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Increased levels of LAPTM4B, VEGF and survivin are correlated with tumor progression and poor prognosis in breast cancer patients

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Oncotarget. 2017; 8:41282-41293. https://doi.org/10.18632/oncotarget.17176

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Sha Li, Lu Wang, Yue Meng, Yanli Chang, Jianjun Xu and Qingyun Zhang _

Abstract

Sha Li1, Lu Wang1, Yue Meng1, Yanli Chang1, Jianjun Xu1 and Qingyun Zhang1

1Department of Clinical Laboratory, Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital & Institute, Beijing 100142, China

Correspondence to:

Qingyun Zhang, email: zhqy_208@163.com

Keywords: breast cancer, LAPTM4B, VEGF, survivin, prognosis

Abbreviations: LAPTM4B, lysosome-associated protein transmembrane-4 beta; VEGF, vascular endothelial growth factor; OS, overall survival; PFS, progression-free survival

Received: December 10, 2016     Accepted: March 27, 2017     Published: April 18, 2017

ABSTRACT

Objective: This study explored the relationships among the expression of LAPTM4B, VEGF, and survivin and clinicopathological characteristics and prognosis in breast cancer patients.

Methods: The expression of these three molecules in 110 stage I-III breast cancer patients with clinicopathological and follow-up data was detected via immunohistochemistry. Kaplan-Meier and Cox proportional hazard regression analyses were performed to assess the prognostic significance of these markers in breast cancer. Moreover, expression levels of these markers were evaluated in 5 breast cell lines via Western blot analysis.

Results: LAPTM4B, VEGF, and survivin were over-expressed in breast cancer specimens and highly expressed in MDA-MB-231 cells. VEGF and nuclear survivin expression was significantly correlated with LAPTM4B expression, and high levels of all three were associated with a tumor size >2cm, TNM stage II+III and lymph node metastasis, which had worse impacts on overall survival and progression-free survival in breast cancer patients. A multivariate Cox analysis identified LAPTM4B over-expression as an independent prognostic marker in breast cancer.

Conclusions: These findings suggest that LAPTM4B, VEGF, and nuclear survivin expression are significantly correlated in breast cancer, which may be predictive of prognosis as well as effective therapeutic targets for new anticancer therapies.


Increased levels of LAPTM4B, VEGF and survivin are correlated with tumor progression and poor prognosis in breast cancer patients | Li | Oncotarget

INTRODUCTION

Breast cancer is one of the most common cancers among women, and epidemiological statistics show that the incidence of this disease and its associated mortality are increasing yearly [1]. The identification of key genes that determine progression and metastasis in breast cancer is urgently needed for early diagnoses and molecular targeted therapies.

Lysosome-associated protein transmembrane-4 beta (LAPTM4B), a novel oncogene that belongs to the mammalian 4-tetra-transmembrane spanning protein superfamily, was initially identified in human hepatocellular carcinoma [2, 3]. Previous studies showed that LAPTM4B-35 activity was elevated in various malignant tumors, which was associated with poor prognosis [46]. Moreover, it was indicated that LAPTM4B could increase the proliferation and metastasis of tumor cells, reduce apoptosis, and assist drug resistance, which involved in activated PI3K/AKT and Ras-MAPK signaling pathways [7].

Angiogenesis is an important feature of carcinogenesis, progression and metastasis in many human malignancies. Vascular endothelial growth factor (VEGF) is thought to be a major mediator of angiogenesis that promotes the proliferation of tumor cells and boosts invasion and metastasis via the activation of the PI3K/AKT pathway [810]. The vascular density of tumors, including breast cancer, has been proven to be closely correlated with prognosis [11].

Survivin is a 16.5-kDa intracellular protein that is a well-known member of the inhibitor of apoptosis protein family, and its expression is elevated in the majority of tumors [12]. It potentially facilitates cell cycle processes and cell division and reduces apoptotic indices, which is strongly related with poor prognosis in breast cancer [13, 14]. Transcription from the survivin gene locus gives rise to 5 splice variants [15]. The relation of the splicing variants with prognosis is currently unclear.

