Background
Dendritic cells (DCs) are the most potent antigen-presenting cells (APCs), and play a central role in the processing and presentation of antigens to T cells during an immune response [
1]. DC progenitors in the bone marrow give rise to circulating precursors that home to the tissue where they reside as immature cells with high phagocytic capacity. Upon tissue damage or exposure to antigens, DCs capture antigens and subsequently migrate to the lymphoid organs, where they select the rare antigen-specific T cells and initiate a cellular immune response [
1,
2]. It has been shown that during migration and within secondary or tertiary lymphoid organs, DCs undergo functional maturation from antigen collection and processing to very potent APCs [
1,
3,
4]. Immature DCs capture antigens, but weakly stimulate T lymphocytes. In the presence of particular signals, such as lipopolysaccharide (LPS) or various cytokines, immature DCs mature into potent T stimulatory cells, a process that is associated with up-regulation of co-stimulatory molecules (CD80, CD86, CD40, CD83, and DC-LAMP), as well as changes in chemokine receptors expressed on their surface [
1‐
6]. Immature CD1a+ DCs are CC-chemokine-receptor (CCR) 6-positive and respond to MIP-3α [
7]. In contrast, mature DCs are attracted by the chemokine, MIP-3ß, or secondary lymphoid chemokines (SLCs) following
de novo expression of CCR7 [
6,
8,
9]. A critical characteristic of fully mature DCs is the production of pro-inflammatory cytokines, particularly IL-12, which plays a critical role in the induction of efficient T-helper cell 1 immunity [
10], as observed for an efficient anti-tumour T cell response [
1,
6].
The involvement of DCs in tumour immunity has clinical importance. The infiltration of DCs into some primary tumour types has been found to be associated with significantly improved patient survival and a reduced incidence of recurrent disease [
11,
12]. It is known that tumours avoid surveillance by the immune system through various mechanisms, including the inhibition of the recruitment of DCs at the tumour site, as well as impairment of function of DCs by local production of immunosuppressive cytokines [
13]. However, the precise knowledge of the tumour environment, which varies between different tumour types, might be important for the design of optimal immunotherapeutic strategies against cancer [
14‐
16].
Promising results have been previously reported using DC-based vaccination against immunogenic tumours, such as melanoma or renal cell carcinoma (RCC) [
17,
18]. A subset of patients with metastatic RCC develops significant immune and clinical responses after immunotherapy with DC vaccination [
1]. In this context mature DCs are thought to play a key role, since they are known to represent the most effective antigen presenting cells for induction of a potent T cell response. In order to give an answer to the question why some patients respond to DC-vaccine based therapies and others not, a detailed knowledge about the cellular T cell immune response in RCC with special regard to antigen-presenting DCs is required. However, detailed studies concerning the type and distribution of DC subsets in RCC are still lacking.
More recently, novel markers have emerged allowing the identification of a broader spectrum of DC subpopulations with respect to their function on formalin-fixed and paraffin-embedded tissue. Thus, we characterized the phenotype, distribution, and maturation of the different DC subsets in RCCs. In addition, we analyzed the local expression of chemokines that are known to play a key role for the recruitment of DC subsets.
Methods
Tissue samples
Tumours and corresponding tumour-free tissue of nephrectomy specimens from 24 patients with RCCs were included in this study. All tumours were freshly obtained from the Urologic Department's operating room. The patient ages ranged from 36-75 years (median age, 60 years). None of the patients investigated in this study were treated before surgery. The formalin-fixed and paraffin-embedded specimens were cut into 5-μm-thick sections and placed on poly-L-lysine-treated glass slides. Representative sections were stained with routine hematoxylin and eosin (H&E) and evaluated. The histologic types of cancer were as follows: clear cell (n = 17); papillary (n = 4); chromophobe (n = 1); and sarcomatoid renal cell carcinoma (n = 2). This study was approved by the Ethics Committee of Georg-August-University Göttingen, and the Helsinki Declaration regarding the use of human tissue was followed. Informed consent was obtained from the patients for the use of their tissue samples.
Immunohistochemistry
The antibodies used in the study and the optimal working dilutions are listed in Table
1. The sections were immunostained applying the biotin-streptavidin-peroxidase method (Multi-Link, DCS, Hamburg, Germany). Immunostaining for chemokines (MIP-3α, MIP-3β, and SLC) required application of the tyramide signal amplification system method (NEN, Boston, MA, USA). In control reactions, isotype- and species-specific matched control antibodies were applied.
Table 1
Antibodies used for immunohistochemistry and immunofluorescence (Ms - mouse, Rb - rabbit antibody).
