Background
Breast cancer is a major health burden worldwide, and the primary cause of cancer-related death in women [
1,
2]. It affects more than 1 million women globally, and is responsible for more than 400,000 deaths annually [
2,
3]. Cancer progression is a complicated process involving immune–tumor cell interactions through numerous molecular and cellular factors within the tumor microenvironment [
4]. The tumor microenvironment is comprised of a diverse milieu of cytokines, growth factors, tumor and immune cells, compounded with anti-tumor functions—mostly in response to tumor-derived signals—suppressed in tumor surroundings [
5]. Several reports have linked the presence or absence of certain cell types in the tumor microenvironment with tumor stages, prognosis, and/or patient survival [
6‐
8].
Immune cells are one of the most important players in the tumor microenvironment which include different types of leukocytes, one of most interest being the T cell [
9]. It has been revealed that infiltrating T cells and production of cytokines into tumor tissue is associated with improved clinical outcome in numerous types of cancers [
7,
10]. More specifically, T helper (Th) cells play central roles in the development of immune responses [
11]. Recent studies have indicated that the balance between different CD4
+ Th subsets (Th1, Th2, Th17, and Treg) is important in anti-tumor immunity, and perhaps, in the process of tumor progression [
12,
13]. Furthermore, it has been shown that the density and type of immune cells as well as various inflammatory factors greatly influence cancer growth [
14‐
16]. In recent studies, the association between tumor progression, metastasis and inflammatory mediators TNF-α, IL-6, vascular endothelial growth factor (VEGF) and C-C motif chemokine receptor 7 (CCR7) have also been investigated [
17‐
19]. Collectively, it is still under investigation whether the immunological patterns are a better predictor of patient survival rather than the histopathological methods presently used for cancer staging. Nevertheless, accumulating data does support the hypothesis that the composition of tumor microenvironment influences the metastatic events and survival of patients.
This study aimed to investigate the presence of different CD4+ T cell subsets (Th1, Th2, Th17, and Treg), the inflammatory cytokines (IL-6 and TNF-α) as well as some other markers which play roles in immune cell functions including IDO (Indoleamine 2,3-dioxygenase), Fas ligand, SOCS1 (suppressor of cytokine signaling 1), VEGF and CCR7. The expression of all these factors was measured in different stages of breast cancer and were compared against normal breast tissues.
Methods
Patients
In the current study, biopsies of untreated breast cancer patients (n = 54) and control breast tissues from apparently healthy subjects referring for aesthetic surgeries (n = 11) were obtained from the Breast Cancer Research Center Biobank (BCRC-BB) in Iran (Table
1). According to the protocols followed by this bank, immediately after excisional biopsy or surgery, sample tissues were snap-frozen in liquid nitrogen and stored at − 70 °C. The content of cancer cells in each sample was pathologically checked and the tissues with less than 80% tumor area were eliminated from the study. ICBC-BB is obliged to ethical guidelines and recommendations for biobanks on the storage and use of human biological samples.
Table 1
Clinicopathological features
Number of cases | 11 | 14 | 15 | 15 | 10 |
Age (years) (mean ± SEM) | 40 ± 2.6 | 48 ± 2 | 53 ± 3 | 43 ± 2.6 | 55 ± 3.5 |
Menopausal status |
Pre | 84 | 84.6 | 55.5 | 73 | 62.5 |
Post | 16 | 15.4 | 44.5 | 27 | 37.5 |
Type |
IDC | NA | 100 | 93 | 87.5 | 100 |
ILC | NA | 0 | 7 | 12.5 | 0 |
Hormone status |
ER Positive | NA | 77 | 53 | 80 | 62.5 |
PR Positive | NA | 54 | 44 | 80 | 50 |
Her2/neu positive | NA | 23 | 37.5 | 53 | 37.5 |
p53 positive | NA | 70 | 30 | 33 | 33 |
Written informed consent was obtained from all patients and controls. The patient cohort was 32–75 years of age, with pathologically confirmed breast cancer with clinical staging according to the TNM method (tumor size, lymph node involvement, and distant metastasis). Stage groupings were based on the American Joint Committee on Cancer (AJCC). Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (Her2/neu) and p53 status are based on immunohistochemistry (IHC) results (Table
1).
RNA extraction and cDNA synthesis
Frozen tissues (10–15 mg) while keeping on dry ice were homogenized. RNA was isolated using the RNeasy mini kit (QIAGEN) according to the manufacturer’s instructions. The concentration of extracted RNA was quantified by spectrophotometer (Hitachi, U-0080D, Japan) and we used ratio at 260/280 and 260/230 to control the purity of RNA. Extracted RNA was used for cDNA synthesis using the QuantiTect reverse transcription kit (QIAGEN). RNA extraction and cDNA synthesis was performed for each sample and then fold change was calculated for individual samples separately.
