Skip to main content
PLOS ONE logoLink to PLOS ONE
. 2012 Jun 29;7(6):e39655. doi: 10.1371/journal.pone.0039655

Value of TP53 Status for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer: A Meta-Analysis

Min-Bin Chen 1,#, Ya-Qun Zhu 2,#, Jun-Ying Xu 3, Li-Qiang Wang 1, Chao-Ying Liu 3, Zhang-Yi Ji 1, Pei-Hua Lu 4,*
Editor: Sharon A Glynn5
PMCID: PMC3387248  PMID: 22768103

Abstract

Background

Numerous studies have yielded inconclusive results regarding the relationship between tumor suppressor protein TP53 overexpression and/or TP53 gene mutations and the response to neoadjuvant chemotherapy in patients with breast cancer. The purpose of the current study was therefore to evaluate the relationship between TP53 status and response to chemotherapy in breast cancer.

Methods and Findings

A total of 26 previously published eligible studies including 3,476 cases were identified and included in this meta-analysis. TP53 status (over expression of TP53 protein and/or TP53 gene mutations) was associated with good response in breast cancer patients who received neoadjuvant chemotherapy (total objective response: risk ratio [RR]  = 1.20, 95% confidence interval [CI]  = 1.09–1.33, p<0.001; pathological objective response: RR = 1.37, 95% CI = 1.20–1.57, p<0.01; total complete response: RR = 1.33, 95% CI = 1.15–1.53, p<0.001; pathological complete response: RR = 1.45, 95% CI = 1.25–1.68, p<0.001). In further stratified analyses, this association also existed among the studies using anthracycline-based neoadjuvant chemotherapy, and the association between response and the presence of gene alterations was stronger than that between response and immunohistochemistry positivity.

Conclusion

The results of the present meta-analysis suggest that TP53 status is a predictive factor for response in breast cancer patients undergoing neoadjuvant chemotherapy. Further larger and well-designed prospective studies are required to evaluate the predictive role of TP53 status in clinical practice.

Introduction

Neoadjuvant chemotherapy, also known as primary or induction chemotherapy, refers to chemotherapy administered before locoregional treatment, such as surgery and/or irradiation. Neoadjuvant chemotherapy has become the standard treatment for the management of locally advanced breast cancer, primarily because of its ability to downsize large tumors. Neoadjuvant chemotherapy is increasingly used for the treatment of early-stage breast cancer. However, despite generally high response rates, a small proportion of patients fail to respond to neoadjuvant chemotherapy, or even progress during therapy. Recent evidence suggests that biological markers may be useful for identifying those patients who would benefit from neoadjuvant chemotherapy [1].

The TP53 gene is a prime candidate for predicting the response of tumors to classic chemotherapy [2]. It is a master gene in the stress response that plays a critical role in cancer development. TP53 is the most frequently mutated gene in human cancer, with mutations occurring in at least 50% of human cancers [1]. It mediates checkpoint or stress responses to several insults and suppresses tumor formation through several mechanisms, including apoptosis, senescence, and autophagy [3]. Experimental evidence suggests a key role for TP53 in apoptosis in response to genotoxic agents [4], [5].

The use of TP53 status as a biological marker to predict the response of breast cancer to neoadjuvant chemotherapy, however, is disappointing, and the findings to date have shown conficting results [6][10]. Several studies [6], [9][11] found that patients with TP53 mutations often had better responses to therapy than those with normal TP53 status. Other studies [7], [8], [12], [13], however, evaluated TP53 status in breast cancer patients and drew different conclusions. The relevance of this gene to clinical therapy thus remains unknown. We therefore performed a meta-analysis of the value of TP53 status for predicting response to neoadjuvant chemotherapy in breast cancer.

Materials and Methods

Publication Search

PubMed, Embase, and Web of Science databases were searched (up to December 20, 2011) using the search terms: ‘TP53’, ‘p53’, ‘p53 protein’, ‘p53 mutation’, ‘17p13 gene’, ‘chemotherapy’ and ‘breast cancer’. All potentially eligible studies were retrieved and their bibliographies were carefully scanned to identify other eligible studies. Additional studies were identified by a hand search of the references cited in the original studies. When multiple studies of the same patient population were identified, we included the published report with the largest sample size. Only studies published in English were included in this meta-analysis.

