- Research
- Open Access
Predictors of circulating INTERLEUKIN-6 levels in head and neck cancer patients
Received: 9 March 2018
Accepted: 1 May 2018
Published: 28 May 2018
Abstract
Background
Circulating interleukin-6 (IL-6) improves outcome prediction for second primary cancer (SPC) in head and neck cancer (HNC) patients. This study aimed to identify factors associated with IL-6 serum levels in HNC patients.
Methods
This study was conducted as part of a phase III chemoprevention trial. IL-6 was measured using chemiluminescent immunometric assay on pretreatment serum sample obtained from 527 stage I-II HNC patients. Patients’ lifestyle habits, sociodemographic, medical and tumor characteristics were evaluated before radiation therapy (RT). Factors independently associated with IL-6 levels before RT were identified using multiple linear regression.
Results
The median IL-6 serum level was 3.1 ng/L. In the multivariate analysis, eight factors were significantly associated (p < 0.05) with IL-6: age, gender, marital status, body mass index, tobacco consumption, comorbidities, Karnofsky Performance Status and HNC site. Smoking duration and lifetime pack-years were positively associated with IL-6 serum levels in a dose-response relationship (p-value for trend ≤0.03).
Conclusions
Circulating IL-6 is a strong predictor of the occurrence of SPC in HNC patients. We identified eight factors independently associated with serum IL-6 levels in 527 stage I-II HNC patients.
The dose-response relationship between lifetime smoking and IL-6 serum levels suggested a causal role of tobacco exposure on IL-6 production. Further studies are needed to establish whether the effect of tobacco exposure on SPC could be partly mediated by IL-6, a pro-inflammatory cytokine.
Keywords
- Head and neck cancer
- Interleukin-6
- Tobacco use
- Alcohol consumption
Background
Head and neck cancers (HNC) are the seventh most common cancer worldwide with an annual incidence of 15 per 100,000 [1]. Due to modern surgery and radiation therapy, locoregional control of early-stage HNC has improved to reach 50 to 95% at 5 years depending on the cancer site [2]. In particular, early-stage glottic cancer has an excellent prognosis with cause-specific survival varying between 88 and 97% at 5 years [3]. However, patients with a history of HNC are at high risk for developing second primary cancers (SPC) [4] as, within 5 years, about 20% will be diagnosed with one or more multiple primary cancers, which strongly compromises their survival.
Interleukin-6 (IL-6) is a pro-inflammatory cytokine that has been described as being involved in many tumorigenesis processes [5], particularly angiogenesis [6, 7], tumor cell migration and invasion [8] and cell growth and proliferation [9, 10]. In a recent cohort study conducted among 6545 middle-aged adults, IL-6 serum level was able to predict all-causes and cancer-related mortalities over a period of 17 years [11]. In addition, when the three promising inflammatory biomarkers (α1-acid glycoprotein, C-reactive protein and IL-6) were considered together, IL-6 was the only one that remained associated with mortality by cancer. Strong evidence from a meta-analysis also showed that higher IL-6 serum levels were associated with poor prognosis in non-small cell lung cancer patients [12]. In HNC, IL-6 was identified as a predictor of recurrence and overall survival in a cohort of 444 HNC patients, most of whom had pharyngeal and advanced cancers [13]. We also reported that higher pre-treatment IL-6 serum levels were significantly associated with the occurrence of SPC [14] and death by SPC in 527 early-stage HNC patients.
Heavy smoking and alcohol consumption are standard risk factors for HNC [15]. In addition, smoking status affects SPC risk and site [16]. Associations between IL-6 serum levels and both tobacco and alcohol consumption have been described in various populations [17, 18]. A cross-sectional study conducted on 444 HNC patients at the time of their diagnosis suggested that only two health behaviors (smoking and decreased sleep) were independently associated with IL-6 serum levels [19]. As IL-6 appears to be a valid predictor in cancer prognosis, it would be useful to further examine the effects of cumulative past exposure to various health behaviors on IL-6 serum levels. The objective of this study was to identify the predictors of IL-6 serum levels in HNC patients. In addition, we specifically examined the influence of long-term tobacco and alcohol consumption on IL-6 serum levels.
Methods
Study population
This study was conducted as part of a randomized controlled chemoprevention trial (NCT00169845) [20] evaluating the efficacy of α-tocopherol and β-carotene supplementation in reducing the incidence of SPC. The ethics review board of the five radiotherapy centers participating in the trial approved the protocol. All patients gave their written informed consent prior to randomization.
Eligible patients were aged 18 years and over, had received a first diagnosis of stage I or II squamous cell carcinoma of the head and neck area (tongue, gums or mouth, oropharynx, hypopharynx and larynx) and were treated by radiation therapy (RT) between October 1, 1994 and June 6, 2000 in one of five radiotherapy centers in the province of Quebec, Canada. A total of 527 patients among the 540 HNC randomized patients (97.6%) with available pretreatment serum samples were included in the analyses.
Baseline data collection
All the baseline data were collected before the patients were randomized in the trial and before they started their RT. Trained research nurses administered a structured general questionnaire to evaluate patients’ characteristics, including their demographic and socioeconomic data, Karnofsky Performance Status (KPS) [21] and medical history. The Charlson Comorbidity Index, a comorbidity score, was calculated based on the medical history [22]. Sleep disturbance was assessed using the item 11 of the EORTC QLQ-C30 instrument [23]. The study nurses weighed and measured the patients during the visit and asked patients about their weight at 20 years of age. Current body mass index (BMI) and BMI at 20 years of age were calculated.
A validated food frequency questionnaire [24] assessing dietary intake over the year preceding randomization was used to evaluate the self-reported consumption of beer, wine, aperitifs and spirits. A standard drink was pre-defined for beverages (beer: 1 bottle; wine: 4 oz; aperitif: 2 oz; spirits: 1 oz) and 10 profiles of consumption were proposed (number of drinks per day, week or month). Average daily intake of alcohol (g per day) was then calculated. The same method was used to assess the average daily intake of alcohol over the past 10 years. In addition, a question assessed whether patients had a history of alcohol abuse.
Lifetime smoking habits were recorded for all tobacco products (cigarette, cigar, pipe, chewing) using a structured questionnaire. For all products and for all smoking periods, we assessed the mean consumption per day, week or month and the duration. In addition, age at first cigarette, time since quitting cigarette smoking and patients’ current cigarette smoking status were recorded. The number of pack-years, the duration and intensity of cigarette smoking as well as the number of years since quitting cigarette smoking were calculated.
