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Int J Med Sci 2018; 15(11):1179-1186. doi:10.7150/ijms.26771

Research Paper

Correlation between CCL4 gene polymorphisms and clinical aspects of breast cancer

Gui-Nv Hu1#, Huey-En Tzeng2,3,4#, Po-Chun Chen5, Chao-Qun Wang6, Yong-Ming Zhao1, Yan Wang7, Chen-Ming Su8 Corresponding address, Chih-Hsin Tang9,10,11 Corresponding address

1. Department of Surgical Oncology, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China
2. Taipei Cancer Center, Taipei Medical University, Taipei, Taiwan
3. Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
4. Division of Hematology/Oncology, Department of Medicine, Taipei Medical University-Shuang Ho Hospital, Taiwan
5. Central Laboratory, Shin-Kong Wu Ho-Su Memorial Hospital, Taipei, Taiwan
6. Department of Pathology, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China
7. Department of Medical Oncology, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China
8. Department of Biomedical Sciences Laboratory, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China
9. Department of Pharmacology, School of Medicine, China Medical University, Taichung, Taiwan
10. Chinese Medicine Research Center, China Medical University, Taichung, Taiwan
11. Department of Biotechnology, College of Health Science, Asia University, Taichung, Taiwan
# These authors have contributed equally to this work

This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions.
How to cite this article:
Hu GN, Tzeng HE, Chen PC, Wang CQ, Zhao YM, Wang Y, Su CM, Tang CH. Correlation between CCL4 gene polymorphisms and clinical aspects of breast cancer. Int J Med Sci 2018; 15(11):1179-1186. doi:10.7150/ijms.26771. Available from http://www.medsci.org/v15p1179.htm

Abstract

Breast cancer is a major cause of cancer mortality amongst women. Chemokine (C-C motif) ligand 4 is encoded by the CCL4 gene; specific CCL4 gene polymorphisms are related to the risks and prognoses of various diseases. In this study, we examined whether CCL4 gene single nucleotide polymorphisms (SNPs) predict the risk and progression of breast cancer. Between 2014 and 2016, we recruited 314 patients diagnosed with breast cancer and a cohort of 209 healthy participants (controls) without a history of cancer. Genotyping of the CCL4 rs1634507, rs10491121 and rs1719153 SNPs revealed no significant between-group differences for these polymorphisms. However, amongst luminal A and luminal B subtypes, compared with patients with the AA genotype, those carrying the AG genotype at SNP rs10491121 were less likely to develop lymph node metastasis. In addition, compared with AA carriers, those carrying the AG + GG genotype at SNP rs10491121 were at lower risk of developing distant metastasis, while the presence of the AT genotype at SNP rs1719153 increased the likelihood of pathologic grade (G3 or G4) disease. Variations in the CCL4 gene may help to predict breast cancer progression and metastasis.

Keywords: single nucleotide polymorphism, breast cancer, chemokine C-C motif ligand 4 (CCL4), genotype

Introduction

Breast cancer is the second leading cause of cancer deaths amongst women worldwide. Nearly million women worldwide are diagnosed with breast cancer annually and more than 500,000 die from this disease [1]. Besides age, reproductive and gynecologic factors, other risk factors such as family history and environmental factors including tobacco and alcohol consumption, as well as overall amount of physical activity, can greatly modify the risk of developing breast cancer [2]. In addition, gynecologic diseases including polycystic ovarian syndrome and adenomyosis have been found to enhance the risk of breast cancer [3, 4].

Mammography screening and genetic testing have limited sensitivity and specificity for estimating breast cancer risk [2]. It is uncertain as to whether single nucleotide polymorphism (SNP) genotyping could more accurately predict breast cancer risk and guide disease management [5, 6]. Susceptibility to breast cancer appears to be influenced by certain SNPs, as well as clinicopathologic status [7]. BRCA1 and BRCA2 gene mutations increase the risk of breast cancer [8, 9]. Fascin-1 (FSCN1) and high-mobility group box protein 1 (HMGB1) genetic polymorphisms have also been identified as predictive biomarkers for breast cancer [10].