Inclusion and Exclusion Criteria

Studies included in this meta-analysis had to meet all of the following criteria: (a) evaluation of TP53 status for predicting the response to neoadjuvant chemotherapy in early-stage breast cancer, locally-advanced breast cancer, (b) described therapeutic response, (c) retrospective or prospective cohort study, (d) inclusion of sufficient data to allow the estimation of a risk ratio (RR) with 95% confidence intervals (95% CI), and (e) studies published in English. Letters to the editor, reviews, and articles published in books, or papers published in a language other than English were excluded.

Data Extraction and Definitions

According to the inclusion criteria listed above, the following data were extracted for each study: the first author’s surname, publication year, country of origin, number of patients analyzed, types of measurement, and treatment. Data on the main outcomes were entered in tables showing the clinical and pathological responses to chemotherapy with respect to TP53 status. Information was carefully and independently extracted from all eligible publications by two of the authors (Chen and Zhu). Any disagreement between the researchers was resolved by discussions until a consensus was reached. If they failed to reach a consensus, a third investigator (Lu) was consulted to resolve the dispute.

We used the definitions and standardizations for ‘TP53’ and ‘response to chemotherapy’ as reported by Pakos et al. [14]. For consistency, we used ‘TP53’ to denote the gene, ‘TP53’ for the expressed protein, and ‘TP53 status’ to refer to both the gene and protein markers. The correlation between protein and gene detection is not straightforward [9], [15]. TP53 alterations increase the half-life of the TP53 protein, leading to nuclear accumulation of mutant TP53, which can be detected by immunohistochemistry (IHC). However TP53 protein accumulation measured by IHC does not necessarily correspond to TP53 mutations. Thus, the overall analysis considered all studies, regardless of whether protein expression or gene mutation was being evaluated. Separate analyses for TP53 protein expression and TP53 gene alterations were also performed. For studies using both protein and gene detection, we used the protein data but also examined the gene detection data, and found similar results (data not shown). TP53 status positive means patients with over expression of TP53 protein and/or TP53 gene mutations. Response was defined as complete response (CR), partial response (PR), or objective response (OR) (OR  =  CR +PR). Non-response was defined as stable disease (SD) or progressive disease (PD), according to WHO criteria [16] or RECIST (Response Evaluation Criteria in Solid Tumors) criteria [17].

Statistical Analysis

RR with 95% CIs was used to estimate the association between TP53 status and response to neoadjuvant chemotherapy in breast cancer patients. Subgroup analyses were performed to evaluate the effects of treatment regimens (anthracycline-based) and different methods of TP53 gene determination (protein and gene). Heterogeneity assumption was checked using the Q test, and a p value >0.10 indicated a lack of heterogeneity among studies. The pooled RR was calculated using a fixed-effects model (the Mantel–Haenszel method) or a random-effects model (the DerSimonian and Laird method), according to the heterogeneity. Funnel plots and the Egger’s test were employed to estimate the possible publication bias. We also performed sensitivity analysis by omitting each study or specific studies to find potential outliers. Statistical analyses were conducted using Stata (version SE/10; StataCorp, College Station, TX). p values for all comparisons were two-tailed and statistical significance was defined as p<0.05 for all tests, except those for heterogeneity.

Results

Eligible Studies

A total of 1,223 articles were retrieved by a literature search of the PubMed, Embase, and Web of Science databases, using different combinations of key terms. As indicated in the search flow diagram (Figure S1), 26 studies reported at least one of the outcomes of interest and were finally included in the meta-analysis [2], [6][13], [15], [18][33]. The characteristics of the eligible studies are summarized in Table 1. Twenty-one of the studies employed IHC, eight employed gene detection (including genomic sequencing, DNA microarray, Functional Analysis of Separated Allele in Yeast [FASAY]), two employed both methods and one employed three methods (Table 1). The sample sizes in all the eligible studies ranged from 20–1,469 patients (median  = 73 patients, mean  = 134 patients, standard deviation [SD]  = 54). Overall, the eligible studies included 3,476 patients. Eighteen of the studies were conducted in European or North American populations with mixed but mostly white participants (1,460 patients), whereas eight were conducted in East Asian populations (748 patients).

Table 1. Characteristics of studies included in the meta-analysis.

