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Abstract

Objectives

To investigate relationships between several protein biomarkers and clinical responses to neoadjuvant chemotherapy (NAC) in breast cancer.

Methods

Tumour tissue samples from female patients with locally advanced breast carcinoma (stages IIA to IIIC), treated with NAC regimens (including 5-fluorouracil, epirubicin, cyclophosphamide and docetaxel, epirubicin, cyclophosphamide) were analysed retrospectively. Immunohistochemical analysis was used to test for protein levels of oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor (HER)-2, protein 53 (p53) and γ-synuclein. Relationships between protein biomarkers and responses to NAC were analysed by multivariate logistic regression analysis.

Results

Data from 154 patients (median age, 51 years; range 27–75 years) were included. Multivariate logistic regression analysis showed that γ-synuclein was an independent predictor of NAC objective response rate, and a statistically significant relationship was observed between NAC regimen, γ-synuclein levels and pathological complete response rate.

Conclusions

These study findings suggest that γ-synuclein – in combination with other markers such as ER, PR and HER-2 – may serve as a biomarker for response to NAC in breast cancer and warrants further study.

Keywords

γ-synuclein breast cancer neoadjuvant chemotherapy sensitivity oestrogen receptor (ER)progesterone receptor (PR)human epidermal growth factor receptor 2 (HER-2)

Introduction

In women, breast cancer is the most common cancer and the second most common cause of cancer-related death.¹ It was proposed in the early 1970s that ‘breast cancer is a systemic disease’ – a concept that is now firmly accepted – and since then comprehensive treatment has been actively promoted.² The role of neoadjuvant chemotherapy (NAC) in comprehensive therapy for breast cancer has been found to achieve disease-free survival (DFS) and overall survival rates similar to those of adjuvant chemotherapy. NAC enables more patients to undergo breast-conserving surgery and improves health-related quality of life without increasing the rate of local recurrence.^2,3 More importantly, NAC provides an ideal clinical model for studying in vivo drug susceptibility.⁴ Although breast cancer responds relatively well to NAC, ∼20% of patients do not benefit from the different chemotherapy regimens currently in use and are, therefore, subjected to toxic drugs without receiving any clinical benefit.³ This often leads to disease progression, which may result in a lost opportunity for a surgeon to obtain durable locoregional control of the disease. Clinically identifying reliable predictive markers that might signify a response to NAC may help identify patients who would benefit from NAC therapy, develop individualized treatment plans and improve the efficacy of chemotherapy in tumours that do not respond well to chemotherapy.

In the late 1990s, γ-synuclein (encoded by the synuclein, gamma [SNCG] gene and also called breast cancer-specific protein 1 [BCSG1]) was isolated from cDNA libraries of normal breast and breast carcinoma by a high-throughput direct-differential cDNA sequencing approach.⁵ Since then, γ-synuclein has been shown to play a role in the development of breast cancer.⁶ It is of interest whether the expression of the SNCG gene can be used as a marker to predict the sensitivity of breast cancer to NAC therapy. The present retrospective study used immunohistochemistry to determine the relationship between γ-synuclein and clinical response to NAC, in breast cancer patients.

Patients and methods

Study population

Consecutive female patients with locally advanced breast carcinoma, classified according to the American Joint Committee on Cancer TNM Staging for Breast Cancer (http://www.cancerstaging.org/staging/) as stage IIA to IIIC, were enrolled in this retrospective study. All case information (including background demographics) was collected from the patient archives of the Department of Surgery, Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou, China, from patients treated between November 2006 and September 2010. Patients who had not received any anticancer therapy (including chemotherapy, radiotherapy, endocrine therapy or surgery) at the time of diagnosis and data collection, who had no cancer other than breast cancer and who had a Kanofsky score >80 points were eligible for the study.

The study protocol was approved by the Ethics Review Committee of Women’s Hospital, School of Medicine, Zhejiang University. Written informed consent was obtained from all patients. The study was conducted in accordance with the Helsinki Declaration of 1975 (revised 1983).

The NAC regimens administered to patients included in this study were: FEC regimen – 21-day cycle of 500 mg/m² cyclophosphamide administered intravenously (i.v.) on day 1, 60–100 mg/m² epirubicin i.v. on day 1 and 500 mg/m² 5-fluorouracil i.v. on day 1; or TEC regimen–21-day cycle of 75 mg/m² docetaxel i.v. on day 1, 60 mg/m² epirubicin i.v. on day 1 and 500 mg/m² cyclophosphamide i.v. on day 1. Patients received between two and four cycles of chemotherapy.