Chemokine (C-C motif) ligand 4 (CCL4) is a protein that is encoded by the CCL4 gene and acts as a chemoattractant for natural killer cells, monocytes and various other immune cells in the site of inflamed or damaged tissue. CCL4 polymorphisms influence gene expression, protein function and susceptibility to various diseases, including hepatocellular carcinoma, oral cancer, and psoriasis [11-14]. CCL4 belongs to a cluster of genes located in the chromosomal region 17q11-q21. The CCL4 protein acts as the chemokine being secreted under mitogenic signals and antigens and attracting monocytes, dendritic cells, natural killer cells and other effector cells into the site of inflamed or damaged tissue [15, 16]. On the other hand, the CCL4 gene polymorphisms has been associated with risk and development in oral cancer and hepatocellular carcinoma [12, 17]. Despite the well-known impact of chemokines on cancer progression and the recognition that CCL4 gene SNPs play important roles in a variety of human diseases, little is known about the association between these SNPs and the susceptibility to breast cancer and its progression. In this study, we evaluated the predictive capacity of three CCL4 SNPs as candidate biomarkers for breast cancer risk.

Materials and Methods

Participants

Between 2014 and 2016, we collected 314 blood specimens from patients (cases) diagnosed with breast cancer at Dongyang People's Hospital. A total of 209 healthy, cancer-free individuals served as controls. Written informed consent was obtained from all participants before study entry. The Ethics Committee of Dongyang People's Hospital granted study approval. Pathohistologic diagnosis used the World Health Organization breast tumor classification and tumors were graded using the Scarff-Bloom-Richardson method [18]. Breast cancer cases were categorized by estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and Ki-67 status and grouped under 1 of 4 subtypes: Luminal A (ER-positive [+] and/or PR+, HER2-negative [-], Ki-67 <14%); Luminal B (ER+ and/or PR+, HER2-, Ki-67 ≥14%; or ER+ and/or PR+, HER2+); HER2-enriched (ER-, PR-, HER2+); or as triple-negative breast cancer (TNBC; ER-, PR-, HER2-) [19-21]. A standardized questionnaire at study entry collected sociodemographic data and electronic medical records provided clinicopathologic information.

Selection of CCL4 polymorphisms

The CCL4 SNPs selected for this study were identified from multi-allelic copy number variation (CNV) profiles encompassing the q12 region of chromosome 17 containing CCL4 genes. Nonsynonymous SNPs rs1634507, rs10491121 and rs1719153 were extracted from a search of the National Center for Biotechnology Information (NCBI) dbSNP database.

Genomic DNA extraction

The QIAamp DNA Blood Mini Kit (Qiagen, Inc., Valencia, CA, USA) purified genomic DNA from peripheral blood leukocytes. The DNA was dissolved in TE buffer (10 mM Tris, 1 mM EDTA; pH 7.8), quantified by OD260, then stored at -20℃ for further analysis.

Real-time PCR

The ABI StepOne™ real-time polymerase chain reaction (PCR) system (Applied Biosystems, Foster City, CA, USA) assessed sequencing of allelic discrimination for the CCL4 SNP. The TaqMan assay used Software Design Specification version 3.0 software (Applied Biosystems) to analyze the discrimination data. Primers and probes consisted of rs1634507 “AGTTTTCTTGACCTCATGAATGCTG-[G/T]TGAGGCTTTATCCCTCTCTCAGGAA” (product ID: C_7451708_10), rs10491121 “CCTATCCCCTTCCTGAATTAAGTCC-[A/G]AATATAGTCAGTCTTTGAGTGTGGA” (product ID: C_11626804_10) and rs1719153 “TAGGGACTGTTGCACCGAGTTTCAC-[A/T]GTTAAGGAAACAGAGGCACAGAGAG” (product ID: C_12120537_10). PCRs were performed in a total volume of 10 μL containing Master Mix (5 μL), probes (0.25 μL) and genomic DNA (10 ng). The real-time PCR reaction included an initial denaturation step at 95°C for 10 min, then 40 amplification cycles of 95°C for 15 secs and 60°C for 1 min [19, 22].