Quantitative reverse-transcription PCR primers
Specific mRNA sequences of studied genes (Table
2) were acquired from the public GenBank sequence database of the National Center for Biotechnology Information (
http://www.ncbi.nlm.nih.gov). Subsequently, all primers were designed using Gene Runner v.3.05 and confirmed with primer express 3.0. In conventional PCR, all primers generated only one amplification band visualized by agarose gel electrophoresis, indicating specificity. In this study, TFRC (transferrin receptor) and ACTB (β-actin) were considered as housekeeping genes, because of the most stable expression in breast tissue [
20].
1 | T.bet | 5′CCAACAATGTGACCCAGATGATT3′ | 85 |
5′TATGCGTGTTGGAAGCGTTG3′ |
2 | IL-12p40 | 5′GCCCAGAGCAAGATGTGTCA3′ | 82 |
5′GGGCATCCGGATACCAATC3′ |
3 | IFN-γ | 5′TCAGCTCTGCATCGTTTTGG 3′ | 79 |
5′GTTCCATTATCCGCTACATCTGAA3′ |
4 | GATA3 | 5′CCCTACTACGGAAACTCGGTCA3′ | 88 |
5′GTAGGGATCCATGAAGCAGAGG3′ |
5 | IL-4 | 5′CAAGCAGCTGATCCGATTCC3′ | 81 |
5′TTCTCTCTCATGATCGTCTTTAGCC3′ |
6 | IL-5 | 5′CCTGTTCCTGTACATAAAAATCACCA3′ | 80 |
5′TTGAATAGTCTTTCCACAGTACCCC3′ |
7 | RORC | 5′ACAGCACCGAGCCTCACG3′ | 85 |
5′CAGACGACTTGTCCCCACAGA3′ |
8 | IL-17 | 5′TTGATTGGAAGAAACAACGATGACT3′ | 81 |
5′TGGATTTCGTGGGATTGTGAT3′ |
9 | CCL22 | 5′TGCCGTGATTACGTCCGTTA3′ | 87 |
5′CGGCACAGATCTCCTTATCCC3′ |
10 | FOXP3 | 5′ACAGCACATTCCCAGAGTTCCT3′ | 82 |
5′GATGAGCGTGGCGTAGGTG3′ |
11 | CTLA4 | 5′TGGATCCTTGCAGCAGTTAGTTC3′ | 79 |
5′CATTTTCACATAGACCCCTGTTGTA3′ |
12 | IL-13 | 5′AGGTCTCAGCTGGGCAGTTTT3′ | 80 |
5′TAATGATGCTTTCGAAGTTTCAGTTG3′ |
13 | STAT3 | 5′CTCAAGAGTCAAGGAGACATGCA3′ | 85 |
5′CTCACTCACGATGCTTCTCCG3′ |
14 | FASL | 5′CTCCGAGAGTCTACCAGCCAGAT3′ | 84 |
5′CATGGACCTTGAGTTGGACTTG3′ |
15 | CCR7 | 5′GTGGTGGCTCTCCTTGTCATTT3′ | 84 |
5′ATGATAGGGAGGAACCAGGCTT3′ |
16 | IL-6 | 5′CCTGAGAAAGGAGACATGTAACAAGAG3′ | 81 |
5′GCAAGTCTCCTCATTGAATCCAG3′ |
17 | VEGF | 5′AGGAGGAGGGCAGAATCATCA3′ | 81 |
5′CTCGATTGGATGGCAGTAGCT3′ |
18 | IL-10 | 5′GTGATGCCCCAAGCTGAGA3′ | 86 |
5′CACGGCCTTGCTCTTGTTTT3′ |
19 | TGF-β | 5′CCTGGACACCAACTATTGCTTCA3′ | 83 |
5′TGCGGAAGTCAATGTACAGCTG3′ |
20 | IDO1 | 5′CTCTGCCAAATCCACAGGAAA3′ | 79 |
5′TCTCAACTCTTTCTCGAAGCTGG3′ |
21 | SOCS1 | 5′CCCTGGTTGTTGTAGCAGCTTAA3′ | 80 |
5′GGTTTGTGCAAAGATACTGGGTATATG3′ |
22 | TNF-α | 5′CCCAGGGACCTCTCTCTAATCA3′ | 84 |
5′ATGGGCTACAGGCTTGTCACTC3′ |
23 | ACTB | 5′CAGCAGATGTGGATCAGCAAG3′ | 83 |
5′GCATTTGCGGTGGACGAT3′ |
24 | TFRC | 5′ACCGGCACCATCAAGCT3′ | 80 |
5′TGATCACGCCAGACTTTGC3′ |
Quantitative reverse-transcription PCR
Quantitative reverse-transcription PCR (qPCR) was carried out in the 96-well plate for each sample using precision ™2X qPCR Mastermix (PrimerDesign Ltd, UK) in 20 μL reactions. The mRNA expression levels were detected by qPCR on the StepOnePlus™ system (Applied Biosystems) using incorporation of SYBR green fluorescent dye into the double-stranded PCR products. The expression level of each gene was normalized to the expression level of ACTB and TFRC housekeeping genes. CT values for each product were determined to calculate 2−ΔΔCT referenced to normal breast tissues.