The radiation oncologists provided detailed information on the primary tumor: precise site, dimensions and clinical stage according to the TNM classification [25].
IL-6 measurement
Baseline serum samples were obtained at the time of randomisation before any trial intervention and before RT. Samples were kept frozen at − 80 °C and then thawed shortly before determination of IL-6 levels. In order to avoid any influence of the trial intervention, IL-6 was measured on baseline samples using an IMMULITE®1000 immunoassay analyzer with chemiluminescent immunometric assay (Siemens Healthcare Diagnostics).
Statistics
IL-6 serum level was the outcome and was treated as a continuous variable. Given the skewed distribution of IL-6, IL-6 was log transformed (natural log) for all analyses. The selected sociodemographic factors were sex, age (≤ 50, 51–60, 61–70 and > 70), marital status (not married vs. married) and household income (< $40,000 vs. ≥ $40,000). Clinical variables considered were KPS (60–80 vs. ≥ 90), Charlson Comorbidity Index (0, 1, ≥ 2), diabetes (yes vs. no), cancer site (glottis vs. other) and TNM stage (stage I vs. II). The selected health behavior variables were BMI, past and current tobacco and alcohol consumption. Current BMI and BMI at 20 years of age were classified according to the WHO categories (< 18.5: underweight; ≥ 18.5 to < 30: normal weight and overweight; ≥ 30: obesity) [26]. History of cigarette smoking was considered using variables measuring the duration of cigarette smoking, the average number of cigarettes smoked and the average number of pack-years consumed. These variables were categorized according to the quartiles in those exposed to cigarette smoking. Alcohol consumption during the preceding year (g/day in quartiles), alcohol consumption in the past 10 years (g/day in quartiles) as well as a history of alcohol abuse (yes vs. no) were considered.
Student t-test or analysis of variance were performed to examine all the associations between IL-6 serum levels and the selected factors. All the variables associated with IL-6 serum levels in the bivariate analyses (P ≤ 0.20) were considered for inclusion in a multivariate linear regression model. The final model was constructed using a backward elimination procedure. Before fitting the final model, tests for collinearity among the variables were done. The regression diagnostics methods used on the final model showed the appropriateness of the regression assumptions (linearity, variance homogeneity, Gaussian distribution of the residuals). A non-parametric bootstrap resampling method was performed on the residuals to assess the reliability of the regression model [27]. The bootstrap validation process began by forming 2000 bootstrap samples of equal size (n = 527) with replacement. Each bootstrap sample was used as a training sample. Regression coefficients were estimated by the bootstrapping method and their 95% confidence intervals were calculated using the method of bias-corrected accelerated percentile intervals.
For all variables describing lifetime cigarette smoking, the associations with IL-6 were tested using a multivariate linear regression adjusting for all factors retained in the final model. Tests for linear trend were done to verify whether IL-6 serum levels tended to increase with cumulative past exposure to cigarette consumption. For trend tests, exposures were considered as linear for ordered categorical variables.
All statistical analyses were performed using SAS (version 9.4; SAS Institute Inc.) and R (version 3.4.0; R development Core Team) statistical software. All statistical tests were 2-sided (α = 0.05).
Results
Sociodemographic, clinical and health behavior characteristics of patients with head and neck cancer (N = 527)
Factors | Categories | N (%) |
|---|---|---|
Age (years) | ≤ 50 | 55 (10.4) |
> 50 ≤ 60 | 155 (29.4) | |
> 60 ≤ 70 | 197 (37.4) | |
> 70 | 120 (22.8) | |
Sex | Female | 112 (21.3) |
Male | 415 (78.8) | |
Current body mass index (kg/m2) | < 18.5 | 18 (3.4) |
≥ 18.5 < 30 | 415 (78.8) | |
≥ 30 | 94 (17.8) | |
Body mass index at 20 years (kg/m2) | < 18.5 | 47 (8.9) |
≥ 18.5 < 30 | 462 (87.7) | |
≥ 30 | 18 (3.4) | |
Marital status | Not married | 137 (26.0) |
Married | 390 (74.0) | |
Household income (per year) | < $40,000 | 388 (73.6) |
≥ $40,000 | 139 (26.4) | |
Karnofsky Performance Status (%) | 90–100 | 485 (92.0) |
60–80 | 42 (8.0) | |
Charlson Comorbidity Index | 0 | 323 (61.3) |
1 | 128 (24.3) | |
≥ 2 | 76 (14.4) | |
Diabetes | No | 488 (92.6) |
Yes | 39 (7.4) | |
Glottic cancer | No | 187 (35.5) |
Yes | 340 (64.5) | |
TNM clinical stage | I | 325 (61.7) |
II | 202 (38.3) | |
Tobacco consumption (all tobacco products) | Never | 26 (4.9) |
Former | 372 (70.6) | |
Current | 129 (24.5) | |
History of alcohol abuse | No | 439 (83.3) |
Yes | 88 (16.7) | |
Sleep disturbance | Not at all | 285 (54.1) |
A little | 132 (25.0) | |
Quite a bit | 62 (11.8) | |
Very much | 48 (9.1) |
Associations between selected factors and IL-6 serum levels (N = 527)
Factors | Categories | Median IL-6 (ng/L) (IQR) | Crude β (SE) | P-value |
|---|---|---|---|---|
Age (years) | ≤ 50 | 2.4 (1.0–3.7) | Reference | |
> 50 ≤ 60 | 2.9 (2.0–3.9) | 0.15 (0.11) | ||
> 60 ≤ 70 | 3.2 (2.4–4.4) | 0.34 (0.11) | ||
> 70 | 3.5 (2.6–5.1) | 0.48 (0.11) | < 0.0001 | |
Sex | Female | 3.0 (2.2–3.9) | Reference | |
Male | 3.1 (2.2–4.6) | 0.15 (0.07) | 0.04 | |
Current body mass index (kg/m2) | < 18.5 | 3.5 (2.5–5.1) | 0.13 (0.17) | |