Statistical analysis

Between-group differences were considered significant if p-values were less than 0.05. Chi-square analysis tested for Hardy-Weinberg equilibrium in the SNP genotype distributions. The Mann-Whitney U-test and Fisher's exact test were utilized for between-group demographic comparisons. Multiple logistic regression models adjusted for confounding variables estimated adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for associations between genotype frequencies and the risk of breast cancer or clinicopathologic characteristics. Haplotype frequencies were analyzed using Haploview [23]. All data were analyzed with the software program Statistical Analytic System version 9.1 and are reported as the sample mean ± the standard deviation (SD).

Results

All study participants were Chinese Han (Table 1). The majority were nonsmokers and did not consume alcohol. There was a significantly higher proportion of younger age participants in the control group compared with the breast cancer cohort (p<0.05). Most patients (77.1%) had stage I/II breast cancer; 22.9% had stage III/IV disease (Table 1). In an analysis of hormone receptor status, tumors were mostly ER- (69.7%), PR- (54.1%), or HER2+ (63.1%) (Table 1).

 Table 1 

Demographic and clinicopathologic characteristics among healthy cancer-free controls and patients with breast cancer.

VariableControls
N=209 (%)
Patients
N=314 (%)
p value
Age (years)Mean ± SDMean ± SD
38.5±16.753.1±11.4*p<0.05
Tobacco smokers
No202 (96.7)313 (99.7)
Yes7 (3.3)1 (0.3)*p<0.05
Alcohol consumption
No203 (97.1)295 (93.9)
Yes6 (2.9)19 (6.1)p>0.05
Clinical stage
I/II242 (77.1)
III/IV72 (22.9)
Tumor size
≤T2298 (94.9)
>T216 (5.1)
Lymph node status
N0+N1247 (78.7)
N2+N367 (21.3)
Distant metastasis
M0304 (96.8)
M110 (3.2)
Histological grade
G1+G2218 (69.4)
G3+G496 (30.6)
ER status
Positive95 (30.3)
Negative219 (69.7)
PR status
Positive144 (45.9)
Negative170 (54.1)
HER2 status
Positive198 (63.1)
Negative116 (36.9)

The Mann-Whitney U-test and Fisher's exact test were used to compare values between controls and patients with breast cancer. *p < 0.05 was statistically significant. T2 = tumor >20 mm but ≤50 mm in greatest dimension; N0 = lymph node-negative; N1 = cancer has spread to 1-3 lymph node(s); N2 = 4-9 lymph nodes; N3 = ≥10 positive lymph nodes; M0 = noninvasive cancer; M1 = cancer has metastasized to organs or lymph nodes away from the breast; G1 = well differentiated (low grade); G2 = moderately differentiated (intermediate grade); G3 = poorly differentiated (high grade); G4 = undifferentiated (high grade); ER = estrogen receptor; PR = progesterone receptor; HER2 = human epidermal growth factor receptor 2.

Polymorphism frequencies are shown in Table 2. All genotypes were in Hardy-Weinberg equilibrium (p > 0.05). In both study groups, the most frequent genotypes for SNPs rs10491121, rs1634507 and rs1719153 were homozygous for A/A, homozygous for G/G and homozygous for A/A. Analyses that adjusted for potential confounders found no significant between-group differences for the polymorphism frequencies.

 Table 2 

Distribution frequencies of CCL4 genotypes among healthy cancer-free controls and patients with breast cancer.

VariableControls
N=209 (%)
Patients
N=314 (%)
OR (95% CI)
rs10491121
AA64 (41)79 (34.2)1.00 (reference)
AG92 (59)152 (65.8)1.338 (0.88-2.035)
GG53 (45.3)83 (51.2)1.269 (0.787-2.044)
AG+GG145 (69.4)235 (74.8)1.313 (0.89-1.938)
rs1634507
GG101 (54.9)135 (49.5)1.00 (reference)
GT83 (45.1)138 (50.5)1.244 (0.855-1.810)
TT25 (19.8)41 (23.3)1.227 (0.701-2.148)
GT+TT108 (51.7)179 (57)1.240 (0.873-1.762)
rs1719153
AA101 (55.5)149 (52.7)1.00 (reference)
AT81 (44.5)134 (47.3)1.121 (0.771-1.630)
TT27 (21.1)31 (17.2)0.778 (0.438-1.382)
AT+TT108 (51.7)165 (52.5)1.036 (0.73-1.470)

The odds ratios (ORs) with their 95% confidence intervals (CIs) were estimated by logistic regression analysis. The adjusted ORs (AORs) with their 95% CIs were estimated by multiple logistic regression analysis that controlled for tobacco smoking, alcohol consumption and age.