Author Year Country Cases TreatmentSubgroup of treatment Detection Response
Makris et al. [18] 1997 UK 80 mitoxantrone, methotrexate (± mitomycin C) and tamoxifen N IHC clinical response CR + PR
Kandioler-Eckersberger et al. [9] 2000 Austria 67 FEC or paclitaxel N PCR amplification sequencing and IHC clinical response CR + PR
Geisler et al. [20] 2001 Norway 90 weekly doxorubicin scheduled for 16 weeks A-b IHC, TTGE and sequencing clinical response PR
Schneider et al. [19] 2001 Spain 52 FAC or CMF N IHC clinical response CR + PR
Aas et al. [11] 2003 Norway 90 doxorubicin A-b IHC clinical response PR+SD
Anelli et al. [6] 2003 Brazil 73 AT A-b IHC clinical response CR + PR
Bonnefoi et al. [22] 2003 Switzerland 179 FEC,EC + G-CSF A-b IHC clinical response CR
Martin-RIHCard et al.[] 2003 Spain 38 FAC or FEC A-b IHC clinical response CR + PR
Geisler et al. [21] 2003 Norway 35 FUMI regimen N IHC clinical response PR
Mathieu et al. [24] 2004 France 129 AVCMF or FAC/FEC A-b IHC Pathologic response CR
Deissler et al. [23] 2004 Germany 50 anthracycline/taxane A-b FASAY clinical response CR
Kim et al. [26] 2005 Japan 63 docetaxel N IHC Pathologic response RR
Learn et al. [25] 2005 USA 121 AC vs. AC+D A-b IHC Pathologic response CR
Bertheau et al. [29] 2007 France 80 EC A-b FASAY Pathologic response CR
Tiezzi et al. [8] 2007 Brazil 60 CMF or FEC N IHC clinical response CR + PR
Keam et al. [27] 2007 Korea 145 docetaxel and doxorubicin A-b IHC Pathologic response CR + PR
Lee et al. [28] 2008 Korea 61 AT A-b IHC clinical response RR
Pathologic response CR
Zhou et al. [7] 2008 China 135 taxanes and anthracycline A-b IHC Pathologic response CR
Yonemori et al. [12] 2009 Japan 44 trastuzumab-containing neoadjuvant N IHC Pathologic response CR
Shekhar et al. [30] 2009 USA 20 AC, AT, FAC, FAT A-b IHC clinical and pathologic response CR + PR
Silver et al. [32] 2010 USA 22 DDP N IHC clinical and pathologic response CR + PR
Masuda et al. [31] 2010 Japan 33 FEC100 and taxanes A-b IHC Pathologic response CR
Sanchez-Munoz et al. [10] 2010 Spain 73 EC followed by GP (+ trastuzumab in Her2 patients) A-b IHC Pathologic response CR
Bonnefoi et al. [2] 2011 Europe 1469 FEC VS. T-ET A-b FASAY clinical and pathologic response CR
Ono et al. [33] 2011 Japan 179 anthracycline-based regimens A-b IHC Pathologic response CR
Oshima et al. [15] 2011 Japan 88 P-FEC A-b genomic sequencing, DNA microarray and IHC Pathologic response CR

IHC, immunohistochemistry; FEC, 5-fluorouracil, epirubicin, and cyclophosphamide; FAC, 5-fluorouracil, doxorubicin, and cyclophosphamide; CMF, cyclophosphamide, mitomycin C and 5-fluorouracil; AVCMF, doxorubicin, vincristine, cyclophosphamide, methotrexate and 5-fluorouracil; P-FEC, sequential paclitaxel and 5-FU/epirubicin/cyclophosphamide; FUMI regimen, 5-fluorouracil (1,000 mg/m2 on days 1 and 2) and mitomycin; EC, epirubicin and cyclophosphamide; A, doxorubicin; E, epirubicin; T, docetaxel; P, paclitaxel; G, gemcitabine; FASAY, RNA-based functional assay in yeast; TTGE, temporal temperature gradient gel electrophoresis. N, can not be grouped; A-b, anthracycline-based neoadjuvant chemotherapy.

Correlation of TP53 Status with Response to Neoadjuvant Chemotherapy in Breast Cancer Patients

Among the studies of breast cancer patients who received neoadjuvant therapy, 26 studies involving 3,476 patients contributed data on total OR (clinical OR + pathological OR). TP53 status-positivity was significantly associated with improved total OR among patients treated with neoadjuvant therapy (RR = 1.20; 95% CI = 1.09–1.33; p<0.001, Figure S2). Thirteen studies involving 2,761 patients contributed data on pathological OR. TP53 status-positivity was significantly associated with improved pathological response (RR = 1.37; 95% CI = 1.20–1.57; p<0.001). Fifteen studies involving 2,736 patients contributed data on total CR. TP53 status-positivity was significantly associated with improved total CR (RR = 1.33; 95% CI = 1.15–1.53; p<0.001). Finally, 12 studies involving 2,434 patients provided information on pathological CR. TP53 status-positivity was significantly associated with significant improvements in pathological CR (RR = 1.45; 95% CI = 1.25–1.68; p<0.001, Figure S3). For studies using both clinical and pathological responses, we used the pathological-response data, but also examined the clinical-response data and found similar results (data not shown).

