Literature DB >> 24948355

Interferon-γ-induced inflammatory markers and the risk of cancer: the Hordaland Health Study.

Hui Zuo1, Grethe S Tell, Stein E Vollset, Per M Ueland, Ottar Nygård, Øivind Midttun, Klaus Meyer, Arve Ulvik, Simone J P M Eussen.   

Abstract

BACKGROUND: It has been reported that interferon-γ (IFN-γ)-induced inflammatory markers, such as circulating neopterin and kynurenine-to-tryptophan ratio (KTR), are increased in patients with cancer and are also a predictor of poor prognosis. However, whether baseline levels of these makers are associated with subsequent cancer risk in the general population remains unknown.
METHODS: We conducted a prospective analysis of the Hordaland Health Study in 6594 adults without known cancer at baseline who were enrolled between April 1998 and June 1999. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using multivariate Cox proportional hazards regression models adjusted for sex, age, body mass index, smoking status, and renal function.
RESULTS: A total of 971 incident cancer cases (507 men and 464 women) were identified over a median follow-up time of 12 years. Baseline plasma neopterin, KTR and C-reactive protein (CRP) were significantly associated with an increased risk of overall cancer in models adjusted for covariates (P for trend across quartiles = .006 for neopterin, .022 for KTR, and .005 for CRP). The multivariate-adjusted HR (95% CI) per SD increment in similar models were 1.09 (1.03-1.16) for neopterin, 1.07 (1.01-1.14) for KTR, and 1.04 (0.98-1.10) for CRP. The associations between the inflammatory markers and risk of major specific cancer types were also provided.
CONCLUSIONS: Our findings indicate that plasma neopterin, KTR, and CRP are associated with a significantly increased risk of overall cancer. Our study revealed novel evidence regarding the role of IFN-γ-induced inflammation in human carcinogenesis.
© 2014 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

Entities:  

Keywords:  CRP; cancer; cohort study; immune activation; inflammation; kynurenine-to-tryptophan ratio; neopterin; risk

Mesh:

Substances:

Year:  2014        PMID: 24948355      PMCID: PMC4283722          DOI: 10.1002/cncr.28869

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


Chronic inflammation is perceived to predispose to different forms of cancer1 and impacts each stage of tumorigenesis, from initiation, promotion, and malignant conversion to invasion and metastasis.2 C-reactive protein (CRP) is a commonly used nonspecific biomarker of systemic inflammation. Evidence on the association between CRP and cancer risk is currently inconsistent. A recent meta-analysis found elevated levels of CRP to be associated with an increased risk of overall cancer, lung cancer, and possibly breast, prostate, and colorectal cancer.3 However, results from Mendelian randomization studies suggest that elevated CRP levels are unlikely to cause cancer.4 Neopterin is a metabolite of guanosine triphosphate and is synthesized by activated macrophages upon stimulation with proinflammatory cytokines, particularly interferon-γ (IFN-γ). Therefore, elevated concentrations of neopterin in body fluids reflect cellular immune activation involving T cells and an endogenous release of INF-γ.5 Studies have observed increased levels of neopterin in patients with malignant diseases such as lung,6 breast,7 and pancreatic cancer.8 The extent of neopterin elevation depends on tumor type and stage,9 and neopterin has been proposed as a potential biomarker of cancer diagnosis and prognosis.8,10 Whether prediagnostic neopterin is associated with future cancer risk is, however, unknown. IFN-γ can also up-regulate enzymatic activity of indoleamine 2,3-dioxygenase (IDO), which catalyzes the conversion of tryptophan to kynurenine followed by further metabolism via the kynurenine pathway.11,12 As a result, the plasma kynurenine-to-tryptophan ratio (KTR) increases during inflammation. Several studies have demonstrated IDO activation, increased tryptophan degradation, and subsequently elevated level of KTR in established cancer, and these indices also predict poor prognosis in patients with cancer such as lung cancer,13,14 gynecological cancer,15 and malignant melanoma.16 It has been postulated that IDO plays a critical role in cancer immunosurveillance.17 Results from in vitro experiments indicate that IDO overexpression by colorectal tumor cells is significantly correlated with the quantity of tumor-infiltrating T cells.18 Based on the role of IDO in immunosuppression and immune escape, selective IDO inhibitors (eg, 1-methyl-tryptophan) have been developed and tested as an adjuvant chemotherapeutic agent in vitro in animal studies and phase 1 trials.19–22 Previous publications from human studies on the relation between neopterin, KTR, and cancer have focused on patients with existing disease. However, whether levels of these inflammatory makers, particularly neopterin and KTR, are associated with subsequent cancer risk among apparently healthy individuals remains unknown. The purpose of this cohort study, therefore, was to examine the associations of the systemic inflammatory markers including neopterin, KTR, and CRP with overall cancer risk among community-dwelling men and women.

