III breast cancer

Biomedicine & Pharmacotherapy 88 (2017) 911–917

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Original article

Changes of serum miR34a expression during neoadjuvant chemotherapy predict the treatment response and prognosis in stage II/III breast cancer Baoquan Liua,1, Fei Sub,1, Yue Lic,1, Xiuying Qia , Xiangchen Liuc, Wenlong Liangc , Kai Youa , Yafang Zhanga,* , Jianguo Zhangc,** a

Department of Anatomy, Harbin Medical University, Harbin, 150081, PR China College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, PR China c Department of General Surgery, The Second Clinical Hospital, Harbin Medical University, Harbin, 150081, PR China b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 29 November 2016 Received in revised form 15 January 2017 Accepted 23 January 2017

Objective: To investigate the predictive value of serum miR34a (ser-miR34a) expression for the neoadjuvant chemotherapy (NACT) response and prognosis in breast cancer patients. Methods: This study included 86 diagnosed stage II/III breast cancer patients and 20 healthy volunteers. Peripheral blood from every participant was collected before the start, at the end of the second cycle, and at the end of NACT. The expression of ser-miR34a was examined by qRT-PCR and its association with the chemotherapy response and prognosis was analyzed. Results: The expression of ser-miR34a in breast cancer patients before NACT was significant higher than that of healthy volunteers. During the NACT, the changes in ser-miR34a expression were significantly associated with treatment response and disease-free survival (DFS). In responding patients, ser-miR34a levels at the end of the second cycle and at the end of NACT were significantly lower than before NACT (P = 0.016 and P = 0.002, respectively), and in non-responding patients, the changes were insignificant. Survival analyses showed that the patients with decreased ser-miR34a expression from the end of the second cycle and the end of NACT to before NACT had improved DFS compared with that of the patients with increasing ser-miR34a expression (P < 0.001 for both). Cox regression analyses showed that the changes of ser-miR34a expression were independent prognostic indicators. Conclusions: Ser-miR34a is a novel, noninvasive predictive marker for NACT response and prognosis in breast cancer patients. © 2017 Published by Elsevier Masson SAS.

Keywords: Breast cancer Serum miR34a Neoadjuvant chemotherapy Prognosis

1. Introduction

Abbreviations: NACT, neoadjuvant chemotherapy; miRNA, microRNA; sermiRNA, serum miRNA; ser-miR34a, serum miR34a; DFS, disease-free survival; TEC, docetaxel (taxotere), epirubicin and cytoxan (cyclophosphamine); CR, complete response; PR, partial response or progestrone receptor; SD, stable disease or standard deviations; PD, progressive disease; ER, estrogen receptor; HER2, human epidermal growth factor receptor-2; qRT-PCR, quantitative reverse transcriptase-polymerase chain reaction; BL, baseline; FEN, the first evaluation during NACT; SEN, the second evaluation during NACT; ROC, constructed receiver operating characteristic; AUC, the area under the ROC curves. * Corresponding author at: Department of Anatomy, Harbin Medical University, 157 Baojian Road, Harbin, 150081, PR China. ** Corresponding author at: Department of General Surgery, The Second Clinical Hospital, Harbin Medical University, 246 Xuefu Road, Harbin, 150081, PR China. E-mail addresses: [email protected] (Y. Zhang), [email protected] (J. Zhang). 1 These authors contributed equally to this work. http://dx.doi.org/10.1016/j.biopha.2017.01.133 0753-3322/© 2017 Published by Elsevier Masson SAS.

