Open Access

Association of angiogenesis and inflammation‑related gene functional polymorphisms with early‑stage breast cancer prognosis

  • Authors:
    • Erika Korobeinikova
    • Rasa Ugenskiene
    • Ruta Insodaite
    • Viktoras Rudzianskas
    • Evelina Jaselske
    • Lina Poskiene
    • Elona Juozaityte
  • View Affiliations

  • Published online on: April 7, 2020     https://doi.org/10.3892/ol.2020.11521
  • Pages: 3687-3700
  • Copyright: © Korobeinikova et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Genetic variations in inflammation- and angiogenesis-related genes may alter the coded protein level and impact the pathogenesis of breast cancer (BC). The present study investigated the association of functional single nucleotide polymorphisms (SNPs) in the VEGFA, IL‑1β, IL‑1α and IL‑6 genes with the early‑stage BC phenotype and survival. Genomic DNA and clinical data were collected for 202 adult Eastern European (Lithuanian) women with primary I‑II stage BC. Genotyping of the SNPs was performed using TaqMan SNP genotyping assays. Nine VEGFA, IL‑1β, IL‑1α and IL‑6 polymorphisms were analysed. The VEGFA and IL‑6 haplotypes were inferred using Phase software. Patients were prospectively followed‑up for recurrence, occurrence of metastasis and mortality until April 30, 2019. All studied genotypes were in Hardy‑Weinberg equilibrium and had the same distribution as the 1,000 Genomes project Phase 3 dataset for European population. Significant associations of the studied SNPs with clinicopathologic variables were observed between IL‑1α rs1800587 C allele and larger primary tumour size; IL‑6 rs1800797 A allele, rs1800797 GA genotype, rs1800795 C allele, IL‑6 (rs1800797‑re1800795) AC diplotype and hormonal receptor‑positive disease; IL‑6 rs1800797 A allele and HER2 negative status. In univariate Cox survival analysis, IL‑1α rs1800587 CC and IL‑6 rs1800797 GG genotype carriers exhibited worse disease‑free survival (DFS), metastasis‑free survival (MFS) and overall survival (OS). The IL‑6 rs1800795 GG genotype was associated with worse OS. IL‑6 (rs1800797, rs1800795) GG/GG diplotype carriers had shorter MFS and OS. Multivariate Cox survival analysis revealed that the IL‑1α rs1800587 CC genotype was an independent negative prognostic factor for DFS, MFS and OS, and the IL6 GG/GG diplotype was an independent negative prognostic factor for MFS and OS. According to the present study, functional SNPs in the IL‑1α and IL‑6 genes may contribute to the identification of patients at higher risk of BC recurrence, development of metastases and worse OS among early‑stage patients with BC.

Introduction

Breast cancer (BC) is one of the most commonly diagnosed cancers and the leading cause of cancer death among women worldwide (1). Improved diagnostic capabilities has led to an increased rate of BC identified at an early stage (2). However, despite early diagnosis and treatment, the rate of recurrence and metastasis following radical treatment remains disappointingly high, and survival varies considerably between patients with closely matching tumour characteristics.

Inflammation and angiogenesis are the main drivers of cancer. These processes are tightly interconnected in the sense that many pro-inflammatory proteins possess proangiogenic properties and vice versa. The formation of new blood vessels in malignant tumours ensures the supply of nutrients and oxygen, hence promoting the spread of tumour cells (3). Microvessel density is a pivotal risk factor for metastasis and a predictor of poor BC prognosis (4).

The vascular endothelial growth factor A (VEGFA, or VEGF) is the best-known proangiogenic molecule. VEGFA mediates the growth of new blood vessels by binding to the endothelial cell surface receptors. It promotes endothelial cell proliferation, migration and the formation of tubular structures (5). Another mechanism of tumour neovascularization is the so-called inflammatory angiogenesis. Such pro-inflammatory cytokines as interleukin-1β (IL-1β), interlukin-1α (IL-1α) and interleukin-6 (IL-6) through a variety of signalling pathways promote endothelial cell migration and proliferation, contributing to tumour angiogenesis that facilitates the survival of cancer cells (6,7). Apart from stimulating angiogenesis, VEGFA, IL-1β1, IL-1α and IL-6 are also involved in inflammatory processes. These proteins may prevent apoptosis and promote cancer cell proliferation, differentiation, migration and metastasis.

The association between the above-mentioned proteins and BC prognosis was demonstrated by several authors. The elevated serum level of VEGFA in metastatic BC patients is linked to worse progression-free survival (PFS) and overall survival (OS) (8). Another cytokine, IL-6, induces epithelial-mesenchymal phenotype and therapeutic resistance in BC cells (9). Higher circulating levels of IL6 were observed in more advanced stages of the disease (10). It was also found that high tumour co-expression of the VEGF and IL-6 family cytokines significantly lowers the human epidermal growth factor receptor 2 (HER2) negative BC survival (11). Moreover, higher expression of pro-inflammatory IL-1β cytokine is correlated with higher BC stage and significantly worse survival (12). In addition, IL-1α acts as a pro-inflammatory molecule itself and also promotes the activity of IL-1β, resulting in an increased growth of BC cells and tumour progression (13).

Common polymorphisms in proinflammatory and proangiogenic cytokine genes may influence their coded protein production and play a role in the course of BC. The polymorphisms with proved functional activity are VEGFA (rs699947, rs833061, rs25648, rs1005230), IL-1β (rs1143634, rs16944), IL-1α (rs1800587) and IL-6 (rs1800795, rs1800797) (1421). Candidate gene studies as well as moderate-sized genome-wide association studies (GWAS) highlight the important role of these polymorphisms in BC risk and aggressiveness (2232), although substantial heterogeneity across studies exists. The currently available results are inconsistent in terms of different ethnicity and cancer stage; therefore, it is necessary to further investigate the role of VEGFA, IL-1β, IL-1α and IL-6 gene polymorphisms in breast carcinogenesis and cancer progression.

This paper describes a cohort study that aimed to examine the contribution of VEGFA, IL-1β, IL-1α and IL-6 gene polymorphisms to the clinicopathologic features and survival in a homogeneous group of Eastern European (specifically, Lithuanian) early-stage BC patients.

Materials and methods

Patients

The study consisted of 202 adult Lithuanian women with primary I–II stage BC. All patients were treated in the Hospital of Lithuanian University of Health Sciences Kaunas Clinics. The exclusion criteria were other malignancies, significant comorbidities and/or incomplete medical documentation. Surgery and adjuvant therapy were chosen by the clinicians, based on pathomorphologic characteristics and validated prognostic factors. The patients were followed until 30 April, 2019 (censoring date).