A comparison of clinicopathologic characteristics and CCL4 genotypes revealed no significant differences (Table 3). Similarly, an analysis of CCL4 genotypic frequencies amongst breast cancer subtypes failed to identify any significant differences between patients and controls (Table 4). However, among luminal A and luminal B subtypes, patients carrying the AG genotype at SNP rs10491121 were less likely to develop lymph node metastasis compared with AA genotype carriers (AOR, 0.298; 95% CI: 0.1-0.885) (Table 5). In addition, patients with the rs10491121 AG + GG genotype were at lower risk of developing distant metastasis compared with AA genotype carriers (AOR, 0.106; 95% CI: 0.011-1.038). Moreover, the presence of the TT haplotype at the SNP rs1719153 (AOR 3.316; 95% CI: 1.12-9.815) increased the likelihood of developing pathologic grade (G3+G4) disease (Table 5).

Figure 1 represents the reconstructed linkage disequilibrium plot of the genotyped polymorphisms in our study population. In one haploblock, rs1634507 and rs10491121 displayed 98% linkage disequilibrium. CCL4 SNPs rs1634507 and rs1719153 expressed 95% linkage disequilibrium; rs10491121 and rs1719153 expressed 97% linkage disequilibrium (Fig. 1).

 Table 3 

Odds ratios and their confidence intervals for clinical status and CCL4 genotypic frequencies in patients with breast cancer.

GenotypePatients
N=314 (%)
OR (95% CI)
Clinical stage
Stage I/IIStage III/IV
rs10491121
AA55 (25)24 (25.5)1.00 (reference)
AG+GG165 (75)70 (74.5)0.972 (0.558-1.694)
rs1634507
GG98 (44.5)37 (39.4)1.00 (reference)
GT+TT122 (55.5)57 (60.6)1.237 (0.757-2.024)
rs1719153
AA109 (49.5)40 (42.6)1.00 (reference)
AT+TT111 (50.5)54 (57.4)1.326 (0.815-2.157)
Tumor size
≤T2>T2
rs10491121
AA76 (25.5)3 (18.8)1.00 (reference)
AG+GG222 (74.5)13 (81.2)1.483 (0.412-5.347)
rs1634507
GG130 (43.6)5 (31.2)1.00 (reference)
GT+TT168 (56.4)11 (68.8)1.702 (0.577-5.021)
rs1719153
AA144 (48.3)5 (31.2)1.00 (reference)
AT+TT154 (51.7)11 (68.8)2.057 (0.698-6.065)
Lymph node status
N0+N1N2+N3
rs10491121
AA68 (86.1)11 (13.9)1.00 (reference)
AG+GG215 (91.5)20 (8.5)0.575 (0.262-1.260)
rs1634507
GG121 (89.6)14 (10.4)1.00 (reference)
GT+TT162 (90.5)17 (9.5)0.907 (0.403-1.911)
rs1719153
AA136 (91.3)13 (8.7)1.00 (reference)
AT+TT147 (89.1)18 (10.9)1.281 (0.605-2.713)
Distant metastasis
M0M1
rs10491121
AA74 (93.7)5 (6.3)1.00 (reference)
AG+GG230 (97.9)5 (2.1)0.322 (0.91-1.142)
rs1634507
GG130 (96.3)5 (3.7)1.00 (reference)
GT+TT174 (97.2)5 (2.8)0.747 (0.212-2.635)
rs1719153
AA144 (96.6)5 (3.4)1.00 (reference)
AT+TT160 (97)5 (3)0.9 (0.255-3.172)
Histologic grade
G1+G2G3+G4
rs10491121
AA58 (73.4)21 (26.6)1.00 (reference)
AG+GG160 (68.1)75 (31.9)1.295 (0.732-2.288)
rs1634507
GG99 (73.3)36 (26.7)1.00 (reference)
GT+TT119 (66.5)60 (33.5)1.387 (0.848-2.267)
rs1719153
AA109 (73.2)40 (26.8)1.00 (reference)
AT+TT109 (66.1)56 (33.9)1.4 (0.862-2.274)

The odds ratios (ORs) with their 95% confidence intervals (CIs) were estimated by logistic regression analysis. The adjusted odds ratios (AORs) with their 95% CIs were estimated by multiple logistic regression analysis that controlled for smoking, consumption and age.

