by the concentration of antibody used for staining even reversing observed relationships.
However, in our study, we observed a significant association between p53
mutations and p53 protein overexpression even if various cutpoints for determination of p53 positive staining were used. Further analysis revealed that missense mutations were responsible for this association, while nonsense, silent, and frameshift/in frame mutations had no effect on immunohistochemistry results. A significant correlation between p53 overexpression and p53
mutations was observed by others [24
] although some authors report no correlation between these two parameters [33
ER/PR status is an important molecular marker of breast tumors with both prognostic and predictive functions [12
]. ER/PR positive tumors are usually better differentiated and have better prognosis and survival rate [36
]. We observed a significant association between ER/PR negative status and p53 protein overexpression, which is consistent with the results of least one [37
], but not all [37
] other studies. We assume any discrepancy across studies may be caused by the reported variability of the p53 immunohistochemistry assay [30
We observed a borderline difference in p53 protein overexpression between in situ
and invasive breast cancer, thus confirming the results of others [24
]. Some studies, however, did not find any difference [25
]. The study of Warnberg et al.
suggests that p53 expression reflects grade rather than invasiveness of the disease [39
The association of p53
mutation status with other clinical and tumor characteristics including ER/PR status has been observed in number of studies [40
]. Similar to these results, our study found women with ER/PR negative tumors had almost a 4-fold higher risk of having p53
mutations than women carrying ER/PR positive tumors.
Mutations in p53
are correlated with higher histological grade of a tumor [41
]. It has been shown that mutations occur in ductal carcinoma in situ
before the development of invasive breast cancer and that their frequency increases with higher grade of the disease [45
]. While p53
mutations are more frequent in advanced breast carcinoma [33
], we observed a slightly higher prevalence of p53 mutations among those with invasive vs. in situ
disease, but the association was not statistically significant which could be due to the substantially lower number of cases with in situ
disease in our sample.
Whether the association between p53
mutations and other clinical parameters of poor prognosis are causal (e.g., p53
mutations lead to the development of tumors with a poor prognosis), a shared etiology (an upstream event/exposure/genetic profile, but not p53
mutations, causes a woman to develop a tumor with multiple indicators of poor prognosis), or it reflects a shared behavioral trait (little or no screening for breast cancer results in the diagnosis of a tumor with multiple indicators of a poor prognosis) is not clear. Thus, it is also unclear whether statistical analyses undertaken to examine the effect of p53
mutations on mortality should be adjusted for the possible confounding effects of hormone receptor status or other clinical indicator of poor prognosis. For example, because it is possible that clinical indicators (other than p53
mutations) are on the causal pathway between the exposure (p53
mutations) and the outcome (mortality), adjustment for causal intermediates would be inappropriate and could yield biased results [48
]. For example, currently, there is no clinical evidence to rule out that these clinical parameters are not on the causal pathway linking p53
mutations and mortality. Thus the most prudent course is to report our findings both unadjusted and adjusted for these other clinical parameters. However, our strong positive findings for the association between p53
mutations and mortality are only evident when we do not adjust for other clinical parameters, such as hormone receptor status.
A number of clinical studies have analyzed the effect of p53
mutations on breast cancer survival [10
], and reported that the presence of p53
mutations was associated with poorer survival, although most are based on small case series of breast cancer patients (which yield unstable results). From these studies, only two were population-based [26
] and two were adjusted to hormone receptor status [42
]. In our large population-based sample, however, once adjustments were made for ER/PR status, there was no effect of mutations on survival. To our knowledge only two studies larger than ours have been published on the prognostic value of p53
mutations in breast cancer [11
]. In the first, a hospital-based case series of Australian women reported by Powell et al.
], 1037 breast tumors were screened for mutations in exons 4–8 by a PCR-SSCP method and 178 samples with mutations were confirmed by sequencing. While an association between p53
mutations and ER/PR negative tumors was observed, in contrast to our study, in the final multivariate analysis, based on 675 cases, both p53
mutations and ER status were significant predictors of poor survival. The second large study was recently published, Olivier et al
., and is based on a pooled analysis of 1,794 breast cancer patients with 308 mutations in p53
]. The samples originated from 10 hospitals in seven European countries and mutation detection was done in five different laboratories using three different screening methods, with the exception of one cohort where direct sequencing of cDNA was used. The methods used inevitably differ in sensitivity which may impact on the number of successfully detected mutations. They also found that in multivariate analyses based on 1,470 patients, p53
mutations interacted with PR-negative status to significantly increase the risk of breast cancer-specific death.