Subgroup Analysis

Among the 26 studies in the neoadjuvant subgroup, 18 used anthracycline-based neoadjuvant chemotherapy,while the remaining studies can not be grouped (table 1). The results of the anthracycline-based neoadjuvant chemotherapies were therefore calculated. TP53 status-positivity was associated with improved response in breast cancer patients who received anthracycline-based neoadjuvant chemotherapy (total OR: RR = 1.18, 95% CI = 1.04–1.33, p = 0.010, Figure S4; pathological OR: RR = 1.33, 95% CI = 1.19–1.62, p = 0.005; total CR: RR = 1.33, 95% CI = 1.15–1.54, p<0.001; pathological CR: RR = 1.45, 95% CI = 1.24–1.69, p<0.001). For studies using both clinical and pathological responses, we used the pathological-response data, but also examined the clinical-response data, and similar results were obtained (data not shown).

Different measurements of TP53 status (either by protein or gene detection) have been used to evaluate associations with favorable responses to neoadjuvant chemotherapy. We therefore calculated the associations using both protein and gene statuses of TP53. The results of subgroup analysis are presented in Table 2. For gene detection, TP53 status-positivity was significantly associated with increased total OR (RR = 1.41, 95% CI = 1.20–1.65, p<0.001, Figure S5), total pathological response (pathological response: RR = 1.49; 95% CI = 1.24–1.79; p<0.001), total CR (RR = 1.46; 95% CI = 1.22–1.75; p<0.001) and pathological CR (RR = 1.49; 95% CI = 1.24–1.79; p<0.001) among patients treated with neoadjuvant chemotherapy. For protein-based detection, TP53 status-positivity was significantly associated with increased total OR (RR = 1.22; 95% CI = 1.01–1.48; p = 0.041) and total CR (RR = 1.32; 95% CI = 1.02–1.69; p = 0.032) among patients treated with neoadjuvant chemotherapy, but not with total OR (RR = 1.06; 95% CI = 0.94–1.20; p = 0.310) or total CR (RR = 1.15; 95% CI = 0.92–1.43; p = 0.235). For studies using both clinical and pathological responses, we used the pathological-response data, but also examined the clinical response data, and the results were similar (data not shown).

Table 2. Risk ratio for the association between TP53 status and response to neoadjuvant chemotherapy.

Comparison Total OR* Pathological OR Total CR* Pathological CR
N RR (95%CI) p value Ph N RR (95%CI) p value Ph N RR (95%CI) p value Ph N RR (95%CI) p value Ph
All studies 26 1.20 (1.09–1.33) <0.001 0.292 15 1.37 (1.20–1.57) <0.001 0.329 15 1.33 (1.15–1.53) <0.001 0.095 12 1.45 (1.25–1.68) <0.001 0.391
Treatment
Anthracycline-based 17 1.18 (1.04–1.33) 0.010 0.298 10 1.33 (1.19–1.62) 0.005 0.109 12 1.33 (1.15–1.54) <0.001 0.031 9 1.45 (1.24–1.69) <0.001 0.175
Type of measurement
Protein 21 1.06 (0.94–1.20) 0.310 0.796 12 1.22 (1.01–1.48) 0.041 0.637 12 1.15 (0.92–1.43) 0.235 0.209 9 1.32 (1.02–1.69) 0.032 0.659
Gene 8 1.41 (1.20–1.65) <0.001 0.207 4 1.49 (1.24–1.79) <0.001 0.089 5 1.46 (1.22–1.75) <0.001 0.076 4 1.49 (1.24–1.79) <0.001 0.089

Subgroup analysis was performed when there were at least two studies in each subgroup.

N, number of studies; Ph, p value of Q-test for heterogeneity.

*

For studies using both clinical and pathological responses, we used the pathological response data, but also examined the clinical response data, and found similar results (data not shown).

#One study (Oshima et al. [15]) used both genomic sequencing and DNA microarray analysis for gene measurement; we used genomic sequencing data, but also also examined the DNA microarray data, and found similar results (data not shown).