≥ 18.5 < 30 | 2.9 (2.1–4.1) | Reference | ||
≥ 30 | 3.8 (2.7–4.9) | 0.22 (0.08) | 0.02 | |
Body mass index at 20 years (kg/m2) | < 18.5 | 3.0 (2.0–4.9) | −0.06 (0.11) | |
≥ 18.5 < 30 | 3.1 (2.2–4.4) | Reference | ||
≥ 30 | 4.1 (2.7–7.0) | 0.43 (0.17) | 0.04 | |
Marital status | Not married | 3.3 (2.5–4.6) | Reference | |
Married | 3.0 (2.1–4.4) | −0.16 (0.07) | 0.02 | |
Household income (per year) | < $40,000 | 3.3 (2.3–4.6) | Reference | |
≥ $40,000 | 2.7 (2.0–3.7) | −0.22 (0.07) | 0.02 | |
Karnofsky Performance Status (%) | 90–100 | 3.0 (2.2–4.3) | Reference | |
60–80 | 4.9 (2.9–5.8) | 0.46 (0.11) | < 0.0001 | |
Charlson Comorbidity Index | 0 | 2.9 (2.1–3.9) | Reference | |
1 | 3.4 (2.1–5.1) | 0.24 (0.07) | ||
≥ 2 | 3.7 (2.8–5.2) | 0.38 (0.09) | < 0.0001 | |
Diabetes | No | 3.0 (2.2–4.4) | Reference | |
Yes | 3.6 (2.8–5.0) | 0.22 (0.12) | 0.06 | |
Glottic cancer | No | 3.5 (2.5–5.0) | Reference | |
Yes | 2.9 (2.1–4.1) | −0.22 (0.06) | 0.0004 | |
TNM clinical stage | I | 2.9 (2.1–4.2) | Reference | |
II | 3.4 (2.4–4.9) | 0.17 (0.06) | 0.007 | |
Tobacco consumption (all tobacco products) | Never | 2.2 (1.0–3.3) | Reference | |
Former | 3.0 (2.2–4.4) | 0.48 (0.14) | ||
Current | 3.5 (2.4–5.1) | 0.57 (0.15) | 0.0008 | |
History of alcohol abuse | No | 3.0 (2.2–4.3) | Reference | |
Yes | 3.6 (2.5–5.3) | 0.18 (0.08) | 0.03 | |
Alcohol consumption during the preceding year (g/d) | 0 | 3.4 (2.3–4.6) | Reference | |
≤ 2.32 | 3.0 (2.1–4.3) | −0.03 (0.09) | 0.31 | |
> 2.32 ≤ 12.48 | 2.9 (2.2–4.2) | −0.13 (0.09) | ||
> 12.48 | 3.1 (2.4–5.0) | 0.02 (0.09) | ||
Alcohol consumption during the past 10 years (g/d) | ≤ 0.39 | 3.3 (2.1–4.3) | Reference | |
> 0.39 ≤ 10.49 | 3.1 (2.2–4.4) | −0.05 (0.09) | ||
> 10.49 ≤ 42.88 | 2.8 (2.1–4.1) | −0.08 (0.09) | ||
> 42.88 | 3.3 (2.5–5.1) | 0.04 (0.09) | 0.50 | |
Sleep disturbance | Not at all | 3.0 (2.1–4.4) | Reference | |
A little | 3.0 (2.2–4.0) | −0.004 (0.07) | ||
Quite a bit | 3.5 (2.5–4.9) | 0.16 (0.10) | ||
Very much | 3.1 (2.5–5.0) | 0.17 (0.11) | 0.20 |
Factors independently associated with IL-6 serum levels in the multivariate linear regression and in the bootstrapping regression model (N = 527)
Factors | Categories | Multivariate linear regression | Bootstrapping regression model | ||||
|---|---|---|---|---|---|---|---|
β (SE) | 95% CI | P-value | β (SE) | 95% CI | P-value | ||
Age (years) | Continuous | 0.01 (0.003) | 0.01; 0.02 | < 0.0001 | 0.01 (0.003) | 0.01; 0.02 | < 0.0001 |
Sex | Female | Reference | Reference | ||||
Male | 0.26 (0.07) | 0.12; 0.41 | 0.0005 | 0.26 (0.07) | 0.12; 0.40 | 0.0005 | |
Current body mass index (kg/m2) | < 18.5 | 0.08 (0.16) | −0.23; 0.38 | 0.63 | 0.07 (0.14) | −0.21; 0.38 | 0.63 |
≥ 18.5 < 30 | Reference | Reference | |||||
≥ 30 | 0.27 (0.07) | 0.12; 0.41 | 0.0003 | 0.27 (0.07) | 0.14; 0.40 | 0.0003 | |
Marital status | Not married | Reference | Reference | ||||
Married | - 0.16 (0.07) | −0.29; −0.03 | 0.02 | −0.16 (0.07) | −0.29; − 0.02 | 0.02 | |
Karnofsky Performance Status (%) | 90–100 | Reference | Reference | ||||
60–80 | 0.38 (0.11) | 0.17; 0.58 | 0.0004 | 0.37 (0.12) | 0.16; 0.64 | 0.0004 | |
Charlson Comorbidity Index | 0 | Reference | Reference | ||||
1 | 0.15 (0.07) | 0.01; 0.28 | 0.03 | 0.15 (0.08) | 0.01; 0.31 | 0.03 | |
≥ 2 | 0.23 (0.08) | 0.07; 0.40 | 0.006 | 0.23 (0.07) | 0.10; 0.39 | 0.006 | |
Glottic cancer | No | Reference | Reference | ||||
Yes | −0.28 (0.06) | −0.40; −0.16 | < 0.0001 | − 0.28 (0.06) | − 0.41; − 0.16 | < 0.0001 | |
Tobacco consumption (all tobacco products) | Never | Reference | Reference | ||||
Former | 0.43 (0.13) | 0.17; 0.69 | 0.001 | 0.43 (0.11) | 0.21; 0.63 | 0.001 | |
Current | 0.51 (0.14) | 0.23; 0.79 | 0.0004 | 0.51 (0.12) | 0.26; 0.74 | 0.0004 | |
Multivariate analyses showing lifetime cigarette consumption variables associated with IL-6 serum levels (N = 527)
Factors | Categories | N (%) | Median IL–6 (ng/L) (IQR) | Adjusted β* (SE) | P-value |
|---|---|---|---|---|---|
Duration of cigarette smoking (years) | Never smokers | 30 (5.7) | 2.2 (1.0–3.3) | Reference | |
Ever smokers | |||||
< 32 | 120 (22.8) | 2.6 (1.5–3.7) | 0.36 (0.13) | 0.008 | |
≥ 32 < 40 | 116 (22.0) | 3.0 (2.2–4.6) | 0.48 (0.13) | 0.0004 | |
≥ 40 < 47 | 131 (24.9) | 3.3 (2.5–4.3) | 0.50 (0.13) | 0.0001 | |
≥ 47 | 130 (24.7) | 3.7 (2.7–5.4) | 0.57 (0.13) | < 0.0001 | |
P-trend < 0.0001 | |||||
P-trend 0.03 (excluding never smokers) | |||||
Average number of cigarettes per day | Never smokers | 30 (5.7) | 2.2 (1.0–3.3) | Reference | |
Ever smokers | |||||
< 20 | 119 (22.6) | 2.9 (2.2–4.3) | 0.40 (0.13) | 0.003 | |
≥ 20 < 25 | 70 (13.3) | 3.0 (2.1–4.3) | 0.52 (0.14) | 0.0003 | |
≥ 25 < 30 | 167 (31.7) | 3.3 (2.4–4.6) | 0.54 (0.13) | < 0.0001 | |
≥ 30 | 141 (26.8) | 3.2 (2.3–4.9) | 0.49 (0.13) | 0.0002 | |
P-trend 0.003 | |||||
P-trend 0.25 (excluding never smokers) | |||||
Pack-years of cigarettes | Never smokers | 30 (5.7) | 2.2 (1.0–3.3) | Reference | |
Ever smokers | |||||
< 32 | 123 (23.3) | 2.7 (2.0–4.0) | 0.35 (0.13) | 0.008 | |
≥ 32 < 47 | 125 (23.7) | 3.0 (2.3–4.3) | 0.52 (0.13) | < 0.0001 | |
≥ 47 < 67 | 123 (23.3) | 3.3 (2.4–4.7) | 0.55 (0.13) | < 0.0001 | |
≥ 67 | 126 (23.9) | 3.5 (2.5–5.2) | 0.52 (0.13) | < 0.0001 | |
P-trend 0.0002 | |||||
P-trend 0.03 (excluding never smokers) | |||||
Years since cigarette smoking cessation | ≥ 10 | 107 (20.3) | 2.8 (2.0–4.3) | Reference | |
≥ 1 < 10 | 60 (11.4) | 3.2 (2.4–4.9) | 0.21 (0.08) | 0.010 | |