Candidate polymorphisms

The genes and polymorphisms known to modulate inflammation and angiogenesis were selected. The selection criteria included: i) functional single nucleotide polymorphisms (SNPs) in the VEGFA, IL-1β, IL-1α and IL-6 genes predicting alterations in the protein level; ii) SNP relevant to outcomes in other settings; and iii) SNP with a minor allele frequency greater than 15% in the study population. We selected nine SNPs: The VEGFA gene rs699947, rs833061, rs25648, and rs1005230; the IL-1β gene rs1143634 and rs16944; the IL-1α gene rs1800587; and the IL-6 gene rs1800795 and rs1800797.

Assay methods

Peripheral blood samples from the study population were collected in 2009–2017. For genomic DNA extraction from peripheral blood leukocytes, a commercially available DNA extraction kit (i.e., Thermo Fisher Scientific Baltics, Lithuania) was used. The DNA was stored at −20°C prior to usage.

Genotyping of the selected polymorphisms was performed at the Dr. K. Janusauskas Laboratory of Genetics of the Institute of Biology Systems and Genetic Research of Lithuanian University of Health Sciences Kaunas Clinics. The SNPs of the target genes were estimated by using TaqMan SNP Genotyping Assays (C_8311602_10, C_1647381_10, C_791476_10, C_8311612_10, C_1839697_20, C_1839695_20, C_9546517_10, C_1839943_10, C_1839943_10; Applied Biosystems; Thermo Fisher Scientific, Inc.). The polymerase chain reaction was performed in a reaction volume of 25 µl containing template DNA (2 ng), 2X TaqMan Universal Master Mix II, no UNG (Applied Biosystems; Thermo Fisher Scientific, Inc.)-12,5 µl, 20X TaqMan SNP Genotyping Assay stock (initial stock of 40X or 80X was diluted to get 20X working stock)-1,25 µl. The final volume of 25 µl was adjusted by adding nuclease free ddH2O. Finally, the 2 µl of DNA was added from each sample. For negative control, nuclease free ddH2O was used instead of patient DNA, while for positive control, the DNA of the known genotype was used. Each sample genotyping was repeated twice for accuracy.

The Applied Biosystems 7900HT Real-Time Polymerase Chain Reaction System (Applied Biosystems; Thermo Fisher Scientific, Inc.) was used for SNP detection. The cycling program started from heating up to 95°C for 10 min followed by 40 cycles (at 95°C for 15 sec and at 60°C for 1 min). Finally, allelic discrimination was done by using the SDS 2.3 software provided by Applied Biosystems; Thermo Fisher Scientific, Inc.

Study design

A prospective cohort study was conducted at the Hospital of Lithuanian University of Health Sciences. For the case selection, information on primarily BC patients was retrieved from the hospital's Pathology Department. The patients who fulfilled the inclusion criteria and signed the informed consent document (approved by the Kaunas Regional Ethics Committee for Biomedical research; Protocol number BE-2-10) were enrolled in the study and their peripheral blood samples were obtained. The characteristics of clinical and pathological features and the course of the disease were obtained for all study subjects. The date of histological BC verification was time zero in the survival analysis. The endpoints of interest were disease-free survival (DFS), metastasis-free survival (MFS) and OS. We checked for associations of SNPs with the known BC prognostic factors and survival endpoints. The guidelines for the reporting of tumour marker prognostic studies were applied while conducting the study (33,34).

Statistical analysis

The allele frequency distributions of the investigated SNPs were compared with the European population data from the 1000 Genomes project phase 3 database (35). For each SNP a Hardy-Weinberg equilibrium was assessed by using Pearson's chi square and Fisher's exact tests. The Haploview v4.1 software was used to check for the linkage disequilibrium between SNPs (36). The VEGFA and IL-6 haplotypes were inferred from the tested SNPs by Bayesian methods as implemented in the Phase software (v2.1; Department of Statistics, University of Washington, Seattle, WA, USA) (37,38). The SNPs were analysed under genotype, allelic and haplotype (for IL-6 and VEGFA SNPs) models. The associations of polymorphisms with clinicopathologic variables were evaluated by Pearson's Chi-square or Fisher's exact test. The Bonferroni-corrected α level was used in the association analysis for multiple comparisons. Moreover, the Cox proportional hazards model was used to estimate the prognostic factors for DFS, MFS and OS. In addition, multivariate analysis was used to determine the interdependency of genotypes and other known prognostic factors, such as age, tumour differentiation grade, tumour size, lymph node status, oestrogen receptor status, progesterone receptor status and human epidermal growth factor receptor 2 (HER2) status. Hazard ratios (HR) and their 95% confidence intervals (CI) were recorded for each tested marker. Finally, the Kaplan-Meier analysis with the log-rank test was applied to compare the survival of the patients with different genotypes. Statistical significance was set at 5% (P<0.05). Statistical analysis was performed using SPSS for Windows v20.0 (Released 2011; IBM Corp).

Results

Sample characteristics

A total of 202 Lithuanian women with early-stage BC were included in the current analysis. The frequency distributions of clinical and tumour biological factors are shown in Table I. For all study participants, primary treatments included surgery (100%), chemotherapy (77%), hormone therapy (71%), trastuzumab (19%) and radiation therapy (97%).

Table I.

Frequency data for clinical and tumour biological factors.

Table I.

Frequency data for clinical and tumour biological factors.

FactorPatients, %
Age at diagnosis, years
  <50 years65
  ≥50 years35
Tumour size, cm
  <264
  2–536
Lymph node status
  Positive55
  Negative45
Grade
  G1 and G278
  G322
ER status
  ER positive68
  ER negative32
PR status
  PR positive60
  PR negative40
HER2 status
  HER2 positive19
  HER2 negative81

[i] ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2.

All the patients were genotyped for a panel of nine SNPs: The VEGFA gene rs699947, rs833061, rs25648 and rs1005230; the IL-1β gene rs1143634 and rs16944; the IL-1α gene rs1800587; the IL-6 gene rs1800795 and rs1800797. The genotypes were found to be in Hardy-Weinberg equilibrium in all the nine SNPs. A strong linkage disequilibrium between four VEGFA and two IL-6 polymorphisms was confirmed (Fig. 1). Our cohort had similar allele distribution to that of the 1000 Genomes project phase 3 for European population. The genotype and allele frequency data is presented in Table II.

Table II.

Allele and genotype frequencies of analysed single nucleotide polymorphisms in the study population and in European population data from the 1000 Genomes Project Phase 3 database.

Table II.

Allele and genotype frequencies of analysed single nucleotide polymorphisms in the study population and in European population data from the 1000 Genomes Project Phase 3 database.