Breast cancer diagnosis

All patients were diagnosed with breast cancer by B ultrasound-guided core needle biopsy, using a B-ultrasound machine model GE Logiq 40 ocL High Frequency Probe (GE Medical Systems, Waukesha, WI, USA). The MAGNUM™ automatic biopsy gun (Bard Peripheral Vascular, Temple, AZ, USA) and the Gudu Medical MN1620 disposable needle (Bard Peripheral Vascular) were used to perform the biopsy. Positioning was conducted with B-ultrasound before puncture. The patients were anaesthetized with 1% lidocaine, then two to three samples, each measuring ∼1.5 cm × 2 cm, were obtained from each mass. Specimens were fixed immediately in 10% formalin and sent to the pathology department for rapid, routine paraffin wax embedding and immunohistochemical analysis.

Immunohistochemical analysis of potential biomarkers

As previously described,^7,8 tumour samples taken from before and after the administration of NAC were analysed for the presence of a variety of breast cancer protein markers including γ-synuclein, estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER)-2. Tissues were fixed in 10% neutral buffered formalin and subjected to routine paraffin-wax embedding and sectioning (serial 4 -µm thick sections). Briefly, tissue sections were deparaffinized and heated for 1–2 min at 105℃ in an autoclave in Target Retrieval Solution (DAKO, Carpinteria, CA, USA) for antigen retrieval. Sections were washed in distilled water for 3 min, incubated in 0.3% hydrogen peroxide for 10 min at room temperature to block endogenous peroxidases and washed three times in 0.01 M phosphate-buffered saline (PBS; pH 7.4). After blocking with 10% goat serum for 1 h at room temperature, sections were incubated with mouse monoclonal or polyclonal antihuman primary antibodies overnight at 4℃ as follows: mouse anti-ER antibody (clone 1D5, 1 : 80 dilution; DAKO, Cambridge, UK); mouse anti-PR antibody (clone PgR636, 1 : 100 dilution; DAKO), mouse anti-HER-2 antibody (HercepTest™, 1 : 50 dilution; DAKO); and goat anti-SNCG polyclonal antibody (SC-10699, 1 : 1000 dilution; Santa Cruz Biotechnolgy, Santa Cruz, CA, USA). Monoclonal antibodies to CD133 (clone NCH-38, 1 : 200 dilution; DAKO) and aldehyde dehydrogenase activity 1 (1 : 100 dilution; BD Bioscience, San Jose, CA) were used as negative and positive controls respectively. Sections were then washed three times with 0.01 M PBS (pH 7.4) and incubated with the appropriate secondary antibodies (1 : 1000 dilution) for 45 min at room temperature using the MaxVision (mouse/rabbit) kit (KIT-5010) and UltraSensitive SP kit (sheep) (KIT-9709) (both from Fuzhou Maixin Biotechnology Development Co. Ltd, Fuzhou, China). Sections were washed a final three times with 0.01 M PBS (pH 7.4) and the signal was visualized using a horseradish peroxidase and diaminobenzidine Cell & Tissue Staining Kit (R&D Systems, Minneapolis, MN, USA) according to the manufacturer’s instructions, followed by counterstaining with haematoxylin.

Immunohistochemical staining of ER, PR and protein 53 (p53) was observed as yellow- to brown-stained particles in the nuclei of tumour cells. For ER and PR, samples with ≤1% tumour cells stained were categorized as negative and samples with >1% tumour cells stained were categorized as positive. For P53, samples with ≤10% tumour cells stained were categorized as negative and samples with >10% tumour cells stained were categorized as positive.

Human epidermal growth factor receptor 2 protein staining was observed as brown-stained particles in the membrane or cytoplasm of tumour cells. HER-2-positive samples were categorized as: −, no staining; +, weak and incomplete staining; ++, moderate and some parts incomplete staining; +++, strong and complete staining. Patients with − and + staining were considered to have low levels, and those with ++ and +++ staining were considered to have high levels, of HER-2.