Breast cancer is one of most common malignant cancers in woman worldwide. In recent years, the morbidity from this disease rose rapidly in many countries including China [1,2]. The treatment of breast cancer included surgery, chemotherapy, and endocrine therapy. In recent years, preoperative neoadjuvant chemotherapy (NACT) was used in the management of breast cancer. NACT not only was recommended for inoperable locally advanced breast cancer, but also for early-stage disease. Apart from reducing the tumor size and eliminating micrometastasis, NACT can increase the rates of breast conserving surgery and enable surgery for inoperable advanced breast cancer. Although the use of NACT has greatly improved the treatment effects of breast cancer, some patients have little benefit because of chemotherapy resistance [3]. Currently, there is no effective method for predicting chemotherapy response. Therefore, it is critical to identify noninvasive and

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specific markers for estimating the benefits from NACT at early stages of treatment. The use of specific markers can provide benefits for the individualization of management and to avoid unnecessary treatments. MicroRNA (miRNA) can negatively regulate gene expression by specifically binding to the 30 untranslated region of target mRNAs [4]. The miRNAs are involved in tumorigenesis, metastasis, treatment, and prognosis of cancer [5,6]. In recent years, some studies have reported miRNAs related to drug resistance of breast cancer, such as miR221, miR222, miR125, and miR34a [7–9]. Notably, miRNAs are stably present in circulating blood, and serve as biomarkers for the diagnosis and monitoring of treatment responses for breast cancer [10]. Although miR34a has been reported to be related to drug resistance in breast cancer tissues and cell lines, there have been few studies identifying the role of circulating miR34a in chemotherapeutic responses for breast cancer [9,11–13]. The purpose of this study was to investigate the predictive values of serum miR34a (ser-miR34a) expression for treatment responses and prognoses in breast cancer patients receiving NACT.

before the start of chemotherapy through day 2, 7.5 mg of oral dexamethasone was given twice a day. All patients received six cycles of NACT for a 21-day cycle. Twenty healthy adult women (as controls) were included in this study. Informed consent was obtained from all participants and the study protocol was approved by the Ethics Committee of Harbin Medical University. Survival data was available for all 86 patients. The median followup period after surgery was 26 months (range, 11–36 months). Six mL of venous blood was drawn from the antecubital area from every patient before the start, at the end of the second cycle, and at the end of NACT. 2.2. Evaluation of chemotherapeutic efficacy The tumors were evaluated using chest and abdomen computerized tomography (CT)-scans and X-rays. Chemotherapeutic responses were assessed by the Response Evaluation Criteria in Solid Tumors [14]. Patients were regarded as responders if a complete response (CR) or partial response (PR) were achieved, while that were considered non-responders if stable disease (SD) or progressive disease (PD) were achieved.

2. Materials and methods 2.3. Preparation of serum and extraction of total RNA 2.1. Patients and blood samples This study recruited 86 diagnosed stage II/III primary breast cancer patients treated between January 2012 and June 2013 at the Department of Breast Surgery of Second Clinical Hospital, Harbin Medical University, Harbin, Heilonjiang, China. HER2 status of all the patients included in this study was negative. All the patients were treated with preoperative NACT with 75 mg/m2 docetaxel (taxotere), 75 mg/m2 epirubicin, and 500 mg/m2 cytoxan (cyclophosphamine) on day 1 (known as the TEC regimen). On the day

Whole blood was left at room temperature for 2 h, and then centrifuged for 20 min at 1900g. The upper serum layer was transferred to a new tube and stored at 80  C. The miRNeasy Serum/Plasma Kit (Qiagen, Hilden, Germany) was used to isolate total RNA from patients’ serum according to the manufacturer’s instructions. The extracted total RNA was eluted in 14 mL of RNAsefree water and was measured using the Nanodrop1-1000 (Thermo Scientific, Waltham, MA, USA). The RNA samples were stored at 80  C until use.