GenePolymorphismStudy allele and genotype frequencies (1000 Genomes Project Phase 3 database allele frequencies)
VEGFArs699947A, 0.53 (0.50)C, 0.47 (0.50)AA, 0.28CA, 0.50CC, 0.22
rs833061T, 0.47 (0.50)C, 0.53 (0.50)TT, 0.21TC, 0.51CC, 0.28
rs25648C, 0.81 (0.83)T, 0.19 (0.17)TT, 0.03CT, 0.32CC, 0.65
rs1005230T, 0.52 (0.50)C, 0.48 (0.50)TT, 0.28CT, 0.49CC, 0.23
IL-6rs1800795C, 0.47 (0.42)G, 0.53 (0.58)CC, 0.24GC, 0.47GG, 0.29
rs1800797A, 0.46 (0.41)G, 0.54 (0.59)AA, 0.23GA, 0.47GG, 0.30
IL-1βrs1143634G, 0.73 (0.75)A, 0.27 (0.25)GG, 0.52GA, 0.42AA, 0.06
rs16944G, 0.66 (0.65)A, 0.34 (0.35)GG, 0.43GA, 0.47AA, 0.10
IL-1αrs1800587C, 0.69 (0.71)T, 0.31 (0.29)CC, 0.48CT, 0.43TT, 0.09

[i] VEGFA, vascular endothelial growth factor A; IL, interleukin.

Inferential analysis

The data on associations between the analysed polymorphisms and clinicopathologic tumour features is shown in Tables SISVI. In the single-locus analysis, the genotype model revealed a significant link between the IL-6 rs1800797 genotypes and the oestrogen receptor (P=0.005) and the progesterone receptor (P=0.007) status (Bonferoni adjusted; significant p value <0.008). The allelic model showed that the A allele of this SNP is associated with positive oestrogen receptors (OR 2.23; 95% CI: 1.19–4.08; P=0.014). Patients carrying the IL-6 rs 1800797 A allele were also predisposed to higher rates of HER2 negative BC (OR 2.21; 95% CI: 1.07–4.57; P=0.042). Additionally, another IL-6 polymorphism, rs1800795, in both genotype and allelic models was linked to oestrogen receptor positive BC. Specifically, 72% of patients carrying the IL-6 rs1800795 C allele had oestrogen receptor positive disease, compared to 58% of non-carriers (OR 1.92; 95% CI: 1.04–3.57; P=0.04).

Linkage disequilibrium analysis showed a high degree of disequilibrium between the two IL-6 SNPs (r2=0.89), meaning that the associations were not independent. As such, haplotype analysis was performed to further explore the relationship between IL-6 variations and other prognostic factors. Phasing revealed three possible IL-6 (rs1800797, rs1800795) haplotypes: GG (51.7%), AC (45.5%) and GC (2.8%). It was further demonstrated that the AC haplotype was positively associated with oestrogen receptor positive BC (HR 2.13; 95% CI 1.14–3.98; P=0.018; Table SII).

By analysing the associations between the IL-1α SNP and clinicopathologic factors (Table SIII), we found a link between the IL-1α rs1800587 SNP C allele and larger primary tumour size (comparing tumours sized <2 vs. 2–5 cm) (OR 4.91; 95% CI: 1.09–22.01; P=0.022).

Other analysed polymorphisms of IL-1β and VEGFA revealed no associations with the evaluated prognostic factors in neither genotype nor allelic models (Tables SIVSVI). Due to the strong linkage disequilibrium, four VEGFA polymorphisms were also analysed in the haplotype model. Three main haplotypes were identified: CCTC (45.5%), ATCC (33.4%) and ATCT (17.6%), as well as several rare variants. None of the VEGFA haplotypes was associated with clinicopathologic prognostic variables.

Survival analysis

In the mean follow-up time of 67 months (range 28–202), progression of the disease was observed for 33 patients. Of those who progressed, 28 had distant metastases. Twenty-two patients with progressive disease died, all due to cancer. The Kaplan-Meier survival analysis showed that the IL-1α rs1800587 SNP is associated with early-stage breast cancer DFS, MFS and OS. In particular, patients homozygous for the C allele (CC) had worse survival rates than patients homozygous and heterozygous for the A allele (CT and TT) (Fig. 2A-C).

The univariate Cox regression analysis (presented in Tables IIIV) revealed that L-1α rs1800587 CC genotype carriers had 2.48 times higher risk of disease recurrence (95% CI: 1.19–5.11; P=0.014), 3.12 times higher risk of metastasis (95% CI: 1.37–7.10; P=0.007) and 2.63 times higher risk of death (95% CI: 1.07–6.46; P=0.035) than the carriers of CT and TT genotypes (Table III).

Table III.

Cox's univariate model for IL-1β and IL-1α SNPs.

Table III.

Cox's univariate model for IL-1β and IL-1α SNPs.

PFSMFSOS



Reference SNP IDModel Genotype/allele/haplotypePatients nUnivariate hazard ratio (95% CI)P-valueUnivariate hazard ratio (CI)P-valueMultivariate hazard ratio (95% CI)P-value
IL-1β rs1143634GenotypeAA1210.04310.06210.271
GA850.443 (0.094–2.100)0.3050.945 (0.116–7.688)0.3600.773 (0.093–6.421)0.811
GG1051.243 (0.292–5.291)0.7682.555 (0.343–19.048)0.9581.667 (0.220–12.630)0.621
AllelicA allele carriers971 1 1
A allele non carriers1052.490 (0.944–5.246)0.0562.686 (0.932–6.102)0.0582.087 (0.851–5.122)0.108
G allele carriers1901 1 1
G allele non carriers121.171 (0.279–4.913)0.8290.563 (0.076–4.148)0.5730.799 (0.107–5.939)0.826
IL-1-β rs16944GenotypeAA2010.33510.34710.715
GA951.657 (0.387–7.096)0.4961.386 (0.320–6.005)0.6631.183 (0.264–5.287)0.826
GG870.974 (0.216–4.396)0.9730.763 (0.165–3.533)0.7290.814 (0.173–3.834)0.794
AllelicA allele carriers1151 1 1
A allele non carriers870.623 (0.302–1.294)0.2010.573 (0.259–1.267)0.1690.706 (0.296–1.684)0.432
G allele carriers1821 1 1
G allele non carriers200.754 (0.180–3.155)0.700.926 (0.220–3.905)0.9170.999 (0.233–4.277)0.99
IL-1α rs1800587GenotypeTT1810.04910.02510.108
CT870.805 (0.174–3.729)0.7821.292 (0.159–10.506)0.8111.015 (0.122–8.428)0.989
CC972.067 (0.486–8.794)0.3263.891 (0.521–29.034)0.1852.664 (0.352–20.187)0.343
AllelicT allele carriers1051 1 1
T allele non carriers972.480 (1.199–5.114)0.014a3.122 (1.372–7.104)0.007a2.632 (1.072–6.461)0.035a
C allele carriers1841 1 1
C allele non carriers180.703 (0.168–2.940)0.6300.392 (0.053–2.888)0.3580.551 (0.074–4.096)0.560

a Significant. Unadjusted hazard ratios for PFS, MFS and OS with each of the SNPs in genotype and allelic model. IL, interleukin; PFS, progression-free survival; MFS, metastasis-free survival; OS, overall survival; SNP, single nucleotide polymorphism.