CD1a | 1:50 | Ms | LabVision, Fremont, CA, USA |
CD3 | 1:50 | Ms | Novocastra, Newcastle, UK |
CD4 | 1:50 | Ms | DAKO, Hamburg, Germany |
CD11c | 1:50 | Ms | DAKO |
CD40 | 1:50 | Ms | Acris, Hiddenhausen, Germany |
CD68 | 1:50 | Ms | DAKO |
CD79a | 1:50 | Ms | DAKO |
CD83 | 1:20 | Ms | Novocastra |
DC-LAMP/CD208 | 1:50 | Ms | Acris |
Langerin | 1:50 | Ms | Acris |
RelB | 1:200 | Rb | SantaCruz |
CCR6 | 1:20 | Ms | R&D Systems |
CCR7 | 1:20 | Ms | R&D Systems |
MIP-3α | 1:20 | Goat | R&D Systems |
MIP-3β | 1:20 | Goat | R&D Systems |
SLC | 1:50 | goat | R&D Systems |
Vimentin | 1:100 | Ms | DAKO |
Fascin | 1:100 | Ms | DAKO |
D2-40 | No | Ms | DCS-Diagnostics, Hamburg, Germany |
Ki-67 | 1:50 | Ms | DAKO |
For double immunofluorescence staining, the slides were stained for 1 hour with unconjugated primary antibody, followed by incubation with indocarbocyanine 2 (Cy2)-conjugated goat anti-mouse or goat anti-rabbit F(ab)-fragments (both from Dianova, Hamburg, Germany) at a saturating concentration for 60 minutes. For the first step in immunofluorescence staining for MIP-3α, MIP-3β, and SLC, we adopted the TSA-Kit (NEN) using FITC-conjugated tyramide for fluorescence amplification. Sections were washed and incubated with the second antibody for 60 minutes at room temperature, followed by incubation with indocarbocyanine 3 (Cy3)-conjugated goat anti-mouse or goat anti-rabbit F(ab)-fragments (both from Dianova) for 60 min at room temperature.
Confocal fluorescence images were obtained on a Leica TCS (Leica Microsystems, Heidelberg, Germany) confocal system mounted on an Olympus BX50 WI microscope (Tokyo, Japan). Possible cross-talk between FITC or Cy2 and Cy3, which could give rise to false-positive co-localization of different signals, was avoided by careful selection of the imaging conditions.
RT-PCR analysis
Sequences of primers used in the study are listed in Table
2. Primers and probes (Operon-Qiagen, Hilden, Germany) were designed using the Primer-3 online primer design program
http://www-genome.wi.mit.edu. Optimal conditions for all primers were established by amplifying cDNA samples from human tonsil or lymph node.
Table 2
PCR primers used for RT-PCR analysis of chemokines
MIP-3α | 5'- CTGTACCAAGAGTTTGCTCC -3' | 193bp |
| | 5'- GCACAATATATTTCACCCAAG -3' | |
MIP-3β | 5'-CCAGCCTCACATCACTCACACCTTGC-3' | 324 bp |
| | 5'-TGTGGTGAACACTACAGCAGGCACCC-3' | |
SLC | 5'-AACCAAGCTTAGGCTGCTCCATCCCA-3' | 249 bp |
| | 5'-TATGGCCCTTTAGGGGTCTGTGACCG-3' | |
β-Actin | 5'- CTACAATGAGCTGCGTGTGGC -3' | 270 bp |
| | 5'- CAGGTCCAGACGCAGGATGGC -3' | |
Total cellular mRNA was extracted with the RNeasy Mini Kit (Operon-Qiagen). RNA integrity and quantity was assessed using the Agilent Bio-analyzer 2100 (Agilent Technologies, Waldbronn, Germany). Reverse transcription with random hexamer primers was performed with the Omniscript RT Kit (Qiagen). Quantification of MIP-3α, MIP-3β, SLC, and ß-actin mRNA expression was performed on an iCycler iQ real-time detection system (Bio-Rad, Hercules, CA, USA) using the HotStar TaqDNA polymerase kit (Qiagen). Expression of MIP-3α, MIP-3β, and SLC was normalized to ß-actin expression to compensate for different sample capacities. Results derived from the PCR standard curve are given in attomoles per μg of total cellular RNA. cDNA from a human lymph node was used as a positive control template for each primer pair. Negative controls with water instead of cDNA were always included.
Tumour cell lines
The RCC cell lines (A498, Caki-1, and Caki-2) were purchased from the Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSZM, Braunschweig, Germany). All 3 cell lines were cultivated at 37°C in 5% CO2 in RPMI-1640 containing 10% fetal calf serum, 10 mm l-glutamine, 1% penicillin/streptomycin, 2.5% HEPES buffer, and 1% amino acid solution.