T2 = tumor >20 mm but ≤50 mm in greatest dimension; N0 = lymph node-negative; N1 = cancer has spread to 1-3 lymph node(s); N2 = 4-9 lymph nodes; N3 = ≥10 positive lymph nodes; M0 = noninvasive cancer; M1 = cancer has metastasized to organs or lymph nodes away from the breast; G1 = well differentiated (low grade); G2 = moderately differentiated (intermediate grade); G3 = poorly differentiated (high grade); G4 = undifferentiated (high grade).

 Table 4 

Distribution frequencies of CCL4 genotypes in breast cancer subtypes.

VariableControl N= 209(%)Patients N= 220(%)
Lumina A + Lumina B
OR (95% CI)VariableControl N= 209(%)Patients N= 94(%)
HER2 overexpression + TNBC
OR (95% CI)
rs10491121rs10491121
AA64 (53.8)55 (46.2)1.00 (reference)AA64 (76.2)20 (23.8)1.00 (reference)
AG92 (45.8)109 (54.2)1.379 (0.875-2.173)AG92 (74.2)32 (25.8)1.113 (0.585-2.118)
GG53 (48.6)56 (51.4)1.23 (0.731-2.069)GG53 (72.6)20 (27.4)1.208 (0.588-2.478)
AG+GG145 (46.8)165 (53.2)1.324 (0.867-2.023)AG+GG145 (73.6)52 (26.4)1.148 (0.634-2.078)
rs1634507rs1634507
GG101 (50.8)98 (49.2)1.00 (reference)GG101 (77.7)29 (22.3)1.00 (reference)
GT83 (46.6)95 (53.4)1.18 (0.787-1.768)GT83 (69.7)36 (30.3)1.511 (0.855-2.668)
TT25 (48.1)27 (49.8)1.113 (0.604-2.050)TT25 (78.1)7 (21.9)0.975 (0.383-2.482)
GT+TT108 (47)122 (53)1.164 (0.796-1.702)GT+TT108 (74.4)72 (25.6)1.387 (0.805-2.388)
rs1719153rs1719153
AA101 (48.1)109 (51.9)1.00 (reference)AA101 (75.9)32 (24.1)1.00 (reference)
AT81 (46.3)94 (53.7)1.075 (0.719-1.607)AT81 (69.8)35 (30.2)1.364 (0.778-2.391)
TT27 (61.4)17 (38.6)0.583 (0.3-1.134)TT27 (84.4)5 (15.6)0.584 (0.208-1.643)
AT+TT108 (49.3)111 (50.7)0.952 (0.652-1.391)AT+TT108 (73)40 (27)1.169 (0.682-2.002)

The odds ratios (ORs) with their 95% confidence intervals (CIs) were estimated by logistic regression analysis. The adjusted odds ratios (AORs) with their 95% CIs were estimated by multiple logistic regression analysis that controlled for smoking, consumption and age.

HER2 = human epidermal growth factor receptor 2; TNBC = triple-negative breast cancer.

 Table 5 

Odds ratios and their confidence intervals for clinical status and CCL4 genotypic frequencies in breast cancer subtypes.