Table V.

Cox's univariate model for VEGFA SNPs.

Table V.

Cox's univariate model for VEGFA SNPs.

PFSMFSOS



Reference SNP IDModel Genotype/allele/haplotypePatients, nUnivariate hazard ratio (95% CI)P-valueUnivariate hazard ratio (95% CI)P-valueUnivariate hazard ratio (95% CI)P-value
VEGFA rs699947GenotypeAA5610.37310.53810.162
CA1011.483 (0.616–3.565)0.3871.104 (0.447–2.754)0.3171.141
(0.383–3.414)0.813
CC452.03 (0.76–5.47)0.1601.689 (0.613–4.622)0.8452.524
(0.822–7.723)0.105
AllelicA allele carriers1571 1 1
A allele non carriers451.568 (0.727–3.383)0.2511.585 (0.697–3.604)0.2722.322
(0.973–5.543)0.058
C allele carriers1461 1 1
C allele non carriers560.613 (0.266–1.415)0.2520.791 (0.336–1.864)0.5920.651
(0.240–1.766)0.399
VEGFA rs833061GenotypeCC5610.29510.43010.115
TC1031.445 (0.600–3.499)0.4101.081 (0.429–2.703)0.8751.124
  (0.377–3.344)0.842
TT432.189 (0.813–5.892)0.1211.801 (0.652–4.974)0.2572.694
(0.880–8.250)0.083
AllelicC allele carriers1591 1 1
C allele non carriers431.709 (0.792–3.687)0.1721.718 (0.755–3.905)0.1972.511
(0.952–5.994)0.058
T allele carriers1461 1 1
T allele non carriers560.609 (0.264–1.405)0.2450.786 (0.334–1.853)0.5830.649
(0.239–1.760)0.395
VEGFA rs1005230GenotypeTT5710.43810.65710.268
CT991.553 (0.646–3.755)0.3271.153 (0.465–2.891)0.7631.204
(0.402–3.593)0.740
CC461.894 (0.702–5.083)0.2071.584 (0.571–4.355)0.3812.281
(0.753–6.974)0.149
AllelicC allele carriers571 1 1
C allele non carriers1450.604 (0.262–1.393)0.2370.779 (0.331–1.835)0.5680.647
(0.238–1.753)0.392
T allele carriers1561 1 1
T allele non carriers462.034 (0.857–4.844)0.1101.440 (0.634–3.269)0.3842.031
(0.851–4.844)0.110
VEGFA rs25648GenotypeCC13110.42510.72710.602
CT650.604 (0.271–1.345)0.2170.7960.5890.706
(0.348–1.820) (0.274–1.819)0.471
TT61.373 (0.185–10.181)0.7561.7060.6031.8610.548
(0.228–12.794) (0.246–14.087)
AllelicT allele carriers711 1 1
T allele non carriers1311.553 (0.721–3.343)0.2611.1810.6811.2910.577
(0.534–2.612) (0.526–3.168)
C allele carriers1961 1 1
C allele non carriers61.593 (0.217–11.703)0.6471.8350.5522.0830.474
(0.248–13.556) (0.280–15.494)

[i] Unadjusted hazard ratios for PFS, MFS and OS with each of the SNPs in genotype and allelic model. VEGFA, vascular endothelial growth factor A; SNP, single nucleotide polymorphism; PFS, progression-free survival; MFS, metastasis-free survival; OS, overall survival.

By analysing the SNPs of the IL-6 gene, we found that the rs1800797 GG genotype was a negative prognostic factor for DFS and MFS. Furthermore, IL-6 rs1800797 GG and IL-6 rs1800795 GG genotype carriers displayed a shorter OS (Table IV). In a haplotype model, the patients who inherited the GG/GG diplotype (AC haplotype non-carriers) had a higher risk of disease recurrence, metastasis and death (Table IV; Fig. 3A and B).

Table IV.

Cox's univariate model for IL-6 SNPs.

Table IV.

Cox's univariate model for IL-6 SNPs.

PFSMFSOS



Reference SNP IDModel Genotype/allele/haplotypePatients, nUnivariate hazard ratio (95% CI)P-valueUnivariate hazard ratio (95% CI)P-valueUnivariate hazard ratio (95% CI)P-value
IL-6 rs1800795GenotypeCC4810.23910.16010.101
GC951.441 (0.518–4.010)0.4840.983 (0.336–2.881)0.9721.216 (0.321–4.560)0.779
GG492.257 (0.811–6.277)0.1192.053 (0.736–5.761)0.1742.842 (0.798–10.193)0.109
AllelicC allele carriers1431 1 1
C allele non carriers491.750 (0.874–3.502)0.1142.074 (0.983–4.375)0.0552.484 (1.075–5.737)0.033a
G allele carriers1441 1 1
G allele non carriers480.568 (0.219–1.473)0.2450.716 (0.272–1.888)0.4990.552 (0.163–1.866)0.339
IL-6 rs1800797GenotypeAA4610.17010.13610.117
GA951.724 (0.621–4.787)0.2961.173 (0.406–3.441)0.7711.536 (0.418–5.783)0.528
GG612.596 (0.934–7.215)0.0672.361 (0.841–6.627)0.1043.174 (0.858–11.355)0.077
AllelicA allele carriers1411 1 1
A allele non carriers612.370 (1.032–5.464)0.044a2.154 (1.009–4.476)0.047a2.373 (1.033–5.461)0.044a
G allele carriers1561 1 1
G allele non carriers460.483 (0.186–1.251)0.1340.610 (0.232–1.606)0.3170.458 (0.135–1.548)0.209
IL-6 ts1800797- rs1800795DiplotypeAC/AC4810.33910.29210.250
GG/AC801.666 (0.599–4.634)0.3281.125 (0.383–3.305)0.8301.141 (0.382–5.434)0.589
GG/GG632.146 (0.772–5.967)0.1431.953 (0.695–5.485)0.2042.555 (0.711–9.161)0.150
HaplotypeAC haplotype carriers1361 1 1
AC haplotype non carriers601.809 (0.905–3.617)0.0942.142 (1.021–4.514)0.045a2.455 (1.062–5.661)0.035a
GG haplotype carriers1491 1 1
GG haplotype non carriers481.818 (0.701–4.713)0.2191.438 (0.546–3.791)0.4621.894 (0.560–6.401)0.304

a Significant. Unadjusted hazard ratios for PFS, MFS and OS with each of the SNPs in genotype, allelic and haplotype models. IL-6, interleukin-6; PFS, progression-free survival; MFS, metastasis-free survival; OS, overall survival; SNP, single nucleotide polymorphism.