Publication Bias

Begg’s funnel plot and Egger’s test were used to estimate the publication bias of the included literature. The shapes of the funnel plots showed no evidence of obvious asymmetry(Figure S6), and Egger’s test indicated the absence of publication bias (p>0.05). Moreover, sensitivity analysis was carried out to assess the influence of individual studies on the summary effect. Trastuzumab would likely have increased the chances of response when combined with a taxane in two of the studies which included patients with HER-2 positive disease, there may be some discordance in response rates in the newer studies compared to the older studies prior to the advent of trastuzumab, this may have falsely credited the anthracycline for the benefit seen and introduced confounding. However, the corresponding pooled RRs were not substantially altered whether or not these studies were included. No individual study dominated this meta-analysis, and the removal of any single study had no significant effect on the overall results (total OR: RR ranged from 1.12[95% CI = 1.01–1.25] to 1.22 [95% CI = 1.10–1.35]; pathological OR: RR ranged from 1.42 [95% CI = 1.22–1.66] to 1.51 [95% CI = 1.18–1.93]; total CR: RR ranged from 1.24 [95% CI = 1.01–1.56] to 1.37 [95% CI = 1.18–1.59]; pathological CR: RR ranged from 1.42 [95% CI = 1.22–1.66] to 1.47 [95% CI = 1.26–1.76]).

Discussion

TP53 status had been shown to play a pivotal role in the response to a large panel of anticancer drugs. Previous studies suggested that breast cancers with TP53 mutations might be either resistant or sensitive to anticancer drugs. However, the issue could not be resolved, because most of the available clinical reports involved small sample sizes, and the results were therefore unable to determine the value of TP53 status for predicting the response to chemotherapy. Additionally, IHC, which lacks sensitivity and specificity, or various DNA sequencing techniques, some of which also lack sensitivity, were the main techniques used in these studies. We therefore concluded that a meta-analysis was the best way of evaluating the association between TP53 status and response to neoadjuvant chemotherapy in a large population.

The current meta-analysis of 26 studies systematically evaluated the association between TP53 status and response to neoadjuvant chemotherapy in a large population. The results indicate that altered TP53 status may predict good response rates to neoadjuvant chemotherapy in patients with breast cancer. TP53 status was associated with total and pathologically relevant increases in OR and CR. Stratification according to different treatments showed that altered TP53 status was significantly associated with increased OR and CR in patients who received anthracycline-based neoadjuvant chemotherapy. Further stratification by gene detection revealed imprecise results, but amplification of the TP53 gene was also associated with relevant increases in OR and CR (both total and pathological); however, although overexpression of TP53 was associated with relevant increases in pathological OR and CR, it was not associated with total OR and CR. Gene detection was associated with advantages regarding response rates to neoadjuvant chemotherapy in patients with breast cancer. Gene detection may thus be a useful approach in future prospective studies.

Despite our attempts to perform a comprehensive analysis, there were some limitations associated with this meta-analysis. First, the meta-analysis may have been influenced by publication bias, we limited the search to studies performed in English, and we did not search conference proceedings and abstract books, which may have introduced publication bias to meta-analysis. We tried to identify all relevant data and retrieve additional unpublished information, some missing data were unavoidable. Second, the studies used different measurements of TP53 status (either protein or gene detection), and the cut-off values for TP53 for overexpression by IHC and for gene amplification differed between studies. Standardization is therefore of great importance for obtaining an accurate assessment of the clinical significance of TP53 status. Although we made considerable efforts to standardize definitions, some variability in definitions of methods, measurements, and outcomes among studies was inevitable. Third, our analysis was observational in nature, and we therefore cannot exclude confounding as a potential explanation of the observed results. Despite these limitations, this meta-analysis had several strengths. First, a substantial number of cases were pooled from different studies, and 3,476 subjects represent a sizeable number, significantly increasing the statistical power of the analysis. Secondly, no publication biases were detected, indicating that the pooled results may be unbiased.

This study is the first meta-analysis to assess the usefulness of TP53 status for predicting the response of breast cancer patients to neoadjuvant chemotherapy. Our data support TP53 status as a useful predictive factor for assessing treatment response to neoadjuvant chemotherapy in breast cancer patients. However, future prospective studies with large sample sizes and better study designs are required to confirm our findings. Moreover, the interactions of this marker with other molecular markers such as HER-2 [34] or estrogen receptor [35] remain unknown, and should be topics for further investigation.

Supporting Information

Figure S1

Improving the quality of reports of meta-analyses of randomized controlled trials; the Quality of Reporting of Meta-Analyses (QUOROM) statement flow diagram.

(EPS)

Figure S2

Forest plots of RR were assessed for association between TP53 and total OR among breast cancer patients treated with neoadjuvant therapy.

