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Introduction

Breast cancer is the leading cause of cancer-associated mortality in women worldwide; ~1.38 million new breast cancer cases and ~0.46 million breast cancer-associated mortalities were estimated to have occurred in 2014 (1). In China, the incidence has increased more than twice as fast as global rates since the 1990s, and is now the most frequently diagnosed cancer and the sixth leading cause of cancer-associated mortality among Chinese women (2). Despite an increase in the five-year survival rate of breast cancer, as a result of early diagnosis and improved local and systemic treatment over the last 20 years, long-term prognosis remains unsatisfactory, mainly due to the recurrence and invasion rates following resection (3). However, little is known about this aggressive behavior. Finding new favorable prognostic biomarkers may help to predict the properties of the malignancy, thus decreasing the rate of unsatisfied outcomes in a high-risk population.

The oncogenic enzyme sphingosine kinase (SPHK) catalyzes the phosphorylation of sphingosine to form sphingosine-1-phosphate, which is suggested to be a bioactive lipid mediator that serves a vital role in regulating various biological processes during tumorigenesis (4). Two functional SPHK isoenzymes, SPHK1 and SPHK2, have been identified in humans (5). Multiple lines of evidence indicate that SPHK1 regulates various processes important for cancer progression (6,7); however, there are limited studies regarding biological functions of SPHK2 in cancer, and it remains unclear whether SPHK1 and SPHK2 have redundant, overlapping, complementary or antagonistic functions in human cancer cells. A previous study showed that downregulation of SPHK2 in MDA-MB-453 breast cancer cells completely eliminated migration towards epidermal growth factor (EGF), suggesting it is similar to SPHK1 (8). Other studies hypothesized that overexpression of SPHK2 suppresses growth and enhances apoptosis, preceded by cytochrome c release and activation of caspase-3 (9,10), indicating that the two isoenzymes have opposite effects. An additional study suggested that non-small cell lung cancer patients with higher SPHK2 expression had a shorter overall survival (OS) time (11). The present study was only focused on the role of SPHK1, instead of SPHK2, in breast cancer long-term survival, since there are a larger number of studies providing evidence of its role in patients with cancer prognosis, thereby supporting the hypothesis.

SPHK1 mRNA has been revealed to be frequently overexpressed in a variety of human solid tumors (12). Other studies have demonstrated that SPHK1 protein expression is unregulated in various types of cancer, including prostate cancer (13), gastric cancer (14), glioblastoma multiforme (15), intestinal adenoma (16), acute erythroleukemia (17), colon cancer (18), salivary gland carcinoma (19) and glioma (20). In addition, there is plenty of evidence indicating that activation of SPHK1 is associated with anti-apoptosis effects, and the transformation, proliferation and survival of tumor cells (21,22). Furthermore, while SPHK1 activity may be stimulated by a variety of cellular stimuli, and anticancer treatments may cause downregulation of SPHK1 activity, it has been suggested that the SPHK1 inhibitors camptothecin and docetaxel suppress tumor growth as well as reduce the occurrence and number of metastases in nude mice (23).

A previous study reported that downregulation of SPHK1 in MCF-7 cells could reduce EGF- and serum-stimulated growth and enhance sensitivity to doxorubicin (a potent chemotherapeutic agent), suggesting that SPHK1 may perform an important role in the migration of MCF-7 cells (24). Increased expression of SPHK1 has been detected in triple-negative human breast tumors compared with receptor-positive tumors, and the SPHK1 ectopic expression is associated with poor overall and progression-free survival in breast cancer patients, as well as poor response to doxorubicin-based treatment (25). These observations propose that SPHK1 may be involved in cell growth and transformation in cancer progression.

However, there are limited studies connecting a comprehensive investigation of the expression and significance of SPHK1 with the long-time prognosis in patients with breast cancer in China. In the present study, the expression of SPHK1 was assessed in mRNA and protein levels in breast cancer tissues and compared with the clinicopathological parameters and survival of patients in 122 breast cancer patients. The present results indicated that SPHK1 may be a promising potential biomarker for predicting the prognosis of patients with breast cancer and a promising new target for breast cancer therapy.