In a multivariate Cox regression model including age at diagnosis, tumour size, lymph node status, tumour differentiation grade, oestrogen receptor, progesterone receptor and HER2 status, the IL-1α 1800587 CC genotype remained a significant predictor of poor DFS, MFS and OS. Furthermore, the IL-6 GG/GG diplotype (non-carrying the AC haplotype) was an independent negative prognostic factor for MFS and OS (Table VI). Finally, other polymorphisms and VEGFA haplotypes were not associated with any of the survival endpoints.

Table VI.

Cox's multivariate model.

Table VI.

Cox's multivariate model.

PFSMFSOS



VariablePatients, nMultivariate hazard ratio (95% CI)P-valueMultivariate hazard ratio (95% CI)P-valueMultivariate hazard ratio (95% CI)P-value
Age at diagnosis, years
  ≥50711 1 1
  <501317.5230.049a6.0810.0829.2370.091
(0.990–56.690) (0.786–46.619) (0.983–57.232)
Tumor size, cm
  <21291 1 1
  2–5731.1020.7951.0180.6311.0210.669
(0.583–2.399) (0.522–1.824) (0.529–1.919)
Lymph node status
  Negative1111 1 1
  Positive912.3310.030a2.413 (1.051–5.587)0.039a2.151 (0.832–5.560)0.115
(1.086–4.989)
Grade
  G1 and G21581 1 1
  G3442.2810.0792.1450.1231.9040.247
(0.916–5.719) (0.815–5.628) (0.636–5.645)
Estrogen receptor status
  Positive1371 1 1
  Negative651.1820.7211.3040.5941.5800.395
(0.482–2.939) (0.496–3.455) (0.545–4.555)
Progesterone receptor status
  Positive1211 1 1
  Negative823.0880.020a3.2840.025a4.6700.018a
(1.193–7.993) (1.164–9.228) (1.315–16.435)
Human epidermal growth factor
receptor 2 status
  Negative1641 1 1
  Positive382.3930.1041.9040.2461.718
(0.841–6.817) (0.641–5.621) (0.518–5.735)0.376
IL-6 haplotype
  AC haplotype carriers (GG/AC+AC/AC)128 1 1
  AC haplotype non carriers (GG/GG)632.750 (1.184–7.690)0.0482.631 (1.042–7.670)0.049
IL-1α rs1800587 1 1 1
  T allele carriers (CT+TT genotypes)1052.704 (1.280–5.683)0.009a3.442 (1.484–7.994)0.004a3.181 (1.252–8.134)0.016a
  T allele non carriers (CC genotype)972.750 (1.184–7.690)0.048a2.631 (1.042–7.670)0.049 a

a Significant. -, not significant in univariate analysis. Adjusted hazard ratios for PFS, MFS and OS. PFS, progression-free survival; MFS, metastasis-free survival; OS, overall survival.

Discussion

In the present study, we investigated the associations between nine functional SNPs in four cytokine genes (i.e., VEGFA, IL-1α, IL-1β and IL-6) and the clinicopathologic profiles and survival rates in a group of Lithuanian women with early-stage BC. We found an association between the IL-6 SNPs and the oestrogen receptor positive, progesterone receptor positive and HER2 negative status, and a link between IL-1α SNP and larger primary tumour size. Furthermore, we confirmed a negative prognostic value of the IL-6 rs1800797-rs1800795 GG/GG diplotype on MFS and OS and of the IL-1α rs1800587 CC genotype on DFS, MFS and OS in a highly homogeneous group of patients.

Several authors have demonstrated that carrying the IL-6 rs1800795 G or IL-6 rs1800795 G alleles is associated with higher IL-6 protein production (1921). Specifically, IL-6 is a cytokine which is considered a prognostic marker as well as a potential therapeutic target for BC patients. This cytokine acts through several pathways, regulating the proliferation, apoptosis and metabolism of BC cells. However, the most important role of IL-6 in breast carcinogenesis is its potential to induce breast metastasis by enhancing angiogenesis and tumour cell migration (39). According to previous studies, IL-6 rs1800797 and rs1800795 polymorphisms appear to be biologically important; however, the data on their clinical importance is still heterogeneous.

The association of IL-6 polymorphisms with BC survival was analysed in several studies (Table VII). Snoussi et al (32) and DeMichele et al (27) analysed patients with non-metastatic stage I–III BC. In both studies the IL-6 rs1800795 GG genotype was associated with decreased DFS and OS. In DeMichele et al (27) the presence of at least one copy of the haplotype rs1800797G-rs1800796G-373(10A/11T)-rs1800795G was associated with worse DFS. Snoussi et al (32) also found a significant link between IL-6 rs1800797 GG polymorphism and decreased DFS and OS. However, in DeMichele et al (28), where only locally advanced stage III patients with more than 10 positive lymph nodes were studied, the results were not replicated. Specifically, there was no impact of IL-6 polymorphisms on DFS and OS in the study population. In the same study, only an unplanned sub-analysis showed an association of the rs1800795 GG and rs1800797 GG genotypes with lower DFS but not OS in the oestrogen receptor positive patient subgroup. Our study is the first to confirm the prognostic value of IL-6 polymorphisms (namely, the IL-6 GG/GG diplotype) on MFS and OS in early-stage BC. Therefore, IL-6 GG/GG may potentially be used for the selection of patients who need intensified adjuvant BC treatment.

Table VII.

Studies evaluating the assocaitions of IL-6 rs1800795, IL-6 rs1800797 and IL-1α rs1800587 single nucleotide polymorphisms with breast cancer survival.

Table VII.

Studies evaluating the assocaitions of IL-6 rs1800795, IL-6 rs1800797 and IL-1α rs1800587 single nucleotide polymorphisms with breast cancer survival.

Author, yearPolymorphismStudy designNumber (inclusion criteria)EthnicityFinding(Refs.)
Abana et al, 2017IL-6 rs1800795Case/control157/158 (stage IV vs. stage I–III)Non-Hispanic whiteGG genotype with distant metastasis(26)
DeMichele et al, 2003IL-6 rs1800795Cohort80 (stage I–III)VariousGG genotype with worse DFS and OS(27)
DeMichele et al, 2009IL-6 rs1800795, rs1800797Cohort346 (non-metastatic, ≥10 positive nodes)VariousGG genotypes of both SNPs with worse DFS in estrogen receptor positive subgroup(28)
Markkula et al, 2014IL-6 rs1800795Cohort634 (stage I–III)No dataC allele in estrogen receptor negative cases with early events(29)
Snoussi et al, 2005IL-6 rs1800795, rs1800797Cohort305 (stage I–III)North AfricanGG genotypes in both SNPs with worse DFS, but not OS(32)
IL-1α rs1800587 TT genotype with worse DFS and OS
Grimm et al, 2009IL-1α rs1800587Cohort262 (stage I–III)CaucasianC allele with OS in the univariate analysis only(31)
Escala-Garcia et al, 2019GWASCohort96.661 (stage I–IV)VariousNo association of IL-1α and IL-6 SNPs with breast cancer-specific mortality(23)
Khan et al, 2017GWASMeta-analysis3.136 (stage I–IV estrogen receptor positive)VariousNo association of IL-1α and IL-6 SNPs with breast cancer-specific mortality(24)
Present studyIL-6 rs1800795, rs1800797Cohort202 (early stage I–II) Eastern-EuropeanGG/GG diplotype with worse MFS (Lithuanian) and OS
IL-1α rs1800587 CC genotype with worse DFS, MFS and OS

[i] GWAS, genome-wide association studies. IL, interleukin-1.

