Introduction
The p53 pathway is ubiquitously abnormal in human cancers, either through mutation of the
p53 gene or via modification of p53 function by interaction with oncogenic cellular or viral proteins [
1,
2]. Somatic
p53 gene mutations, found in about 25% of breast cancers, are associated with poor prognosis [
3,
4]. Patients bearing mutant
p53 breast cancer have resistance to several chemotherapy agents but may be more sensitive to taxanes, at least in the neoadjuvant setting [
5‐
10]. However, the uncertainties around the relationships between
p53 mutation, therapeutic response and outcome in breast cancer suggest that additional factors may be involved.
The human
p53 gene expresses at least nine different p53 protein isoforms containing different domains of the p53 protein (p53, p53β, p53γ, Δ133p53α, Δ133p53β, Δ133p53γ, Δ40p53α, Δ40p53β and Δ40p53γ) as a result of multiple splicing, alternative initiation of translation and internal promoter usage [
11‐
13]. The p53 isoforms are differentially expressed in normal human tissues, with normal breast tissue expressing p53, p53β and p53γ [
13]. Abnormal expression of p53 isoforms has been identified in several human cancer types [
13‐
19]. We have previously reported that p53 isoforms such as p53β can interact with p53 and modulate p53 tumour suppressor activity [
13,
19,
20]. Taken together, these findings suggest that the p53 isoforms may play a role in human cancers.
In this report, expression of the p53β and p53γ isoforms is examined in relation to clinical and pathological markers, p53 mutation and disease outcome in a cohort of 127 randomly selected primary breast tumours. The patient group expressing the p53γ isoform had abrogation of the poor prognostic effect associated with p53 mutation, with a low risk of cancer recurrence and a survival rate as good as that of the patient group bearing wild-type p53 breast cancer. Conversely, patients expressing only mutant p53, without p53γ isoform expression, had a particularly poor prognosis. The p53γ isoform may explain the inconsistent relationship between p53 mutation and breast cancer in the literature.
Materials and methods
Clinical samples
Previously untreated operable primary breast cancer in 127 Caucasian women (age range, 32 to 89 years; median age, 60 years) with sufficient tumour tissue surplus for diagnostic requirements and complete clinical and pathological data was analysed. Tumour tissues were macrodissected by a specialist breast pathologist and snap-frozen in liquid nitrogen prior to storage at -80°C. Samples were examined following Local Research Ethics Committee approval under delegated authority from the Tayside Tissue Bank. The Tayside Tissue Bank has received ethical approval for its activities (REC Reference 07/S1402/90).
Reverse transcription-polymerase chain reaction analysis
Approximately 10 mg of tumour tissue (>40% of tumour cells) was homogenised in 750 μL of QIAzol lysis reagent (Qiagen Ltd, Crawley, West Sussex, UK), and total RNA was extracted (Qiagen). RNA quality was assessed using the BioAnalyzer 2100™ (Agilent Technologies, Palo Alto, CA, USA) prior to reverse transcription-polymerase chain reaction (RT-PCR) analysis, and all samples with a 28S:18S ratio <1.2 were discarded. RT was performed with 0.5 μg of total RNA using the Cloned AMV Reverse Transcription Kit (Invitrogen, Paisley, UK), and cDNA quality was confirmed by PCR amplification of actin. Samples for which actin could not be amplified after 30 cycles of PCR were discarded. p53 isoform cDNA was amplified by two consecutive PCR assays (nested PCR) of 30 cycles each, and the PCR primers used were specific for each of the p53 isoforms analysed. The different primers used and their corresponding sequences are indicated in Table S1 in Additional file
1. To determine p53γ mutation status, the entire open reading frame of the isoform was sequenced using the Sanger method (BigDye Terminator, ABI 3730 Genetic Analyser; (Applied Biosystems, Warrington, UK) with the primers JWF (5'-AGCCAAGTCTGTGACTTGCA) and MP9ER (5'-TCTCCCAGGACAGCACAAACACG).
p53mutation analysis
The
p53 mutation status was determined using 100 ng of genomic DNA extracted from homogenised frozen tissues as described previously using the AmpliChip p53 Test (Roche Diagnostics, Pleasanton, CA, USA) [
21].