(EPS)

Figure S3

Forest plots of RR were assessed for association between TP53 and pathological CR among breast cancer patients treated with neoadjuvant therapy.

(EPS)

Figure S4

Forest plots of RR were assessed for the evaluation of total OR in anthracycline-based settings.

(EPS)

Figure S5

Forest plots of RR were assessed for the evaluation of total OR in gene-based detection settings.

(EPS)

Figure S6

The funnel plot shows that there was no obvious indication of publication bias for the outcome of total OR.

(EPS)

Footnotes

Competing Interests: The authors have declared that no competing interests exist.

Funding: This work was supported by the Natural Science Foundation of Jiangsu Province (No. BK2010160, BK2011374) and the National Natural Science Foundation (No.81108676, 81101801). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Tewari M, Krishnamurthy A, Shukla HS. Predictive markers of response to neoadjuvant chemotherapy in breast cancer. Surg Oncol. 2008;17:301–311. doi: 10.1016/j.suronc.2008.03.003. [DOI] [PubMed] [Google Scholar]
  • 2.Bonnefoi H, Piccart M, Bogaerts J, Mauriac L, Fumoleau P, et al. TP53 status for prediction of sensitivity to taxane versus non-taxane neoadjuvant chemotherapy in breast cancer (EORTC 10994/BIG 1–00): a randomised phase 3 trial. Lancet Oncol. 2011;12:527–539. doi: 10.1016/S1470-2045(11)70094-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Vousden KH, Prives C. Blinded by the Light: The Growing Complexity of p53. Cell. 2009;137:413–431. doi: 10.1016/j.cell.2009.04.037. [DOI] [PubMed] [Google Scholar]
  • 4.Lowe SW, Ruley HE, Jacks T, Housman DE. p53-dependent apoptosis modulates the cytotoxicity of anticancer agents. Cell. 1993;74:957–967. doi: 10.1016/0092-8674(93)90719-7. [DOI] [PubMed] [Google Scholar]
  • 5.Lowe SW, Bodis S, McClatchey A, Remington L, Ruley HE, et al. p53 status and the efficacy of cancer therapy in vivo. Science. 1994;266:807–810. doi: 10.1126/science.7973635. [DOI] [PubMed] [Google Scholar]
  • 6.Anelli A, Brentani RR, Gadelha AP, Amorim De Albuquerque A, Soares F. Correlation of p53 status with outcome of neoadjuvant chemotherapy using paclitaxel and doxorubicin in stage IIIB breast cancer. Ann Oncol. 2003;14:428–432. doi: 10.1093/annonc/mdg104. [DOI] [PubMed] [Google Scholar]
  • 7.Zhou B, Yang DQ, Xie F. Biological markers as predictive factors of response to neoadjuvant taxanes and anthracycline chemotherapy in breast carcinoma. Chin Med J (Engl) 2008;121:387–391. [PubMed] [Google Scholar]
  • 8.Tiezzi DG, Andrade JM, Ribeiro-Silva A, Zola FE, Marana HR, et al. HER-2, p53, p21 and hormonal receptors proteins expression as predictive factors of response and prognosis in locally advanced breast cancer treated with neoadjuvant docetaxel plus epirubicin combination. BMC Cancer. 2007;7:36. doi: 10.1186/1471-2407-7-36. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Kandioler-Eckersberger D, Ludwig C, Rudas M, Kappel S, Janschek E, et al. TP53 mutation and p53 overexpression for prediction of response to neoadjuvant treatment in breast cancer patients. Clin Cancer Res. 2000;6:50–56. [PubMed] [Google Scholar]
  • 10.Sanchez-Munoz A, Duenas-Garcia R, Jaen-Morago A, Carrasco E, Chacon I, et al. Is it possible to increase pCR in the neoadjuvant treatment with a dose-dense/sequential combination?: results from a phase II Trial combining epirubicin and cyclophosphamide followed by paclitaxel and gemcitabine +/− trastuzumab in stage II and III breast cancer patients. Am J Clin Oncol. 2010;33:432–437. doi: 10.1097/COC.0b013e3181b4eff9. [DOI] [PubMed] [Google Scholar]
  • 11.Aas T, Geisler S, Eide GE, Haugen DF, Varhaug JE, et al. Predictive value of tumour cell proliferation in locally advanced breast cancer treated with neoadjuvant chemotherapy. Eur J Cancer. 2003;39:438–446. doi: 10.1016/s0959-8049(02)00732-3. [DOI] [PubMed] [Google Scholar]