The above-mentioned studies by Snoussi et al (32) and DeMichele et al (27,28) did not analyse MFS as a survival endpoint. To the best of our knowledge, the only study that evaluated the association between IL-6 polymorphisms and BC metastasis was a case-control study conducted by Abana et al (26). The authors demonstrated the significant link between the IL-6 rs1800795 GG genotype and the development of BC metastases with an OR of 1.52. However, due to case-control design, we have no data on MFS differences. In our study IL-6 GG/GG predicted MFS and OS, but not DFS. Taking into account the critical role of IL-6 in the development of BC metastasis and our study results, we propose the hypothesis that IL-6 polymorphisms may predict the development of metastasis rather than loco-regional relapse.

It is important to mention that, in contrast with the findings of the above-mentioned studies, Markkula et al (29), who analysed a Swedish cohort of patients with any primary stage non-metastatic BC, demonstrated that the carriers of the C allele in rs1800795 SNP had a higher risk of early BC events. The authors, however, conducted no DFS, MFS or OS analyses. Furthermore, none of the GWAS studies showed a statistically significant association between IL-6 polymorphisms and BC survival (23,24). The contrasting findings in IL-6 polymorphism studies may be due to sampling errors or differences in patient ethnicity. Nevertheless, most of the experimental data and the possible biological pathway support our findings.

IL-6 also acts as a regulator of oestrogen synthesis and may modulate the tumour cell growth related to the hormone receptor status (40). Hormone-sensitive cells exhibit a higher response to IL-6, while ER-negative cells are suppressed by IL-6 (41). However, there is no clear mechanism of association between IL-6 SNPs and the oestrogen receptor positive, progesterone receptor positive and HER2 negative status. Therefore, further studies are needed.

As far as IL-1α SNP is concerned, Um et al (18) demonstrated that the IL-1α rs1800587 CC genotype is associated with higher transcriptional activity of the IL−1α gene. Overexpression of the IL-1α promotes tumour invasiveness and metastasis by inducing the expression of angiogenic genes and growth factors (12). A large meta-analysis performed by Xia et al (30) showed that the IL-1α rs1800587 C allele and CC genotype are associated with increased cancer risk in general. The studies which investigated the associations between IL-1α rs1800587 polymorphism and BC survival are presented in Table VII. Grimm et al (31) analysed 262 Caucasian BC patients and found that the IL-1α rs1800758 C allele in the univariate model is associated with OS; however, the multivariate model failed to repeat the association. In our study, the multivariate survival analysis confirmed the statistically significant impact of the CC genotype on DFS, MFS and OS. Contrasting data is provided by Snoussi et al (32), who analysed North African BC patients and found that the rs1800587 homozygous TT genotype showed a significant association with reduced DFS and OS rate. However, the allele and genotype frequency of rs1800587 SNP in African population differs substantially from that in the population with European ancestry. This difference may be the cause of the observed inconsistency between these studies. We demonstrated that in an Eastern-European population the IL-1α rs1800758 C allele is associated with more aggressive local disease (i.e., larger tumour size) and for the first time we proposed that the IL-1α rs1800758 CC genotype is an independent negative prognostic biomarker for early-stage BC. As the allele frequencies of the IL-1α rs1800758 SNP in our study correspond to those of the 1000 Genomes project phase 3 database for European population, these findings could potentially be replicated for European population, but larger confirmatory studies are warranted.

Although experimental data suggests that VEGFA and IL-1β play a role in BC, our findings, along with the results from several other studies (2224), do not suggest that several common polymorphisms in these genes are associated with BC clinical and morphological variables and BC survival rates.

Potential limitations of our study include a limited sample size, lack of access to tumour and/or tumour stromal tissue (which would have allowed for the assessment of the presence of SNPs in those tissues), the risk of other confounders, possible gene-gene and gene-environment interactions, and non-random sampling. We also acknowledge that VEGFA, IL-1α, IL-1β and IL-6 measurements were not available in the current study. However, our study supports the relevance of functional IL-6 and IL-1α germline polymorphisms to BC prognosis. Further investigations, preferable on larger cohorts with different ethnic origins, are needed to confirm the results of the current study.

In conclusion, we found an association between the IL−1α rs1800587 C allele and larger primary tumour size. The IL-6 rs1800797 A allele, GA genotype, IL-6 rs1800795 C allele and IL-6 (rs1800797-re1800795) AC diplotype were linked to hormonal receptor positive BC. Additionally, IL-6 rs1800797 A was associated with HER2 negative status. The multivariate IL-1α rs1800587 CC genotype was confirmed as an independent negative prognostic factor for DFS, MFS and OS, and the IL6 GG/GG diplotype for MFS and OS in early-stage BC patients. Our findings confirm the hypothesis that functional SNPs in angiogenesis- and inflammation-associated genes are associated with early-stage BC prognosis in Lithuanian population.

Supplementary Material

Supporting Data

Acknowledgements

Not applicable.

Funding

The present study was partially supported by the Lithuanian University of Health Sciences Science Foundation.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors' contributions

EK, RU and EJu designed the research study. EK, RU, RI, LP, VR, EJa and EJu performed the research. EK and RU analyzed the data. RU and RI contributed essential reagents or tools. EK wrote the manuscript.