< 1 | 201 (38.1) | 3.0 (2.3–4.4) | 0.20 (0.11) | 0.060 | |
P-trend 0.02 | |||||
Discussion
This study showed that eight factors were independently associated with circulating IL-6, a marker of HNC patients’ prognosis. IL-6 serum levels were higher with increasing age, in males, in unmarried patients, in patients with lower KPS or higher Charlson Comorbidity Indexes, and in those with HNC at a site other than the glottis. Two health behavior factors, obesity and smoking status, were independently associated with IL-6. In addition, we showed that lifetime cigarette consumption was a strong predictor of pro-inflammatory IL-6 serum levels in HNC patients with a dose-response relationship.
This cross-sectional study, based on baseline data collected at the time of randomization in a clinical trial, has several strengths and limitations. Our study population was derived from a representative population of patients with stage I and II HNC treated by radiation therapy, since 85% of the eligible HNC patients agreed to participate in this multicenter trial conducted in the province of Quebec. Only 2.4% of the participants were not included in these analyses because no serum samples were available. The bootstrapping method used for validation of the model identifying eight independent factors showed that the model was reliable in predicting circulating IL-6. To corroborate our findings, we also examined the relationships between IL-6 and long-term alcohol and tobacco exposure. To our knowledge, this is the first study conducted on HNC patients that has examined the associations between long-term exposure to alcohol and tobacco and IL-6. In cross-sectional studies, associations with lifetime exposure could be affected to some extent by patients’ ability to recall their past exposure. This potential source of bias was probably minimized in our study, since past exposure was assessed independently of the patients’ IL-6 status using a well-structured interview conducted by trained research nurses. In addition, the associations with long-term exposure to tobacco or alcohol corroborated well with those found with their respective current exposure.
High IL-6 serum levels have consistently been reported with advancing age [28] and, to a lesser extent, in middle-aged subjects selected from general populations [29, 30]. IL-6 serum levels might reflect a dysregulation of the immune system in older people but could also act as a disease marker. Ferrucci et al. [30] reported that IL-6 serum levels increased linearly with age in 367 men and 731 women aged 20–102 years from a general population. However, when cardiovascular disease, cancers and other conditions were taken into account, the magnitude of the association between age and circulating IL-6 decreased substantially but remained statistically significant in men. A recent study conducted among 987 healthy and non-obese subjects aged 20 to 80 showed that after adjusting for sex, BMI, tobacco and alcohol status, IL-6 levels in both serum and peripheral blood mononuclear cells were higher only in subjects aged 65 to 80 [31]. In our HNC population that consisted mostly of middle-aged and older people as well as in Duffy et al.’s HNC study population [19], age remained positively associated with IL-6 serum levels after adjustment for comorbidities and several risk factors, suggesting a true association with age. However, residual confounding could have occurred in these studies, since part of the age association with IL-6 in HNC patients could be due to the presence of occult second primary cancer at the time of HNC diagnosis, a condition associated with increased IL-6 serum levels [14].
Recent studies, using Mendelian randomization analyses, conducted among thousands of people, have established a causal relationship between genetic markers of adiposity and circulating IL-6 levels [32–34]. The BMI-genetic scores were consistently and positively associated with IL-6, but the associations were attenuated in younger subjects and in men [32]. Among HNC patients, we also found a positive association between IL-6 and obesity, as defined by a BMI ≥ 30 kg/m2. Adipose tissue contains multiple types of cells, including adipocytes, macrophages and immune active cells, all metabolically active in producing IL-6, especially in the context of obesity [35, 36]. Studies have suggested that IL-6 could be released differentially according to body fat distribution patterns [37]. Adipose tissue biopsies done in 47 healthy overweight or obese subjects showed that pro-inflammatory T-helper (Th)-1, Th17 and CD8 T-cells were significantly more frequent in visceral adipose tissue (VAT) than in subcutaneous adipose tissue (SAT) [38]. Concurrently, IL-6 expression, a marker of Th1 and M1 macrophage activation, was twofold greater in VAT than in SAT. In 97 subjects aged 22–69, randomly selected from the general population, VAT and SAT were quantified using a two-dimensional ultrasound image [39]. IL-6 serum levels were positively associated with VAT in overweight/obese participants, while there was no association with SAT. This differential expression of IL-6 according to the VAT and SAT compartments might partly explain the discordance between studies of the effect of sex on circulating IL-6 [29, 30, 40]. Large studies conducted in general populations in the United States showed that, compared with women, men have a higher volume of VAT [41] and a lower volume of SAT [42].