  • 12.Yonemori K, Tsuta K, Shimizu C, Hatanaka Y, Hashizume K, et al. Immunohistochemical expression of PTEN and phosphorylated Akt are not correlated with clinical outcome in breast cancer patients treated with trastuzumab-containing neo-adjuvant chemotherapy. Med Oncol. 2009;26:344–349. doi: 10.1007/s12032-008-9127-2. [DOI] [PubMed] [Google Scholar]
  • 13.Martin-Richard M, Munoz M, Albanell J, Colomo L, Bellet M, et al. Serial topoisomerase II expression in primary breast cancer and response to neoadjuvant anthracycline-based chemotherapy. Oncology. 2004;66:388–394. doi: 10.1159/000079487. [DOI] [PubMed] [Google Scholar]
  • 14.Pakos EE, Kyzas PA, Ioannidis JP. Prognostic significance of TP53 tumor suppressor gene expression and mutations in human osteosarcoma: a meta-analysis. Clin Cancer Res. 2004;10:6208–6214. doi: 10.1158/1078-0432.CCR-04-0246. [DOI] [PubMed] [Google Scholar]
  • 15.Oshima K, Naoi Y, Kishi K, Nakamura Y, Iwamoto T, et al. Gene expression signature of TP53 but not its mutation status predicts response to sequential paclitaxel and 5-FU/epirubicin/cyclophosphamide in human breast cancer. Cancer Lett. 2011;307:149–157. doi: 10.1016/j.canlet.2011.03.027. [DOI] [PubMed] [Google Scholar]
  • 16.Miller AB, Hoogstraten B, Staquet M, Winkler A. Reporting results of cancer treatment. Cancer. 1981;47:207–214. doi: 10.1002/1097-0142(19810101)47:1<207::aid-cncr2820470134>3.0.co;2-6. [DOI] [PubMed] [Google Scholar]
  • 17.Therasse P, Arbuck SG, Eisenhauer EA, Wanders J, Kaplan RS, et al. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J Natl Cancer Inst. 2000;92:205–216. doi: 10.1093/jnci/92.3.205. [DOI] [PubMed] [Google Scholar]
  • 18.Makris A, Powles TJ, Dowsett M, Osborne CK, Trott PA, et al. Prediction of response to neoadjuvant chemoendocrine therapy in primary breast carcinomas. Clin Cancer Res. 1997;3:593–600. [PubMed] [Google Scholar]
  • 19.Schneider J, Gonzalez-Roces S, Pollan M, Lucas R, Tejerina A, et al. Expression of LRP and MDR1 in locally advanced breast cancer predicts axillary node invasion at the time of rescue mastectomy after induction chemotherapy. Breast Cancer Res. 2001;3:183–191. doi: 10.1186/bcr293. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Geisler S, Lonning PE, Aas T, Johnsen H, Fluge O, et al. Influence of TP53 gene alterations and c-erbB-2 expression on the response to treatment with doxorubicin in locally advanced breast cancer. Cancer Res. 2001;61:2505–2512. [PubMed] [Google Scholar]
  • 21.Geisler S, Borresen-Dale AL, Johnsen H, Aas T, Geisler J, et al. TP53 gene mutations predict the response to neoadjuvant treatment with 5-fluorouracil and mitomycin in locally advanced breast cancer. Clin Cancer Res. 2003;9:5582–5588. [PubMed] [Google Scholar]
  • 22.Bonnefoi H, Diebold-Berger S, Therasse P, Hamilton A, van de Vijver M, et al. Locally advanced/inflammatory breast cancers treated with intensive epirubicin-based neoadjuvant chemotherapy: are there molecular markers in the primary tumour that predict for 5-year clinical outcome? Ann Oncol. 2003;14:406–413. doi: 10.1093/annonc/mdg108. [DOI] [PubMed] [Google Scholar]
  • 23.Deissler H, Kafka A, Schuster E, Sauer G, Kreienberg R, et al. Spectrum of p53 mutations in biopsies from breast cancer patients selected for preoperative chemotherapy analysed by the functional yeast assay to predict therapeutic response. Oncol Rep. 2004;11:1281–1286. [PubMed] [Google Scholar]
  • 24.Mathieu MC, Rouzier R, Llombart-Cussac A, Sideris L, Koscielny S, et al. The poor responsiveness of infiltrating lobular breast carcinomas to neoadjuvant chemotherapy can be explained by their biological profile. Eur J Cancer. 2004;40:342–351. doi: 10.1016/j.ejca.2003.08.015. [DOI] [PubMed] [Google Scholar]