For γ-synuclein, protein staining was observed as brown-stained particles in the cytoplasm of tumour cells. Very few cases exhibited nuclear staining. Results were evaluated according to two indices: percentage of positive cells and staining colour intensity. The percentage of positive cells was scored as follows: 0, <25% positive cells; 1, 26–50% positive cells; 2, 51–75% positive cells; 3, >75% positive cells. Staining intensity was scored as follows: 1, weak staining; 2, moderate staining; 3, strong staining. The sum of the two scores of each sample provided the composite result for each tumour, with < 3 points considered as low levels and > 3 points as high levels of γ-synuclein.

Clinical response to NAC

Tumour response to NAC was assessed by physicians experienced at using B-ultrasound. Tumour diameters were assessed before and after NAC, according to the Response Evaluation Criteria in Solid Tumors.⁹ Tumours were classified as follows: complete response (clinical) (CR), defined as the disappearance of all lesions, assessed by preoperative imaging, determined by two observations ≥4 weeks apart; partial response, (PR), a reduction of ≥30% in the total diameter of the target lesions; progressive disease (PD), any measured increase of ≥20% or appearance of new lesions; stable disease (SD), a decrease less than that of PR or an increase less than that of PD. The objective response rate was defined as CR plus PR. Pathological complete response (pCR) was defined as the disappearance of all target lesions as assessed by postoperative pathological evaluation and included the complete disappearance of infiltrates, including lymph node infiltrates, with or without intraductal components.

Statistical analyses

Statistical analyses were carried out using the SPSS® software package, version 7.0 (SPSS Inc. Chicago, IL, USA) for Windows®. The relationship between ER, PR, HER-2, p53 and γ-synuclein levels and the response to NAC was analysed using the χ²-test or Fisher’s exact test, as appropriate. Multivariate logistic regression analysis was used to assess the relationship between ER, PR, HER-2, p53 and γ-synuclein and clinical response, with ER, PR, HER-2, p53 and γ-synuclein as confounding factors. A P-value < 0.05 was considered to be statistically significant.

Results

A total of 154 female patients (median age 51 years; range, 27 –75 years) with locally advanced breast were included. In total, 29 (18.8%) cases were stage IIA, 70 (45.5%) cases were stage IIB, 46(29.9%) cases were stage IIIA, six (3.9%) cases were stage IIIB and three (1.9%) cases were stage IIIC. In terms of type of NAC received, 93 (60.4%) cases received FEC, 61 (39.6%) received TEC and 136 (88.3%) received more than three cycles of NAC.

A total of 76 (49.4%) patients were ER-positive, 65 (42.2%) were PR-positive and 57 (37.0%) were p53-positive. In addition, 49 (31.8%) patients showed high HER-2 levels and 80 (51.9%) showed high γ-synuclein levels. The level of γ-synuclein was significantly associated with lymph node metastasis (χ²= 18.632, P < 0.001) and ER status (χ²= 5.018, P < 0.01) but showed no significant association with any other parameter.

Complete response was observed in 17 cases, PR in 80 cases, SD in 42 cases and PD in 15 cases, with an objective response rate of 63.0%. A pCR was only observed in 7 (4.5%) cases. There was no significant association between age, menstrual status, number of chemotherapy cycles, PR, p53 and HER-2 status, and objective response rate to NAC. Chemotherapy regimen (P = 0.042), primary tumour size (P < 0.001), ER status (P < 0.001) and γ-synuclein status (P < 0.001) were all significantly associated with objective response rate to NAC (Table 1). There was no significant association between age, menstrual status, primary tumour size, number of chemotherapy cycles, ER, PR, p53 and HER-2 positive status and pCR to NAC. Chemotherapy regimen (P = 0.031) and SNCG (P = 0.015) were significantly associated with pCR rate to NAC (Table 2).

Table 1.

The relationship between objective response rate to neoadjuvant chemotherapy (NAC) and clinical characteristics and immunohistochemical biomarkers among female patients with locally advanced breast carcinoma (stage IIA to IIIC; n = 154), retrospectively analysed for potential predictive biomarkers of response to NAC.

