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Weekly PCb (paclitaxel + carboplatin) in neoadjuvant chemotherapy (NCT) for breast cancer has a high pathological complete remission (pCR) rate. The present study was to identify pCR predictive biomarkers and to test whether integrating candidate molecular biomarkers can improve the pCR predictive accuracy. Ninety-one breast cancer patients treated with weekly PCb NCT were retrospectively analyzed. Eleven candidate molecular biomarkers (Tau, β-tubulin III, PTEN, MAP4, thioredoxin, multidrug resistance-1, Ki67, p53, Bcl-2, BAX, and ERCC1) were detected by immunohistochemistry in pre-NCT core needle biopsy specimens. We analyzed the relationship between these biomarkers and pCR. Univariate analysis showed that estrogen receptor, progesterone receptor, molecular classification (clinicopathological markers), and Tau, β-tubulin III, p53, Bcl-2, ERCC1 (candidate molecular biomarkers) expression were associated with pCR rate; however, multivariate analysis revealed that only β-tubulin III, Bcl-2, and ERCC1 were independent pCR predictive factors. Patients with β-tubulin III negative, Bcl-2 negative, or ERCC1 negative tumors were associated with higher pCR rate, with OR (odds ratios) 6.03 (95% confidence interval [CI], 1.44–25.24, P = 0.014), 7.54 (95% CI, 1.52–37.40, P = 0.013), and 4.09 (95% CI, 1.17–14.30, P = 0.028), respectively. To compare different logistic regression models, built with different combinations of these variables, we found that the model integrating routine clinical and pathological variables, as well as the β-tubulin III, Bcl-2, ERCC1 molecular biomarkers had the highest pCR predictive power. The area under the ROC curve for this model was 0.900 (95% CI, 0.831–0.968), indicating that it deserves further investigation. Trial name: Weekly Paclitaxel Plus Carboplatin in Preoperative Treatment of Breast Cancer. (Cancer Sci 2012; 103: 262–268)
Neoadjuvant chemotherapy is the standard treatment for patients with locally advanced breast cancer. In early breast cancer, NCT is associated with significantly higher breast conservation rate compared with those receiving adjuvant chemotherapy.(1) Numerous phase III randomized clinical trials have shown that patients who achieved pathological complete remission after NCT had better prognosis than those who did not.(2,3) Furthermore, NCT can test in vivo tumor chemosensitivity. It offers great opportunities to carry out biological studies on primary tumor, and to better understand the mechanisms of tumor response and chemoresistance, thus improving the efficacy of breast cancer treatment.
Paclitaxel, knowing its antitumor activity through tubulin stabilization and cell cycle arrest, has revolutionized breast cancer therapy.(4) The Early Breast Cancer Trialists’ Collaborative Group has revealed that taxane-based adjuvant chemotherapy can significantly improve the outcome of patients compared to those treated with anthracyclin-based therapy. The mechanism of carboplatin action involves covalent binding to purine DNA bases, which primarily leads to cellular apoptosis.(5) Paclitaxel combined with carboplatin has shown great activity in ovarian and non-small-cell lung cancer treatment. In NCT, we have previously reported that a weekly PCb regimen had great antitumor activity and tolerability in breast cancer patients, with the pCR rate as high as 19.4%.(6)
Not all patients who receive NCT can achieve pCR, with pCR rates in early studies reported to be 6% and 28%.(7) Similarly, the pCR rate was 19.4% in patients treated with PCb. So we need to identify the patients who will respond, thus allowing a tailored NCT to be formulated.(8) However, at present, we still lack reliable markers to predict the efficacy of PCb in breast cancer treatment.
Breast cancer is a heterogeneous disease. Patients with histologically similar tumors may have different prognosis and treatment responses. In NCT, several factors like HR negativity, high histological grade, and Ki67 levels may correlate with a high pCR rate, whereas the predictive value of other biomarkers, like HER2 expression, and Bcl-2 and p53 status, are still unclear.(8) Based on microarray and real-time PCR technology, we have identified several molecular classifications of breast cancer by different gene expression profiling, which can better predict prognosis and efficacy compared to routine clinicopathological parameters.(9–16) In addition, models based on gene expression profiling have great pCR predictive accuracy.(13–16) A nomogram that includes several clinicopathological factors can more accurately predict pCR than a single clinicopathological marker.(17) With the development of pharmacogenomics, we can predict the efficacy of NCT from the genetic level, using candidate gene or whole genome methods.(18) Several molecular biomarkers, such as Tau, MAP4, β-tubulin III, PTEN, thioredoxin, MDR-1, Ki67, p53, Bcl-2, BAX, ER, and HER2, could be associated with paclitaxel efficacy.(19,20) Apoptosis-related genes (p53, Bcl-2, and BAX) and DNA repair genes (ERCC1) may correlate with carboplatin activity.(21) Candidate molecular biomarker status can be detected by IHC rather than RT-PCR assay, with the following advantages: (i) it eliminates the stromal and inflammatory cell contamination problem by observing only staining cancer cells; (ii) it enables retrospective analysis by using paraffin sections; and (iii) it represents more reliable gene function than mRNA expression.(22)
Based on these factors, we analyzed these candidate molecular biomarkers in breast cancer patients treated with weekly PCb to identify pCR predictive markers. Furthermore, constructed different models using various factors to evaluate whether models integrating candidate molecular biomarkers can improve pCR predictive accuracy.