Interestingly, a previous study revealed that tissues with elevated expression of LAPTM4B had significantly more new capillary blood vessels than tissues with reduced expression in a mouse xenograft model of liver cancer, indicating that LAPTM4B over-expression might be significantly associated with increased angiogenic activity [16]. Recent studies have also shown that silencing LAPTM4B remarkably reduces the expression of VEGF in HeLa cells [17] and that increased LAPTM4B-35 combined with positive VEGF expression might serve as a new biological marker to predict outcomes in cervical carcinoma [18]. In addition, it has been proven that the upregulation of LAPTM4B-35 promotes the activation of AKT and Bad, which would maintain cell survival [16].

The correlations among LAPTM4B, VEGF, and survivin have not been investigated in breast cancer. Therefore, we performed a retrospective study including 110 breast cancer patients who underwent surgical resection, primarily exploring relationships among the expression of these three markers, clinical variables and survival.

RESULTS

Expression of LAPTM4B, VEGF, and survivin

Statistical analyses showed that the expression of these three markers was significantly elevated in breast cancer specimens (P<0.05) (Table 1). As shown in Figure 1a-1k, LAPTM4B and VEGF protein staining were localized in the cytoplasm. Survivin staining differed among the cases: 63 cases (57.27%) showed expression only in the nucleus, 21 (19.09%) only in the cytoplasm, and 17 (15.45%) in both the nucleus and cytoplasm. Additionally, high VEGF and nuclear survivin protein expression were linearly correlated with that of LAPTM4B (P<0.001), as shown in Table 2.

Table 1: Expression of LAPTM4B, VEGF and survivin in breast tissue specimens

Groups

N

LAPTM4B expression

Pa

VEGF expression

Pa

Survivin expression

Pa

High expression

%

High expression

%

High expression

%

Benign breast tumor

10

1

10

0.013*

1

10

0.007*

3

30

0.038*

Breast cancer

110

62

56.3

66

60.0

75

68.1

aCalculated by χ2 test.

*P < 0.05.

Table 2: Correlations among LAPTM4B, VEGF and survivin in 110 breast cancer patients

Total no.

LAPTM4B

Pa

Low expression

High expression

VEGF

< 0.001*

Total no.

110

48

62

Low expression

44

14

52

High expression

66

34

10

Nuclear survivin

< 0.001*

Total no.

89

35

54

Low expression

27

12

50

High expression

62

23

4

Cytoplasmic survivin

0.103

Total no.

47

33

14

Low expression

22

15

10

High expression

25

18

4

aCalculated by χ2 test.

*P < 0.001.

Representative pictures by immunohistochemistry for LAPTM4B, VEGF, and survivin in 110 breast cancer patients.

Figure 1: Representative pictures by immunohistochemistry for LAPTM4B, VEGF, and survivin in 110 breast cancer patients. LAPTM4B expression: (a) low expression in benign breast tumor specimens, (b) low expression in breast cancer, (c) high expression in breast cancer. VEGF expression: (d) low expression in benign breast tumor specimens, (e) low expression in breast cancer, (f) high expression in breast cancer. Survivin expression: (g) low expression in benign breast tumor specimens, (h) low nuclear expression in breast cancer, (i) high nuclear expression in breast cancer, (j) only cytoplasmic expression in breast cancer, (k) both nuclear and cytoplasmic expression in breast cancer. (a–k, original magnification, ×200).

Figure 2a shows that LAPTM4B, VEGF and survivin expression levels were increased in MDA-MB-231 cells, which were more highly metastatic than the other cell lines. Furthermore, we extracted the nuclear and cytoplasmic fractions in 5 breast cell lines and found that survivin protein expression was highest in the nuclear fractions of highly malignant MDA-MB-231 cells. For the cytoplasmic protein samples, survivin expression in MDA-MB-231 cells was lower than in the other cell lines (Figure 2b).

LAPTM4B, VEGF, nuclear and cytoplasmic survivin protein expression in breast cell lines by Western blot analysis.

Figure 2: LAPTM4B, VEGF, nuclear and cytoplasmic survivin protein expression in breast cell lines by Western blot analysis. Protein samples were obtained from 5 breast cell lines (MDA-MB-231, ZR-75-1, T47D, MCF-7 and MCF-10A). (a) β-Actin was used as an internal control for the total protein. High expression of LAPTM4B, VEGF and survivin was detected in MDA-MB-231 cells. (b) Histone H3 and β-Actin were used as an internal control for the nuclear and cytoplasmic protein samples, respectively. High levels of survivin were expressed in the nuclear protein of MDA-MB-231 cells.

