Regulatory T cells, interleukin (IL)-6, IL-8, Vascular endothelial growth factor (VEGF), CXCL10, CXCL11, epidermal growth factor (EGF) and hepatocyte growth factor (HGF) as surrogate markers of host immunity in patients with renal cell carcinoma


  • M.P. and M.N. contributed equally to this work.



  • To identify a phenotype that could be informative and prognostic in patients with renal cell carcinoma (RCC) peripheral blood was evaluated for TH1, TH2, regulatory T cells (Tregs), natural killer (NK) and NKT cells and for cytokines/chemokines.

Patients and Methods

  • Peripheral blood from 77 patients with RCC and 40 healthy controls was evaluated by flow cytometry using monoclonal antibodies against CD4, CD25, FoxP3, CD45RA, CD45RO, CD152, CD184, CD279, CD3, CD16, CD56, CD161, CD158a, CD4, CD26, CD30, CD183 and CD184.
  • A concomitant evaluation of 38 molecules was conducted in patients’ serum using a multiplex biometric ELISA-based immunoassay.


  • The number of NK cells CD3/CD16+, CD3/CD16+/CD161+ (NK) and CD3/CD16+/CD161+/CD158a+ (NK- Kir 2+) was greater in the patients with RCC (P < 0.05); and the number of Treg cells CD4+/CD25high+/FOXP3+ and the subset CD4+/CD25high+/FOXP3+/CD45RA+ (naïve) and CD45R0+(memory) cells, were greater in the patients with RCC (P < 0.001).
  • An increase in the following was observed in the serum of patients with RCC compared with healthy controls: interleukin (IL)-4, IL-6, IL-8, IL-10, G-CSF, CXCL10, CXCL11, hepatocyte growth factor (HGF) and vascular endothelial growth factor (VEGF). According to Ingenuity Pathway Analysis (IPA), CXCL10, IL-6, IL-8, epidermal growth factor (EGF), HGF and VEGF were associated with a network that controls cellular movement, tissue development and cellular growth.
  • Kaplan–Meier analysis for disease-free survival showed that high numbers of CD4+/CD25high+/FOXP3+/CD45RA+ (Treg naïve) and low numbers of CD3/CD16+/CD161+/CD158a+ (NK-Kir+) cells predict short disease-free survival in patients with RCC.


  • Concomitant evaluation of Treg (CD4+/CD25high+/FOXP3+ and CD4+/CD25high+/FOXP3+/CD45RA+) and of six soluble factors (IL-6, IL-8 ,VEGF, CXCL10, CXCL11, EGF, HGF) might be a surrogate marker of host immunity in patients with RCC.

regulatory T cell




natural killer


American Joint Committee on Cancer


Ingenuity Pathway Analysis


tumour-infiltrating lymphocyte


Von Hippel Lindau


Currently, RCC accounts for 3% of all adult malignancies. According to recent reports the incidence as well as the detection of RCC is increasing, especially with regard to small localized tumours [1, 2]. Surgical resection, including the use of nephron-sparing techniques, is the standard therapy and is curative for most patients with tumours pathologically confined to the kidney (pT1 or pT2). Despite low rates of progression in patients with localized RCC, almost 30% develop metastatic RCC [3]. Currently, pathological stage (pT), lymph node status (pN) and Fuhrman grade are the main prognostic variables [4]. RCC is considered an immunogenic cancer, with pathological specimens frequently containing large numbers of tumour-infiltrating lymphocytes (TILs) [5]. Tyrosine kinase inhibitors and anti-angiogenic agents dramatically changed the therapeutic approach for metastatic RCC [6] where immune therapy was considered the mainstay of therapy [7]. The response of patients with RCC to interleukin (IL)-2 correlated with the stimulation of natural killer (NK) and T cells targeted against tumour cells [8]. Nevertheless, in a large proportion of patients, the neoplasm acquires the ability to escape from the immune response with local recruitment/induction of regulatory T cells (Tregs) [9]. It was recently reported that functional Tregs accumulated inside the tumour and that their intratumoural and peripheral frequency is associated with a worse prognosis in RCC [10]. The precise molecular mechanisms of suppression by human Treg cells remain to be determined, although in vitro and in vivo studies have implicated modulation of the cytokine micro-environment, metabolic disruption of the target cell, alteration of dendritic cell-activating capacity and cytolysis [11-13]. We investigated immunoregulatory cells and cyto-chemokines in the peripheral blood of 77 patients with RCC, who were disease-free after undergoing nephrectomy, with the aim of identifying a peripheral phenotype informative and potentially prognostic of the patients’ disease. The patients were evaluated for TH1, TH2, Tregs, NK and NKT cells as well as for peripheral cyto-chemokines and growth factors in peripheral blood.