Clinical index	SD + PD n = 57	CR + PR n = 97	Objective response rate^a, %	χ²-value	Statistical significance^b
Age, years
<50	22	47	68.1	1.411	NS
≥50	35	50	58.8
Menstrual status
Premenopausal	30	41	57.7	1.552	NS
Postmenopausal	27	56	67.5
Primary tumour size, cm
≤5	32	81	71.7	13.762	P < 0.001
>5	25	16	39.0
NAC regimen^c
FEC	41	52	55.9	4.127	P = 0.042
TEC	17	44	72.1
Chemotherapy cycles
≤2	10	8	44.4	3.006	NS
>2	47	89	65.4
Estrogen receptor status
Negative	20	58	74.4	8.767	P < 0.001
Positive	37	39	51.3
Progesterone receptor status
Negative	28	61	68.5	2.788	NS
Positive	29	36	55.4
Protein 53 status
Negative	35	62	63.9	0.097	NS
Positive	22	35	61.4
HER-2 status
Low protein level	41	64	61.0	0.586	NS
High protein level	16	33	67.3
γ-synuclein status
Low expression	14	60	78.3	20.574	P < 0.001
High expression	43	37	42.5

Data presented as n of patients.

Objective response rate defined as the sum of patients with complete remission or partial response as a percentage of the total number of patients.

χ²-test or Fisher’s exact test as appropriate.

FEC regimen: 21-day cycle, 500 mg/m² cyclophosphamide administered intravenously (i.v.) on day 1, 60–100 mg/m² epirubicin i.v. on day 1 and 500 mg/m² 5-fluorouracil i.v. on day 1; or TEC, 21-day cycle, 75 mg/m² docetaxel i.v. on day 1, 60 mg/m² epirubicin i.v. on day 1 and 500 mg/m² cyclophosphamide i.v. on day 1. Patients received between two and four cycles of chemotherapy.

SD, stable disease; PD, progressive disease; CR, complete response (clinical); PR, partial response; NS, not statistically significant (P ≥ 0.05); HER-2, human epidermal growth factor receptor 2.

Table 2.

The relationship between the pathological complete response rate (pCR)of breast carcinoma to neoadjuvant chemotherapy (NAC) and clinical characteristics and immunohistochemical biomarkers among female patients with locally advanced breast carcinoma (stage IIA to IIIC; n = 154), analysed retrospectively for potential predictive biomarkers of response to NAC.

Clinical index	Non-pCR	pCR	pCR rate^a, %	χ²-value	Statistical significance^b
Age, years
<50	66	3	4.3	0.080	NS
≥50	81	4	4.7
Menstrual status
Premenopausal	66	5	7.0	0.976	NS
Postmenopausal	81	2	2.4
Primary tumour size, cm
≤5	107	6	5.3	0.101	NS
>5	40	1	2.5
NAC regimen^c
FEC	92	1	1.1	4.654	0.031
TEC	55	6	9.8
Chemotherapy cycles
≤2	18	0	0	0.146	NS
>2	129	7	5.1
Estrogen receptor status
Negative	72	6	7.7	2.287	NS
Positive	75	1	1.3
Progesterone receptor status
Negative	84	5	5.6	0.127	NS
Positive	63	2	3.1
Protein 53status
Negative	92	5	5.2	0.005	NS
Positive	55	2	3.5
HER-2 status
Low protein level	101	4	3.8	0.051	NS
High protein level	46	3	6.1
γ-synuclein status
Low protein level	67	7	9.5	5.898	0.015
High protein level	80	0	0

Data presented as n of patients.

pCR defined as disappearance of all target lesions.

χ²-test or Fisher’s exact test as appropriate.

NS, not statistically significant (P ≥ 0.05); HER-2, human epidermal growth factor receptor 2.

Although chemotherapy regimen, primary tumour size, ER status and γ-synuclein status were all significantly associated with objective response rate to NAC, multivariate logistic regression analysis showed that only γ-synuclein status (low versus high levels) was an independent predictor of objective response to NAC (Table 3).

Table 3.

Multivariate logistic regression analysis of the objective clinical response rate to neoadjuvant chemotherapy (NAC) among female patients with locally advanced breast carcinoma (stage IIA to IIIC; (n = 154), analysed retrospectively for potential predictive biomarkers of response to NAC.

Clinical index	Analysis	B-value	SE	Wald value	P-value	Exp (B-value)	95% CI for Exp(B-value)
Clinical index	Analysis	B-value	SE	Wald value	P-value	Exp (B-value)	Lower	Upper
Estrogen receptor	Negative versus positive	−0.567	0.472	1.444	NS	0.567	0.225	1.430
γ-synuclein	Low versus high protein level	−1.042	0.471	4.893	0.031	0.353	0.140	0.888
NAC	FEC versus TEC^a	0.596	0.470	1.610	NS	1.815	0.723	4.555
Tumour size	≤5 cm versus > 5 cm	−0.585	0.486	2.825	NS	2.679	0.849	8.452

NS, not statistically significant (P ≥ 0.05).

