Background
Breast cancer is the most frequent cancer in women worldwide, currently affecting 12% of all women at one time in their life [
1]. It is a heterogeneous disease including a wide range of biological behaviors and prognostic characteristics [
2]. During the last decades, early diagnosis and novel therapies helped to improve survival rate in breast cancer [
2]. However, current therapeutic approaches are still limited and breast cancer still accounts for 14% of cancer-related mortality [
3]. In the recent years, with the emergence of checkpoint inhibitors and the possibilities of engineered T cells, cancer immunotherapy has experienced a breakthrough in some tumor entities [
4]. Also in breast cancer, checkpoint inhibitors are currently evaluated in several clinical trials and might be effective in a subgroup of patients [
5‐
8]. However, a close understanding of the tumor microenvironment and its mechanistic is required to successfully develop immunotherapeutic strategies in breast cancer.
Regulatory T cells (Treg) are a subtype of immunosuppressive CD4+ T cells that inhibit the cytotoxic function of CD8+ T lymphocytes [
9]. The physiological role of Treg is to protect the body from autoimmunity by suppressing self-reactive cells, including CD8+ cytotoxic T cells, B cells and natural killer cells (NK cells) [
10,
11]. However, Treg also play an important role in cancer-associated immunosuppression [
12]. The presence of Treg in tumor, serum or lymph nodes of cancer patients is related to poor survival in a variety of malignant diseases [
13,
14]. In breast cancer, a strong infiltration with CD8+ cytotoxic T lymphocytes has been reported to be associated with a favorable response to neoadjuvant chemotherapy and good clinical outcome in breast cancer [
15‐
17]. By contrast, a high number of Treg has been associated to poor prognosis in different types of breast cancer [
18‐
20]. In order to prevent Treg recruitment to tumor tissues, it is important to identify the mechanisms of Treg attraction. One of the most extensively described mechanisms of Treg attraction to tumor sites is intratumoral expression of the chemokine CCL22 [
21].
CCL22 was found in several cancer types, often associated with high infiltration of Treg and low survival [
22‐
24]. Likewise, high expression of CCL22 in breast cancer is related to a higher Treg infiltration and reduced prognosis [
25]. Another more recently described chemokine that promotes Treg de novo conversion and also Treg attraction to tumors is CCL1 [
26,
27]. It was shown that Sox2-mediated CCL1 expression in murine breast cancer models was related to a higher infiltration by Treg and CCL1 overexpression led to an increase of Treg accumulation [
27]. To our knowledge, CCL1 expression in human breast cancer tissues and its relation to Treg infiltration have not been described to date.
In order to determine the role of CCL1 and CCL22 on Treg attraction to breast cancer, we analyzed 199 breast cancer tissue samples that were previously stained [
28] for expression of CCL1, CCL22 and FoxP3. Chemokine expression and Treg infiltration were statistically examined for their effects on patient survival. We found a significantly increased expression of CCL1 in breast cancer tissues, which was related to a higher infiltration of Treg. By contrast, expression of CCL22 was not upregulated in tumor tissues compared to healthy breast tissue and showed no impact on Treg infiltration. Our data highlight the role of CCL1 on Treg migration into breast cancer tissue, a finding that might lead to novel therapeutic strategies in breast cancer immunotherapy.
Methods
Tissue samples and patient characteristics
All tissue samples derived from female patients diagnosed with mammary carcinoma at the Klinikum der Universität München between 1986 and 2007 (n = 199). All patients underwent surgical treatment of either mastectomy or wide local excision with radiotherapy at the local gynecology unit within 7 months after diagnosis. Histological and molecular characteristics of tumors were determined by the local Institute of Pathology according to the current WHO classification. One hundred eighty of the tumors were classified as ductal, 14 as lobular and 5 as unclassifiable. Non-malignant control tissues were obtained from women that underwent breast reduction surgery (n = 7).
Tissue microarray (TMA) and immunohistochemistry
A total of 7 TMA blocks containing 199 consecutive cases were constructed by inserting cylindric tissue cores measuring 2 mm in diameter into a paraffin block. For each tumor and non-malignant tissue 2 cores were embedded. Sections of each TMA block were mounted on silane-coated slides and subsequently further processed for immunohistochemistry as described before [
29]. In short, antigen retrieval was performed by 5 min cooking in citric buffer (pH = 6.0). For blocking ZytoChem Plus (HRP) Polymer Kit (Zytomed, Berlin, Germany) was used according to manufacturer’s instructions. Primary antibodies against CCL22 (Peprotech, Hamburg, Germany), FoxP3 (Abcam, Cambridge, USA) and CCL1 (Atlas antibodies, Stockholm, Sweden) were incubated for 16 h at 4 °C. Subsequent to 30 min of incubation with a horseradish peroxidase-polymer (Zytomed, Berlin, Germany) staining was carried out using 3,3-diaminobenzidine-substrate solution (DAB) (Dako, Glostrup, Denmark).