Table 1 Clinicopathologic characteristic and baseline ser-miR34a expression of breast cancer patients. Characteristic

n

Ser-miR34a expression

P

Age (years) 44.3 (34–78)

40 <40

27 59

5.83  3.04 5.78  2.71

0.937

Histological type

Invasive ductal carcinoma Others

73 13

5.84  2.85 5.54  2.59

0.731

Differentiation

Well Moderate Poor

26 42 18

5.99  3.22 5.54  2.36 6.10  3.20

0.713

Stage

II III

43 43

6.01  3.02 5.57  2.59

0.467

Lymph node matastasis

Positive Negative

45 41

5.73  2.90 5.86  2.73

0.828

ER status

Positive Negative

69 17

6.00  2.89 4.95  2.30

0.166

PR status

Positive Negative

57 29

6.01  3.09 5.38  2.11

0.330

HER2 stutus

Positive Negative

0 86

– 5.79  1.06

–

Menopausal status

Premenopause Postmenopause

37 49

5.95  3.17 5.68  2.52

0.662

Chemotherapy response

CR PR SD PD

18 37 26 5

5.56  2.56 5.95  2.65 5.67  3.28 5.45  2.81

0.826

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2.4. Quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) Thirty nanograms of total RNA were reverse transcribed using specific miR34a primers according to the instructions of the PrimeScriptTM RT reagent Kit (Clontech, Mountain View, CA, USA). The qRT-PCR was performed using the SYBR1 Premix Ex TaqTM II (Takara Biotechnologies Inc., Tokyo, Japan) on the Agilent Technologies (Santa Clara, CA, USA) Stratagene Mx3000P. Thermal cycling was performed as follows: 95  C for 30 s, then 40 cycles of 95  C for 5 s, and 60  C for 30 s. The expression of serum miR16 has high stability across normal individuals and cancer patients [15,16]. Therefore, miR16 levels were used to normalize the expression of ser-miR34a. The relative expression levels of sermiR34a were calculated using the 2 DDCt method. The DCt = the Ct value of miR34a minus the Ct value of miR16, and the DDCt = the Ct value of breast cancer patients minus the average Ct value of healthy volunteers.

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characteristics. We constructed receiver operating characteristic (ROC) curves and calculated the area under the ROC curves (AUC) to evaluate the predictive power of ser-miR34a for the NACT response. Survival analyses were performed using the Kaplan– Meier method and Cox proportional hazards model. A P value of <0.05 was considered statistically significant. 3. Results 3.1. Expression of ser-miR34a in breast cancer patients and healthy volunteers The qRT–PCR results confirmed that the expression of sermiR34a in breast cancer patients before the start of NACT (5.79  2.80) was significant higher than that of the healthy women (1.06  0.33) (P < 0.001). A comparison between clinicopathological parameters and ser-miR34a expression is shown in Table 1. There was no significant relationship between the expression of ser-miR34a and clinicopathological parameters.

2.5. Statistical analyses All experiments were performed independently at least in triplicate and the results were analyzed with SPSS 18.0 software (SPSS, Chicago, IL, USA). Data were expressed as the means  standard deviations (SD). The means of ser-miR34a expression between groups were compared using the t-test and one-way analysis of variance. The chi-squared test was used to identify the associations of ser-miR34a expression with clinicopathological

3.2. Changes of ser-miR34a expression during NACT correlated with treatment response After NACT, of 86 patients receiving NACT, 18 patients had CR, 37 PR, 26 SD, and 5 had PD. Therefore, 55 patients were responders and 31 were non-responders. The expression of ser-miR34a in the responding and non-responding patients before the start of NACT (Baseline, BL), at the end of the second cycle (the first evaluation

Fig. 1. Mean serum miR34a expression in responding and non-responding patients during the NACT. a. Mean serum of miR34a expression in responding and non-responding patients at BL, FEN and SEN. b, c, e, f. Changes in serum miR34a expression from BL to FEN and from BL to SEN in every patient. Black lines: decreased ser-miR34a level, red lines: increased ser-miR34a level. d. Changes in serum miR34a expression from BL to FEN and from BL to SEN in responding and non-responding patients, *P < 0.05, **P < 0.01.