MATERIALS AND METHODS

Study Design and Cohort

The Hordaland Health Study is a community-based study that was conducted jointly by the University of Bergen, the National Institute of Public Health, and the Municipal Health Service in Hordaland. The study participants consisted of men and women born during the periods 1925-1927 and 1950-1951 in Hordaland County in western Norway. The individuals in these two specific age groups originated from an earlier study called the Hordaland Homocysteine Study conducted in 1992-1993,23 which was established to examine the determinants of homocysteine and homocysteine as a risk factor for disease. To be able to examine age effects on homocysteine as well as homocysteine as a risk factor for age-related conditions, such as cardiovascular disease and cancer, the middle-aged cohort was expanded to also include the older cohort, which has a much higher prevalence of disease. Details of the study design have been published elsewhere.24 The initial study cohort included 7051 participants who were enrolled between April 1998 and June 1999. Data were collected via self-administered questionnaires, anthropometric assessment, and blood analyses. The study protocol was approved by the Regional Committee for Medical Research Ethics and the Norwegian Data Inspectorate. All participants provided written informed consent. Of the 7051 participants, we excluded 426 participants who were diagnosed with cancer (other than nonmelanoma skin cancer) before enrollment. Participants with missing data on blood measurements (neopterin, kynurenine, tryptophan, and CRP) (n = 31) were also excluded. A total of 6594 participants (2958 men and 3636 women) were therefore included in the final analysis.

Biochemical Analyses

Nonfasting blood samples were collected at baseline. Aliquots of serum and plasma were frozen at −80°C until analyses. Plasma neopterin, kynurenine, tryptophan, and serum creatinine were measured by liquid chromatography-tandem mass spectrometry.25,26 Plasma high-sensitive CRP was determined by a novel immuno-MALDI-MS method (unpublished data). All biochemical analyses were performed at Bevital A/S (www.bevital.no). Within-day coefficients of variation for neopterin, kynurenine, and tryptophan were 2.5%-4.7%, and between-day coefficients of variation were 5.7%-10.0%.25

Outcome Assessment

Cancer cases were ascertained through linkage with the Cancer Registry of Norway. Cancer incidence diagnoses were coded according to the 3rd edition of the International Classification of Diseases for Oncology (ICD-O-3)27 and the 10th revision of the International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10) (http://apps.who.int/classifications/icd10/browse/2010/en). Only the first primary neoplasm was included in the analysis. Mortality data were collected from the Cause of Death Registry at Statistics Norway and coded according to ICD-10.

Additional Data

Self-administered questionnaires provided information on sociodemographic data, health status, and lifestyle factors. Information on smoking (never, former, or current smokers) was coded as categorical variables. Height and weight were measured following standard protocols. Body mass index (BMI) was calculated as kg/m2 and categorized as normal (BMI <25 kg/m2), overweight (25 kg/m2 ≤ BMI < 30 kg/m2), and obese (BMI ≥30 kg/m2) according to the World Health Organization's recommendation. Renal function was assessed using an estimated glomerular filtration rate (eGFR) based on serum creatinine levels.28