Statistical analysis
The results are expressed as mean ± standard error of mean (SEM). For multiple group, a 1-way ANOVA with Tukey’s post hoc comparisons was used. P value < 0.05 was considered significant. All analysis was done using Graph Pad Prism 3.02 (GraphPad Software, San Diego, Calif).
Discussion
In this study, the gene expression profiling of four subsets of T CD4
+ cells was investigated in the four different stages of breast cancer. We documented the presence of a significantly lower expression of Th1 and Th17 subset markers in the biopsies of breast cancer patients compared to control samples, however, a difference in the amount of Th2 or Treg cells between tumors and control groups was not seen. In this study, decreased infiltration of Th1 lymphocytes were shown in the microenvironment of advanced stages of breast cancer. The lowest expression of Th1 subset specific genes, including T-bet, IFN-γ and IL-12 were seen in stage IV. The cytokine IL-12, which stimulates Th1-dominant immunity, was shown to have strong anti-tumor activity against a variety of tumors, suggesting that Th1 cells may play an important role in tumor rejection [
21]. IL-12 has effects on cytotoxic T lymphocytes and Th1 cells to produce IFN-γ which inhibits tumor cell cycle [
22]. Reduction in the Th1 subset is related to tumor progression; suggesting that it may be directly implicated in the mechanisms that allow the tumor to progress and metastasize.
In this study, we found that the Th17 markers STAT3 and RORC were significantly decreased in stage IV. However, previous studies have reported controversial results. For example, one study consistent with our study suggested that the infiltration of Th17 cells reduced in progressive stages of breast cancer [
23] while another demonstrated Th17 accumulation in association with cancer progression [
24]. In the current study, progression of breast cancer probably is due to the decreasing of Th1 and Th17 levels in the microenvironment.
We found no significant changes of Th2 genes expression in the different stages of breast cancer. Th2 cells secrete IL-4, IL-5, IL-10 and IL-13 cytokines which induce T cell anergy and loss of T cell-mediated cytotoxicity [
25]. In vitro assays discovered that cancer cells could direct the tumor-infiltrated T cells toward the Th2 phenotype. For example, cancer cells promote the production of IL-4 and down-regulate the expression of IFN-γ in the tumor microenvironment [
26]. In contrast, some studies provide the finding that Th2-derived cytokines (IL-4, IL-5, IL-10, and IL13) show anti-tumor activities in vivo that are as strong as the anti-tumor activities of Th1 cytokines [
21]. Nevertheless, in the current study the Th2 accumulation in different stages of breast cancer and normal breast samples was similar. However, it is likely that more samples are required to survey Th2 presence. Similar to Th2 markers, we found no significant changes in the expression of Treg markers. Our data shows that in patients with hormone receptors (ER and PR positive), the expression of Th2 marker (GATA3) was significantly higher than ER and PR negative patients. Consistently, it has been reported that the number of suppressive T cells is lower in triple negative (ER
−/PR
−/Her2
−) patients [
27]. Therefore, we assume that higher number of Th2 marker in breast cancer patients may be considered as a poor prognostic marker.
Breast cancer has a high level of heterogeneity both intertumorally and in the microenvironment. The microenvironment itself displays a wide variation in tissue cellularity and hormone receptor status between individuals [
28]. It has been shown that hormone receptor profile is associated with the type of infiltrated immune cells in the tumor microenvironment; more T cell infiltration and higher expression of T cell markers were observed in patients with hormone receptor negativity [
29,
30]. Moreover, the degree of T cell infiltration and T cell functionality differ among the molecular subtypes of breast cancer [
29]. Therefore, we assume that this large intertumor heterogeneity may be possible reasons as to why we could not identify any difference in the expression of Th2 and Treg markers.
Contradictory to the process of acute inflammation which leads to tumor rejection, chronic inflammation is related to tumor progression [
31,
32]. The results of the current study showed that the amount of TNF-α increases in parallel with the disease stage. It has been reported that in murine model of breast cancer in which inflammation was induced by LPS (lipopolysaccharide), cancer cells metastasize progressively [
33].
Furthermore, the suppressive condition of the tumor microenvironment is due to several inhibitory markers which are produced by tumor or immune cells. In agreement with our results, one study demonstrated that after injection of chemotherapeutic drugs the amount of some soluble apoptosis markers such as soluble FASL is increased in stage II and III breast cancer [
34]. The higher expression of IDO was reported in stages II and III of breast cancer [
35] similar to our study. VEGF plays a crucial role in angiogenesis which is necessary for tumor development [
36,
37]. Based on our data, there was an increase in VEGF expression followed by a decrease once the tumor was established (i.e. Stage IV). Still, the accumulation of immune cells in tumor microenvironment and their role in breast cancer prognosis are controversial.
Authors’ contributions
RE, RE, KB carried out the molecular analyses and wrote the manuscript. RM designed the study and wrote the manuscript. SdL wrote the manuscript. MA carried out the molecular analyses. HS, JH and KM designed the study. All authors read and approved the final manuscript.