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Table 2 Expression level changes of miR34a from BL to FEN and from BL to SEN in the responders and non-responders. BL (SD)

FEN (SD)

SEN (SD)

P

Change from BL to FEN (SD)

P

Change from BL to SEN (SD)

P

Responders

5.82 (2.60)

4.63 (2.55)

4.27 (2.45)

1.23 (1.28)

<0.001

1.58 (1.46)

<0.001

Non-responders

5.73 (3.17)

5.60 (3.19)

5.48 (3.18)

0.016a 0.002b 0.872a 0.748b

a b

0.13 (1.25)

0.26 (1.40)

FEN compared to BL. SEN compacred to BL.

during NACT, FEN), and at the end of NACT (the second evaluation during NACT, SEN) was evaluated by qRT-PCR. The results showed no significant statistical difference in mean expression levels of ser-miR34a in the responding and non-responding patients at BL, FEN, and SEN (Fig. 1a). However, the changes of ser-miR34a expression during NACT were significantly associated with the chemotherapeutic responses. At FEN, of 55 responders, 48 had decreased expression of ser-miR34a compared with that at BL. However, of 31 non-responders, only 9 patients had decreased expression of ser-miRNA, and a significant difference was found in the two response groups (P < 0.001, Fig. 1b and c). The mean expression level of ser-miR34a at FEN (4.63  2.55) was significantly lower than at BL (5.82  2.60) in the responding patients (P = 0.016). However, there was no significant difference in the nonresponding patients (5.60  3.19 versus 5.73  3.17) (Fig. 1d). In addition, the change of ser-miR34a expression from BL to FEN was 1.23  1.28 in the responding patients compared with 0.13  1.25 in the non-responding patients (P < 0.001) (Table 2). The results from SEN were similar as FEN. At SEN, of 55 responders, 48 had decreased expression of ser-miR34a compared with that at BL. However, of 31 non-responders, only 11 had decreased expression, and a significant difference was found in the two response groups (P < 0.001, Fig. 1e and f). The mean level of ser-miR34a at SEN (4.27  2.45) was significantly lower than at BL (5.82  2.60) in the responders (P = 0.002), however, there was no significant difference in non-responders (5.48  3.18 versus 5.73  3.17) (Fig. 1d). In addition, the change of ser-miR34a expression from BL to SEN was 1.58  1.46 in the responders compared with 0.26  1.40 in the non-responders (P < 0.001) (Table 2). These results indicated that the changes of ser-miR34a expression during NACT could predict the treatment response.

3.3. The predictive power of changes in ser-miR34a expression for use with the NACT response To evaluate the predictive power of the changes in ser-miR34a expression for treatment responses, the ROC curves were constructed and AUCs were calculated. The AUC for changes in ser-miR34a expression from BL to FEN and from BL to SEN were 0.816 and 0.808, respectively (P < 0.001 for both, Fig. 2). These results indicated that the changes in ser-miR34a expression during NACT discriminated between the responders and non-responders with high accuracy. 3.4. The changes in ser-miR34a expression correlated with the diseasefree survival (DFS) of patients with primary breast cancer receiving NACT Survival analyses were used to determine the prognoses values of ser-miR34a expression. Ser-miR34a expression at BL, FEN, and SEN showed no significant relationship with the DFS. In contrast, the changes in ser-miR34a expression from BL to FEN and from BL to SEN were significantly associated with the DFS. The patients with decreased ser-miR34a expression from BL to FEN and from BL to SEN had favorable DFSs compared with those with increasing ser-miR34a expression (P < 0.001 for both, Fig. 3). To confirm if changes in ser-miR34a expression were independent prognostic indicators, Cox regression analyses were carried out. Univariate analyses revealed that five variables (TNM stage, lymph node metastasis, chemotherapy response status, change of ser-miR34a from BL to FEN, and change of ser-miR34a from BL to SEN) were significantly associated with DFS, while multivariate analyses showed that only changes of ser-miR34a from BL to FEN

Fig. 2. ROC curve analysis based on the changes of ser-miR34a expression (a) from BL to FEN and (b) from BL to SEN for the discrimination between responding and nonresponding patients.