Discussion

Breast carcinoma is the most common cancer and the second most common cause of cancer-related death in women.¹ Chemotherapy – including neoadjuvant, adjuvant or rescue chemotherapy for recurrent and metastatic disease – is critical for the comprehensive treatment of breast carcinoma. NAC has been called initial or induction chemotherapy, which refers to the systematic use of cytotoxic drugs to treat nonmetastatic tumours before local treatment commences. NAC was first used in locally advanced breast cancer with satisfactory outcomes in 1998.² The NSABP B-18 test confirmed that no differences exist in DFS and overall survival between NAC and adjuvant chemotherapy.¹⁰ Thus, NAC has become standard treatment for locally advanced breast carcinoma and is used increasingly in its early treatment. It can shrink tumours, increase the rate of breast-conserving surgery without increasing local recurrence and improve patients’ health-related quality of life.^4,11 In addition, NAC can indicate whether the tumour is sensitive to chemotherapy. CR, classified as clinical or pathological, is the ultimate goal of NAC.⁴ NAC always uses traditional measurement or imaging data to evaluate clinical remission, and reduction of tumour volume is a good indicator of the effectiveness of the NAC dose. Between 60 and 90% of breast cancer patients are able to achieve clinical remission through NAC.^10,12,13 Only a maximum of 30%, however, achieve pCR.¹⁴ The objective response rate for 154 NAC patients in the present study was 63.0%. Although the efficacy of NAC was high, 37% of the patients did not respond to treatment, which delayed their local treatment. Such patients require a more accurate predictor of the efficacy of NAC before adjuvant chemotherapy, to avoid treatment delays.

Several markers of therapeutic response have been studied in breast carcinoma, including: tumour size; hormone receptor status; tumour type and differentiation; HER-2;¹¹ Ki-67;^15,16 apoptosis related to p53;¹⁷ Bcl-2;¹⁸ Bax;¹⁹ concentrations of tumour-associated substances in serum; breast cancer subtype; nuclear medicine imaging. Genetic studies and gene chip technology have shown that gene expression levels in drug-sensitive and drug-resistant tumours are significantly different, suggesting new markers that might predict the therapeutic response to NAC in breast cancer.^17,20 Such models may be used to predict patients where NAC is most effective, and to test the effectiveness of this strategy. Models with high predictive value for response to NAC include: the 23-gene model, which predicts the efficacy of taxol;²¹ a model that predicts the pCR rate to gemcitabine + epirubicin + docetaxel;²² and the 92-gene model, which predicts the effect of docetaxel NAC in breast cancer.²³ Although these gene models achieved good results in predicting the effect of NAC on breast carcinoma, there are several disadvantages including high cost and difficulty in implementation. Using immunohistochemistry to determine gene-expression patterns and predict the effect of NAC on breast carcinoma may be cost-effective and practical.

The present study used immunohistochemistry to determine tumour protein levels of ER, PR, HER-2, P53 and γ-synuclein before NAC, and identified the relationship between these markers and clinical response to NAC. It was shown that chemotherapy regimen, primary tumour size, ER and γ-synuclein status were all significantly associated with objective response rate to NAC. Only seven (4.5%) cases showed a pCR, which was lower than the pCR rate reported elsewhere.^6,12 A significant association was only observed between the chemotherapy regimen and γ-synuclein status, and pCR rate to NAC, in the present study.

