Breast cancer is the most frequent invasive tumor diagnosed in women, showing growing incidence primarily in advanced countries. In the Czech Republic the average incidence of breast cancer in the population of women during the period 2005–2010 was 65.9 cases per 100,000, with an average mortality of 16.4. In contrast, in the years 1985–1990 the average incidence was 42.9, with average mortality 19.7 (data retrieved from The Czech National Cancer Registry) (1). As indicated, although the incidence has increased by more than one-third in the respective time periods, mainly due to improved screening programs and diagnostics, conversely, mortality has decreased due to earlier detection and more effective treatment. A similar trend is also observed in other European countries; for example, Cancer Research UK reports for the same time periods show an increase in the incidence rate by ~36%, however mortality rate decreased by almost one third (2). Although the success in breast cancer screening, treatment and familial cancer diagnosis highlight the effort of the international cancer research community, the cause of a large majority of breast cancers is unknown and the prospects for curing invasive or chemoresistant breast cancers remains relatively low.

Breast cancer has several important markers with worldwide clinical utility: the estrogen receptor, progesterone receptor and ErbB2 status. These three gene products play an important role in driving breast cancer development and anti-estrogen or anti-ErbB2 therapies are proving to be useful in treating many breast tumors. Nevertheless, successful breast cancer treatment is complicated by the fact that significant chemoresistance and metastasis can obstruct the current treatments. Thus, although therapeutic success is highly related to expression of hormonal receptors, it remains difficult to predict those individuals who will not respond to conventional therapy and/or will show metastatic progression. Significant efforts have been made to link the common oncogenic or tumor suppressor mutations in cancers to predict patient prognosis and/or tumor responses. One of the most studied genes in oncology for the last 35 years is TP53. The product of this gene, p53 protein has been named ‘guardian of the genome’. This protein mediates the response to various forms of genotoxic stress, and is involved in cell cycle regulation (3), DNA repair (4), senescence and apoptosis (3), and substantially prevents cells from malignant transformation. Its role as a tumor suppressor is reflected in its high rate of mutations in human cancers and there have been many studies evaluating the prognostic role of p53 for the outcome of different types of cancer (5). It was shown that genetic alterations leading to p53 inactivation cause abnormal pathological behavior (6) and even that mutations in p53 by dominant negative manner suppress the normal functions of the wild-type (wt) protein (7).

Considerable data indicate that mutant p53 proteins not only lose their tumor suppressive functions, but also gain new oncogenic properties that are independent of wt p53. This ‘gain of function’ received its first support when transfection of mutant p53 into TP53 null cells was shown to enhance their ability to form tumors in mice. Then, a number of studies demonstrated a wide range of oncogenic properties for p53 mutants and provided key mechanistic insights to explain these phenomena (8).

p53 is composed of three domains: i) the trans-activation domain [amino acids (AAs) 1–95], ii) the DNA binding domain (DBD) (AA 102–292), and iii) the oligomerization domain (AA 300–393) (9). The mutation rate of p53 in breast cancer is ~30% (10) and the most common p53 mutations for breast cancer, similar to other types of cancer, are missense mutations in the DBD (11). A closer look at missense mutations shows they can be separated on DNA-binding motif (DBM) mutations involving: i) AAs from L2 and L3 loops (AAs 164–194 and 237–250) and ii) mutations in LSH (loop-sheet- helix) motif (AAs 119–135 and 272–287), and non-DBM mutations including other AAs (12). Missense mutations in DBM were shown to be associated with poorer prognosis (12–15) in comparison to missense mutations in non-DBM regions. Another method to sub-divide TP53 mutations that have clinical value is the classification into ‘nondisruptive’ and ‘disruptive’ mutations, which include either truncating mutations or produce dissimilar AAs in the L2 or L3 loops (13).

In the present study, we investigated the role of TP53 mutations for hospital-based study in breast cancer and we correlated them with standard clinicopathological characteristics. Furthermore, we compared specific groups of mutations in TP53 with clinicopathological variables and patient outcome. We found that the prognostic significance of TP53 mutation status in breast cancer is dependent on the specific mutation type, and that nonsense mutations in contrast to mutations in the DNA-binding domain are the most important for estimating the prognosis of breast cancer patients.