In our study population of early-stage HNC, site was a stronger predictor of IL-6 serum levels than TNM stage. This is explained well by other studies. Elevated serum levels of IL-6 are consistently observed among patients with advanced-stage HNC, in particular in those with positive lymph nodes [19, 43]. In patients with early-stage (T1-T2, N0, M0) laryngeal cancer, those with glottic cancer have significantly lower IL-6 serum levels compared with those with supraglottic cancer, while there was no difference between laryngeal subsites in advanced stages [44]. In our study, 50% of the patients had stage I glottic cancer, which is an infiltrating tumor limited to the vocal cords and frequently no more than a few millimeters in size. Using high throughput technologies, several gene signatures and protein networks have been identified in HNC [45]. The IL-6/IL-6R/JAK/STAT3 is one of these pathways, which contributes to the development and progression of HNC cancers [45, 46]. The IL-6 gene is also a target of nuclear factor–kappa B (NF-kB) [45, 47]. NF-kB inhibition downregulates IL-6 gene and protein expression and decreases the release of several cytokines. In addition, there is a cross-talk between NF-kB and STAT3 signaling pathways in HNC cell lines. Experimental studies are currently being conducted to identify selective inhibitors of IL-6 induced STAT3 in the treatment of HNC [46, 48, 49].
Human Papilloma Virus (HPV) infection is recognized to be a risk factor for specific HNC sites, in particular for oropharyngeal cancer [50]. In our cohort of early HNC, most of the patients had laryngeal cancer (83.0%), while 11.7% had oral cancer and only 3.2% had oropharyngeal cancer. A large international study using 3680 samples, estimated that the prevalence of HPV-DNA, targeting 25 HPV types, was only 5.7% in laryngeal cancer, which represents the majority of our study population [51]. For oral cavity cancer, the HPV-DNA prevalence was 7.4%, while for oropharyngeal cancers, the prevalence increased over calendar time. During the time-period 1995–1999, corresponding to the recruitment of the majority of our HNC cohort, HPV-DNA prevalence was 10.1%. We could reasonably conclude that a small number of patients in our cohort were HPV-positive. In HNC, few studies have evaluated the association between HPV infection and circulating IL-6. These studies, conducted among small series of HNC patients, gave conflicting results. Guerrera et al. [52] found that IL-6 serum levels were significantly higher among HPV-negative patients compared to HPV-positive patients, while Argiris et al. [53] reported no difference in serum IL-6 levels between HPV-positive and negative patients.
In our study, married patients showed lower IL-6 levels compared to non-married patients. It is doubtful that this relationship could be attributable to HPV infection since the opposite would be expected, according to the findings of Guerrera et al. [52]. One plausible explanation is that married people have better dietary and other health behaviours associated with lower levels of circulating cytokines [54]. Overall, these data suggest that HPV status probably had little impact on IL-6 status in this HNC cohort.
Modifiable health behaviors have been reported to influence systemic IL-6 levels [17–19]. Some authors have hypothesized that IL-6 levels might differ according to sex because of different health behaviors [29]. Large studies conducted in general populations have consistently reported a U- or J-shaped association between alcohol intake and IL-6 serum levels with a nadir for moderate consumption (1–2 drinks per day) [55–58]. In particular, a recent prospective cohort study conducted among 8209 British civil servants showed that moderate drinkers (8 to 168 g of ethanol per week for men and 8 to 112 g for women) stable over a period of 10 years had lower serum levels of IL-6 compared with stable non-drinkers and stable heavy drinkers [55]. Current and past alcohol consumption were not predictors of IL-6 serum levels in our study, but most of the patients had low and moderate alcohol consumption. As reported by Duffy et al. [19], we found that only patients with a history of alcohol abuse had higher IL-6 serum levels, but this association was no longer statistically significant after adjustment for other covariates, including tobacco.
Activated monocytes/macrophages [59–61] and epithelial cells [62] have been described as producing pro-inflammatory cytokines, including IL-6. These cell types can be activated by carcinogens found in tobacco products [63, 64]. In a mouse model, cigarette smoke has been shown to upregulate IL-6, leading to the differentiation of T-helper cells in IL-17-producing T-cells [65]. In addition, tobacco-induced oxidative stress also activates the NF-kB family of transcription factors, which upregulates the expression of pro-inflammatory cytokines [66, 67]. In our study, current smoking status was a health behavior independently associated with IL-6 serum levels. This corroborates well with the findings of the only cross-sectional study previously conducted on HNC patients [19] as well as with studies conducted on healthy people [68]. In addition, our study showed that cumulative exposure to cigarette smoking was significantly associated in a dose-dependent manner with IL-6 serum levels. This supports a causality link between smoking and IL-6 status in HNC patients. Due to the impact of tobacco on IL-6 serum levels found in this HNC population and our previous findings showing that IL-6 serum level was a strong predictor of SPC in HNC patients [14], further analyses will be conducted to examine whether the association between tobacco and SPC is partly mediated by IL-6. This will contribute to a better understanding of the role of inflammation in the occurrence of cancer.
Declarations
Funding
This study was supported by grants from the Canadian Cancer Society Research Institute. The funding body did not take part in the design of the study and collection, analysis, and interpretation of data or in writing the manuscript.
Availability of data and materials
The datasets generated and analyzed during the current study are not publicly available due to ethical reasons. Data are however available from the authors upon reasonable request and with permission of the ethical board of the CHU de Québec – Université Laval.
Authors’ contributions
All authors have read and approved the submitted manuscript. The manuscript is not under consideration elsewhere nor published elsewhere in whole or in part. All authors participated in the conception, design and development of methodology of this study. They also participated in the acquisition, analysis and interpretation of the data and in the writing and revision of the manuscript.
IB and FM, MDs and cancer epidemiologists, were the principal investigators of the study, which was supported by the Canadian Cancer Society Research Institute. Serum IL-6 dosages were done under the supervision of PD, MD (Biochemistry). ST, MSc (Biostatistics), conducted the statistical analyses under the principal investigators’ supervision. SCC, PhD, also performed statistical analyses, data interpretation and was in charge of writing the manuscript.
Ethics approval and consent to participate
The ethics review board of the five radiotherapy centers participating in the trial approved the protocol [20]. All patients gave their written informed consent prior to randomization.
Competing interests
The authors declare that they have no competing interests.
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Authors’ Affiliations
References
- Howlader N NA, Krapcho M, Miller D, Bishop K, Altekruse SF, Kosary CL, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA (eds). : SEER Cancer Statistics Review, 1975–2013, National Cancer Institute.. In., Based on November 2015 SEER data submission, posted to the SEER web site. edn. Bethesda, MD, http://seer.cancer.gov/csr/1975_2013/; April 2016.