Patients and Methods


The study population comprised 77 patients with RCC and 40 healthy donors, with no evidence of kidney disease [14]. Peripheral blood samples, using EDTA as an anticoagulant, and serum were collected after obtaining informed consent. The patients with RCC were evaluated 6 months after undergoing nephrectomy to detect a possible shift toward an immunosuppressive phenotype. The patients’ clinical characteristics are listed in Table 1. Pathological staging was in accordance with the TNM staging system. Stages pT1, pT2 and pT3 were pooled together. Tumour size was determined on pathological specimens as the greatest diameter in cm. The study was approved by the Human Ethics Committee.

Table 1. Patient and tumour characteristics
Median (range) age, years60 (32–80)
Age, n (%) 
<65 years51 (66.2)
≥65 years26 (33.7)
Gender, n 
AJCC stage, n 
Tumour size, n 
<5 cm21
5–7 cm9
>7 cm20
Histological variant, n 
Symptoms at diagnosis, n 
Fuhrman grade, n 

Flow cytometry

Flow cytometry was performed on whole blood, using a FACSCanto II 6-colour flow cytometer, daily calibrated with calibrite beads (Fitc, Pe, PerCP and APC) and compbeads (Pe-Cy7 and APC-Cy7; Becton Dickinson, San Jose, CA, USA). Fluorochrome-labelled monoclonal antibodies (BD Pharmingen, San Diego, CA, USA) were used against CD4, CD25, FOXP3, CD45RA, CD45RO, CD152, CD184, CD279 for Treg cells, against CD3, CD16, CD56, CD161, CD158a for NK and NKT cells, and against CD4, CD26, CD30, CD183, CD184 for TH1 and TH2 cells. Monoclonal antibodies were used together with the appropriate corresponding isotype controls to allow the identification of positive and negative cell populations. A minimum of 50 000 events for each sample were collected and data were analysed using FacsDiva software. Intracellular staining for FOXP3 was performed using a commercially available kit (BD Cytofix/Cytoperm; fixation and permeabilization kit; BD Pharmingen) and this was performed according to the manufacturer's instructions.

Cytokine evaluation

Sera were collected by centrifugation (2250 g for 10 min at 4 °C), aliquoted, and stored at −80 °C until analysed. A multiplex biometric ELISA-based immunoassay, containing dyed microspheres conjugated with a monoclonal antibody specific for a target protein was used according to the various manufacturers’ instructions (Bio-Rad Lab. Inc., Hercules, CA; Invitrogen Corp., Camarillo, CA; R&D Systems, Inc. Minneapolis, MN, USA). Three different landmarks were used for serum factor screening to include and cross-validate the highest number of proteins. Soluble molecules were measured using three commercially available kits:

  1. 27-Plex kit (BioRad): CXCL10, IL-1β, IL-1ra, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12, IL-13, IL-15, IL-17, eotaxin, basic FGF, G-CSF, GM-CSF, interferon (IFN)-γ, MCP-1, MIP-1α, MIP-1β, PDGF-ββ, RANTES, TNF- α, VEGF;
  2. 30-Plex kit (Invitrogen): CXCL9, CXCL10,IL-1β, IL-1ra, IL-2, IL-2R, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12, IL-13, IL-15, IL-17, EGF, eotaxin, FGF-basic, G-CSF, HGF, IFN-α, IFN-γ, GM-CSF, MCP-1, MIP-1α, MIP-1β, RANTES, TNF-α, VEGF;
  3. 31-Plex kit (R&D): CD40 Ligand, CXCL5/ENA78, CXCL10, CXCL11, EGF, eotaxin, basic FGF, G-CSF, GM-CSF, HGF, IFN- γ, IL-1α, IL-1β, IL-1ra, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12, IL-13, IL-17, Leptin, MCP-1, MIP-1α, MIP-1β, RANTES, TNF- α, Tpo and VEGF.