Materials and methods

Patients and specimens

The analysis of human tissues was approved by the Human Research Ethical Committee of Chongqing Medical University (CQMU; Chongqing, China). Informed consent was obtained from all patients or their relatives. A total of 32 breast tumors and paired surgical-margin tissues (>1 cm away from the tumor area) were obtained from the First Affiliated Hospital of CQMU (Chongqing, China). Tissues to be subjected to RNA extraction were frozen in liquid nitrogen. Tissue samples from 122 patients who underwent surgical resection for primary invasive breast cancer at the First Affiliated Hospital of CQMU between December 2006 and November 2013 were collected. All samples were evaluated and subject to histological diagnosis by pathologists. Subsequent to surgery, the majority of patients were treated with the standard practice guidelines at that time and were followed up regularly. In total, 15 normal breast specimens were obtained from the defect border while removing a benign breast tumor using the Mammotome biopsy technique (26). Formalin-fixed, paraffin-embedded materials were used for routine staining with hematoxylin and eosin (H&E; Zhongshan Jinqiao, Beijing, China) and for staining by immunohistochemical techniques. Grading of tumors was achieved by staining with H&E.

RNA extraction and reverse transcription-quantitative polymerase chain reaction (RT-qPCR)

Total RNA was isolated from the tissue of patients using TRIzol reagent (Molecular Research Center, Cincinnati, OH, USA). Levels of RNA expression were determined using the 7500 Fast System SDS software package (version 1.3.1; Applied Biosystems; Thermo Fisher Scientific, Inc., Waltham, MA, USA).

RT-qPCR was performed in triplicate with an Applied Biosystems Prism 7500 Fast Sequence Detection System (Thermo Fisher Scientific, Inc., USA) using Takara universal PCR master mix, according to the manufacturer's protocol (Takara Bio, Inc., Otsu, Japan). Primers were purchased from Shanghai Shenggong Genetech Co. (Shanghai, China). β-actin was used as an endogenous control. Melting curve analysis was performed to verify specificity of PCR products. In addition, PCR products were electrophoresed on 2% agarose gel to confirm product sizes and specificity. The sequences were as follows: SPHK1 forward, 5′-CTTGCAGCTCTTCCGGAGTC-3′ and reverse, 5′-GCTCAGTGAGCATCAGCGTG-3′; and β-actin forward, 5′-TCCTGTGGCATCCACGAAACT-3′ and reverse, 5′-GAAGCATTTGCGGTGGACGAT-3′. Reaction conditions were set as follows: 95°C for 30 sec; followed by 40 cycles of 95°C for 5 sec; and 60°C for 34 sec. The association stage was set to check the specificity of primers as follows: 95°C for 15 sec; followed by 60°C for 1 min; 95°C for 15 sec; and then 60°C for 15 sec. Each sample was performed in triplicate in a 20 µl reaction volume. Relative quantification of gene expression was performed using the 2−ΔΔCq calculation formula, based on Cq values for target and reference genes (27).

Immunohistochemistry

A rabbit polyclonal antibody against human SPHK1 (cat. no., ab16491; dilution, 1:300; Abgent, Inc., San Diego, CA, USA) was used. Immunohistochemistry was performed using a two-step method. Sections (4 µm) were deparaffinized by 100% xylene (4 times, 10 min each) and rehydrated in a series of ethanol (100, 95, 85 and 70% for 2 min each). The sections were hydrated and underwent sodium citrate (pH 6.0) antigen retrieval. Antigen retrieval was performed for 15 min in a microwave by intermittent heating to avoid boiling buffer, which may damage the tissue or dislodge it from the slide. Endogenous peroxidase activities were blocked by 3% hydrogen peroxide. The sections were then incubated with the primary antibody (cat. no., SP-9000; dilution, 1:250; Zhongshan Jinqiao) overnight for 18 h at 4°C, followed by incubation with horseradish peroxidase-conjugated goat anti-rabbit immunoglobulin G secondary antibody (cat. no., SP-9000; dilution, 1:1,000; Zhongshan Jinqiao) at 37°C for 1 h. Finally, slides were counterstained with hematoxylin. To eliminate nonspecific staining, a negative control was performed by replacing the primary antibody with PBS.