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Fig. 3. Kaplan-Meier survival analysis for DFS depending on the changes of ser-miR34a expression (a) from BL to FEN and (b) from BL to SEN.

and from BL to SEN were independent prognostic indicators for DFS (Table 3). 4. Discussion Several studies on breast cancer tissues and cell lines have reported that miR34a was associated with proliferation, apoptosis, drug resistance, diagnosis, and prognosis. However, there was a great discrepancy in the roles of miR34a across these studies. Yang [17] found that miR34a was a metastasis suppressor. The expression of miR34a was significantly decreased in metastatic breast cancer cells and primary breast cancer with lymph node metastasis. In contrast, overexpression of miR34a inhibited breast cancer cell migration and invasion in vitro and distal metastasis in vivo. Agarwal [18] showed that miR34a was a breast cancer suppressor gene, and the patients with less expression of miR34a had a worse DFS. Park [11] reported that the miR34a expression was downregulated in doxorubicin-resistant MCF-7 cells compared with that of normal MCF7 cells, and that miR34a overexpression increased the sensitivity to doxorubicin. The results in prostatic cancer [19], colorectal cancer [20], and Ewing's sarcoma [21] were similar with these studies. However, additional studies showed opposite results. Kastl [12] reported that docetaxel resistance in MCF-7 and MDA-MB231 cells was associated with increased expression of miR34a. Dutta [22] showed that miR34a was overexpressed in some human cancers, and knockdown of

miR34a significantly inhibited proliferation in rat renal carcinoma cells, HeLa cells, and MCF-7 cells. Altogether, these results demonstrated the complexity of miR34a influences on breast cancer. However, it is necessary to further study the mechanism of miR34a action in a larger patient cohort. Circulating microRNAs can be stably present in the blood, and are characterized by their non-invasiveness, constant presence, and use to dynamically monitor the disease. Therefore, microRNAs possess great potential in cancer detection, prognosis, and in predicting chemotherapy responses. In recent years, several studies have demonstrated the roles of circulating miR34a in breast cancer; however, to date the conclusions have been controversial. Hagrass [23] showed that ser-miR34a expression was significantly downregulated in breast cancer patients compared with that of healthy controls. In addition, it was significantly more decreased in patients with distant metastasis than in those without metastasis. These results were consistent with Bommer et al., using non-small cell lung cancer [24]. However, Roth [25] reported that ser-miR34a expression was significantly higher in M1 stage breast cancer patients than in normal controls. Some circulating miRNAs have been reported to be associated with NACT responses in breast cancer. Gu [26] showed that the ser-miR451 expression level was significantly lower in the drug resistant group compared with that of the sensitive group in breast cancer patients receiving NACT with a epirubicin/docetaxel regimen. Wu [27] reported lower levels of ser-miR375 and higher levels of ser-

Table 3 Cox proportional hazards models analysis for DFS in breast cancer patients. Univariate analysis

Age Histological type Differentiation TNM stage Lymph node metastasis ER expression PR expression Menopausal status Chemotherapy response status Ser-miR34a expression at BL Ser-miR34a expression at FEN Ser-miR34a expression at SEN Changes of Ser-miR34a from BL to FEN Changes of Ser-miR34a from BL to SEN Bold values indicate P < 0.05.