Statistical Analysis

Continuous variables are presented as medians (interquartile ranges) due to skewed distributions; categorical variables are given as counts (percentages). Wilcoxon–Mann–Whitney tests were used to compare differences between groups for continuous variables. For each participant, person-years of follow-up were calculated from the date of entry until the date of cancer diagnosis, death, emigration, or the end of follow-up (December 31, 2010), whichever came first. The association of plasma neopterin, KTR, and CRP with risk of overall cancer was evaluated using Cox proportional hazards regression models with person-years as the underlying time metric. Proportionality was verified using analysis of residuals. Hazard ratios (HR) and 95% confidence intervals (CI) are reported. Models were fitted with neopterin, KTR, and CRP as continuous variables (per SD increment) and as sex-specific quartiles based on the distribution of the study population. Linear trends were tested across increasing quartiles by modeling quartile categories as a continuous variable in the regression models. Multivariable models included the following covariates: age (46-49 years vs 70-74 years), sex, BMI (normal, overweight, and obese), smoking status (never, former, or current smokers) and renal function (normal, eGFR > 60 mL/min/1.73 m2 or impaired, 1 < eGFR ≤ 60 mL/min/1.73 m2). Risk estimates did not change materially by additional adjustment for physical activity, which therefore was not included in final models. Kaplan-Meier plots were made for cumulative cancer incidence according to neopterin, KTR, and CRP quartiles, and the corresponding P values of the log-rank test for possible trends across quartiles are presented. Multivariable adjusted dose-response relations between inflammatory marker levels and cancer risk were also visualized by generalized additive regression plots.29 In these plots, biomarker values were fitted with smoothing spline in Cox proportional hazard models including the same covariates as described above. Interaction analysis was performed between the three markers and sex/age/BMI/smoking status/renal function for cancer risk by including product terms in the regression models. In addition, we also conducted a lag analysis by excluding the first 1 year of follow-up to test for the possibility of reverse causality. All statistical tests were 2-sided and were considered statistically significant at P < 0.05. All statistical analyses were conducted using the SAS (version 9.2, SAS Institute Inc, Cary, NC) and figures generated using R (version 2.15 for Windows).

RESULTS

Population Characteristics

Baseline characteristics of the participants are presented in Table 1. Plasma neopterin concentration was significantly higher in women, in the older age group, in participants with higher BMI, and in those with impaired renal function (P<.01). Plasma concentrations of KTR and CRP were significantly higher in participants in the older age group, in participants with high BMI, and in participants with impaired renal function (P<.01), whereas no significant sex differences were observed with regard to KTR or CRP levels. Plasma neopterin and KTR were lower, and CRP levels higher in current smokers as compared with former and never smokers (P<.01). Additional details regarding the distribution of neopterin and KTR are described elsewhere.30 The three markers were intercorrelated (Spearman correlation coefficients were 0.56, 0.27, and 0.24 [P<.001] for the pairs neopterin/KTR, CRP/KTR, and CRP/neopterin, respectively).
Table 1

Baseline Characteristics of the Study Participants in the Hordaland Health Study

No. (%)Median (IQR)
Neopterin (nmol/L)KTR (nmol/µmol)CRP (mg/L)
Overall6594 (100.0)7.6 (6.3-9.2)22.4 (18.4-27.7)1.6 (0.7-3.6)
Sex
 Men2958 (44.9)7.4 (6.2-9.0)22.4 (18.6-27.5)1.6 (0.7-3.5)
 Women3636 (55.1)7.7 (6.4-9.4)a22.4 (18.2-27.8)1.5 (0.6-3.6)
Age, y
 46-493632 (55.1)6.9 (5.9-8.2)20.0 (17.1-23.7)1.1 (0.5-2.6)
 70-742962 (44.9)8.6 (7.3-10.5)a26.1 (21.8-31.7)a2.2 (1.1-4.4)a
BMI
 Normal2976 (45.2)7.5 (6.3-9.1)21.4 (17.9-26.5)1.1 (0.5-2.4)
 Overweight2809 (42.7)7.6 (6.4-9.3)22.9 (18.6-28.1)1.8 (0.9-3.8)
 Obese797 (12.1)7.8 (6.4-9.7)a25.0 (19.9-30.4)a3.3 (1.7-6.6)a
Smoking
 Never smoker2597 (40.6)7.7 (6.5-9.4)22.6 (18.3-28.0)1.4 (0.6-3.2)
 Former smoker2131 (33.3)7.9 (6.6-9.6)23.4 (19.3-29.0)1.6 (0.7-3.6)
 Current smoker1668 (26.1)7.1 (5.9-8.6)a21.0 (17.5-25.4)a1.9 (0.8-4.0)a
Renal function
 Normal6000 (91.0)7.4 (6.3-8.9)21.8 (18.1-26.6)1.5 (0.6-3.4)
 Impaired594 (9.0)10.1 (8.5-12.6)a31.4 (25.3-38.4)a2.6 (1.2-5.4)a

Abbreviations: BMI, body mass index; CRP, C-reactive protein; IQR, interquartile range; KTR, kynurenine-to-tryptophan ratio.

Not all sums are equal to the total number of the participants due to missing values.

P<.01 for difference between groups.

Baseline Characteristics of the Study Participants in the Hordaland Health Study Abbreviations: BMI, body mass index; CRP, C-reactive protein; IQR, interquartile range; KTR, kynurenine-to-tryptophan ratio. Not all sums are equal to the total number of the participants due to missing values. P<.01 for difference between groups.