All staining was assessed by two pathologists blinded to the origination of the samples and subject outcome. The widely accepted German semi-quantitative scoring system was used to assess the staining intensity and area extent (28). Each specimen was assigned a score according to the intensity of the nucleic, cytoplasmic and/or membrane staining (no staining, 0; weak staining, 1; moderate staining, 2; and strong staining, 3; and the extent of stained cells (0%, 0; 1–24%, 1; 25–49%, 2; 50–74%, 3; and 75–100%, 4). The final score was calculated by multiplying the intensity score with the extent of staining score, ranging between 0 (the minimum score) and 12 (the maximum score). Scores ≥8 were defined as high expression and scores <8 were defined as low expression.

Outcome of patients

Following a median follow-up of 56.5 months (7–106 months), 41 recurrence or metastasis cases and 22 mortalities occurred in all patients.

Statistical analysis

Statistical analysis was performed using SPSS 17.0 software (SPSS, Inc., Chicago, IL, USA). The OS time was counted from the date of diagnosis being confirmed as breast carcinoma to the date of last follow-up or mortality. Disease-free survival (DFS) time was calculated from the date of confirmed diagnosis to the date of last follow-up or metastatic diseases. χ2 and Fisher's exact tests were used to compare variables. Survival analysis was performed using the log-rank test, and survival plots were created using Kaplan-Meier methods. Multivariate analysis was performed using Cox proportional hazard regression analysis. All P-values reported were two-sided, and P<0.05 was considered to indicate a statistically significant difference.

Results

Demographic and clinicopathological features

To validate the association between SPHK1, clinicopathological parameters and clinical outcome, an independent cohort of breast cancers with follow-up information was included in the present study. A total of 122 consecutive breast cancer specimens were collected, including 9 of carcinoma in situ and 113 of invasive ductal carcinoma. The mean age of the total patients enrolled was 52 years, ranging from 27–75 years. Histological types of the total 122 samples were defined according to the World Health Organization classification criteria (2007) into grade I (9 cases), grade II (76 cases), grade III (11 cases) and 26 cases with missing data.

SPHK1 mRNA expression

The mRNA level of SPHK1 in 32 tissues of patients, determined by RT-qPCR, revealed that the gene expression level of SPHK1 was significantly upregulated (P<0.0001). SPHK1 mRNA expression was upregulated [tumor/normal (T/N) ratio >1] in breast cancer tissues compared with that in matched adjacent breast tissues (expression=1) in 19 of 32 paired tissue specimens (59.4%). In 13 of 32 specimens (40.6%), SPHK1 was downregulated (T/N ratio >1; Fig. 1).

Figure 1. SPHK1 messenger RNA expression levels in 32 paired breast cancer and adjacent normal tissues of patients. T/N, tumor/normal; SPHK1, sphingosine kinase 1; Q-PCR, quantitative-polymerase chain reaction.

SPHK1 immunostaining

Immunohistochemical analysis was performed using 122 paraffin-embedded breast cancer tissue blocks to evaluate the expression of the SPHK1 protein. Negative staining was examined in all 15 normal breast cases (data not shown). Examples of the different SPHK1 staining of breast tumors are shown in Fig. 2, according to aforementioned methods. Positive staining for SPHK1 was mainly observed in the cytoplasm of the breast cancer cells. Among the 122 breast carcinomas, weak staining was observed in 26 specimens (21.3%), moderate expression was observed in 57 (46.7%) and strong staining was observed in 39 (32.0%).

Figure 2. Immunohistochemical staining of SPHK1 in breast carcinomas. (left panel) Representative breast carcinomas stained weakly, moderately and strongly positive for SPHK1. Magnification, ×10 (top) and ×40 (bottom). SPHK1, sphingosine kinase 1.