Relationships between LAPTM4B, VEGF, and survivin protein expression and clinicopathological factors in breast cancer patients

As shown in Table 3, high levels of LAPTM4B, VEGF, and nuclear survivin were found in cases where factors related to tumor progression were present, such as tumor sizes >2 cm, TNM stage II+III and lymph node metastasis. Moreover, there was a significantly positive correlation between LAPTM4B and VEGF expression levels and the probability of tumor-associated venous thrombus (P=0.012 and P<0.001, respectively).

Table 3: Associations between the expression levels of LAPTM4B, VEGF and survivin and clinicopathological factors in 110 breast cancer patients

Characteristics

LAPTM4B expression

Pa

VEGF expression

Pa

Nuclear survivin expression

Pa

Cytoplasmic survivin expression

Pa

High/Low

High/Low

High/Low

High/Low

Patient No.

62/48

66/44

62/27

25/22

Age (years)

0.290

0.936

0.424

0.344

≤55

21/21

25/17

22/12

8/10

>55

41/27

41/27

40/15

17/12

Menopausal status

0.178

0.507

0.279

0.351

Pre-menopausal

17/19

20/16

18/11

7/9

Post-menopausal

45/29

46/28

44/16

18/13

Tumor size (cm)

<0.001*

<0.001*

0.001*

0.355

≤2

8/24

11/21

13/15

6/8

>2

54/24

55/23

49/12

19/14

Histological type

0.607

0.350

0.873

0.280

IDC

55/41

56/40

52/23

22/22

Others

7/7

10/4

10/4

3/0

Histological grade

0.053

0.089

0.230

0.697

G1

5/10

6/9

8/7

2/2

G2/G3

57/38

60/35

54/20

23/20

TNM stage

<0.001*

<0.001*

0.001*

0.355

I

6/23

9/20

11/14

6/8

II/III

56/25

57/24

51/13

19/14

Lymph node metastasis

<0.001*

<0.001*

<0.001*

0.072

No

16/33

20/29

19/19

13/17

Yes

46/15

46/15

43/8

12/5

Tumor thrombus in vena

0.012*

<0.001*

0.607

0.058

No

38/40

38/40

45/21

14/18

Yes

24/8

28/4

17/6

11/4

ER status

0.121

0.234

0.077

0.137

Negative

15/6

15/6

12/2

8/3

Positive

47/42

51/38

50/25

17/19

PR status Negative

20/14

0.727

22/12

0.656

18/8

0.954

10/8

0.798

Positive

42/34

44/32

44/19

15/14

Her-2 status

0.130

0.119

0.478

0.556

Negative

44/40

47/37

48/19

20/16

Positive

18/8

19/7

14/8

5/6

Recurrence

0.336

0.044*

0.090

0.855

No

47/40

48/39

45/24

21/19

Yes

15/8

18/5

17/3

4/3

aCalculated by χ2 test.

*P < 0.05.

Univariate and multivariate survival analyses

As shown by the survival analyses, death and recurrence occurred in 12 (10.91%) and 23 cases (20.91%), respectively. The Kaplan–Meier and log-rank tests showed that tumor sizes >2 cm and lymph node metastasis were correlated with poor overall survival (OS) and progression-free survival (PFS) in breast cancer (Table 4; Figures 3 and 4). A more advanced TNM stage was closely associated with a significantly worse PFS. The univariate model indicated that OS and PFS were significantly lower in cases with elevated LAPTM4B, VEGF, and nuclear survivin levels than in cases with lower levels of these molecules.

Table 4: Univariate Kaplan–Meier survival analysis of OS and PFS in 110 breast cancer patients

Variables

N

OS (months)

Pa

PFS (months)

Pa

Mean ± SE

95 % CI

Mean ± SE

95 % CI

Age (years)

0.437

0.366

≤55

42

50.000±1.561

46.941-53.059

48.000±3.121

41.882-54.118

>55

68

46.000±2.257

41.577-50.423

44.000±1.805

40.463-47.537

Menopausal status

0.186

0.183

Pre-menopausal

36

51.000±1.420

48.218-53.782

50.000±2.860

44.394-55.606

Post-menopausal

74

46.000±2.121

41.842-50.158

44.000±1.885

40.306-47.694

Tumor size (cm)