Classical Risk Factors And Future Cancer Risk

A total of 971 incident cancer cases (507 men and 464 women) among the 6594 participants were identified over a median follow-up time of 12 years. Age as a categorical variable was positively associated with overall cancer risk (adjusted HR, 4.18; 95% CI, 3.60-4.86). Women had a lower risk than men (adjusted HR, 0.71; 95% CI, 0.62-0.82). Compared with never smokers, the adjusted HR (95% CI) were 1.35 (1.16-1.58) for former smokers and 1.62 (1.36-1.93) for current smokers. BMI and renal function, assessed by eGFR, were not significantly associated with cancer risk (data not shown).

Inflammatory Markers at Baseline and Future Cancer Risk

Figure 1 shows the cumulative incidence of overall cancer according to quartiles of neopterin, KTR, and CRP levels, respectively. The unadjusted cancer risk increased significantly in higher quartiles for each of the inflammatory markers (P<.001). For instance, the cumulative hazard of overall cancer increased much more rapidly over follow-up time in the fourth quartile of neopterin compared with the first quartile (left panel).
Figure 1

Kaplan-Meier survival curves for cumulative incidence of overall cancer according to sex-specific quartiles of neopterin, kynurenine-to-tryptophan ratio (KTR), and C-reactive protein (CRP) levels.

Kaplan-Meier survival curves for cumulative incidence of overall cancer according to sex-specific quartiles of neopterin, kynurenine-to-tryptophan ratio (KTR), and C-reactive protein (CRP) levels. The results from multivariate Cox models are shown in Table 2. Baseline neopterin, KTR, and CRP were associated with an increased risk of overall cancer both in unadjusted analyses and analyses adjusted for age, sex, BMI, smoking status, and renal function (P for trend across quartiles = .006 for neopterin, .022 for KTR and .005 for CRP). The multivariate-adjusted HR (95% CI) per SD increment in similar models were 1.09 (1.03-1.16) for neopterin, 1.07 (1.01-1.14) for KTR, and 1.04 (0.98-1.10) for CRP. As shown in Figure2, positive dose-response relations were observed between neopterin, KTR and CRP and cancer risk.
Table 2

HRs and 95% CIs for Incident Cancer in the Hordaland Health Study (n=6594)

UnadjustedSex, age-adjustedMultivariate-adjusteda
HR (95% CI)P trendHR (95% CI)P trendHR (95% CI)P trend
Neopterin (mmol/L)
 Quartile 11.00 (ref.)<.0011.00 (ref.).0121.00 (ref.).006
 Quartile 21.24 (1.01-1.52)0.97 (0.79-1.19)1.01 (0.82-1.25)
 Quartile 31.67 (1.37-2.03)1.08 (0.88-1.32)1.11 (0.90-1.36)
 Quartile 42.33 (1.94-2.81)1.23 (1.01-1.50)1.29 (1.05-1.59)
 Continuousa1.21 (1.16-1.27)<.0011.07 (1.01-1.14).0241.09 (1.03-1.16).007
KTR (nmol/µmol)
 Quartile 11.00 (ref.)<.0011.00 (ref.).0441.00 (ref.).022
 Quartile 21.42 (1.15-1.75)1.17 (0.95-1.45)1.17 (0.94-1.45)
 Quartile 31.92 (1.57-2.34)1.24 (1.01-1.53)1.25 (1.01-1.54)
 Quartile 42.51 (2.07-3.04)1.25 (1.02-1.54)1.29 (1.04-1.60)
 Continuous1.17 (1.13-1.20)<.0011.05 (0.99-1.11).1421.07 (1.01-1.14).037
CRP (mg/L)
 Quartile 11.00 (ref.)<.0011.00 (ref.)<.0011.00 (ref.).005
 Quartile 21.36 (1.10-1.68)1.01 (0.82-1.24)0.98 (0.80-1.22)
 Quartile 32.04 (1.68-2.48)1.34 (1.09-1.63)1.31 (1.07-1.61)
 Quartile 42.10 (1.73-2.55)1.31 (1.07-1.60)1.25 (1.01-1.53)
 Continuous1.10 (1.05-1.14)<.0011.06 (1.00-1.12).0411.04 (0.98-1.10).164

Abbreviations: CI, confidence interval; CRP, C-reactive protein; HR, hazard ratio; KTR, kynurenine to tryptophan ratio.