Association between SPHK1 expression and clinicopathological features

The association between the expression of SPHK1 and various clinicopathological parameters is listed in Table I. A significant association was observed between the high and low expression groups in the presence of lymph node metastasis (P=0.0016), number of positive lymph nodes (P=0.0268) and presence of distant metastasis (P=0.0097). High SPHK1 expression was also associated with human epidermal growth factor receptor 2 (HER2) status (P=0.0100), initial symptoms (P=0.0025) and tumor location (P=0.0457). However, no significant association was observed between the expression level of SPHK1 and age, times of pregnancy, age at menarche, tumor histological types, histological grade, tumor size or hormonal receptor (HR; estrogen receptor or progesterone receptor) status. There was also no significant difference in SPHK1 expression among the different intrinsic subtypes of breast cancer, as defined by the St Gallen consensus conference (29). These data showed that the expression of SPHK1 increases as breast cancer clinically progresses, but cancer intrinsic subtypes do not appear to be associated with the level of SPHK1 expression in the samples included in the present study.

Table I. Main characteristics of patients with breast cancer, and the association between the SPHK1 and clinicopathological parameters (n=122).

Table I.

Main characteristics of patients with breast cancer, and the association between the SPHK1 and clinicopathological parameters (n=122).

		SPHK1 expression
Features	No.	High, n (%)	Low, n (%)	χ2	P-value
Age,				2.6011	0.1068
<60 years	93	45 (36.9)	48 (39.3)
≥60 years	29	19 (15.6)	10 (8.2)
Gravidity				0.8801	0.9321
1	60	30 (24.6)	30 (24.6)
2	22	12 (9.8)	10 (8.2)
3	7	4 (3.3)	3 (2.5)
4	11	7 (5.7)	4 (3.3)
≥5	5	3 (2.5)	2 (1.6)
Unknown	17	7 (5.7)	10 (8.2)
Age at menarche, years				2.8928	0.4171
≤12	14	5 (4.1)	11 (9.0)
13–14	78	40 (32.8)	38 (31.1)
15–16	15	9 (7.4)	6 (4.9)
≥17	6	3 (2.5)	3 (2.5)
Missing data	7	7 (5.7)	0 (0)
Initial symptoms				14.3048	0.0025a
Lump	92	39 (32.0)	53 (43.5)
Pain	13	12 (9.8)	1 (0.8)
Nipple changes	5	2 (1.6)	3 (2.5)
Clinical screening	6	5 (4.1)	1 (0.8)
Unknown	6	6 (4.9)	0 (0)
Tumor location				5.3123	0.0457a
Right	61	26 (21.3)	35 (28.7)
Left	60	37 (30.3)	23 (18.9)
Both-sides	1	1 (0.8)	0 (0)
Tumor histology				0.7865	0.3752
Carcinomas in situ	9	6 (4.9)	3 (2.5)
Invasive carcinomas	113	58 (47.5)	55 (45.1)
Types of invasive carcinomas				5.5517	0.0843
Ductal	97	53 (46.9)	44 (38.9)
Lobular	4	2 (1.8)	2 (1.8)
Mucinous adenocarcinoma	5	0 (0)	5 (4.4)
Cephaloma	2	1 (0.9)	1 (0.9)
Others	5	2 (1.8)	3 (2.6)
Histological grade				2.9182	0.2531
I	10	8 (6.6)	2 (1.6)
II	70	38 (31.1)	32 (26.3)
III	11	5 (4.1)	6 (4.9)
Unknown	31	10 (8.2)	21 (17.2)
Tumor size, cm				0.4706	0.8883
<2.0	36	15 (12.2)	11 (9.0)
≥2.0 and ≤5.0	78	39 (32.0)	39 (32.0)
>5.0	6	3 (2.5)	3 (2.5)
Unknown	12	6 (4.9)	6 (4.9)
Lymph nodes status				10.3477	0.0013a
Positive	62	41 (33.6)	21 (17.2)
Negative	55	20 (16.4)	35 (28.7)
Unknown	5	3 (2.5)	2 (1.6)
No. of positive lymph nodes				7.2395	0.0268a
<5	92	42 (34.4)	50 (41.0)
5–10	16	11 (9.0)	5 (4.1)
>10	14	11 (9.0)	3 (2.5)
Distant metastasis				8.8374	0.0030a
Positive	32	24 (19.7)	8 (6.5)
Negative	90	40 (32.8)	50 (41.0)
ER status				0.0104	0.9186
Positive	57	29 (23.8)	26 (21.3)
Negative	52	29 (23.8)	25 (20.5)
Unknown	13	6 (4.9)	7 (5.7)
PR status				1.2539	0.2628
Positive	38	23 (18.9)	15 (12.3)
Negative	71	35 (28.7)	36 (29.5)
Unknown	13	6 (4.9)	7 (5.7)
HER2 status				6.6422	0.0100a
Positive	44	30 (24.6)	14 (11.5)
Negative	65	28 (23.0)	37 (30.3)
Unknown	13	6 (4.9)	7 (5.7)
P53 status				0.0778	0.7803
Positive	37	19 (15.6)	18 (14.8)
Negative	72	39 (32.0)	33 (27.0)
Unknown	13	6 (4.9)	7 (5.7)
Intrinsic subtype				1.5973	0.6600
Luminal A	54	28 (23.0)	26 (21.3)
Luminal B	7	4 (3.3)	3 (2.5)
HER2 type	5	4 (3.3)	1 (0.8)
Basal-like	43	22 (18.0)	21 (17.2)
Undefined	13	6 (4.9)	7 (5.7)