0.027*

0.009*

≤2

32

52.000±1.697

48.674-55.326

52.000±1.697

48.674-55.326

>2

78

45.000±1.778

41.514-48.486

43.000±1.068

40.907-45.093

Histological type

0.613

0.665

IDC

96

48.000±1.854

44.367-51.633

46.000±1.722

42.625-49.375

Others

14

51.000±4.330

42.513-59.487

47.000±6.062

35.118-58.882

Histological grade

0.390

0.333

G1

15

52.000±3.146

45.835-58.165

52.000±1.797

48.477-55.523

G2/G3

95

48.000±1.914

44.248-51.752

44.000±1.499

41.063-46.937

TNM stage

0.077

0.033*

I

29

52.000±2.596

46.911-57.089

52.000±2.596

46.911-57.089

II/III

81

47.000±2.205

42.678-51.322

44.000±0.976

42.087-45.913

Lymph node metastasis

0.021*

0.010*

No

49

51.000±1.916

47.244-54.756

51.000±2.000

47.080-54.920

Yes

61

45.000±1.760

41.550-48.450

44.000±1.439

41.179-46.821

Tumor thrombus in vena

0.366

0.315

No

78

49.000±1.612

45.840-52.160

48.000±1.881

44.313-51.687

Yes

32

47.000±3.339

40.456-53.544

44.000±2.782

38.546-49.454

ER status

0.201

0.190

Negative

21

45.000±1.831

41.411-48.589

43.000±1.144

40.757-45.243

Positive

89

50.000±1.347

47.360-52.640

48.000±1.886

44.304-51.696

PR status

0.841

0.931

Negative

34

47.000±2.328

42.436-51.564

43.000±1.458

40.143-45.857

Positive

76

50.000±1.337

47.379-52.621

48.000±1.743

44.584-51.416

Her-2 status

0.982

0.669

Negative

84

49.000±1.309

46.434-51.566

48.000±1.666

44.735-51.265

Positive

26

45.000±2.550

40.003-49.997

44.000±3.389

37.357-50.643

LAPTM4B

0.004*

0.001*

Low

48

51.000±1.954

41.170-54.830

50.000±1.873

46.329-53.671

High

62

45.000±1.687

41.693-48.307

44.000±0.781

42.470-45.530

VEGF

0.010*

0.003*

Low

44

51.000±1.873

47.329-54.671

51.000±1.561

47.941-54.059

High

66

45.000±1.195

42.658-47.342

44.000±0.446

43.126-44.874

Nuclear survivin

0.022*

0.009*

Low

27

48.000±3.674

40.799-55.201

48.000±3.674

40.799-55.201

High

62

47.000±2.789

41.534-52.466

44.000±0.970

42.099-45.901

Cytoplasmic survivin

0.875

0.868

Low

22

48.000±2.152

43.782-52.218

48.000±2.152

43.782-52.218

High

25

53.000±1.208

50.633-55.367

53.000±3.019

47.083-58.917

OS, overall survival; PFS, progression-free survival; CI, confidence interval.

aLog-rank test.

*P < 0.05.

Kaplan-Meier curves for overall survival in 110 patients with breast cancer.

Figure 3: Kaplan-Meier curves for overall survival in 110 patients with breast cancer. High expression of LAPTM4B (a), VEGF (b) and nuclear survivin (c) was significantly associated with poor overall survival (P = 0.004, 0.01 and 0.022).

Kaplan-Meier curves for progression-free survival in 110 patients with breast cancer.

Figure 4: Kaplan-Meier curves for progression-free survival in 110 patients with breast cancer. The progression-free survival was statistically shorter in groups with elevated expression of LAPTM4B (a), VEGF (b) and nuclear survivin (c) (P = 0.001, 0.003 and 0.009). Expression of cytoplasmic survivin (d) was not related to the progression-free survival.

The multivariate analysis showed that high levels of LAPTM4B were an independent prognostic marker for both OS and PFS in breast cancer (Table 5; P=0.007 and P=0.002, respectively).