Adjusted for sex, age (46-49 years vs 70-74 years), body mass index (normal, overweight, or obese), smoking (never, former, or current smoker), and renal function (normal or impaired).

Biomarkers as continuous variables (per SD increment).

Figure 2

Dose–response relations between inflammatory marker levels and cancer risk by generalized additive regression. Models were adjusted for age, sex, body mass index, smoking status, and renal function. The solid lines represent hazard ratios; the shaded areas represent 95% confidence intervals. Density plots show the distribution of biomarkers, and white vertical lines denote the 25th, 50th, and 75th percentiles.

HRs and 95% CIs for Incident Cancer in the Hordaland Health Study (n=6594) Abbreviations: CI, confidence interval; CRP, C-reactive protein; HR, hazard ratio; KTR, kynurenine to tryptophan ratio. Adjusted for sex, age (46-49 years vs 70-74 years), body mass index (normal, overweight, or obese), smoking (never, former, or current smoker), and renal function (normal or impaired). Biomarkers as continuous variables (per SD increment). Dose–response relations between inflammatory marker levels and cancer risk by generalized additive regression. Models were adjusted for age, sex, body mass index, smoking status, and renal function. The solid lines represent hazard ratios; the shaded areas represent 95% confidence intervals. Density plots show the distribution of biomarkers, and white vertical lines denote the 25th, 50th, and 75th percentiles. There were no interactions between the three markers and age, BMI, smoking status, or renal function in association with cancer risk. However, significant interactions were found between the markers and sex (P interaction = 0.011, 0.002, and 0.063 for neopterin, KTR, and CRP, respectively). Stratified analysis by sex showed consistently stronger associations in men than in women (data not shown). Results from lag analyses for the associations of neopterin (HR, 1.09; 95% CI, 1.02-1.16), KTR (HR, 1.07; 95% CI, 1.01-1.14), and CRP (HR, 1.04; 95% CI, 0.98-1.11) with overall cancer risk excluding the first 1 year of follow-up were not materially different from those including the whole follow-up period. We conducted secondary analyses on major specific cancer types (ie, colorectal cancer [n = 175], prostate cancer [n = 140], breast cancer [n = 108] and lung cancer [n = 88], as shown in Figure3. Neopterin and KTR were positively associated with risk of colorectal cancer (HR per SD increment [95% CI]: 1.16 [1.02-1.32] for neopterin, 1.15 [1.04-1.28] for KTR), whereas CRP was found to be associated with an increased risk of lung cancer (HR per SD increment [95% CI]: 1.15 [1.06-1.25]).
Figure 3

Forest plot showing risk of different cancer types (colorectal cancer [n = 175], prostate cancer [n = 140], breast cancer [n = 108], and lung cancer [n = 88]) according to plasma inflammatory markers. The blue squares represent hazard ratios (HR); the horizontal bars represent 95% confidence intervals (95% CI). The Cox models were adjusted for age, sex, body mass index, and renal function.

Forest plot showing risk of different cancer types (colorectal cancer [n = 175], prostate cancer [n = 140], breast cancer [n = 108], and lung cancer [n = 88]) according to plasma inflammatory markers. The blue squares represent hazard ratios (HR); the horizontal bars represent 95% confidence intervals (95% CI). The Cox models were adjusted for age, sex, body mass index, and renal function.

DISCUSSION

Principal Findings

In this prospective cohort study, we observed a positive association of IFN-γ–induced inflammatory markers (neopterin and KTR) and CRP with risk of overall cancer among 6594 adults followed for a median of 12 years. These associations were largely unaffected by adjustment for sociodemographic and lifestyle factors, including smoking.

Inflammatory Markers and Incident Cancer Risk

Prospective studies on the association between IFN-γ–induced inflammatory markers and incident cancer risk have not been reported previously, except for a recent study focusing on KTR and lung cancer risk.31 Reported associations between CRP and cancer risk in prospective cohort studies are inconsistent.32–34 Although having substantial heterogeneity, a recent meta-analysis3 including 11 prospective cohort studies reported that the pooled HR (95% CI) per natural log unit change in CRP was 1.11 (1.03-1.18) for overall cancer, 1.31 (1.10-1.52) for lung cancer, 1.04 (0.91-1.17) for breast cancer, 1.06 (0.97-1.16) for prostate cancer, and 1.06 (0.93-1.18) for colorectal cancer. Our results support positive associations of circulating CRP levels with risk of overall cancer and lung cancer. More importantly, our study goes beyond this commonly used nonspecific inflammatory parameter by addressing systemic inflammatory markers reflecting IFN-γ–mediated immune activation with regard to cancer risk. We report that elevated baseline levels of neopterin and KTR were both significantly associated with an increased risk of overall cancer and colorectal cancer.