VariableLuminal A + Luminal B
N=220 (%)
HER2 overexpression + TNBC
N=94 (%)
Clinical StageClinical Stage
Stage I/IIStage III/IVOR (95% CI)Stage I/IIStage III/IVOR (95% CI)
rs10491121
AA40 (72.7)15 (27.3)1.00 (reference)19 (79.2)5 (20.8)1.00 (reference)
AG93 (85.3)16 (14.7)0.459 (0.207-1.017)27 (62.8)16 (37.2)2.252 (0.704-7.206)
GG40 (71.4)16 (28.6)1.067 (0.465-2.445)23 (85.2)4 (14.8)0.661 (0.155-2.813)
AG+GG133 (80.6)32 (19.4)0.642 (0.316-1.302)50 (71.4)20 (28.6)1.52 (0.499-4.627)
rs1634507
GG77 (78.6)21 (21.4)1.00 (reference)29 (78.4)8 (21.6)1.00 (reference)
GT74 (77.9)21 (22.1)1.041 (0.525-2.062)28 (65.1)15 (34.9)1.942 (0.712-5.294)
TT22 (81.5)5 (18.5)0.833 (0.282-2.464)12 (85.7)2 (14.3)0.604 (0.112-3.272)
GT+TT96 (78.7)26 (21.3)0.993 (0.519-1.899)40 (70.2)17 (29.8)1.541 (0.586-4.051)
rs1719153
AA85 (78)24 (22)1.00 (reference)32 (80)8 (20)1.00 (reference)
AT74 (78.7)20 (21.3)0.957 (0.49-1.871)25 (62.5)15 (37.5)2.4 (0.879-6.556)
TT14 (82.4)3 (17.6)0.759 (0.201-2.86)12 (85.7)2 (14.3)0.667 (0.124-3.597)
AT+TT88 (79.3)23 (20.7)0.926 (0.486-1.764)37 (68.5)17 (31.5)1.838 (0.701-4.821)
Tumor sizeTumor size
≤T2>T2OR (95% CI)≤T2>T2OR (95% CI)
rs10491121
AA53 (96.4)2 (3.6)1.00 (reference)23 (95.8)1 (4.2)1.00 (reference)
AG106 (97.2)3 (2.8)0.75 (0.122-4.626)38 (88.4)5 (11.6)3.026 (0.332-27.548)
GG54 (96.4)2 (3.6)0.981 (0.133-7.225)24 (88.9)3 (11.1)2.875 (0.279-29.677)
AG+GG160 (97)5 (3)0.828 (0.156-4.395)62 (88.6)8 (11.4)2.968 (0.352-25.054)
rs1634507
GG95 (96.9)3 (3.1)1.00 (reference)35 (94.6)2 (5.4)1.00 (reference)
GT92 (96.8)3 (3.2)1.033 (0.203-5.248)37 (86)6 (14)2.838 (0.537-15.01)
TT26 (96.3)1 (3.7)1.218 (0.122-12.201)13 (92.9)1 (7.1)1.346 (0.112-16.13)
GT+TT118 (96.7)4 (3.3)1.073 (0.235-4.914)50 (87.7)7 (12.3)2.45 (0.48-12.501)
rs1719153
AA106 (97.2)3 (2.8)1.00 (reference)38 (95)2 (5)1.00 (reference)
AT91 (96.8)3 (3.2)1.165 (0.229-5.913)34 (85)6 (15)3.353 (0.634-17.738)
TT16 (94.1)1 (5.9)2.208 (0.216-22.548)13 (92.9)1 (7.1)1.462 (0.122-17.482)
AT+TT107 (96.4)4 (3.6)1.321 (0.289-6.044)47 (87)7 (13)2.83 (0.555-14.423)
Lymph node statusLymph node status
N0+N1N2+N3OR (95% CI)N0+N1N2+N3OR (95% CI)
rs10491121
AA46 (83.6)9 (16.4)1.00 (reference)22 (91.7)2 (8.3)1.00 (reference)
AG103 (94.5)6 (5.5)0.298 (0.1-0.885)*37 (86)6 (14)1.784 (0.331-9.619)
GG48 (85.7)8 (14.3)0.852 (0.303-2.397)27 (100)0 (0)0.917 (0.813-1.034)
AG+GG151 (91.5)14 (8.5)0.474 (0.193-1.166)64 (91.4)6 (8.6)1.031 (0.194-5.489)
rs1634507
GG87 (88.8)11 (11.2)1.00 (reference)34 (91.9)3 (8.1)1.00 (reference)