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- Materials and Methods
- Disclosure Statement
- Supporting Information
The aim of our present study was to evaluate the pCR predictive factors for breast cancer patients treated with weekly PCb NCT, and we found patients with negative β-tubulin III, negative Bcl-2, or negative ERCC1 tumors had a significantly higher pCR rate than those with positive disease. Furthermore, the pCR predictive model integrating routine clinical and pathological variables and β-tubulin III, Bcl-2, ERCC1 status had the highest accuracy to predict the pCR possibility, which indicated that, on the basis of clinicopathological variables, measuring β-tubulin III, Bcl-2, and ERCC1 can improve pCR predictive accuracy in patients treated with weekly PCb NCT.
Taxanes are microtubule-stabilizing agents that function primarily by interfering with spindle microtubule dynamics, causing cell cycle arrest and apoptosis.(4,20) Microtubules are composed of α- and β-tubulin heterodimers, and the cellular target for paclitaxel is on the β-tubulin site.(20)β-tubulin III is an isotype of the β-tubulin family, which is less stable with an increased tendency toward depolymerization compared to other β-tubulin isotypes, indicating that β-tubulin III expression is related with taxane efficacy.(23) Several in vivo studies reported that β-tubulin III status could be considered as a predictive biomarker of taxane treatment response, with high expression of β-tubulin III significantly associated with taxane resistance.(24,25) In a group of 70 patients with advanced breast cancer treated with paclitaxel-based chemotherapy, β-tubulin III status could predict the treatment efficacy; only 2% of patients with low β-tubulin III expression progressed after paclitaxel chemotherapy compared with 38% of those with high β-tubulin III expression (P < 0.001).(26) In our study, we found that patients with β-tubulin III negative tumors had a significantly higher pCR rate than those with positive disease. In multivariate analysis, β-tubulin III status was an independent pCR predictive factor, which indicated that β-tubulin III status was associated with paclitaxel-containing treatment efficacy. Furthermore, Dumontet et al.(27) reported that β-tubulin III status was a prognostic factor for node-positive breast cancer patients treated with docetaxel-based regimen in the BCIRG 001 trial. Long follow-up is required to evaluate the relationship between β-tubulin III expression and outcome in our study.
Bcl-2 is a protein that can inhibit the process of cell apoptosis. Taxane treatment can cause Bcl-2 phosphorylation through various signaling pathways, leading to the inactivation of Bcl-2 and induction of apoptosis.(20) In breast cancer treatment, the efficacy of paclitaxel given every 3 weeks was inferior to a weekly regimen, which may inhibit tumor regrowth between cycles and limit the emergence of malignant cell populations resistant to chemotherapy by enhancing its apoptotic and antiangiogenic effects.(28) In addition, carboplatin can also cause apoptotic effects by causing DNA damage. In an in vivo study, estrogen could increase the intracellular Bcl-2 level and inhibit paclitaxel-induced apoptosis of human breast cancer MCF-7 cells. Blocking the estrogen by tamoxifen could decrease the expression of Bcl-2, which resumed the sensitivity of paclitaxel.(29) In the current study, we found that Bcl-2 was an independent pCR predictive marker; patients with negative Bcl-2 tumors had a higher pCR rate than those with positive disease. However, Poelman et al.(30) had shown that there was no significant association between Bcl-2 expression and response or outcome in metastatic breast cancer patients treated with single paclitaxel. The main explanations for this difference are that patients in our series were treated with weekly paclitaxel and concurrently with weekly carboplatin, which might have greater anti-apoptosis effects than single paclitaxel given with every 3 weeks.(28)
Platinum–DNA adducts can cause distortions in DNA platinum drugs (cisplatin and carboplatin), thus leading to cellular apoptosis. There are several mechanisms involved in DNA repair pathways, including NER, base-excision repair, mismatch repair, and double-strand-break repair. However, NER is considered as the major pathway to remove platinum drug lesions from DNA. As an NER endonuclease protein, ERCC1 plays an important role in the NER pathway and may be related with platinum drug response.(21) In several solid tumors, such as ovarian cancer, lung cancer, and bladder cancer, patients with low ERCC1 level disease had a significantly higher response rate and better outcome than those with high ERCC1 expression disease, and may get more benefit from platinum-based therapy.(31–35) However, there are relatively few data on ERCC1 expression and platinum-based treatment efficacy in breast cancer. Among our cohort of 91 breast cancer patients treated with weekly PCb, we found that patients with ERCC1 negative breast cancer had a much higher response rate than those with positive disease, which was similar to previous reports in other solid tumors.