In the late 1990s, three groups, using different methods, simultaneously identified the same gene encoding γ-synuclein: named the BCSG1 gene,⁵ the SNCG gene,²⁴ and persyn.²⁵ Sequences for these three genes were very similar, with only five nucleotide differences and no difference in the 3′ untranslated regions. The SNCG gene was highly expressed in a breast cancer cDNA library, but scarcely expressed in a normal breast cDNA library.⁵ SNCG gene expression is undetectable in normal or benign breast lesions and shows only partial in situ expression in ductal carcinoma (15%), but is highly expressed in advanced infiltrating breast cancer (74%).⁸ Its overexpression leads to lymph node and distant metastases,⁴ and, therefore, γ-synuclein is considered as promoting breast-cancer progression. Patients with γ-synuclein-positive tumours have a significantly shorter DFS and a higher probability of death than those with γ-synuclein-negative tumours.^8,26–28 As well as being extensively studied in breast cancer, the role of γ-synuclein as a new tumour marker and therapeutic target in other tumours is of increasing interest.^6,28–30 Animal studies have shown that SNCG gene overexpression in breast cancer significantly increases motility and invasiveness in vitro and profoundly augments metastasis in vivo.³¹ Furthermore, studies have suggested that γ-synuclein is associated with the degree of malignancy of breast cancer^26,27 and that γ-synuclein-positive breast cancer is not sensitive to chemotherapy.^28,32,33 Exogenous expression of the SNCG gene in ovarian and breast cancer cells significantly enhances cell migration and resistance to paclitaxel-induced apoptosis.³² It is thought that γ-synuclein blocks mitochondria-related apoptosis by downregulating the activation of c-Jun N-terminal kinases (JNK); this is one of the mechanisms of antimicrotubule drugs such as paclitaxel.³³ In vitro, γ-synuclein can directly participate in microtubule regulation by binding and promoting tubulin polymerization, inducing microtubule bundling and altering microtubule morphology in the presence of microtubule associated protein 2 (MAP2).³² Overexpression of SNCG may reduce the chemosensitivity of tumour cells by decreasing microtubule rigidity.^32,34 γ-Synuclein-positive cells are significantly more resistant to chemotherapeutic drugs, such as paclitaxel and vinblastine, compared with the parental cells.^33,35 The resistance to paclitaxel is partially removed by inhibiting extracellular signal-regulated kinase (ERK) activity with the mitogen activated protein kinase/ERK kinase 1/2 inhibitor, U0126. Activation of JNK, and its downstream target caspase-3, by paclitaxel or vinblastine is significantly downregulated in γ-synuclein-positive cells, indicating that paclitaxel- or vinblastine-activated apoptosis may be blocked by γ-synuclein. In contrast, etoposide does not activate JNK and SNCG overexpression has no apparent effect on etoposide-induced apoptosis.³⁵ SNCG interacts with BubR1, a mitotic checkpoint kinase that enhances tumour-cell resistance³⁴ A novel designed peptide (ANK) interacts with γ-synuclein; its microinjection into a breast-cancer cell line overexpressing SNCG (MCF7-SNCG) exhibits a similar cell-killing response to nocodazole as observed in SNCG-negative MCF7 parent cells.³⁴ Overexpression of enhanced green fluorescent protein-tagged ANK reduced γ-synuclein-mediated resistance to paclitaxel by ∼3.5-fold, and coimmunoprecipitation and colocalization studies confirmed the intracellular association of ANK and γ-synuclein.³⁴ Flow cytometry confirmed that both cell-cycle G₁ phase DNA content and histone H3 phosphorylation increased, suggesting that ANK restored MCF7-SNCG cell sensitivity to taxol and enhanced the role of mitotic arrest.³⁴

In conclusion, the present study showed a significantly lower objective response rate and pCR rate in patients with high versus low levels of SNCG expression, indicating that patients with SNCG overexpression have poor response to chemotherapy. Multivariate logistic regression analysis showed that SNCG was an independent predictor for objective response rate to NAC. Thus, γ-synuclein, in combination with other biomarkers such as ER, PR and HER-2, may serve as a biomarker to predict the effect of NAC in breast cancer and warrants further study. There were some limitations to the present study. First, this was a retrospective study; larger prospective clinical studies should be considered, to evaluate the relationship between SNCG and response to NAC in breast cancer. Moreover, this study used semiquantitative immunohistochemistry, which has limitations in terms of quantitative accuracy. Thus, quantitative methods to assess serum and tumour γ-synuclein protein levels (such as enzyme-linked immunosorbent assay) could be considered, to study the clinical significance of γ-synuclein and its clinical application.³⁶

Footnotes

Declaration of conflicting interest

The authors declare that there are no conflicts of interest.

Funding

This project was supported in part by National Natural Science Foundation of China (No. 30973465, 81071879).

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Clinical study of the relationship between γ-synuclein and the response of neoadjuvant chemotherapy in breast cancer

Abstract

Objectives

Methods

Results

Conclusions

Keywords

Introduction

Patients and methods

Study population

Breast cancer diagnosis

Clinical response to NAC

Statistical analyses

Results

Discussion

Footnotes

Declaration of conflicting interest

Funding

References