Each experiment was performed in duplicate, using the same previously described procedure [15-17]. The analyte concentration was calculated using a standard curve with software provided by the manufacturer (Bio-Plex Manager Software). Regression analysis was performed to derive an equation that was then used to predict the concentration of cytokines in serum samples.

Data analysis and statistics

The non-parametric Mann–Whitney U-test was used to evaluate differences between the value of peripheral cytokine, chemokine and growth factor from patients with RCC and healthy controls.The correlations between the cytokine levels and clinical data were determined using the Pearson correlation coefficient. A P value < 0.05 was considered to indicate statistical significance. The statistical program Prism 4 (GraphPad Software, San Diego, CA, USA) was used.

Disease-free survival was defined as the time elapsed from the date of the diagnosis to the appearance of local relapse or distant metastasis. The Kaplan–Meier product limit method was applied to plot the disease-free survival of 77 patients (including three patients with unknown histology and one patient with lost follow-up). Univariate analysis was performed using the log-rank test. Risk factors (covariates) were considered dichotomous (male vs female; age < 70 vs 70 years; American Joint Committee on Cancer (AJCC) stage 1 vs 2 vs 3 vs 4; Fuhrman grade 1 vs 2 vs 3 vs 4; Clinical presentation accidental vs local vs systemic; CD4+/CD25high+/FOXP3+/CD45RA+ ≥ 0.5% vs <0.5%; CD3/CD16+/CD161+/CD158a+ ≥ 2% vs. <2%). The statistical software MedCalc version was used.

DNA extraction and mutation detection

Genomic DNA was isolated using a QIAmp DNA mini kit (Qiagen, Valencia, CA, USA). Von Hippel Lindau (VHL) gene status was characterized with the following primers:


Purified PCR products were then sequenced by using the Big Dye terminators version 3.1 cycle sequencing kit (Applied Biosystems, Courtaboeuf, France) and the 3130 Genetic Analyzer (Applied Biosystems). Data were analysed using Sequence Scanner v1.0 (Applied Biosystems).


Patient characteristics

The patient characteristics are shown in Table 1. The study group comprised 77 patients, of whom 42 were men and 35 were women, who had undergone nephrectomy and were disease-free. The stage distribution was as follows: 31 patients were T1; 16 patients were T2; 16 patients were T3; and 14 patients had missing stage data. Histological analysis showed that the majority (61 patients) had clear-cell RCC, while seven had papillary, three had chromophobe, two had adenocarcinoma and one was unknown (Table 1).

TH1, TH2, Treg, NK and NKT cells in peripheral blood in patients with RCC

With the aim of identifying a peripheral immune profile that would be informative of patients’ prognosis, we evaluated TH1, TH2, Treg, NK and NKT cells in 77 patients with RCC and compared them with those of healthy controls using the non-parametric Mann–Whitney U-test. Table 2 shows the cellular subgroups that were significantly different between the patients and healthy controls. NK cells CD3/CD16+, CD3/CD16+/CD161+ and CD3/CD16+/CD161+/CD158a+ (P < 0.05) and Treg cells CD4+/CD25high+/FOXP3+, mainly the subset CD4+/CD25high+/FOXP3+/CD45RA+ (Treg naïve) and CD4+/CD25high+/FOXP3+/CD45R0+ (Treg memory) were greater in number in the patients with RCC (P < 0.001). Figure 1 shows an example of the Treg subsets CD4+/CD25high+/FOXP3+/CD45RA+ and CD4+/CD25high+/FOXP3+/CD45R0+.

Figure 1.