a P-values were calculated using the χ² test or Fisher's exact test. The significance of bold values is P<0.05. HER2, human epidermal growth factor receptor 2; ER, estrogen receptor; PR, progesterone receptor; SPHK1, sphingosine kinase 1.

SPHK1 expression and survival of patients

Survival curves plotted using the Kaplan-Meier method demonstrated that increased expression of SPHK1 was associated with a decrease in OS and DFS (Fig. 3). Statistical analysis of the impact of classic clinicopathological features and protein expression by the log-rank (Mantel-Cox) test revealed that patients with SPHK1-positive tumors had a significantly poorer prognosis than those with SPHK1-negative tumors (P<0.05). Other features associated with decreased survival were lymph node status, distant metastasis, HER2 status and intrinsic subtype, whereas other clinicopathological variables were not significant (Table II). By multivariate analysis, high SPHK1 expression was independently associated with greater cancer-specific OS (HR, 0.196; 95% CI, 0.058–0.655; P=0.0081; Table III).

Figure 3. Kaplan-Meier survival curves for patients of (A) disease-free survival and (B) overall survival, according to the levels of SPHK1 expression. SPHK1, sphingosine kinase 1.

Table II. Survival of patients associated with clinicopathological features and biomarkers.

Table II.

Survival of patients associated with clinicopathological features and biomarkers.