Unlike these previously published large studies, we found that p53
mutations did not have an independent prognostic value in breast cancer, nor was there an effect on mortality among women with hormone receptor negative tumors. We cannot find any easy explanation for these discrepancies. While the large sample size of both studies might explain why their results differed from previously published substantially smaller studies, our sample size was still relatively large (and actually larger than the final sample analyzed in the Australian study). Differences between studies might be attributed to different screening methods for p53
mutations utilized across these internationally based studies. Or, perhaps, differences in the sampling strategies used to assemble the study populations could contribute to the differences in results. For example, our study is a population-based sample, drawn from over 33 hospitals in a single geographic area in the northeastern U.S. In contrast, the two previous reported studies are based on hospital case series drawn from multiple institutions across Europe or several institutions in Australia. The results derived from hospital-based series may be influenced by the large number of referral patients with more advanced stages of disease who have sought care at these higher quality institutions; the much higher mortality rate of 20% reported in the Australian case series [42
], as compared with the 10% mortality observed among our population-based sample, is consistent with this possibility. Thus, the previously published reports are more likely to reflect the experience of very ill breast cancer patients who are referred to large hospitals, whereas our findings may be more applicable to women in the general population. Also, we have to take into account the possible effect of the stage of the disease on the frequency of p53
mutations. The tumor samples analyzed in our study were obtained from women with probably less advanced stage than that of women from hospital-based studies. p53
mutation frequency increases with advanced stages of breast cancer. Therefore, our estimate of p53
mutation frequency may be lower than in both the above-mentioned studies. We cannot rule out the possibility of misclassification of p53 mutation status in our study and its impact on breast cancer survival analysis. The tumor tissues obtained after the initial surgery may have been without p53 mutations while the tumors that reemerged later and caused the death of patients likely carried p53 mutations. For the survival analysis DNA extracted from tumors from initial surgery was used. Thus, tumors classified as p53 -mutation negative may have been incorrectly associated with poor survival. In more advanced tumor samples obtained in hospital-based studies this misclassification is less likely.
Alternatively, differences in study findings could be due to differences in the underlying genetic profile of these diverse populations. For example, a recent study found that the association between tumor p53
mutation status and breast cancer was modified by polymorphisms in MDM2 [50
]. Tumor p53
status was not associated with survival among carriers of the variant MDM2 SNP309 allele (G/T or G/G), suggesting other factors may impact the effects of p53 on survival.
Studies investigating the relationship between p53 overexpression and breast cancer survival have also produced conflicting results [10
]. Some studies, including ours, reported no relationship with breast cancer survival [38
], while other authors found a significant decrease in survival associated with p53 expression [54
In our study we analyzed p53
mutations only in exons 5–8 which is sufficient due to the fact that these exons contain >90% of the mutations reported in breast cancer [11
]. Although our sample size was smaller than in the two above-mentioned studies using p53
mutation analysis, our study has several advantages. First, unlike the study by Olivier et al.
], all the samples were processed and analyzed in one laboratory with one screening method resulting in maximal reliability of the data. Second, p53 protein overexpression was assessed and correlated with p53
mutation data in the same study in a larger sample size than previously studied. Lastly, our tumor tissue was drawn from a population-based sample of women diagnosed with a first primary breast cancer who reside in two counties in New York, rather than a case series drawn from single hospitals drawn from multiple countries in Europe or Australia.
In conclusion, in our population-based sample of women with breast cancer, p53 protein overexpression was associated with the frequency of p53 mutations in tumor tissue, but neither marker was associated with survival, once we adjusted for the effects of hormone receptor status. While p53 mutations, particularly missense mutations in DBD, may have some impact on survival, in our study they did not appear to be a major independent prognostic factor.