High numbers of CD4+/CD25high+ and CD4+/CD25 high+/FOXP3+. T lymphocytes in the peripheral blood of patients with RCC. The lymphocytes CD3+/CD4+ were stained for flow cytometric analysis and gated according to forward and side scatter characteristics. A, Dot plots showing the typical staining of CD4 and CD25 with the CD4+/CD25high+ gate. B, Dot plots showing the cells gated CD4+/CD25high+ that coexpress FOXP3. C and D, Dot plots showing the cells gated CD4+/CD25high+/FOXP3+ that coexpress CD45RA and CD45R0, respectively.

Table 2. P values obtained for NKT and Treg numbers in patients with RCC compared with healthy control subjects using the non-parametric Mann–Whitney U-test)
Healthy controls, % cells (sd)Patients, % cells (sd)P
  1. *P < 0.05; **P < 0.01.
CD3/CD16+9.77 (7.24)8.72 (0.10)0.042*
CD3/CD16+/CD161+7.59 (5.66)7.48 (0.09)0.012*
CD3/CD16+/CD161+/CD158a+1.53 (1.35)1.98 (0.04)0.024*
CD8+/CD184+15.53 (5.09)8.35 (0.09)0.008**
CD4+/CD25high+/FOXP3+0.30 (0.18)0.81 (0.01)<0.001**
CD4+/CD25high+/FOXP3+/CD45RA+0.09 (0.11)0.162 (0.005)<0.001**
CD4+/CD25high+/FOXP3+/CD45R0+0.23 (0.15)0.52 (0.01)<0.001**
CD4+/CD25high+/FOXP3+/CD279+0.15 (0.10)0.23 (0.02)<0.001**
CD4+/CD25high+/FOXP3+/CD184+0.27 (0.19)0.48 (0.01)0.03*

Peripheral cytokines in patients with RCC

To identify a concomitant peripheral cyto-chemokine profile with prognostic relevance in patients with RCC, 38 molecules were simultaneously evaluated using a multiplex biometric ELISA-based immunoassay, while control subjects were evaluated using the non-parametric Mann–Whitney U-test (Table 3, Fig. 2). The tested cytokines were chosen with the aim of testing a broad range of cytokines in the most reliable way; thus, three different cyto-chemokine panels were evaluated to obtain the most valid results. A significantly higher amount of the following molecules was detected in patients with RCC: IL-1rα, IL-10, IL-12, IL-4, IL-6, IL-8, CXCL10, CXCL11, eotaxin, MIP-1α, EGF, G-CSF, HGF, PDGF-ββ, VEGF and CD40 ligand. In addition, we focused on the growth factors VEGF and HGF after subdividing the patients on the basis of four different Fuhrman grades: I, II, III and IV. No difference in VEGF was found in the four subgroups, whereas HGF was significantly different in patients with grades III and IV (Fig. 3). The resultant soluble factors that were found to be increased in patients with RCC were analysed using Ingenuity Pathway Analysis (IPA). IPA is a biological data analysis software that evaluates data from a variety of experimental platforms and provides accurate biological insight into the interactions between genes, proteins, chemicals, pathways, cellular phenotypes and disease processes in a subject's system [18, 19]. CXCL10, IL-6, IL-8, EGF, HGF and VEGF were correlated through IPA to a network associated with cellular movement, tissue development and cellular growth and proliferation (Fig. 4). Previous studies have shown that CXCL10, IL-6, IL-8, EGF, HGF and VEGF participate in cancer and inflammatory response; EGF, HGF, IL-6, IL-8 and VEGF are implicated in renal and urological disorders and CXCL10, EGF, HGF and IL-6 in the proliferation of renal cells [20-24]. The results suggest that, although a wide panel of serum factors was evaluated, IPA results support the histological involvement of CXCL10, IL-6, IL-8, EGF, HGF and VEGF in RCC patients. High numbers of CD4+/CD25high+/FOXP3+/CD45RA+ and low numbers of CD3/CD16+/CD161+/CD158a+ cells predict disease-free survival in patients with RCC. Table 2 shows the comparison between the peripheral immune phenotype of patients with that of healthy controls. Cellular subgroups were significantly represented between patients with RCC and healthy contols. Comparing the identified cellular subgroups with the consolidated RCC prognostic factors identified that CD4+/CD25high+/FOXP3+ and CD4+/CD25high+/FOXP3+/CD45RA+ were correlated with disease stage (P = 0.019; P = 0.007), a strong prognostic factor. Moreover, CD4+/CD25high+/FOXP3+/CD45RA+ significantly correlated with tumour size (P = 0.046). No other significant correlations were identified with regard to the activated Kir-expressing NK cells (CD3/CD16+/CD161+/ CD158a+ [Table 4]). Kaplan–Meier analysis curves for disease-free survival showed that high numbers of CD4+/CD25high+/FOXP3+/CD45RA+ (P = 0.032) and low numbers of CD3/CD16+/CD161+/CD158a+ (P = 0.037) cells significantly correlated with worse disease-free survival (Fig. 5 and B). Moreover, since VHL mutational status is implicated in the recognition and activation of immune cells, particularly NK cells and a decreased expression of HLA-I molecules in mutated VHL renal tumour cells sensitizes them to NK-mediated lysis [41], the VHL mutational status was verified in 39 out of the 77 patients available. Table 5 shows VHL status; it can be seen that 10 out of 39 patients carried a mutated VHL. Nevertheless when the mutational status was analysed with regard to the NK population, CD3/CD16+/CD161+/CD158a+ and/ or to Treg, CD4+/CD25high+/FOXP3+/CD45RA+, no significant correlations were detected, although there was a trend towards greater numbers of CD3/CD16+/CD161+/CD158a+ cells in mutant VHL (data not shown).