Table 5: Multivariate Cox regression analysis of various predictive factors for OS and PFS in 110 breast cancer patients

Variables

OS (months)

PFS (months)

RR

95 % CI

Pa

RR

95 % CI

Pa

Tumor size (cm)

N/A

N/A

N/A

N/A

N/A

N/A

TNM stage

N/A

N/A

N/A

N/A

N/A

N/A

Lymph node metastasis

N/A

N/A

N/A

N/A

N/A

N/A

LAPTM4B

1.730

1.163-2.574

0.007*

1.839

1.239-2.730

0.002*

VEGF

N/A

N/A

N/A

N/A

N/A

N/A

Nuclear survivin

N/A

N/A

N/A

N/A

N/A

N/A

Cytoplasmic survivin

N/A

N/A

N/A

N/A

N/A

N/A

OS, overall survival; PFS, progression-free survival; RR, relative risk; CI, confidence interval.

a Cox regression test.

*P < 0.05.

DISCUSSION

Despite the fact that an increasing number of genes have been discovered and various targeted therapies have also been developed in recent years, the survival rate for breast cancer is not satisfactory [19]. Thus, it is of great importance to identify biomarkers that are effective in helping to improve the prognosis in breast cancer.

A number of studies have shown that the proliferation of cells overexpressing LAPTM4B is closely correlated with tumor progression and metastasis [20, 21]. In our study, increased LAPTM4B expression was strongly associated with prognosis-related features, including tumor size, TNM stage and lymph node metastasis. Further analysis revealed that breast cancer patients with high levels of LAPTM4B protein expression had worse OS and PFS rates.

Our study found that the relationship between VEGF and nuclear survivin expression levels and the expression of LAPTM4B was remarkable. Furthermore, several reports have shown that VEGF could stimulate survivin expression via the PI3K/AKT pathway [22]. This up-regulation of survivin was found to enhance tumor angiogenesis mediated by VEGF [15, 23], suggesting the need for further research into the clinical relevance of these three molecules.

In a further step, strategies should be developed to determine whether the detection of LAPTM4B in combination with other molecules is of diagnostic and prognostic value in assessing breast carcinoma cases. Tang et al. examined LAPTM4B and CD34 proteins in non-small cell lung cancer, and their results revealed that LAPTM4B might promote tumor progression by inducing tumor angiogenesis [24]. Meng et al. indicated that the downregulation of LAPTM4B suppressed tumor migration and invasion and significantly decreased VEGF expression. Subsequently, they verified that the coexpression of LAPTM4B and VEGF resulted in poor prognosis for cervical cancer [17, 18]. Consistent with these findings, our results show that high levels of LAPTM4B and VEGF led to poor clinical outcomes with regard to OS and PFS.

Li et al. revealed that nuclear survivin levels might predict poor survival in breast cancer [25]. The present study indicates that survivin expression is predominantly nuclear rather than cytoplasmic [26], which is line with the majority of previous results. Interestingly, a few reports have indicated that the expression of survivin is nearly equivalent in the nucleus and cytoplasm [27] or only occurs in the cytoplasm [28], which might be attributed to differences in reagents, tissues and clinical stages. In our studies, we separately analyzed the expression of nuclear and cytoplasmic survivin. According to the statistical analyses, nuclear survivin protein expression was dramatically associated with tumor progression and poor survival. Researchers have found LAPTM4B-35 accelerates tumorigenesis in transgenic mice by upregulating the antiapoptotic molecule Bcl-2 and downregulating the proapoptotic molecule Bax. However, the expression of survivin in Ad-AE-infected cells was not altered [16]. Hence, the relationship of the subcellular localization of survivin with other molecules should be further investigated as a greater understanding of this relationship could improve prognostic assessments and individualized therapies.

Fan et al. suggested that LAPTM4B*2 was associated with an increased risk of breast cancer in a cohort of Chinese women [29]. Li et al. demonstrated that MDA-MB-231 cells that had the *2/2 genotype exhibited increased LAPTM4B expression [30]. Similar to these results, our study demonstrated that increased VEGF and nuclear survivin expression occurs in MDA-MB-231 cells.

In conclusion, our findings indicate for the first time that LAPTM4B, VEGF, and survivin protein expression is significantly associated with various clinicopathological characteristics and prognosis in breast cancer patients. In particular, the relation of VEGF and survivin protein levels with the expression of LAPTM4B indicates that they could have clinical potential as promising prognostic markers to identify individuals with poor outcomes and may be regarded as therapeutic targets for breast cancer. However, the limitations in this study included the small sample size and its retrospective nature, such as the limited follow-up time, which could be why the expression of VEGF and survivin was not linked to OS and PFS in the multivariate analysis.