Statistics
The evaluation of immunoreactivity was performed on sections stained for CD1a and CD83. Because of the heterogeneous distribution of DC, the quantification was performed by the hot-spot method. This method allows quantification of cells in hot spots defined in this study as areas containing the highest density of positive cells. Accordingly, five hot spots per section were counted with an eyepiece graticule at 400x magnification. Statistical analyses were applied using GraphPad Prism (version 5.00 for Mac; GraphPad Software, San Diego, CA, USA). Statistical comparisons were performed applying the unpaired t-test or the Mann-Whitney test; p values < 0.05 were considered as statistically significant.
Discussion
A RCC is considered to be one of the most immunoresponsive cancers in humans. During the last few decades, promising new immunologic-based treatment strategies for this tumour entity have been developed [
18]. However, the tumour response is observed only in a subset of patients. Thus, detailed knowledge of the mechanisms underlying the immune response at the interface between immune attack and immune suppression might help to improve the promising immunotherapeutic approaches in RCCs. More recently, emphasis has shifted to the use of DC vaccines for active immunization of cancer patients with
in vitro-generated DCs, which have been fused with tumour cells or loaded with tumour antigens [
19‐
21].
Different approaches of RCC vaccines have been explored in the metastatic and adjuvant setting in several studies [
22,
23]. Reviewing the current literature, about 20 non-randomised phase 1 or 2 immunotherapeutic trials have been published for DC-vaccines in metastasized RCCs [
24‐
40]. As a summary, none of these patients developed significant treatment-related toxicity or autoimmunity-related side effects, while approximately 40% of the patients demonstrated clinical tumour regression [
18]. Nevertheless, the results of DC vaccination in these non-randomised studies should be viewed with caution because of the relative small number of patients within each trial and the diversity of the vaccination strategies used. Although most groups currently use monocyte-derived DCs for clinical vaccine trials [
41], the isolation procedures of the monocytes, the differentiation procedures towards DCs, and the loading and maturation procedures are heterogeneous between the published clinical studies [
42]. Thus, the current data suggest that DC vaccination in patients with metastatic RCCs appears to be safe and results in a tumour-specific immune response which can achieve tumour regression in a significant subset of patients [
18]. However, for efficient and reliable immunotherapy of tumours, the optimal protocol for DC-based vaccination remains to be clarified further. Therefore, detailed knowledge concerning the immune response in RCCs with special regard to the role of DCs
in vivo is required for development of an optimal vaccination strategy. One very important issue in this context represents a detailed knowledge concerning the type and distribution of DC subsets, as well as the mechanisms underlying their migration, maturation, and function in RCCs. Recent data point to a significant role of DC subsets in Th1/Th2 polarization and the induction of the tumour immune response [
14,
43]. Thus, the determination of the origin and immune competence of tumour-associated DCs will be of great importance to our understanding of the development of tumour immunity for RCCs [
44]. Therefore, we investigated the distribution and maturation of the different DC subtypes in RCCs and corresponding normal kidney tissues. The findings in the current study extend previous investigations for other tumour entities [
14,
15,
45,
46]. The results demonstrate a unique compartmentalization of immature and mature DCs within kidneys affected by RCCs.
All tumour samples displayed variable immature DC infiltration. Tumour-infiltrating immature DCs were heterogeneous, and two populations were identified. One population represented the CD1a+/Langerin+ Langerhans-cell type and the other type was CD1a+/Langerin- non-Langerhans cell. Since dermal (interstitial) DCs were found
in vitro and
in vivo to express CD1a, but not Langerin, we currently conclude that CD1a+/Langerin- tumour-infiltrating DCs represent immature interstitial DCs. The significance of this heterogeneity remains to be established. Earlier studies revealed that interstitial DCs generated
in vitro from CD34+ precursors display more potent phagocytic activity than LCs [
1,
3].