Figure 2.

High levels of soluble molecules in patients with RCC who were disease-free after nephrectomy. Significant cytokine levels from healthy controls and post-nephrectomy disease-free patients are plotted with box-and-whisker graphs. The boxes extend from the 25th to the 75th percentile, and the line in the middle is the median. The error bars extend down to the lowest value and up to the highest. *P < 0.05; **P < 0.01; ***P < 0.001.

Figure 3.

The cytokine levels were compared using a Mann–Whitney U-test and only HGF values between the patients with grades III and IV were found to be significantly different P < 0.001.

Figure 4.

CXCL10, IL-6, IL-8, EGF, HGF and VEGF assessed using IPA. The network is shown linking CXCL10, IL-6, IL-8, EGF, HGF and VEGF (grey symbols) and other molecules with white symbols.

Figure 5.

Kaplan–Meier curves for disease-free survival in patients with RCC. High CD4+/CD25high+/FOXP3+/CD45RA+(A) and low CD3/CD16+/CD161+/CD158a+ (B) levels affect progression-free survival in patients with RCC who have undergone nephrectomy.

Table 3. P-values obtained for all significant molecules in patients with RCC compared with healthy control subjects using the non-parametric Mann–Whitney U-test
Mean (sd), pg/mLP
  1. *P < 0.05; **P < 0.01.
CD40 ligand14 986 (7568)<0.001**
CXL1016 (10)<0.001**
CXCL1145 (36)0.007**
EGF289 (191)<0.001**
Eotaxin337 (293)0.016*
G-CSF301 (251)0.004**
HGF843 (685)<0.001**
IL-10105 (68)0.044*
IL-12402 (351)<0.001**
IL-1RA569 (335)0.001**
IL-4387 (133)0.005**
IL-6193 (101)0.008**
IL-855 (49)<0.001**
MIP1β281 (202)<0.001**
PDGF-ββ5 012 (4470)0.017**
VEGF39 (28)<0.001**
Table 4. Patient and tumour characteristics stratified by CD4+/CD25high+/FOXP3+, CD4+/CD25high+/FOXP3+/CD45RA+ and CD3/CD16+/CD161+/CD158a+ peripheral level
Negative (<1%)Positive (≥1%)PNegative (<0.5%)Positive (≥0.5%)PNegative (<2%)Positive (≥2%)P
Median (range) age, years60 (32–80)         
Age, n (%)   0.935  0.921  0.411
<65 years51 (66.2)2624 2513 1822 
≥65 years26 (33.7)1213 136 128 
Gender   0.736  0.301  0.121
Male422219 238 1219 
Female351618 1511 1811 
AJCC stage, n (missing = 14)   0.019  0.007  0.413
T1311714 184 1315 
T216115 93 37 
T316312 49 75 
Tumour size, n (missing = 27)   0.736  0.046  0.666
<5 cm211110 134 79 
5–7 cm954 41 53 
>7 cm20811 610 65 
Histological variant, n (missing = 3)   0.305  0.508  0.092
Conventional613130 2817 2722 
Papillar752 51 13 
Cromophobe312 11 03 
Adenocarcinoma202 20 20 
Symptoms at diagnosis, n (missing = 39)   0.893  0.282  0.641
Incidental27918 129 810 
Local734 14 21 
Systemic412 12 21 
Furhman's grade, n (missing = 10)   0.3414  0.4799  0.368
11385 102 55 
2241112 97 129 
3241212 117 610 
4615 32 41 
Table 5. Mutation of the VHL gene
Patient InitialsGenderMutationExonProtein changeMutation typeStatus of Disease