Tumour grade, oestrogen receptor, progesterone receptor and HER2 status
Immunohistochemical staining was carried out on 4-μm sections of formalin-fixed, paraffin-embedded tumours with the mouse monoclonal anti-oestrogen receptor α (ER) antibody 6F11 (Novocastra Laboratories Ltd, Newcastle upon Tyne, UK), progesterone receptor (PR) antibody clone 16 (Novocastra Laboratories Ltd) and mouse monoclonal anti-HER2 antibody CB11 (Novocastra Laboratories Ltd). Additional analyses were performed according to histological tumour grade (graded by a specialist consultant breast pathologist); pathological tumour size (pT1, tumours <2 cm; pT2 and pT3 cancers, tumours ≥2 cm) [
22]. ER status (ER negative 0 to 3 versus ER positive 4 to 18) was determined using the quickscore method [
23]. Briefly, immunoreactivity scored semiquantitatively for both the intensity and the proportion of cells staining. Intensity was given scores from 0 to 3 (no staining = 0, light staining = 1, moderate staining = 2 and strong staining = 3) and proportion was given scores from 1 to 6 (0% to 4% = 1, 5% to 20% = 2, 21% to 40% = 3, 41% to 60% = 4, 61% to 80% = 5 and 81% to 100% = 6). The two scores were then multiplied to obtain the final result of 0 to 18. Human epidermal growth factor receptor 2 (HER2) scoring was performed as previously described [
24].
Statistical analysis
The primary outcomes in this study were breast cancer-specific overall survival (abbreviated to overall survival) and breast cancer-specific disease-free survival (abbreviated to disease-free survival or cancer recurrence throughout the text), and accordingly, non-breast cancer deaths were censored at the time of death (that is, at the time of death, the women were considered to have survived breast cancer but died as a result of other causes). Statistical analysis was performed using Minitab version 15.1.0.0 statistical software (Minitab Inc., PA 16801-3008, USA) for χ2, two-sided Fisher's exact test and Kaplan-Meier analyses. These univariate analyses test for associations between variables in a pairwise manner (for example, A versus B), but they do so without adjusting for influences exerted by other associated variables (for example, both A and B may be associated with confounding variables C, D and E, casting doubt on the validity of the relationship between A and B).
To clarify the univariate analyses and adjust for possible confounding variables, the selected variables were interrogated using the multivariate methods of binary logistic regression (BLR) with associated odds ratios (OR) and the Cox proportional hazards regression model (CR) with associated risk ratios (RR), both utilising the backwards stepwise elimination method. (For more detailed methods, read the "method" section in Additional file
2.)
In the tables of results for these multivariate analyses, the β value is a regression coefficient that indicates the strength of association between the predictor and response variables, where a large β indicates a strong association. A positive β indicates a positive association between the predictor and response variables, whilst a negative β indicates a negative association.
The OR is used to assess the risk of a particular outcome if a certain factor (or exposure) is present, indicating how much more likely it is that someone who is exposed to the factor under study will develop the outcome as compared to someone who is not exposed. If the odds are greater than 1, then the event is more likely to happen than not, whilst if the odds are less than 1, then the event is less likely. One 'reads' the risk ratios in precisely the same way.
The results of the univariate and multivariate analyses were consistent, and for clarity and brevity only the results of BLR, CR and Kaplan-Meier analyses are presented. Throughout the analyses the null hypothesis was rejected at an α level of 10% (P < 0.10), and observations considered to be marginal (that is, worthy of further analysis) for an α level between 5% and 10% (0.05 ≤ P ≤ 0.10) and significant at 5% (P < 0.05). The P value represents the probability of error that is involved in accepting our observed result as valid. For example, P = 0.05 indicates that there is a 5% probability that the relation between the variables found in the sample occurred by chance.
Discussion
The p53 network is thought to be ubiquitously altered in human cancers, either through mutation of the
p53 gene or through inactivation of p53 protein [
1]. In breast cancer, it has been difficult to link p53 mutation status to therapeutic response and clinical outcome, suggesting that additional factors may affect the p53 network. We previously reported that the
p53 gene expresses at least nine p53 protein isoforms in normal human tissue, including p53β and p53γ, which are differentially expressed in breast cancer as in other types of cancer [
13‐
19]. In this study, we report the analysis of expression of p53β and p53γ in relation to clinical and pathological markers and disease outcome in a cohort of 127 randomly selected primary breast tumours.
In our cohort, p53β expression was detected in 36% of the primary breast tumours and was associated with ER expression but not with disease outcome. p53γ expression was detected in 37% of primary breast tumours and was associated with p53 gene mutation. The potentially clinically significant finding was that p53γ expression allowed discrimination between two subpopulations of patients bearing mutant p53 tumours: (1) patients bearing mutant p53 cancer and expressing p53γ who had disease-free survival and overall survival as good as patients with wild-type p53 and (2) patients bearing mutant p53 tumours without detectable p53γ isoform expression who had a particularly poor prognosis. Importantly, there was no significant difference in the ER status of patients bearing p53 mutations between the p53γ-positive and p53γ-negative cohorts (P = 0.254, Fisher's exact test). Therefore, the better outcomes of the breast cancer patients expressing p53γ and mutant p53 are not due to endocrine therapy in ER-positive cancers.