Variables	Patients	Events	DFS rate, %	Median ± SE	P (log-rank)	Events	OS rate, %	Median ± SE	P (log-rank)
Age					0.0938				0.0888
<60 years	93	13	14.0	84±2.6695592		8	8.6	84±3.1875801
>60 years	29	28	96.6	70±5.4070979		14	48.3	70±6.3744223
Tumor size					0.2281				0.3939
<2.0	36	3	8.3	87±5.6198349		5	13.9	87±4.5836602
≥2.0 and ≤5.0	78	16	20.5	82±3.6060642		26	33.3	82±3.0635466
>5.0	6	2	33.3	73±16.0603030		3	50	75±12.8443676
Unknown	12	1	8.3	NA		7	58.3	NA
Lymph node status					<0.0001a				0.0062a
Positive	62	7	11.3	87±2.0293832		5	8.1	87±2.6739158
Negative	55	31	56.4	63±3.8471953		14	25.5	53±4.4754747
Unknown	5	3	60	NA		3	60	NA
Distant metastasis					<0.0001a				<0.0001a
Positive	32	32	100	87±2.4340914		22	68.8	88±2.0415520
Negative	90	9	0.03	27±3.5732850		0	0	40.5±3.7709387
ER status					0.0822				0.2415
Positive	57	16	28.1	87±3.6671959		8	14.0	86±4.1966608
Negative	52	22	42.3	75±3.6619246		12	23.1	73±4.5150288
Unknown	13	3	23.1	NA		2	14.4	NA
PR status					0.2300				0.6557
Positive	40	11	27.5	82±4.7006779		7	17.5	80±5.2390218
Negative	69	27	39.1	79±3.1488219		13	18.8	79±3.9022241
Unknown	13	3	23.1	NA		2	15.4	NA
HER2 status					0.0097a				0.7220
Positive	48	5	10.4	60±4.8890965		5	10.4	53±5.6055087
Negative	61	32	52.5	82±2.7297154		14	23.0	80±3.4181057
Unknown	13	4	30.8	NA		3	23.1	NA
P53 status					0.1206				0.3823
Positive	37	16	43.2	82±5.5693640		7	18.9	82±6.3899854
Negative	72	22	30.6	79±2.7109243		12	16.7	79±3.3807911
Unknown	13	3	23.1	NA		2	15.4	NA
SPHK1					0.0001a				0.0007a
Positive	64	31	48.4	70±3.6525019		18	28.1	62±4.2430458
Negative	58	10	17.2	88±2.4733977		4	6.9	88±3.1148016
Intrinsic subtype					0.0415a				0.0005a
Luminal A	53	16	30.2	86±3.7240436		9	17.0	85.5±4.2700536
Luminal B	8	1	12.5	80±11.8289970		0	0	80±13.0198697
HER2 type	6	4	66.7	59±13.6623570		4	66.7	30±13.9835618
Basal-like	42	17	40.5	75±3.9125198		8	19.0	75±5.0232251
Undefined	13	3	23.1	NA		1	7.8	NA

a Statistically significant. ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2; SPHK1, sphingosine kinase 1; OS, overall survival; DFS, disease-free survival; NA, not applicable; SE, standard error.

Table III. Multivariate logistic regression analysis of different prognostic variables in patients with breast cancer by Cox regression analysis.

Table III.

Multivariate logistic regression analysis of different prognostic variables in patients with breast cancer by Cox regression analysis.

	Multivariate analysis
	DFS			OS
Characteristics	P-value	RR	Hazard ratio, 95% CI	P-value	RR	Hazard ratio, 95% CI
Age (<60 vs. ≥ 60 years)	0.4648	1.343	0.609–2.958	0.4762	1.471	0.509–4.257
Lymph node metastasis (yes vs. no)	0.0003a	6.067	2.28–16.082	0.0299a	3.530	1.131–11.020
SPHK1 expression (positive vs. negative)	0.0518	0.453	0.204–1.006	0.0081a	0.196	0.058–0.655
ER (negative vs. positive)	0.0671	3.339	0.919–12.131	0.0411a	5.107	1.068–24.422
PR (negative vs. positive)	0.5753	1.335	0.486–3.666	0.3761	1.840	0.477–7.095
HER2 score (negative vs. positive)	0.3707	0.707	0.331–1.510	0.2559	1.893	0.630–5.692

a Statistically significant. OS, overall survival; DFS, disease-free survival; RR, relative risk; CI, confidence interval; NA, not applicable; ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2; SPHK1, sphingosine kinase 1.

Discussion

Breast cancer is one of the most common malignancies worldwide; thus, it has been the object of intensive research, which is now revealing the complexity of this disease. It was initially reviewed that breast cancer dissemination is a non-random, organotropic process, originally based on Paget's theory of seed and soil, which suggests that disseminated cancer cells (seeds) can form metastases as they reach a microenvironment (soil), which is congenial enough for their survival and proliferation (30,31). Nevertheless, how seeds fit in the exclusive soil has not been fully understood yet. The molecular subtypes of breast cancer have been proved to provide marginal metastasis site-specific prognostic information (32), but site-specific biomarkers with improved accuracy are required.