Statistical analysis
Stained slides were scanned with a high resolution scanner MIRAX MIDI (Zeiss, Jena, Germany). CCL1- and CCL22-positive cells (cytoplasmic staining) as well as FoxP3-positive cells (nuclear staining) were counted independently by two observers (BK and IP).
To calculate the number of stained cells per mm2 the area of each core was determined using ImageJ software (V1.50i, NIH, USA). Of the 199 tumors on the array, 180 presented an assessable FoxP3 staining, 175 an assessable CCL1 staining and 174 an assessable CCL22 staining.
The numbers of stained cells per mm2 were compared between covariates using the Mann-Whitney-Wilcoxon test. For correlations, the Spearman correlation coefficient was used. Survival probabilities were estimated using the Kaplan-Meier method and compared using the log-rank test. Hazard ratios were derived from the Cox proportional hazards model. P values below 0.05 were considered significant. Due to the exploratory character of this work, all p values have to be interpreted descriptively.
Ethics
The restrospectively registered study was approved by the ethics committee of the Ludwig-Maximilians-Universität München.
Discussion
The unfavorable role of Treg in cancers has extensively been demonstrated in the past decades, also in breast cancer. Most publications show a detrimental role on overall survival with high Treg numbers in breast cancer tissues [
19,
33]. In order to prevent Treg accumulation at the tumor site, a profound knowledge of the mechanisms of Treg migration is indispensable. In 2004, CCL22 was identified as a Treg attracting chemokine in ovarian cancer [
21]. Since then, the role for CCL22 in attraction of CCR4+ Treg to tumors was proven in numerous studies [
25,
34,
35]. Other chemokines which have been associated with Treg recruitment to tumors are CCL1, CCL5, CCL17, CCL20 and CCL28, acting on the chemokine receptors CCR4, CCR5, CCR6, CCR8 and CCR10 [
22,
36‐
38]. Amongst these, CCL1 has been described to play a role on Treg de novo conversion and Treg recruitment to murine breast cancer models [
32,
39]. CCL1 binds to CCR8, a receptor that is known to be crucial for Treg function and proliferation [
39]. In order to investigate the role of CCL1 and CCL22 on Treg infiltration and overall survival in breast cancer patients, we stained tissue microarrays of 199 breast cancer patients for the CCL1, CCL22 and FoxP3. Surprisingly, our data showed upregulation of CCL1 in breast cancer tissues, whereas CCL22 expression was not elevated when compared to normal breast tissue and did not correlate with Treg infiltration.
Chemokine expression and chemokine functions have widely been studied in breast cancer. Chemokines with well-known functions in mammary cancer include CCL2, CCL5, CCL19, CCL20, CCL21 and CCL22 [
40]. Their role ranges from angiogenesis and metastasis to attraction of various immune cell subtypes as macrophages, dendritic cells and regulatory T cells [
41‐
45]. By contrast, CCL1 is known to activate Treg and promote FoxP3 expression, de novo conversion and CCR8 expression on Treg [
32,
39]. Its role in shaping the tumor microenvironment was recently demonstrated by the fact that CCL1 blockade in murine breast cancer models led to reduced Treg numbers [
32]. Moreover, phenotyping of human breast cancer infiltrating Treg revealed high expression of CCR8 as compared to peripheral blood Treg and CCR8 expression on intratumoral Treg had a negative impact on clinical outcome [
46]. These data affirm our findings, which identify CCL1 as a major component of the breast cancer immunosuppressive machinery. The fact that high expression of CCL1 and FoxP3 was found in high-grade tumors again suggests their detrimental effect on prognosis, although we could not find a significant effect on overall survival or tumor-free survival in our analysis. We saw a correlation of CCL1 expression to estrogen receptor status, which will be interesting to follow up on in further studies. Considering the heterogeneity of breast cancer, we believe that survival analysis will have to be repeated in a bigger patient cohort, which will facilitate to account for the different breast cancer subtypes. A more extensive analysis might thus unravel the role of CCL1 mediated Treg recruitment on breast cancer patient survival.
Conclusion
In summary, we identified CCL1 as a major Treg-attracting chemokine in human invasive breast cancer. CCL1 was highly upregulated in breast cancer, positively correlated with Treg infiltration and high grade tumors, whereas none of these was found for CCL22. We conclude that CCL1 might offer new interesting starting points for immunotherapy in breast cancer.
Acknowledgements
We thank Christoph Freier, who does not want to be co-author on this study, for helping in establishing the histologic staining of CCL1 and performing a preliminary data analysis.
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