  • 25.Learn PA, Yeh IT, McNutt M, Chisholm GB, Pollock BH, et al. HER-2/neu expression as a predictor of response to neoadjuvant docetaxel in patients with operable breast carcinoma. Cancer. 2005;103:2252–2260. doi: 10.1002/cncr.21037. [DOI] [PubMed] [Google Scholar]
  • 26.Kim SJ, Miyoshi Y, Taguchi T, Tamaki Y, Nakamura H, et al. High thioredoxin expression is associated with resistance to docetaxel in primary breast cancer. Clin Cancer Res. 2005;11:8425–8430. doi: 10.1158/1078-0432.CCR-05-0449. [DOI] [PubMed] [Google Scholar]
  • 27.Keam B, Im SA, Kim HJ, Oh DY, Kim JH, et al. Prognostic impact of clinicopathologic parameters in stage II/III breast cancer treated with neoadjuvant docetaxel and doxorubicin chemotherapy: paradoxical features of the triple negative breast cancer. BMC Cancer. 2007;7:203. doi: 10.1186/1471-2407-7-203. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Lee J, Im YH, Lee SH, Cho EY, Choi YL, et al. Evaluation of ER and Ki-67 proliferation index as prognostic factors for survival following neoadjuvant chemotherapy with doxorubicin/docetaxel for locally advanced breast cancer. Cancer Chemother Pharmacol. 2008;61:569–577. doi: 10.1007/s00280-007-0506-8. [DOI] [PubMed] [Google Scholar]
  • 29.Bertheau P, Turpin E, Rickman DS, Espie M, de Reynies A, et al. Exquisite sensitivity of TP53 mutant and basal breast cancers to a dose-dense epirubicin-cyclophosphamide regimen. PLoS Med. 2007;4:e90. doi: 10.1371/journal.pmed.0040090. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Shekhar MP, Biernat LA, Pernick N, Tait L, Abrams J, et al. Utility of DNA postreplication repair protein Rad6B in neoadjuvant chemotherapy response. Med Oncol. 2010;27:466–473. doi: 10.1007/s12032-009-9235-7. [DOI] [PubMed] [Google Scholar]
  • 31.Masuda H, Masuda N, Kodama Y, Ogawa M, Karita M, et al. Predictive factors for the effectiveness of neoadjuvant chemotherapy and prognosis in triple-negative breast cancer patients. Cancer Chemother Pharmacol. 2011;67:911–917. doi: 10.1007/s00280-010-1371-4. [DOI] [PubMed] [Google Scholar]
  • 32.Silver DP, Richardson AL, Eklund AC, Wang ZC, Szallasi Z, et al. Efficacy of neoadjuvant Cisplatin in triple-negative breast cancer. J Clin Oncol. 2010;28:1145–1153. doi: 10.1200/JCO.2009.22.4725. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Ono M, Tsuda H, Shimizu C, Yamamoto S, Shibata T, et al. Tumor-infiltrating lymphocytes are correlated with response to neoadjuvant chemotherapy in triple-negative breast cancer. Breast Cancer Res Treat. 2011. [DOI] [PubMed]
  • 34.Hayes DF, Thor AD, Dressler LG, Weaver D, Edgerton S, et al. HER2 and response to paclitaxel in node-positive breast cancer. N Engl J Med. 2007;357:1496–1506. doi: 10.1056/NEJMoa071167. [DOI] [PubMed] [Google Scholar]
  • 35.Berry DA, Cirrincione C, Henderson IC, Citron ML, Budman DR, et al. Estrogen-receptor status and outcomes of modern chemotherapy for patients with node-positive breast cancer. JAMA. 2006;295:1658–1667. doi: 10.1001/jama.295.14.1658. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figure S1

Improving the quality of reports of meta-analyses of randomized controlled trials; the Quality of Reporting of Meta-Analyses (QUOROM) statement flow diagram.

(EPS)

Figure S2

Forest plots of RR were assessed for association between TP53 and total OR among breast cancer patients treated with neoadjuvant therapy.

(EPS)

Figure S3

Forest plots of RR were assessed for association between TP53 and pathological CR among breast cancer patients treated with neoadjuvant therapy.

(EPS)

Figure S4

Forest plots of RR were assessed for the evaluation of total OR in anthracycline-based settings.

(EPS)

Figure S5

Forest plots of RR were assessed for the evaluation of total OR in gene-based detection settings.

(EPS)

Figure S6

The funnel plot shows that there was no obvious indication of publication bias for the outcome of total OR.

(EPS)


Articles from PLoS ONE are provided here courtesy of PLOS

RESOURCES