Ethics approval and consent to participate

The present study was approved by Kaunas Regional Ethics Committee for Biomedical Research (protocol no. BE-2-10). Informed consent for participation in the study and use of tissue was obtained from all participants.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Glossary

Abbreviations

Abbreviations:

BC

breast cancer

SNP

single nucleotide polymorphism

VEGFA

vascular endothelial growth factor A

IL-6

interleukin-6

IL-1α

interleukin-1α

IL-1β

interleukin-1β

A

adenine

G

guanine

T

thymine

C

cytosine

DFS

disease-free survival

MFS

metastasis-free survival

OS

overall survival

HR

hazard ratio

OR

odds ratio

CI

confidence interval

HER2

human epidermal growth factor receptor 2

GWAS

genome-wide association study

References

1 

IARC: World Cancer Report 2014. Stewart BW and Wild CP: IARC; Lyon: 2014

2 

Cancer Trends Progress Report. National Cancer Institute, NIH, DHHS; Bethesda, MD: 2019, https://progressreport.cancer.gov

3 

Zhao Y and Adjei AA: Targeting angiogenesis in cancer therapy: Moving beyond vascular endothelial growth factor. Oncologist. 20:660–673. 2015. View Article : Google Scholar : PubMed/NCBI

4 

Bielenberg DR and Zetter BR: The contribution of angiogenesis to the process of metastasis. Cancer J. 21:267–273. 2015. View Article : Google Scholar : PubMed/NCBI

5 

Cartland SP, Genner SW, Zahoor A and Kayurma MM: Comparative evaluation of TRAIL, FGF-2 and VEGF-A-induced angiogenesis in vitro and in vivo. Int J Mol Sci. 17:E20252016. View Article : Google Scholar : PubMed/NCBI

6 

De Palma M, Biziato D and Petrova TV: Microenvironmental regulation of tumour angiogenesis. Nat Rev Cancer. 17:457–474. 2017. View Article : Google Scholar : PubMed/NCBI

7 

Marech I, Leporini C, Ammendola M, Porcelli M, Gadaleta CD, Russo E, De Sarro G and Ranieri G: Classical and non-classical proangiogenic factors as a target of antiangiogenic yherapy in tumor microenvironment. Cancer Lett. 380:216–226. 2016. View Article : Google Scholar : PubMed/NCBI

8 

Banys-Paluchoothtwski M, Witzel I, Riethdorf S, Pantel K, Rack B, Janni W, Fasching PA, Aktas B, Kasimir-Bauer S, Hartkopf A, et al: The clinical relevance of serum vascular endothelial growth factor (VEGF) in correlation to circulating tumor cells and other serum biomarkers in patients with metastatic breast cancer. Breast Cancer Res Treat. 172:93–104. 2018. View Article : Google Scholar : PubMed/NCBI

9 

Gyamfi J, Eom M, Koo JS and Choi J: Multifaceted roles of interleukin-6 in adipocyte-breast cancer cell interaction. Transl Oncol. 11:275–285. 2018. View Article : Google Scholar : PubMed/NCBI

10 

Knüpfer H and Preiss R: Significance of interleukin-6 (IL-6) in breast cancer (Review). Breast Cancer Res Treat. 102:129–135. 2007. View Article : Google Scholar : PubMed/NCBI

11 

Tawara K, Scott H, Emathinger J, Ide A, Fox R, Greiner D, LaJoie D, Hedeen D, Nandakumar M, Oler AJ, et al: Co-expression of VEGF and IL-6 family cytokines is associated with decreased survival in HER2 negative breast cancer patients: Subtype-specific IL-6 family cytokine-mediated VEGF secretion. Transl Oncol. 12:245–255. 2019. View Article : Google Scholar : PubMed/NCBI

12 

Litmanovich A, Khazim K and Cohen I: The role of interleukin-1 in the pathogenesis of cancer and its potential as a therapeutic target in clinical practice. Oncol Ther. 6:109–127. 2018. View Article : Google Scholar

13 

Balasubramanian SP, Azmy IA, Higham SE, Wilson AG, Cross SS, Cox A, Brown NJ and Reed MW: Interleukin gene polymorphisms and breast cancer: A case control study and systematic literature review. BMC Cancer. 6:1882006. View Article : Google Scholar : PubMed/NCBI

14 

Koukourakis MI, Papazoglou D, Giatromanolaki A, Bougioukas G, Maltezos E and Siviridis E: VEGF gene sequence variation defines VEGF gene expression status and angiogenic activity in non-small cell lung cancer. Lung Cancer. 46:293–298. 2004. View Article : Google Scholar : PubMed/NCBI

15 

Watson CJ, Webb NJ, Bottomley MJ and Brenchley PE: Identification of polymorphisms within the vascular endothelial growth factor (VEGF) gene: Correlation with variation in VEGF protein production. Cytokine. 12:1232–1235. 2000. View Article : Google Scholar : PubMed/NCBI

16 

Ray D, Mishra M, Ralph S, Read I, Davies R and Brenchley P: Association of the VEGF gene with proliferative diabetic retinopathy but not proteinuria in diabetes. Diabetes. 53:861–864. 2004. View Article : Google Scholar : PubMed/NCBI

17 

Hall SK, Perregaux DG, Gabel CA, Woodworth T, Durham LK, Huizinga TW, Breedveld FC and Seymour AB: Correlation of polymorphic variation in the promoter region of the interleukin-1 beta gene with secretion of interleukin-1 beta protein. Arthritis Rheum. 50:1976–1983. 2004. View Article : Google Scholar : PubMed/NCBI

18 

Um JY, Rim HK, Kim SJ, Kim HL and Hong SH: Functional polymorphism of IL-1 alpha and its potential role in obesity in humans and mice. PLoS One. 6:e295242011. View Article : Google Scholar : PubMed/NCBI

19 

Rana BK, Flatt SW, Health DD, Pakiz B, Quintana EL, Natarajan L and Rock CL: The IL-6 gene promoter SNP and plasma IL-6 in response to diet intervention. Nutrients. 9:E5522017. View Article : Google Scholar : PubMed/NCBI

20 

Boeta-Lopez K, Duran J, Elizondo D, Gonzales E, Rentfro A, Schwarzbach AE and Nair S: Association of interleukin-6 polymorphisms with obesity or metabolic traits in young Mexican-Americans. Obes Sci Pract. 4:85–96. 2017. View Article : Google Scholar : PubMed/NCBI

21 

Sampaio AM, Balseiro SC, Silva MR, Alarcão A, d'Aguiar MJ, Ferreira T and Carvalho L: Association between IL-4 and IL-6 expression variants and gastric cancer among portuguese population. GE Port J Gastroenterol. 22:143–152. 2015. View Article : Google Scholar : PubMed/NCBI

22 

Langsenlehner U, Hofmann G, Renner W, Gerger A, Krenn-Pilko S, Thurner EM, Krippl P and Langsenlehner T: Association of vascular endothelial growth factor--a gene polymorphisms and haplotypes with breast cancer metastases. Acta Oncol. 54:368–376. 2015. View Article : Google Scholar : PubMed/NCBI

23 

Escala-Garcia M, Guo Q, Dörk T, Canisius S, Keeman R, Dennis J, Beesley J, Lecarpentier J, Bolla MK, Wang Q, et al: Genome-wide association study of germline variants and breast cancer-specific mortality. Br J Cancer. 120:647–657. 2019. View Article : Google Scholar : PubMed/NCBI