  1. wt, wild type; NED, no evidence of disease; DP, disease progression; DFD, died from disease; DOC: dead from other causes.
DVAMalewt   NED
CAFemalewt   PD
CFFemale239 G>AExon1Ser80AsnMissenseNED
ACMalewt   NED
CAFemalewt   NED
BBMalewt   NED
GGFemale210delC insATAATExon1133TruncationFrameshiftNED
TAMalewt   DFD
VAMalewt   DFD
VRFemalewt   NED
TSMale194 C>GExon1Ser65TrpMissenseNED
GAMalewt   NED
CIFemalewt   NED
TCFemalewt   NED
OLMalewt   NED
DSGMalewt   NED
CFFemale210delC insATAATExon1133TruncationFrameshiftDFD
GEFemalewt   NED
PAMalewt   NED
PGRMalewt   NED
AGFemalewt   NED
FBRMalewt   NED
FCFemalewt   NED
DMMFemalewt   NED
BRMalewt   DFD
ARMale394 C>TExon2Gln132StopNonsenseNED
CCMalewt   NED
DRMMalewt   NED
SMFemale217 insCExon1132TruncationFrameshiftNED
RSMalewt   NED
GAMalewt   PD
CMMale239 G>AExon1Ser80AsnMissenseNED
BSMalewt   NED
RCFemale227delTCTExon176 deletionIn-frame deletionNED
VPFemalewt   NED
ZGMalewt   NED
PSMalewt   NED
DPAMalewt   NED


In the present study, patients with RCC were evaluated for TH1, TH2, Treg, NK and NKT peripheral value and concomitant multiple serum factors (cyto-chemokines and growth factors) with the aim of identifying an informative and potentially a prognostic patient profile. A greater number of Treg (CD4+/CD25high+/FOXP3+ CD4+/CD25high+/FOXP3+/CD45RA+) and NK (CD3/CD16+/CD161+/CD158a+) cells was detected in the studied population and the concomitant greater number of CD4+/CD25high+/FOXP3+/CD45RA+ cells and lower number of CD3/CD16+/CD161+/CD158a+ cells identified patients with a short progression-free survival. Detection of higher percentages of Tregs in Peripheral Blood Lymphocytes (PBL) or TILs has previously been associated with poor survival outcomes in several cancers, such as ovarian [25], pancreatic [26] and liver [27] cancer, while the role of Tregs in RCC is still controversial [28-30]. A robust, positive correlation between CD25high and CD25+/Foxp3+ cells was found in TILs and a smaller, but significant, correlation was found in peripheral blood, suggesting that CD25high circulating T cells in patients with RCC include not only Tregs, but also probably activated CD25+ effector lymphocytes [30]. The expression of specific chemokine receptors CCR5, CXCR3, and CXCR6, as well as CCR6, the ligand for which (CCL20) is detected in RCC, characterized intratumoural Tregs compared with peripheral Tregs. The CCR5, CXCR3 and CXCR6 corresponding ligands CCL4-5, CXCL9-11, and CXCL16 were all detected in RCC tissue [31], suggesting that they play a role in the selective recruitment of T cells into RCC tissue and, together with CCR6, in the recruitment of Tregs. In particular, an increase in CD4+/CD25high+/FOXP3+/CD45RA+ was detected. Although CD4+/CD25high+/FOXP3+/CD45RA+ are classified as naïve Tregs, they possess a potent suppressive function derived from a shared development programme with CD4+/CD25high+/FOXP3+/CD45R0+ cells [12].