Breast cancer represents the most common female malignancy, responsible for over 400,000 deaths yearly worldwide. This is a disease with a complex, heterogeneous genetic and biochemical background and no single genomic or metabolic condition may be considered as decisive for its formation and progression. However, a few key factors can be pointed out including TP53 tumor suppressor gene. Mutant p53 is known to affect multiple oncogenic processes during breast tumorigenesis including tumor formation and development, growth and metastasis. Due to loss of tumor suppressor function and pro-oncogenic properties of mutant p53, many studies focused on analysis of TP53 mutations as a prognostic and/or predictive biomarker (8). Mutations in the TP53 gene were found to be more frequent in high-grade, large-size, node-positive breast tumors that typically lack functional ER and PR (12). In accordance to these findings, recent analysis of ~2,000 breast tumors found the lowest frequency of TP53 mutations in luminal subtype A ~5%, followed by subtypes luminal B ~13%, Her2 ~22% and basal-like ~34% (16). The present study is compatible with those data (Table I).

To date, only limited information is available on the value of mutant p53 in breast cancer. Since p53 mutations occur mostly in ER- and PR-negative tumors, where chemotherapy usually combined with radiotherapy is applied, it is reasonable to study the impact of p53 status on these treatment regimens. In agreement with our data, several reports demonstrated that breast carcinomas expressing mutant p53 show lower sensitivity to treatment by anthracyclines (10,17,18). On the other hand, treatment by taxanes with respect to p53 status does not exhibit convincing data. Despite promising preliminary data (19,20), a recent large phase-3 clinical trial has shown similar sensitivity to taxanes in breast tumors bearing both wt and mutant p53 (21).

Increasingly more studies are focused on the localization and/or type of TP53 mutations and their impact on patient prognosis. Due to the function of p53 as a transcriptional factor, many studies focus on missense mutations located in DBM (chiefly in the L2/L3 loops) showing association with a poorer outcome compared to mutations outside these motifs (17,22,23). Similarly in a large cohort of unselected breast tumors, Olivier et al found that missense mutations in DBM are associated with poorer survival than missense mutations outside DBM (12). Notably, they also found that truncating (nonsense) mutations compared to missense mutations in DBM have fairly similar prognostic value. However, retrospective study on the prognosis and predictive values of TP53 somatic mutations in the BIG 02–98 randomized phase III trial, led by the same group, concluded that i) missense mutations are not associated with poor survival, ii) discrimination of missense mutations according to location inside DBM and outside DBM does not significantly affect patient outcome, and iii) only truncated (nonsense) mutations may serve as an independent predictor of poor DFS and OS (24). Our findings are consistent with their results showing significantly poorer effect of nonsense p53 mutations on patient outcome in comparison with both all TP53 missense mutations and missense mutations located in the DBM only. Our results are also consistent with a study by Lai et al showing significant association of nonsense mutations with breast cancer-specific mortality (HR with 95% CI: 9.43, 1.29–69.12) (25). Our data is also indirectly supported by Geisler et al showing that mutations in DBM are associated with poorer prognosis; nevertheless, approximately half of the mutations classified in this manner are represented by truncating mutations (17,22). In contrast, categorization of p53 mutations according to the location and the predicted amino acid alterations showed no significant difference in impact on patient survival between disruptive and nondisruptive p53 mutations.

In conclusion, our results in general confirm a negative prognostic value of p53 mutations. However, the limitations of assessing the predictive value of a molecular marker in treatment regimens that combine drugs with different modes of action regarding this marker should be considered. With this in mind, our study demonstrates that clinical outcome for breast cancer patients is associated with different TP53 mutation types and indicates potential utilization of TP53 mutational status to predict response to treatment by anthracyclines and radiotherapy. However, further functional studies are required to clarify the impact of particular p53 mutations on patient outcome and response to specific therapy.