- Bernier J. 1950- éditeur intellectuel SpringerLink (service en ligne): head and neck cancer : multimodality management. Switzerland: Springer; 2016.Google Scholar
- Halperin ECP, Carlos A, 1934- Ovid Technologies, Inc. Perez and Brady's principles and practice of radiation oncology. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins; 2013.Google Scholar
- Morris LG, Sikora AG, Hayes RB, Patel SG, Ganly I. Anatomic sites at elevated risk of second primary cancer after an index head and neck cancer. Cancer Causes Control. 2011;22(5):671–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Kumari N, Dwarakanath BS, Das A, Bhatt AN. Role of interleukin-6 in cancer progression and therapeutic resistance. Tumour Biol. 2016;Google Scholar
- Nilsson MB, Langley RR, Fidler IJ. Interleukin-6, secreted by human ovarian carcinoma cells, is a potent proangiogenic cytokine. Cancer Res. 2005;65(23):10794–800.View ArticlePubMedPubMed CentralGoogle Scholar
- Gopinathan G, Milagre C, Pearce OM, Reynolds LE, Hodivala-Dilke K, Leinster DA, Zhong H, Hollingsworth RE, Thompson R, Whiteford JR, et al. Interleukin-6 stimulates defective angiogenesis. Cancer Res. 2015;75(15):3098–107.View ArticlePubMedPubMed CentralGoogle Scholar
- Sun W, Liu DB, Li WW, Zhang LL, Long GX, Wang JF, Mei Q, Hu GQ. Interleukin-6 promotes the migration and invasion of nasopharyngeal carcinoma cell lines and upregulates the expression of MMP-2 and MMP-9. Int J Oncol. 2014;44(5):1551–60.View ArticlePubMedGoogle Scholar
- Calo V, Migliavacca M, Bazan V, Macaluso M, Buscemi M, Gebbia N, Russo A. STAT proteins: from normal control of cellular events to tumorigenesis. J Cell Physiol. 2003;197(2):157–68.View ArticlePubMedGoogle Scholar
- Wei LH, Kuo ML, Chen CA, Chou CH, Lai KB, Lee CN, Hsieh CY. Interleukin-6 promotes cervical tumor growth by VEGF-dependent angiogenesis via a STAT3 pathway. Oncogene. 2003;22(10):1517–27.View ArticlePubMedGoogle Scholar
- Singh-Manoux A, Shipley MJ, Bell JA, Canonico M, Elbaz A, Kivimaki M. Association between inflammatory biomarkers and all-cause, cardiovascular and cancer-related mortality. CMAJ. 2017;189(10):E384–90.View ArticlePubMedPubMed CentralGoogle Scholar
- Liao C, Yu Z, Guo W, Liu Q, Wu Y, Li Y, Bai L. Prognostic value of circulating inflammatory factors in non-small cell lung cancer: a systematic review and meta-analysis. Cancer Biomark. 2014;14(6):469–81.View ArticlePubMedGoogle Scholar
- Duffy SA, Taylor JM, Terrell JE, Islam M, Li Y, Fowler KE, Wolf GT, Teknos TN. Interleukin-6 predicts recurrence and survival among head and neck cancer patients. Cancer. 2008;113(4):750–7.View ArticlePubMedGoogle Scholar
- Meyer F, Samson E, Douville P, Duchesne T, Liu G, Bairati I. Serum prognostic markers in head and neck cancer. Clin Cancer Res. 2010;16(3):1008–15.View ArticlePubMedGoogle Scholar
- Maasland DH, van den Brandt PA, Kremer B, Goldbohm RA, Schouten LJ. Alcohol consumption, cigarette smoking and the risk of subtypes of head-neck cancer: results from the Netherlands cohort study. BMC Cancer. 2014;14:187.View ArticlePubMedPubMed CentralGoogle Scholar
- Gan SJ, Dahlstrom KR, Peck BW, Caywood W, Li G, Wei Q, Zafereo ME, Sturgis EM. Incidence and pattern of second primary malignancies in patients with index oropharyngeal cancers versus index nonoropharyngeal head and neck cancers. Cancer. 2013;119(14):2593–601.View ArticlePubMedPubMed CentralGoogle Scholar
- Mukamal KJ, Jenny NS, Tracy RP, Siscovick DS. Alcohol consumption, interleukin-6 and apolipoprotein E genotypes, and concentrations of interleukin-6 and serum amyloid P in older adults. Am J Clin Nutr. 2007;86(2):444–50.View ArticlePubMedPubMed CentralGoogle Scholar
- Lu B, Solomon DH, Costenbader KH, Keenan BT, Chibnik LB, Karlson EW. Alcohol consumption and markers of inflammation in women with preclinical rheumatoid arthritis. Arthritis Rheum. 2010;62(12):3554–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Duffy SA, Teknos T, Taylor JM, Fowler KE, Islam M, Wolf GT, McLean S, Ghanem TA, Terrell JE. Health behaviors predict higher interleukin-6 levels among patients newly diagnosed with head and neck squamous cell carcinoma. Can Epidemiol Biomarkers Prev. 2013;22(3):374–81.View ArticleGoogle Scholar
- Bairati I, Meyer F, Gelinas M, Fortin A, Nabid A, Brochet F, Mercier JP, Tetu B, Harel F, Masse B, et al. A randomized trial of antioxidant vitamins to prevent second primary cancers in head and neck cancer patients. J Natl Cancer Inst. 2005;97(7):481–8.View ArticlePubMedGoogle Scholar
- Schag CC, Heinrich RL, Ganz PA. Karnofsky performance status revisited: reliability, validity, and guidelines. J Clin Oncol. 1984;2(3):187–93.View ArticlePubMedGoogle Scholar
- Charlson M, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol. 1994;47(11):1245–51.View ArticlePubMedGoogle Scholar
- Aaronson NK, Ahmedzai S, Bergman B, Bullinger M, Cull A, Duez NJ, Filiberti A, Flechtner H, Fleishman SB, de Haes JC, et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst. 1993;85(5):365–76.View ArticlePubMedGoogle Scholar
- Meyer F, Bairati I, Fradet Y, Moore L. Dietary energy and nutrients in relation to preclinical prostate cancer. Nutr Cancer. 1997;29(2):120–6.View ArticlePubMedGoogle Scholar
- Cancer. AJCo: Manual for staging of cancer. 4th ed. Philadelphia: Lippincott-Raven; 1993.Google Scholar
- Body mass index - BMI [http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/a-healthy-lifestyle/body-mass-index-bmi].