GT87 (91.6)8 (8.4)0.727 (0.279-1.896)38 (88.4)5 (11.6)1.491 (0.331-6.712)
TT23 (85.2)4 (14.8)1.375 (0.401-4.721)14 (100)0 (0)0.919 (0.835-1.011)
GT+TT110 (90.2)23 (10.5)0.863 (0.363-2.049)52 (91.2)5 (8.8)1.09 (0.244-4.861)
rs1719153
AA99 (90.8)10 (9.2)1.00 (reference)37 (92.5)3 (7.5)1.00 (reference)
AT84 (89.4)10 (10.6)1.179 (0.468-2.968)35 (87.5)5 (12.5)1.762 (0.392-7.929)
TT14 (82.4)3 (17.6)2.121 (0.52-8.658)14 (100)0 (0)0.925 (0.847-1.01)
AT+TT98 (88.3)13 (11.7)1.313 (0.55-3.136)49 (90.7)5 (9.3)1.259 (0.283-5.605)
Distant metastasisDistant metastasis
M0M1OR (95% CI)M0M1OR (95% CI)
rs10491121
AA52 (94.5)3 (5.5)1.00 (reference)22 (91.7)2 (8.3)1.00 (reference)
AG109 (100)0 (0)0.945 (0.887-1.007)*40 (93)3 (7)0.825 (0.128-5.317)
GG55 (98.2)1 (1.8)0.315 (0.032-3.127)26 (96.3)1 (3.7)0.423 (0.036-4.985)
AG+GG164 (99.4)1 (0.6)0.106 (0.011-1.038)*66 (94.3)4 (5.7)0.667 (0.114-3.893)
rs1634507
GG95 (96.9)3 (3.1)1.00 (reference)35 (94.6)2 (5.4)1.00 (reference)
GT95 (100)0 (0)0.969 (0.936-1.004)39 (90.7)4 (9.3)1.795 (0.31-10.408)
TT26 (96.3)1 (3.7)1.218 (0.122-12.201)14 (100)0 (0)0.946 (0.876-1.022)
GT+TT121 (99.2)1 (0.8)0.262 (0.027-2.556)53 (93)4 (7)1.321 (0.229-7.602)
rs1719153
AA106 (97.2)3 (2.8)1.00 (reference)38 (95)2 (5)1.00 (reference)
AT94 (100)0 (0)0.972 (0.942-1.004)36 (90)4 (10)2.111 (0.364-12.24)
TT16 (94.1)1 (5.9)2.208 (0.216-22.548)14 (100)0 (0)0.95 (0.885-1.02)
AT+TT110 (99.1)1 (0.9)0.321 (0.033-3.137)50 (92.6)4 (7.4)1.52 (0.264-8.738)
Histological gradeHistological grade
G1+G2G3+G4OR (95% CI)G1+G2G3+G4OR (95% CI)
rs10491121
AA45 (81.8)10 (18.2)1.00 (reference)13 (54.2)11 (45.8)1.00 (reference)
AG95 (87.2)14 (12.8)0.663 (0.274-1.608)16 (37.2)27 (62.8)1.994 (0.724-5.495)
GG40 (71.4)16 (28.6)1.8 (0.734-4.417)9 (33.3)18 (66.7)2.364 (0.761-7.343)
AG+GG135 (81.8)30 (18.2)1 (0.453-2.206)25 (35.7)45 (64.3)2.127 (0.831-5.446)
rs1634507
GG81 (82.7)17 (17.3)1.00 (reference)18 (48.6)19 (51.4)1.00 (reference)
GT81 (85.3)14 (14.7)0.824 (0.381-1.781)16 (37.2)27 (62.8)1.599 (0.654-3.906)
TT18 (66.7)9 (33.3)2.382 (0.916-6.196)4 (28.6)10 (71.4)2.368 (0.628-8.926)
GT+TT99 (81.1)23 (18.9)1.107 (0.554-2.212)20 (35.1)37 (64.9)1.753 (0.754-4.074)
rs1719153
AA90 (82.6)19 (17.4)1.00 (reference)19 (47.5)21 (52.5)1.00 (reference)
AT80 (85.1)14 (14.9)0.829 (0.39-1.76)13 (32.5)27 (67.5)1.879 (0.759-4.655)
TT10 (58.8)7 (41.2)3.316 (1.12-9.815)*6 (42.9)8 (57.1)1.206 (0.354-4.115)
AT+TT90 (81.1)21 (18.9)1.105 (0.557-2.195)19 (35.2)35 (64.8)1.667 (0.723-3.841)