Previous studies have indicated that ER,(36,37) HER2,(38) Tau,(39) MAP4,(40) MDR-1,(41,42) Ki67,(43) PTEN,(44,45) p53,(46) thioredoxin,(16,22) and BAX(21) status might be associated with taxane or carboplatin response. In univariate analysis, we found that patients with Tau negative tumors had a significantly higher pCR rate than those with positive tumors, which was similar to patients treated with neoadjuvant paclitaxel followed by FAC.(39) However, in multivariate analysis, Tau expression was no longer an independent pCR predictive factor, which may due to the significant correlation with another microtubulin-associated protein, β-tubulin III. In addition, patients with ER or p53 negative disease had a higher chance to achieve pCR, but again in multivariate analysis, these were not independent pCR predictive factors. The absence of an independent relationship between ER status and pCR when adjusting for all markers was surprising, but the direct relationship with Bcl2 expression could provide a possible explanation (Spearman correlation analysis, r = 0.491, P < 0.001).
Many studies have been aimed at predicting the response of NCT in breast cancer, based on gene expression signatures of variably expressed genes detected by gene-chip assay, and have shown that these classifications were superior compared with routine clinical and pathological variables.(13–16) In patients treated with paclitaxel followed by FAC NCT, molecular classification determined by a “breast intrinsic” gene set could predict the pCR rate, and patients with basal-like and HER2 subtypes were more sensitive to NCT than those with other tumors.(47) In our current study, breast cancer molecular classification, constructed by ER, PR, and HER2 status, was an independent pCR predictive factor among routine clinical and pathological variables. Furthermore, Rouzier et al.(47)built three logistic regression models, including various combinations of clinical and histopathological variables, and the molecular class yielded similar AUC values, which indicated that the molecular class alone can replace histopathologic characteristics to predict pCR. However, another report indicated that a model combining clinical and genomic information was nominally best, and may further improve the pCR prediction performance.(14) A logistic regression model, incorporating routine clinicopathological variables and these three candidate molecular biomarkers, had the highest AUC value (0.900, 95% CI, 0.831–0.968) and was much higher than models only including routine clinical factors plus pathological variables or molecular classification, which also indicated that integrating these new candidate molecular biomarkers could improve the pCR predictive performance. In addition, Tau protein expression was inversely associated with the pCR rate in patients receiving NCT.(39) However, high Tau protein expression was associated with better prognosis in patients treated with adjuvant anthracycline and paclitaxel chemotherapy and endocrine therapy in the NSABP-B 28 trial.(48) So, with this relatively short period of follow-up, we are not able to show the relationship between the pCR predictive model and patient survival, which may be due to the heterogeneity of luminal A disease and the effects of adjuvant endocrine therapy after chemotherapy.
There are also several potential limitations to this study. We lack an independent cohort of patients to validate this pCR predictive model due to the retrospective nature of the study and the limited number of patients enrolled. Therefore, our results are still exploratory, and further study is needed to confirm them, especially in the context of other neoadjuvant trials that combine weekly paclitaxel with carboplatin. In addition, selection bias existed in our study by applying the candidate biomarker approach. Finally, breast cancer is a highly heterogeneous disease, which includes many subtypes, such as ER positive, triple-negative, or HER2 positive, each with varying treatment responses and prognosis.(16,47) So, it would be better to study the pCR predictive factors in certain breast cancer subtypes to test whether this predictive model would be useful for all phenotypic subsets of disease or just within some certain phenotypes, like ER negative, high histological grade, or high Ki67 expression disease, thereby reducing the influence of disease heterogeneity.
In summary, β-tubulin III, Bcl-2, and ERCC1 can predict the pCR rate among patients treated with weekly PCb NCT. Patients with β-tubulin III negative, Bcl-2 negative, or ERCC1 negative disease had a higher pCR rate than those with positive disease. A model incorporating routine clinical and pathological variables as well as β-tubulin III, Bcl-2, and ERCC1 improved the pCR predictive power. Further investigation is needed to confirm the clinical significance of these biomarkers in a large number of patients.