- Fox J: Bootstrapping regression models: an R and S-plus companion to applied regression. 2002.Google Scholar
- Krabbe KS, Pedersen M, Bruunsgaard H. Inflammatory mediators in the elderly. Exp Gerontol. 2004;39(5):687–99.View ArticlePubMedGoogle Scholar
- Navarro SL, Kantor ED, Song X, Milne GL, Lampe JW, Kratz M, White E. Factors associated with multiple biomarkers of systemic inflammation. Cancer Epidemiol Biomarkers Prev. 2016;25(3):521–31.View ArticlePubMedPubMed CentralGoogle Scholar
- Ferrucci L, Corsi A, Lauretani F, Bandinelli S, Bartali B, Taub DD, Guralnik JM, Longo DL. The origins of age-related proinflammatory state. Blood. 2005;105(6):2294–9.View ArticlePubMedGoogle Scholar
- Lee DH, Kim M, Kim M, Lee YJ, Yoo HJ, Lee SH, Lee JH: Age-dependent alterations in serum cytokines, peripheral blood mononuclear cell cytokine production, natural killer cell activity, and prostaglandin F2alpha. Immunol Res. 2017;65(5):1009–16.Google Scholar
- Fall T, Hagg S, Ploner A, Magi R, Fischer K, Draisma HH, Sarin AP, Benyamin B, Ladenvall C, Akerlund M, et al. Age- and sex-specific causal effects of adiposity on cardiovascular risk factors. Diabetes. 2015;64(5):1841–52.View ArticlePubMedPubMed CentralGoogle Scholar
- Dale CE, Fatemifar G, Palmer TM, White J, Prieto-Merino D, Zabaneh D, Engmann JEL, Shah T, Wong A, Warren HR, et al. Causal associations of adiposity and body fat distribution with coronary heart disease, stroke subtypes, and type 2 diabetes mellitus: a Mendelian randomization analysis. Circulation. 2017;135(24):2373–88.View ArticlePubMedGoogle Scholar
- Holmes MV, Lange LA, Palmer T, Lanktree MB, North KE, Almoguera B, Buxbaum S, Chandrupatla HR, Elbers CC, Guo Y, et al. Causal effects of body mass index on cardiometabolic traits and events: a Mendelian randomization analysis. Am J Hum Genet. 2014;94(2):198–208.View ArticlePubMedPubMed CentralGoogle Scholar
- Jung UJ, Choi MS. Obesity and its metabolic complications: the role of adipokines and the relationship between obesity, inflammation, insulin resistance, dyslipidemia and nonalcoholic fatty liver disease. Int J Mol Sci. 2014;15(4):6184–223.View ArticlePubMedPubMed CentralGoogle Scholar
- Engin A. The pathogenesis of obesity-associated adipose tissue inflammation. Adv Exp Med Biol. 2017;960:221–45.View ArticlePubMedGoogle Scholar
- Fain JN. Release of inflammatory mediators by human adipose tissue is enhanced in obesity and primarily by the nonfat cells: a review. Mediat Inflamm. 2010;2010:513948.View ArticleGoogle Scholar
- McLaughlin T, Liu LF, Lamendola C, Shen L, Morton J, Rivas H, Winer D, Tolentino L, Choi O, Zhang H, et al. T-cell profile in adipose tissue is associated with insulin resistance and systemic inflammation in humans. Arterioscler Thromb Vasc Biol. 2014;34(12):2637–43.View ArticlePubMedPubMed CentralGoogle Scholar
- Schlecht I, Fischer B, Behrens G, Leitzmann MF. Relations of visceral and abdominal subcutaneous adipose tissue, body mass index, and waist circumference to serum concentrations of parameters of chronic inflammation. Obesity facts. 2016;9(3):144–57.View ArticlePubMedPubMed CentralGoogle Scholar
- Seyed-Sadjadi N, Berg J, Bilgin AA, Grant R. Visceral fat mass: is it the link between uric acid and diabetes risk? Lipids Health Dis. 2017;16(1):142.View ArticlePubMedPubMed CentralGoogle Scholar
- Bidulescu A, Liu J, Hickson DA, Hairston KG, Fox ER, Arnett DK, Sumner AE, Taylor HA, Gibbons GH. Gender differences in the association of visceral and subcutaneous adiposity with adiponectin in African Americans: the Jackson heart study. BMC Cardiovasc Disord. 2013;13:9.View ArticlePubMedPubMed CentralGoogle Scholar
- Camhi SM, Bray GA, Bouchard C, Greenway FL, Johnson WD, Newton RL, Ravussin E, Ryan DH, Smith SR, Katzmarzyk PT. The relationship of waist circumference and BMI to visceral, subcutaneous, and total body fat: sex and race differences. Obesity (Silver Spring, Md). 2011;19(2):402–8.View ArticleGoogle Scholar
- Riedel F, Zaiss I, Herzog D, Gotte K, Naim R, Hormann K. Serum levels of interleukin-6 in patients with primary head and neck squamous cell carcinoma. Anticancer Res. 2005;25(4):2761–5.PubMedGoogle Scholar
- Sotirovic J, Peric A, Vojvodic D, Baletic N, Zaletel I, Stanojevic I, Erdoglija M, Milojevic M. Serum cytokine profile of laryngeal squamous cell carcinoma patients. J Laryngol Otol. 2017;131(5):455–61.View ArticlePubMedGoogle Scholar
- Yan B, Broek RV, Saleh AD, Mehta A, Van Waes C, Chen Z. Signaling networks of activated oncogenic and altered tumor suppressor genes in head and neck Cancer. J Carcinog Mutagen. 2013;Suppl 7:4.PubMedPubMed CentralGoogle Scholar
- Sen M, Johnston PA, Pollock NI, DeGrave K, Joyce SC, Freilino ML, Hua Y, Camarco DP, Close DA, Huryn DM, et al. Mechanism of action of selective inhibitors of IL-6 induced STAT3 pathway in head and neck cancer cell lines. J Chem Biol. 2017;10(3):129–41.View ArticlePubMedPubMed CentralGoogle Scholar
- Squarize CH, Castilho RM, Sriuranpong V, Pinto DS Jr, Gutkind JS. Molecular cross-talk between the NFkappaB and STAT3 signaling pathways in head and neck squamous cell carcinoma. Neoplasia. 2006;8(9):733–46.View ArticlePubMedPubMed CentralGoogle Scholar
- Mihara M, Hashizume M, Yoshida H, Suzuki M, Shiina M. IL-6/IL-6 receptor system and its role in physiological and pathological conditions. Clinical science (Lond). 2012;122(4):143–59.View ArticleGoogle Scholar