The odds ratios (ORs) with their 95% confidence intervals (CIs) were estimated by logistic regression analysis. The adjusted odds ratios (AORs) with their 95% CIs were estimated by multiple logistic regression analysis that controlled for smoking, consumption and age. * p<0.05.

HER2 = human epidermal growth factor receptor 2; TNBC = triple-negative breast cancer; T2 = tumor >20 mm but ≤50 mm in greatest dimension; N0 = lymph node-negative; N1 = cancer has spread to 1-3 lymph node(s); N2 = 4-9 lymph nodes; N3 = ≥10 positive lymph nodes; M0 = noninvasive cancer; M1 = cancer has metastasized to organs or lymph nodes away from the breast; G1 = well differentiated (low grade); G2 = moderately differentiated (intermediate grade); G3 = poorly differentiated (high grade); G4 = undifferentiated (high grade).

 Figure 1 

Linkage disequilibrium patterns of three single nucleotide polymorphisms in the CCL4 gene.

Int J Med Sci Image (Click on the image to enlarge.)

Discussion

CCL4, also known as macrophage inflammatory protein-1β (MIP-1β), belongs to the pro-inflammatory CC subfamily. MIP proteins recruit pro-inflammatory cells and thus play a crucial role in acute and chronic inflammatory responses in various conditions including asthma, granuloma formation, wound healing, arthritis, multiple sclerosis, pneumonia, and psoriasis [16]. Accumulating evidences indicated CCL4 expression associated with cancer progression such as oral cancer and hepatocellular carcinoma [12, 17]. We have previously suggested that CCL4 gene polymorphisms influence susceptibility to oral cancer and hepatocellular carcinoma and affect their progression [11, 12]. We found that CCL4 rs1634507 G/T polymorphism increased a risk in oral-cancer susceptibility, but CCL4 rs10491121 A/G polymorphism decreased a risk in hepatocellular carcinoma. Now, the findings from this study indicate that CCL4 SNPs may serve as candidate biomarkers for susceptibility to breast cancer.

The 5-year relative survival rate for breast cancer has gradually increased since the early 1990s; between 2007 and 2011 it was ~89.2%. As breast cancer prognosis depends upon the disease stage at the time of diagnosis, increasing screening rates and making genetic testing more widely available increase the chances of early diagnosis [24, 25]. Our study is the first to examine the expression of SNPs rs1634507, rs10491121 and rs1719153 and their possible association with the development of breast cancer. Our investigation into possible associations between these CCL4 SNPs, clinicopathologic markers, and disease susceptibility failed to find any significant differences between patients and healthy controls. Moreover, CCL4 SNPs did not differ significantly according to breast cancer clinical aspects. Amongst luminal A and luminal B subtypes, patients carrying the AG haplotype at SNP rs10491121 were less likely to develop lymph node metastasis compared with patients with the AA haplotype, while patients carrying the AG + GG haplotype at rs10491121 were less likely to develop distant metastasis. The presence of the AT haplotype at the SNP rs1719153 increased the likelihood of developing pathologic grade (G3+G4) disease.

Linkage disequilibrium is expressed across the human genome. Thus, loci can be used as genetic markers to locate adjacent variants that participate in the detection and treatment of disease. Haplotype analyses clarify genetic contribution to disease susceptibility [26, 27]. We observed 98% linkage disequilibrium between rs1634507 and rs10491121, 95% linkage disequilibrium between rs1634507 and rs1719153, and 97% between rs10491121 and rs1719153. These results suggest that these CCL4 haplotypes play an important role in breast cancer development.

This is the first study to demonstrate a correlation between CCL4 polymorphisms and breast cancer risk. CCL4 may prove to be a diagnostic marker and therapeutic target for breast cancer therapy.

Acknowledgements

This work was supported by two grants from China Medical University Hospital (CMU106-S-05) of Taiwan and Medical and Health Science and Technology Project of Zhejiang Province (2012KYB230) of China.

Competing Interests

The authors have declared that no competing interest exists.

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Author contact

Corresponding address Corresponding authors: Chih-Hsin Tang PhD; Department of Pharmacology, School of Medicine, China Medical University, Taichung, Taiwan. E-mail: chtangcmu.edu.tw and Chen-Ming Su, PhD; Department of Biomedical Sciences Laboratory, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China. E-mail: ericsucmcom, proof814com


Received 2018-4-19
Accepted 2018-6-30
Published 2018-7-30