MATERIALS AND METHODS

Patients and tissue samples

Specimens were collected from 110 breast cancer patients with stages I-III and 10 patients with benign breast tumors who underwent surgical resection at the Beijing Cancer Hospital between January 2011 and July 2013. All patients provided written informed consent, and none of the patients received chemotherapy, immunotherapy, or radiotherapy before surgery. The Ethics Committee of Beijing Cancer Hospital approved this protocol. All patients with breast cancer were followed-up for the survival analysis until September 2016 (median, 49 months; range, 10–67 months).

Immunohistochemical staining

Paraffin-embedded samples were cut into four-micrometer sections and stained with hematoxylin and eosin for tumor confirmation. Selected sections were immersed in a retrieval buffer solution for antigen recovery and incubated with a polyclonal rabbit anti-LAPTM4B antibody (dilution 1:200, bs-6542R, Bioss, USA), a polyclonal rabbit anti-VEGF antibody (dilution 1:150, ZA-0509, ZSGB, China) and a monoclonal mouse anti-survivin antibody (dilution 1:2000, produced by our lab) overnight at 4°C. Finally, the slides were stained and mounted. Negative controls were provided by replacing the primary antibodies with normal goat serum.

Staining evaluation

LAPTM4B, VEGF, and survivin protein expression levels were semi-quantitatively classified. The percentage of positive cells was measured as follows: 0, less than 9% staining; 1, 10% to 25% staining; 2, 26%-50% staining; 3, 51%-75% staining and 4, >75% staining. The staining intensity was evaluated as follows: 0, no staining; 1, weak staining; 2, moderate staining; 3, strong staining. The total score of stained cells was calculated by multiplying the above two scores to define the expression levels: 0, negative expression; 1 to 4, weak expression; 5 to 8, positive expression; 9 to 12, strong expression. Tumor tissues with scores of 0–4 were defined as having low expression and those with scores of 5–12, as having high expression.

Follow-up

Each patient was scheduled for an examination, which included a physical examination, blood analysis, and computed tomography analysis. Tumor progression was based on clinical, radiological or histological diagnosis, and the site and time of tumor progression were both recorded. Follow-up was performed until September 2016 for 110 patients.

Cell lines

Breast cancer cell lines (MDA-MB-231, ZR-75-1, T47D, and MCF-7) were kindly provided by Dr. SHOU Cheng-chao from Department of Biochemistry and Molecular Biology, Peking University Cancer Hospital & Institute. MCF-10A cells were obtained from MeiXuan Biological Technology Company Limited of Shanghai, China. They were cultured in appropriate media supplemented with essential materials in the 5% CO2 incubator [31].

Western blot analysis

Protein extracts were separated via 12% SDS polyacrylamide gel electrophoresis and transferred onto PVDF filters. The filters were incubated with a rabbit anti-LAPTM4B polyclonal antibody (dilution 1:1000, AP20870a, ABGENT, China), a rabbit anti-VEGF polyclonal antibody (dilution 1:500, 19003-1-AP, Proteintech, USA) and a rabbit anti-survivin monoclonal antibody (dilution 1:1000, 2808, Cell Signaling Technology, USA) overnight at 4°C. The blots were detected using a chemiluminescence detection system. β-Actin and histone H3 were used as internal controls for the total, cytoplasmic protein expression and nuclear protein expression.

Statistical analysis

SPSS 18.0 software was used to perform the statistical analyses, and χ2 tests were used to evaluate the associations between the three biomarkers and the clinicopathological characteristics. The follow-up data was analyzed using the Kaplan–Meier method and Cox regression tests. P<0.05 was considered statistically significant.

Author contributions

Sha Li carried out experiments, analyzed results and drafted the manuscript. Lu Wang, Yue Meng, Yanli Chang and Jianjun Xu performed partial experiments and analyzed some data. Qingyun Zhang designed the study, interpreted the data and revised the manuscript for important intellectual content.

ACKNOWLEDGMENTS

We would like to thank all people who participated in the study.

CONFLICTS OF INTEREST

The authors have declared that no competing interests exist.

FUNDING

This work was supported by the National Natural Science Foundation of China (No. 81572910).

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