- Finkel KA, Warner KA, Kerk S, Bradford CR, McLean SA, Prince ME, Zhong H, Hurt EM, Hollingsworth RE, Wicha MS, et al. IL-6 inhibition with MEDI5117 decreases the fraction of head and neck Cancer stem cells and prevents tumor recurrence. Neoplasia. 2016;18(5):273–81.View ArticlePubMedPubMed CentralGoogle Scholar
- Anantharaman D, Gheit T, Waterboer T, Abedi-Ardekani B, Carreira C, McKay-Chopin S, Gaborieau V, Marron M, Lagiou P, Ahrens W, et al. Human papillomavirus infections and upper aero-digestive tract cancers: the ARCAGE study. J Natl Cancer Inst. 2013;105(8):536–45.View ArticlePubMedGoogle Scholar
- Castellsague X, Alemany L, Quer M, Halec G, Quiros B, Tous S, Clavero O, Alos L, Biegner T, Szafarowski T, et al. HPV involvement in head and neck cancers: comprehensive assessment of biomarkers in 3680 patients. J Natl Cancer Inst. 2016;108(6):djv403.View ArticlePubMedGoogle Scholar
- Guerrera IC, Quetier I, Fetouchi R, Moreau F, Vauloup-Fellous C, Lekbaby B, Rousselot C, Chhuon C, Edelman A, Lefevre M, et al. Regulation of interleukin-6 in head and neck squamous cell carcinoma is related to papillomavirus infection. J Proteome Res. 2014;13(2):1002–11.View ArticlePubMedGoogle Scholar
- Argiris A, Lee SC, Feinstein T, Thomas S, Branstetter BF, Seethala R, Wang L, Gooding W, Grandis JR, Ferris RL. Serum biomarkers as potential predictors of antitumor activity of cetuximab-containing therapy for locally advanced head and neck cancer. Oral Oncol. 2011;47(10):961–6.View ArticlePubMedPubMed CentralGoogle Scholar
- Eng PM, Kawachi I, Fitzmaurice G, Rimm EB. Effects of marital transitions on changes in dietary and other health behaviours in US male health professionals. J Epidemiol Community Health. 2005;59(1):56–62.View ArticlePubMedPubMed CentralGoogle Scholar
- Bell S, Mehta G, Moore K, Britton A. Ten-year alcohol consumption typologies and trajectories of C-reactive protein, interleukin-6 and interleukin-1 receptor antagonist over the following 12 years: a prospective cohort study. J Intern Med. 2017;281(1):75–85.View ArticlePubMedGoogle Scholar
- Marques-Vidal P, Bochud M, Bastardot F, von Kanel R, Ferrero F, Gaspoz JM, Paccaud F, Urwyler A, Luscher T, Hock C, et al. Associations between alcohol consumption and selected cytokines in a Swiss population-based sample (CoLaus study). Atherosclerosis. 2012;222(1):245–50.View ArticlePubMedGoogle Scholar
- Volpato S, Pahor M, Ferrucci L, Simonsick EM, Guralnik JM, Kritchevsky SB, Fellin R, Harris TB. Relationship of alcohol intake with inflammatory markers and plasminogen activator inhibitor-1 in well-functioning older adults: the health, aging, and body composition study. Circulation. 2004;109(5):607–12.View ArticlePubMedGoogle Scholar
- Pai JK, Hankinson SE, Thadhani R, Rifai N, Pischon T, Rimm EB. Moderate alcohol consumption and lower levels of inflammatory markers in US men and women. Atherosclerosis. 2006;186(1):113–20.View ArticlePubMedGoogle Scholar
- Li YY, Hsieh LL, Tang RP, Liao SK, Yeh KY. Interleukin-6 (IL-6) released by macrophages induces IL-6 secretion in the human colon cancer HT-29 cell line. Hum Immunol. 2009;70(3):151–8.View ArticlePubMedGoogle Scholar
- Del Corno M, Donninelli G, Varano B, Da Sacco L, Masotti A, Gessani S. HIV-1 gp120 activates the STAT3/interleukin-6 axis in primary human monocyte-derived dendritic cells. J Virol. 2014;88(19):11045–55.View ArticlePubMedPubMed CentralGoogle Scholar
- Aarstad HJ, Aarstad HH, Vintermyr OK, Kross KW, Lybak S, Heimdal JH. In vitro monocyte IL-6 secretion levels following stimulation with autologous spheroids derived from tumour or benign mucosa predict long-term survival in head and neck squamous cell carcinoma patients. Scand J Immunol. 2017;85(3):211–9.View ArticlePubMedGoogle Scholar
- Shi L, Dong N, Ji D, Huang X, Ying Z, Wang X, Chen C. Lipopolysaccharide-induced CCN1 production enhances interleukin-6 secretion in bronchial epithelial cells. Cell Biol Toxicol. 2017;Google Scholar
- Walters MJ, Paul-Clark MJ, McMaster SK, Ito K, Adcock IM, Mitchell JA. Cigarette smoke activates human monocytes by an oxidant-AP-1 signaling pathway: implications for steroid resistance. Mol Pharmacol. 2005;68(5):1343–53.View ArticlePubMedGoogle Scholar
- Lee J, Taneja V, Vassallo R. Cigarette smoking and inflammation: cellular and molecular mechanisms. J Dent Res. 2012;91(2):142–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Zhou H, Hua W, Jin Y, Zhang C, Che L, Xia L, Zhou J, Chen Z, Li W, Shen H. Tc17 cells are associated with cigarette smoke-induced lung inflammation and emphysema. Respirology. 2015;20(3):426–33.View ArticlePubMedGoogle Scholar
- Yeon JY, Suh YJ, Kim SW, Baik HW, Sung CJ, Kim HS, Sung MK. Evaluation of dietary factors in relation to the biomarkers of oxidative stress and inflammation in breast cancer risk. Nutrition. 2011;27(9):912–8.View ArticlePubMedGoogle Scholar
- Karin M. Nuclear factor-kappaB in cancer development and progression. Nature. 2006;441(7092):431–6.View ArticlePubMedGoogle Scholar
- Fernandez-Real JM, Vayreda M, Richart C, Gutierrez C, Broch M, Vendrell J, Ricart W. Circulating interleukin 6 levels, blood pressure, and insulin sensitivity in apparently healthy men and women. J Clin Endocrinol Metab. 2001;86(3):1154–9.View ArticlePubMedGoogle Scholar