Multivariate analysis

HR

95% CI

P

1.738 0.655 1.269 2.303 2.406 1.766 0.616 1.873 0.245 1.101 1.014 1.701 0.075 0.076

0.792–3.815 0.287–1.496 0.802–2.006 1.163–4.560 1.199–4.827 0.686–4.541 0.317–1.196 0.921–3.808 0.124–0.484 0.563–2.153 0.514–2.002 0.876–3.304 0.034–0.164 0.036–0.160

0.168 0.316 0.309 0.017 0.013 0.238 0.152 0.083 <0.001 0.778 0.968 0.117 <0.001 <0.001

HR

95% CI

P

0.298 3.455

0.036–2.489 0.420–28.450

0.264 0.249

1.138

0.507–2.557

0.754

0.185 0.211

0.061–0.567 0.074–0.601

0.003 0.004

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miR122 significantly correlated with both breast cancer relapse and resistance to NACT with a docetaxel/doxorubicin/cyclophosphamide combined with trastuzumab regimen. Our present results showed that levels of ser-miR34a at BL, FEN, and SEN were not related to NACT responses. However, the dynamic changes of sermiR34a expression during NACT were related to chemotherapy responses. The results indicated that the patients with decreased levels of ser-miR34a during NACT had a better treatment response than those with increased levels. The survival analysis results showed patients with decreased levels of ser-miR34a during NACT had a better DFS than those with increased levels. Notably, ROC curves showed that the change of ser-miR34a from BL to FEN had a good discrimination power between responders and non-responders with high accuracy. This indicated that the change of sermiR34a expression could predict the treatment effects at the early stages of NACT. In addition, our results showed that the changes of ser-miR34a levels reflected a dynamic process in breast cancer, and therefore could be used to monitor disease recurrence after NACT and mammectomy. A recent study has reported that the change of circulating microRNA levels was related to chemotherapy effects. Hansen [28] showed that a decreased ser-miR126 level was associated with good chemotherapeutic responses and with a favorable prognosis for patients with metastatic colorectal cancer treated with first-line chemotherapy combined with bevacizumab. The mechanism of this phenomenon could be related to the close relationship between miR126 and vascular endothelial cells, which are targets of bevacizumab action. Our results showed that mean levels of ser-miR34a in healthy controls were significantly lower than that in breast cancer patients, and that the levels of sermiR34a in the NACT responders were decreased. However, it is still unclear whether this phenomenon is due to the death of cancer cells in the responders. The details of this mechanism need to be studied in the future. Our study had some limitations. The patients collected in our study were from China therefore our present study did not evaluate the marker in different ethnic populations. This limited the determination of its potential use as a marker in different populations. In addition, the biological characteristics of breast cancer to a great extent were affected by molecular subtypes [29]. Therefore, the contradictory conclusions from previous studies may, in part, be due to the variety of molecular subtypes of the patients. Further studies according to molecular subtypes are therefore necessary. Finally, this study used the TEC chemotherapy regimen, and further verification using different chemotherapy regimens is necessary. In conclusion, the present study identified a novel non-invasive marker for breast cancer. Dynamic monitoring of the expression of ser-miR34a can predict the treatment effects of NACT and DFS. The results may provide benefits for personalized management and more effective administration of NACT in breast cancer. Conflict of interest The authors declare that they have no conflicts of interest. Fundings The project sponsored by National Natural Science Foundation of China (Grant number 81372838) and the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry. Ethical approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the

institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. References [1] R.L. Siegel, K.D. Miller, A. Jemal, Cancer statistics, 2016, CA Cancer J. Clin. 66 (2016) 7–30. [2] W. Chen, R. Zheng, P.D. Baade, S. Zhang, H. Zeng, F. Bray, A. Jemal, X.Q. Yu, J. He, Cancer statistics in China, 2015, CA Cancer J. Clin. 66 (2016) 115–132. [3] M.C. Casey, K.J. Sweeney, J.A. Brown, M.J. Kerin, Exploring circulating microRNA in the neoadjuvant treatment of breast cancer, Int. J. Cancer 139 (2016) 12–22. [4] D.P. Bartel, MicroRNAs: genomics, biogenesis, mechanism, and function, Cell 116 (2004) 281–297. [5] F.J. Nassar, R. Nasr, R. Talhouk, MicroRNAs as biomarkers for early breast cancer diagnosis, prognosis and therapy prediction, Pharmacol. Ther. (2016), doi: http://dx.doi.org/10.1016/j.pharmthera.2016.11.012. [6] H.T. Liu, P. Gao, The roles of microRNAs related with progression and metastasis in human cancers, Tumour Biol. (2016), doi:http://dx.doi.org/ 10.1007/s13277-016-5436-9. [7] I.P. Pogribny, J.N. Filkowski, V.P. Tryndyak, A. Golubov, S.I. Shpyleva, O. Kovalchuk, Alterations of microRNAs and their targets are associated with acquired resistance of MCF-7 breast cancer cells to cisplatin, Int. J. Cancer 127 (2010) 1785–1794. [8] M. Zhou, Z. Liu, Y. Zhao, Y. Ding, H. Liu, Y. Xi, W. Xiong, G. Li, J. Lu, O. Fodstad, A.I. Riker, M. Tan, MicroRNA-125b confers the resistance of breast cancer cells to paclitaxel through suppression of pro-apoptotic Bcl-2 antagonist killer 1 (Bak1) expression, J. Biol. Chem. 285 (2010) 21496–21507. [9] G.Q. Chen, Z.W. Zhao, H.Y. Zhou, Y.J. Liu, H.J. Yang, Systematic analysis of microRNA involved in resistance of the MCF-7 human breast cancer cell to doxorubicin, Med. Oncol. 27 (2010) 406–415. [10] D.P. Joyce, M.J. Kerin, R.M. Dwyer, Exosome-encapsulated microRNAs as circulating biomarkers for breast cancer, Int. J. Cancer 139 (2016) 1443–1448. [11] E.Y. Park, E. Chang, E.J. Lee, H.W. Lee, H.G. Kang, K.H. Chun, Y.M. Woo, H.K. Kong, J.Y. Ko, H. Suzuki, E. Song, J.H. Park, Targeting of miR-34a-NOTCH1 axis reduced breast cancer stemness and chemoresistance, Cancer Res. 74 (2004) 7573– 7582. [12] L. Kastl, I. Brown, A.C. Schofield, miRNA-34a is associated with docetaxel resistance in human breast cancer cells, Breast Cancer Res. Treat. 131 (2012) 445–454. [13] H. Wang, G. Tan, L. Dong, L. Cheng, K. Li, Z. Wang, H. Luo, Circulating MiR-125b as a marker predicting chemoresistance in breast cancer, PLoS One 7 (2012) e34210. [14] P. Therasse, S.G. Arbuck, E.A. Eisenhauer, J. Wanders, R.S. Kaplan, L. Rubinstein, J. Verweij, M. Van Glabbeke, A.T. van Oosterom, M.C. Christian, S.G. Gwyther, 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. 92 (2009) 205–216. [15] H.M. Heneghan, N. Miller, A.J. Lowery, K.J. Sweeney, J. Newell, M.J. Kerin, Circulating microRNAs as novel minimally invasive biomarkers for breast cancer, Ann. Surg. 251 (2010) 499–505. [16] C. Roth, B. Rack, V. Muller, W. Janni, K. Pantel, H. Schwarzenbach, Circulating microRNAs as blood-based markers for patients with primary and metastatic breast cancer, Breast Cancer Res. 12 (2010) R90. [17] S. Yang, Y. Li, J. Gao, T. Zhang, S. Li, A. Luo, H. Chen, F. Ding, X. Wang, Z. Liu, MicroRNA-34 suppresses breast cancer invasion and metastasis by directly targeting Fra-1, Oncogene 32 (2013) 4294–4303. [18] S. Agarwal, J. Hanna, M.E. Sherman, J. Figueroa, D.L. Rimm, Quantitative assessment of miR-34a as an independent prognostic marker in breast cancer, Br. J. Cancer 112 (2015) 61–68. [19] S. Singh, D. Chitkara, R. Mehrazin, S.W. Behrman, R.W. Wake, R.I. Mahato, Chemoresistance in prostate cancer cells is regulated by miRNAs and Hedgehog pathway, PLoS One 7 (2012) e40021. [20] M. Rokavec, M.G. Öner, H. Li, R. Jackstadt, L. Jiang, D. Lodygin, M. Kaller, D. Horst, P.K. Ziegler, S. Schwitalla, J. Slotta-Huspenina, F.G. Bader, F.R. Greten, H. Hermeking, IL-6R/STAT3/miR-34a feedback loop promotes EMT-mediated colorectal cancer invasion and metastasis, J. Clin. Invest. 124 (2014) 1853– 1867. [21] F. Nakatani, M. Ferracin, M.C. Manara, S. Ventura, V. Del Monaco, S. Ferrari, M. Alberghini, A. Grilli, S. Knuutila, K.L. Schaefer, G. Mattia, M. Negrini, P. Picci, M. Serra, K. Scotlandi, miR-34a predicts survival of Ewing's sarcoma patients and directly influences cell chemo-sensitivity and malignancy, J. Pathol. 226 (2012) 796–805. [22] K.K. Dutta, Y. Zhong, Y.T. Liu, T. Yamada, S. Akatsuka, Q. Hu, M. Yoshihara, H. Ohara, M. Takehashi, T. Shinohara, H. Masutani, J. Onuki, S. Toyokuni, Association of microRNA-34a overexpression with proliferation is cell typedependent, Cancer Sci. 98 (2007) 1845–1852. [23] H.A. Hagrass, S. Sharaf, H.F. Pasha, E.A. Tantawy, R.H. Mohamed, R. Kassem, Circulating microRNAs – a new horizon in molecular diagnosis of breast cancer, Genes Cancer 6 (2015) 281–287. [24] G.T. Bommer, I. Gerin, Y. Feng, A.J. Kaczorowski, R. Kuick, R.E. Love, Y. Zhai, T.J. Giordano, Z.S. Qin, B.B. Moore, O.A. MacDougald, K.R. Cho, E.R. Fearon,