24 

Khan S, Fagerholm R, Kadalayil L, Tapper W, Aittomäki K, Liu J, Blomqvist C, Eccles D and Nevanlinna H: Meta-analysis of three genome-wide association studies identifies two loci that predict survival and treatment outcome in breast cancer. Oncotarget. 9:4249–4257. 2017.PubMed/NCBI

25 

Peng X, Shi J, Sun W, Ruan X, Guo Y, Zhao L, Wang J and Li B: Genetic polymorphisms of IL-6 promoter in cancer susceptibility and prognosis: A meta-analysis. Oncotarget. 9:12351–12364. 2018. View Article : Google Scholar : PubMed/NCBI

26 

Abana CO, Bingham BS, Cho JH, Graves AJ, Koyama T, Pilarski RT, Chakravarthy AB and Xia F: IL-6 variant is associated with metastasis in breast cancer patients. PLoS One. 12:e01817252017. View Article : Google Scholar : PubMed/NCBI

27 

DeMichele A, Martin AM, Mick R, Gor P, Wray L, Klein-Cabral M, Athanasiadis G, Colligan T, Stadtmauer E and Weber B: Interleukin-6 −174G->C polymorphism is associated with improved outcome in high-risk breast cancer. Cancer Res. 63:8051–8056. 2003.PubMed/NCBI

28 

DeMichele A, Gray R, Horn M, Chen J, Aplenc R, Vaughan WP and Tallman MS: Host genetic variants in the interleukin-6 promoter predict poor outcome in patients with estrogen receptor-positive, node-positive breast cancer. Cancer Res. 69:4184–4191. 2009. View Article : Google Scholar : PubMed/NCBI

29 

Markkula A, Simonsson M, Ingvar C, Rose C and Jernström H: IL6 genotype, tumour ER-status, and treatment predicted disease-free survival in a prospective breast cancer cohort. BMC Cancer. 14:7592014. View Article : Google Scholar : PubMed/NCBI

30 

Xia H, Chen Y, Meng J and Liang C: Effect of polymorphisms on IL1A to cancer susceptibility: Evidence based on 34,016 subjects. Artif Cells Nanomed Biotechnol. 47:3138–3152. 2019. View Article : Google Scholar : PubMed/NCBI

31 

Grimm C, Kantelhardt E, Heinze G, Polterauer S, Zeillinger R, Kölbl H, Reinthaller A and Hefler L: The prognostic value of four interleukin-1 gene polymorphisms in Caucasian women with breast cancer: A multicenter study. BMC Cancer. 9:782009. View Article : Google Scholar : PubMed/NCBI

32 

Snoussi K, Strosberg AD, Bouaouina N, Ben Ahmed S and Chouchane L: Genetic variation in pro-inflammatory cytokines (interleukin-1beta, interleukin-1alpha and interleukin-6) associated with the aggressive forms, survival, and relapse prediction of breast carcinoma. Eur Cytokine Netw. 16:253–260. 2005.PubMed/NCBI

33 

Hayes DF, Ethier S and Mippman ME: New guidelines for reporting of tumor marker studies in breast cancer research and treatment: REMARK. Breast Cancer Res Treat. 100:237–238. 2006. View Article : Google Scholar : PubMed/NCBI

34 

McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M and Clark GM; Statistics Subcommittee of the NCI-EORTC Working Group on Cancer Diagnostics, : Reporting recommendations for tumor marker prognostic studies (REMARK). J Natl Cancer Inst. 97:1180–1184. 2005. View Article : Google Scholar : PubMed/NCBI

35 

1000 Genomes Project Consortium, ; Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, Korbel JO, Marchini JL, McCarthy S, McVean GA and Abecasis GR: A global reference for human genetic variation. Nature. 526:68–74. 2015. View Article : Google Scholar : PubMed/NCBI

36 

Barrett JC, Fry B, Maller J and Daly MJ: Haploview: Analysis and visualization of LD and haplotype maps. Bioinformatics. 21:263–265. 2005. View Article : Google Scholar : PubMed/NCBI

37 

Stephens M, Smith NJ and Donnelly P: A new statistical method for haplotype reconstruction from population data. Am J Hum Genet. 68:978–989. 2001. View Article : Google Scholar : PubMed/NCBI

38 

Stephens M and Scheet P: Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation. Am J Hum Genet. 76:449–462. 2005. View Article : Google Scholar : PubMed/NCBI

39 

Kumari N, Dwarakanath BS, Das A and Bhatt AN: Role of interleukin-6 in cancer progression and therapeutic resistance. Tumour Biol. 37:11553–11572. 2016. View Article : Google Scholar : PubMed/NCBI

40 

Dethlefsen C, Højfeldt G and Hojman P: The role of intratumoral and systemic IL-6 in breast cancer. Breast Cancer Res Treat. 138:657–664. 2013. View Article : Google Scholar : PubMed/NCBI

41 

Masjedi A, Hashemi V, Hojjat-Farsangi M, Ghalamfarsa G, Azizi G, Yousefi M and Jadidi-Niaragh F: The significant role of IL-6 and its signaling pathway in the immunopathogenesis and treatment of breast cancer. Biomed Pharmacother. 108:1415–1424. 2018. View Article : Google Scholar : PubMed/NCBI

Related Articles

Journal Cover

June-2020
Volume 19 Issue 6

Print ISSN: 1792-1074
Online ISSN:1792-1082

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Korobeinikova E, Ugenskiene R, Insodaite R, Rudzianskas V, Jaselske E, Poskiene L and Juozaityte E: Association of angiogenesis and inflammation‑related gene functional polymorphisms with early‑stage breast cancer prognosis. Oncol Lett 19: 3687-3700, 2020
APA
Korobeinikova, E., Ugenskiene, R., Insodaite, R., Rudzianskas, V., Jaselske, E., Poskiene, L., & Juozaityte, E. (2020). Association of angiogenesis and inflammation‑related gene functional polymorphisms with early‑stage breast cancer prognosis. Oncology Letters, 19, 3687-3700. https://doi.org/10.3892/ol.2020.11521
MLA
Korobeinikova, E., Ugenskiene, R., Insodaite, R., Rudzianskas, V., Jaselske, E., Poskiene, L., Juozaityte, E."Association of angiogenesis and inflammation‑related gene functional polymorphisms with early‑stage breast cancer prognosis". Oncology Letters 19.6 (2020): 3687-3700.
Chicago
Korobeinikova, E., Ugenskiene, R., Insodaite, R., Rudzianskas, V., Jaselske, E., Poskiene, L., Juozaityte, E."Association of angiogenesis and inflammation‑related gene functional polymorphisms with early‑stage breast cancer prognosis". Oncology Letters 19, no. 6 (2020): 3687-3700. https://doi.org/10.3892/ol.2020.11521