The observed numbers of immature CD1a+ DCs in the tumour environment was much higher than in normal kidney tissues, suggesting increased homing and infiltration of immature DCs by the tumour. This finding was also been described by Troy et al. [
47,
48] nearly a decade ago. This may be best explained by the high levels of intratumoural MIP3-α, a chemokine, which is known to specifically attract immature DCs. Our results show an increased expression of MIP-3α by tumour cells of RCCs by RT-PCR and immunohistochemistry. The immunohistochemistry analysis with anti-MIP3-α is unfortunately not precise enough to allow a correlation between the amount of MIP3-α protein by the tumour cells and the amount of infiltrating immature DCs. However, our finding of an increased expression of MIP-3α mRNA in RCC cell lines, as well as in RCC tissue compared to mRNA derived from normal kidney, underlines a role for an increased expression of MIP-3α in homing or recruitment of immature DCs to RCC tissues. The increased number of immature DCs could also reflect a transient stage due to the high in-and-out migration or the sequestering of immature DCs within the tumour tissue. Another explanation might be tumour-induced maturation arrest of tumour-infiltrating DCs. Studies for different tumour entities have shown that in cancer patients, DCs in the blood, tumour tissues, and draining lymph nodes are often functionally defective and possess poor T cell stimulatory capacity [
49]. One possible explanation for this observation might be the expression of tumour-derived factors, such as VEGF, TGF-β, and IL-10, which have been shown to inhibit differentiation or functional maturation of DCs [
49‐
53]. Therefore, it has been suggested that immaturity of DCs in the tumour tissue may mediate tumour tolerance instead of immune activation caused by induction of T-cell anergy or favouring the development of regulatory T cells [
54,
55].
However, in contrast to the observed immaturity of intratumoural DCs, the more important finding might be the presence of numerous mature DCs accumulating specifically within the peri-tumoural areas. This finding suggests that additional factors might be involved in mature DC distribution. Because mature DCs are typically observed in lymphoid organs, where they closely interact with T cells, it is tempting to consider that their presence within the tumour tissue might reflect an ongoing tumour-specific immune response. Thus, the mature DCs could derive from any of the immature DC subset discussed above within the tumour tissues. The peri-tumoural localization of mature DCs observed in our study corresponds to observations in other tumour types, and RCC as well [
15,
47]. The preferential localization of mature DCs in lymphocyte-rich peri-tumoural areas of RCCs could be due to the resemblance of these areas to secondary lymphoid organs where mature DCs are normally found.
What instigates the mechanisms underlying the accumulation of mature DCs with a prominent T cell response in RCCs. Our results support the concept that specific homing of CCR7+ leucocytes to the tumour border may contribute to the anti-tumour response in RCCs, which at least partly resembles de novo development of a tertiary lymphoid tissue at the invasive margin of the tumours. Our results show a significant increased expression of lymphoid chemokines (SLC and MIP-3β) at the tumour border in contrast to tumour and normal kidney tissues. These results imply that the increased expression of SLC and MIP-3β may lead to a chemokine microenvironment normally observed in secondary lymphatic tissues. Expression of these chemokines favours homing and interaction of CCR7-expressing cells, such as mature myeloid DCs and naïve or memory T cells, facilitating their interaction for an optimal anti-tumour immune response. Thus, in analogy to secondary lymphoid organs, such as lymph nodes, chemokine-dependant co-localization of T-cells and antigen-presentation occurs at the tumour border, leading to the local generation of anti-tumour-specific T cells.
Interestingly, various studies have shown that the presence of a dense DC infiltration has been associated with prolonged survival and reduced incidence of metastases in patients with various human cancers, such as colorectal, gastric, esophageal, oral, and lung carcinoma [
56‐
59]. In breast cancer, the number of CD83+ mature DCs, but not the number of CD1a+ or S100+ DCs, has been shown to be of prognostic relevance [
60]. In light of their importance in anti-tumour immunity, surprisingly few studies have been aimed at the presence of DCs and its potential clinical correlates in RCCs. For interferon pre-treated RCCs a trend toward a better outcome and better prognosis has been found in patients with a higher number of S100+ DCs within the tumour tissue [
61,
62]. Although S100 protein has long been used to indicate DCs, its significance is still under confusion. In our experiments, we found S100 protein to be co-expressed by numerous CD68+ macrophages. Thus, S100 immunohistochemistry was not suitable for evaluation of DC numbers in RCCs (data not shown). In a more recent study, Kobayashi et al. [
63] investigated whether or not the local immune environment might be associated with the tumour response following treatment with interferon-α and interleukin-2 in RCCs. Their results demonstrated a higher number of mature CD83+ DCs in tumour tissue of responders following cytokine treatment. In addition, the responders survived longer than non-responders. In contrast, other tumour-associated immune cells, such as CD8+ T-cells or tumour-associated macrophages, were not associated with treatment response or survival outcome. Thus, the presence of high number of CD83+ mature DCs might represent a predictive factor for the clinical outcome in patients with RCCs [
63].
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
PM performed the design of the study and the statistical analysis. PM and SB performed the experimental investigations. WM participated in the writing of the manuscript. HJR participated in conception of the idea and writing of the manuscript. All authors read and approved the final manuscript.