We have chosen to perform this analysis without previously classifying tumours according to immunohistochemical phenotype (luminal (A and B), HER2, basal (triple-negative: ER-, PR-, HER-) and unclassified) because, in our cohort, the low number of tumours in each immunohistochemical phenotype did not allow us to perform CR and Kaplan-Meier log-rank analyses to investigate p53 isoform expression in relation to clinical outcome. Indeed, among the 85 luminal tumours (ER+, PR+ and HER-), only 10 tumours expressed mutant p53. This low number of p53 mutations did not allow us to find a significant statistical association between p53 isoform expression and p53 mutation. By contrast, regarding patients who were not in the luminal group (basal and unclassified tumours), 13 of 16 tumours with a p53 mutation expressed p53γ (81%), whilst 14 of 18 tumours with wild-type p53 did not express p53γ (78%). This finding confirms that p53γ expression is associated with p53 mutation status. Regarding patients who were in the basal group (triple-negative), there was a significant positive association between p53γ expression and p53 mutation, with 6 of 7 tumours with a p53 mutation expressing p53γ (86%), whilst 9 of 10 tumours with wild-type p53 did not express p53γ (90%). The result in nonluminal patients is consistent with the results obtained without classifying tumours according to immunohistochemical phenotype. Of note, the lack of association in luminal patients between p53γ expression and p53 mutation is probably due to the low number of p53 mutations in this breast cancer subtype.
By sequencing p53γ cDNA in breast tumours expressing mutant p53, we noted that p53γ cDNA contained the same mutation as the p53 gene, indicating that p53γ was expressed by the tumour cells and not by cells from the stroma. Therefore, this finding suggests either that the mutant p53γ isoform has an intrinsic activity abrogating the poor prognosis associated with p53 mutation or that p53γ is just an inactive marker of better outcomes for mutant p53 breast cancer patients. Future investigations will seek to determine the biological and biochemical activities of mutant p53γ and its interplay with mutant p53 in tumour cells.
We did not differentiate between the different categories of p53 mutations (nonsense mutations, missense mutations, 'DNA-contact' mutations or 'conformational' mutations), as there were not enough cases in each p53 mutation category for confident statistical analysis. However, in larger breast cancer cohorts, it would be interesting to take the different p53 mutation categories and molecular subtypes of breast cancer into account to refine the statistical analysis.
Currently, p53γ expression can be specifically detected only by PCR. From a clinical utility perspective, it would be useful to analyse p53β and p53γ expression by using immunohistochemistry. The mouse monoclonal antibodies DO-1 and DO-7 recognise p53, p53β and p53γ, but not the other p53 isoforms. The rabbit or sheep polyclonal p53 antibodies (CM1 and Sapu, respectively) raised against recombinant full-length human p53 protein recognize all p53 isoforms, while the KJC8 antibody recognises specifically all p53β isoforms (that is, p53β, Δ40p53β and Δ133p53β). However, we have been unable to stain paraffin-embedded sections using the KJC8 antibody. Since p53β and p53γ can be localised in both the nucleus and the cytoplasm, we have attempted to determine by performing immunohistochemistry on paraffin-embedded breast tumour sections using DO-1 or CM1 p53 antibodies whether p53β or p53γ expression is associated with cytoplasmic or nuclear staining. There was no significant association between p53 cytoplasmic or nuclear staining by DO-1 or CM1 and p53β or p53γ expression. Pending the generation of isoform-specific antibodies, p53 immunostaining on tumour sections should be interpreted with caution and should be complemented by PCR analysis to determine p53 isoform mRNA expression in tumours.
Treatment influences were not identified in this analysis, although no taxane, cisplatin or trastuzumab therapy was administered to the patients studied, and anthracycline-based chemotherapy was the standard agent used during the sample accrual period.
p53 mutation may be associated with resistance to several chemotherapy agents; but
p53 mutant breast cancer may be more sensitive to taxanes, at least in the neoadjuvant setting [
5‐
10], and the predictive value of
p53 mutational status in breast cancer remains controversial [
3,
4]. The influence of the p53γ isoform in the setting of clinical trials such as the neoadjuvant European Organisation for Research and Treatment of Cancer (EORTC) 10994 Trial, which is testing the association between
p53 mutation and taxane versus anthracycline therapy, merits consideration and would provide potential validation of the association of the p53γ isoform with
p53 mutation and prognosis in the setting of a randomized, controlled trial. In addition, since mutant
p53 cancers are generally of basal or triple-negative phenotype, the influence of the p53 isoforms on platinum therapies and poly(ADP-ribose) polymerase inhibitors in appropriate clinical trials would be of interest. Meanwhile, the apparently dominant effects of the p53γ isoform influencing the p53 network may provide an explanation for the conflicting literature regarding the clinical associations between mutant
p53 and breast cancer and issue a warning that clinical decisions made on the basis of
p53 mutation status alone may need to be approached with caution.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
JCB, DPL and AT conceived and designed the study. CP and LJ conducted the pathological review. AD, MK, KF, MA and ML performed the experiments. MK, LB, PQ, ACP, JCB and AT contributed to data analysis and interpretation. LB, MK, KF, JCB and AT contributed to the writing of the report.