By contrast, the molecular mechanisms of tumor cell migration and metastasis to lymph nodes in vivo remain unclear, although several internal molecules in tumor cells have been reported to perform critical roles in the process of cell motility (33). Alteration in cell-cell adhesion and the secretion and activation of proteolytic enzymes is considered to be essential for optimal tumor cell invasion and migration through and across the extracellular barriers. In these aspects, several internal molecules have been reported to be associated with lymph node metastasis of breast carcinoma, including membrane-type 1 matrix metalloproteinase (34), microRNA-21 (35) and vascular endothelial growth factor C (36). SPHK1 was previously identified to be involved in cervical cancer development and progression and its expression was associated with well-known prognostic parameters, including lymph node metastasis, lymphovascular invasion, tumor size, Federation of Gynecology and Obstetrics stage and invasion depth (37).

Multiple studies have revealed that SPHK1 is a key enzyme critical to the sphingolipid metabolic pathway, which serves a vital role in cancer progression. Studies have shown that ectopic expression of SPHK1 in NIH3T3 fibroblasts may promote the growth of cells in soft agar and the ability to form tumors in non-obese diabetic/severe combined immunodeficiency mice (6), and it may be due to its association with Ras and extracellular-signal regulated kinase 1/2 signaling (38). The expression of SPHK1 was revealed to be upregulated in breast cancer by using a microarray data of 1,269 tumor samples, and the expression status was positively associated with the survival of patients, indicating a potential prognostic value of this enzyme (39). It was suggested that SPHK1 is involved in EGF-mediated activation and migration of breast cancer MDA-MB-453 cells (40). Consistently, SPHK1 was revealed to be induced by transforming growth factor-β (TGF-β) in fibroblasts and mesangioblasts, demonstrating that SPHK1 protein is an important component of the TGF-β signaling pathway (41,42). A previous study identified that the regulation of SPHK1 gene expression and kinase activity was mediated by TGF-β, which is critical to MDA-MB-231 cell viability (43).

These results support the evidence that SPHK1 has oncogenic potential in breast cancer progression. The prognostic role of SPHK1 has been studied in several cancer types, including gastric cancer (14) and astrocytoma (44), suggesting that patients with increased SPHK1 expression had shorter OS time, whereas those with lower SPHK1 survived longer. These studies indicate that SPHK1 is a prognostic indicator for a number of diseases. However, the roles of SPHK1 have not been extensively studied, particularly in the long-term survival of patients with breast cancer. In the present study, SPHK1 expression was associated with lymph node metastasis and the number of metastatic lymph nodes, indicating a role for SPHK1 in enhancing the progression of tumor cell migration and metastasis. Significant differences were also observed in other clinicopathological features and long-term prognosis among SPHK1-positive and SPHK1-negative samples. Previous studies along with the present study supported a hypothesis that SPHK1 is involved in functions other than its intracellular regulating function; it may also perform a vital role in breast cancer progression.

However, the present study has certain limitations, including a lack of intensive study into biological mechanisms involved in the association of SPHK1 expression and tumor metastasis. Additional investigations into the mechanisms of SPHK1 in breast cancer metastasis will be performed in future studies, using a larger sample size with longer follow-up time periods.

In conclusion, SPHK1 may be a potential novel drug-interfering target for cancer, and additional understanding of the function and molecular mechanisms of SPHK1 in regulating the progression of breast cancer may provide new insights into breast cancer therapy.

Acknowledgments

The authors would like to thank Ms. Ke Yang and Qian Liu from the Clinical and Pathological Diagnosis Center of Chongqing Medical University for technical support and assistance. The present study was supported by the National Natural Science Foundation of China to Dr Ke Zheng (grant no. 81202090).

References