B. Liu et al. / Biomedicine & Pharmacotherapy 88 (2017) 911–917 p53-mediated activation of miRNA34 candidate tumor-suppressor genes, Curr. Biol. 17 (2007) 1298–1307. [25] C. Roth, B. Rack, V. Müller, W. Janni, K. Pantel, H. Schwarzenbach, Circulating microRNAs as blood-based markers for patients with primary and metastatic breast cancer, Breast Cancer Res. 12 (2010) R90. [26] X. Gu, J.Q. Xue, S.J. Han, S.Y. Qian, W.H. Zhang, Circulating microRNA-451 as a predictor of resistance to neoadjuvant chemotherapy in breast cancer, Cancer Biomark. 16 (2016) 395–403. [27] X. Wu, G. Somlo, Y. Yu, M.R. Palomares, A.X. Li, W. Zhou, A. Chow, Y. Yen, J.J. Rossi, H. Gao, J. Wang, Y.C. Yuan, P. Frankel, S. Li, K.T. Ashing-Giwa, G. Sun, Y.

917

Wang, R. Smith, K. Robinson, X. Ren, S.E. Wang, De novo sequencing of circulating miRNAs identifies novel markers predicting clinical outcome of locallyadvanced breast cancer, J. Transl. Med. 10 (2012) 42. [28] T.F. Hansen, A.L. Carlsen, N.H. Heegaard, F.B. Sørensen, A. Jakobsen, Changes in circulating microRNA-126 during treatment with chemotherapy and bevacizumab predictstreatment response in patients with metastatic colorectal cancer, Br. J. Cancer 112 (2015) 624–629. [29] X. Dai, T. Li, Z. Bai, Y. Yang, X. Liu, J. Zhan, B. Shi, Breast cancer intrinsic subtype classification, clinical use and future trends, Am. J. Cancer Res. 5 (2015) 2929– 2943.