We also detected that the peripheral number of NK cells, CD3/CD16+/CD161+/CD158a+, correlated with prognosis. Patients with RCC in whom CD3/CD16+/CD161+/CD158a+ ≥ 2% was expressed were found to have a longer disease-free survival. This result confirms previous studies linking low peripheral blood NK cell activity with increased cancer risk [32]. A better outcome was described in non-small cell lung carcinoma [33-35], clear-cell RCCs [36] and colorectal cancer [37] with NK tumour infiltration [38]. In metastatic melanoma a significant decrease in NK activity and NK-cell IFN-γ production, with reduced expression of activating receptors (CD161 and NKG2D), and increased expression of CD158a NK-cell expression (inhibiting NK receptors), was reported [39]. It was recently reported that VHL mutational status affects the NK effector function. The mutated VHL, frequently detected in clear-cell RCC [40], increased the NK cell-mediated lysis of RCC cells [41]. To this end, the VHL mutational status was evaluated in 39 out of 77 patients. The frequency of VHL mutation was lower than generally reported in the literature (10/39; ∼40%), which is probably attributable to the limited number of patients. In addition, we were not able to detect a significant correlation between VHL mutational status, NK cells and or Tregs and prognosis, although there was a trend suggesting that a higher percentage of NK CD3/CD16+/CD161+/CD158a+ cells was detected in patients with the VHL mutation. Although the inflammatory cytokines detected in the plasma of patients with RCC were associated with a poor prognosis, the primary cell type involved in producing cytokines and their biological significance remain unknown. Inflammation is associated with oxidative stress, upregulation of hypoxia inducible factor 1-α, and production of pro-inflammatory gene products. IL-6 and IL-8 are secreted solely from RCC cells exposed to hypoxia and enhanced levels of IL-6 and IL-8 result in RCC cell invasion [24]. Hypoxia promotes neutrophil survival by inhibiting apoptosis, increases neutrophil tumour infiltration through the secretion of hypoxia-induced chemokines CXCL12, CXCL1, MIF and VEGF [42]. Increased expression of VEGF is associated with increased angiogenesis and is prognostic of overall survival in RCC [43, 44]. In the selected population, higher levels of IL-4, IL-6, IL-8, IL-10, G-CSF, CXCL10, CXCL11, HGF and VEGF were reported in affected patients compared with healthy controls; the concomitant analysis of the serum factors using IPA recognized molecules belonging to a network associated with cellular movement, tissue development and cellular growth and proliferation. This evidence strengthens the biological role of serum factors significantly different in patients with RCC. The network also identifies NF-kB in the development, progression and metastasis of RCC [45]. Thus, IPA indicated that six molecules are involved in cancer and inflammatory response and that EGF, HGF, IL-6, IL-8 and VEGF are implicated in renal and urological disorders and CXCL10, EGF, HGF and IL-6 in the proliferation of renal cells. Thus, although the single finding of naïve Tregs and/or induced [26], NK cells [41] and cytokines [24, 31, 44, 46] has been previously described in RCC, to the best of our knowledge, this is the first report of a combined prognostic profile derived from peripheral blood considering cellular and serum factors. The study may provide a better understanding of host–tumour interactions and define the patient subgroups most likely to benefit from immunotherapy. Thus the easy, accessible concomitant evaluation of Tregs (CD4+/CD25high+/FOXP3+, CD4+/CD25high+/FOXP3+/CD45RA+), the NK population (CD3/CD16+/CD161+/CD158a+) and six soluble factors (IL-6, IL-8 ,VEGF, CXCL10, CXCL11, EGF, HGF) might be a surrogate marker of host immunity in patients with RCC.

Conflict of Interest

None declared.