Possible Mechanisms

Chronic inflammation due to infections, autoimmune disease, environmental irritants, or obesity plays a crucial role in each step of tumorigenesis4 through induction of oncogenic mutations, genomic instability, early tumor promotion, and enhanced angiogenesis.2 As a classic acute-phase protein, CRP levels are moderately elevated in response to chronic inflammation.4 Precise mechanisms binding the association of CRP with cancer risk remain uncertain. The association between CRP and cancer incidence may reflect the production of various cytokines and chemokines by occult tumor cells that attract leukocytes. Some cancerous cells express CRP and secrete interleukin-6 and interleukin-8, which stimulate CRP production in the liver.32 From the available data, it is not possible to elucidate whether elevated CRP is a marker of occult cancer or is causative in carcinogenesis.3,32 Neopterin is produced by oxidation of 7,8-dihydroneopterin, and the amounts of neopterin produced by activated macrophages not only reflect IFN-γ activity but also correlate with their capacity to form and release reactive oxygen species. Neopterin can enhance the toxic effects induced by reactive oxygen species during cell-mediated immune response.9,35 In addition, epidemiological studies show that elevation of neopterin production correlates with increasing age in healthy individuals.9 Furthermore, plasma neopterin and KTR have been positively associated with risk of coronary events in an apparently healthy population36 and mortality in patients with stable coronary artery disease.37 Taken together, these findings suggest that the pathological process associated with immune activation may precede the appearance of clinical disease. Malignant tumors emerge partly because early cancer cells escape from immunosurveillance.19 IDO and tryptophan-2,3-dioxygenase (TDO) catabolize the essential amino acid tryptophan, which promotes selective apoptosis of T lymphocytes38 and suppress antitumor immune responses.39 This has been attributed to tryptophan depletion and/or formation of immunomodulating kynurenines.39 TDO is activated in tumor cells and has a similar effect of nonspecific immunosuppression.40 Plasma KTR reflects the activities of IDO and TDO, both of which may indirectly reflect the antitumor capability of the body.39

Methodological Considerations

The risk estimates in the current study were not affected by excluding the first year of follow-up, which suggests that reverse causality (changes in levels of inflammatory markers due to an undetected cancer) was unlikely. Dose–response relationships between all 3 markers and cancer risk further indicated the robustness of the results. However, when specifying cancer types as outcomes, we found similar results in some but not all cancer types, which may be due to reduced sample size and number of cancer cases. Smoking was a risk factor of cancer as consistently demonstrated by others41, but stratified analysis by smoking status indicated that smoking status was not a significant effect modifier, demonstrating that the associations between inflammatory markers and cancer risk did not depend on the smoking status of the participants. The effects of cigarette smoking on host immunity are complex, and its net effect on immunity depends on many variables, including dose and type of tobacco, mode of exposure, and the presence of other inflammatory mediators.42–44 Smoking has both proinflammatory and suppressive effects and may impair host immune responses and thereby promote cancer.45

Strengths and Limitations

This is the first prospective community-based study evaluating IFN-γ–induced inflammatory markers, neopterin, and KTR, and the risk of overall cancer. The main strengths of the current study are the large sample size, complete and long-term follow-up, and different markers reflecting inflammatory status. When examining the associations, we adjusted for important confounding factors, including age, sex, BMI, smoking status, and renal function. Such adjustment was undertaken because these factors affect cancer risk, and also because a previous study in the same population showed associations between systemic inflammatory markers and these potential confounders.30 This study also has several limitations. The study population was drawn from a small geographic region, representing two narrow age ranges, which may potentially limit generalizability. Furthermore, within-subject reproducibility of the systemic inflammatory markers together with other lifestyle factors over the follow-up period was not considered. This is important because single time point assessment of biomarker status may lead to regression dilution bias, which may attenuate “true” associations.46 However, we have assessed within-subject reproducibility over 3.5 years for neopterin and KTR in another population. The observed intraclass correlation coefficients were 0.67 and 0.74, respectively, indicating fair to good reproducibility.47 In conclusion, elevated plasma neopterin, KTR, and CRP are associated with a significantly higher risk of developing cancer. The current study reveals novel evidence regarding the role of IFN-γ–induced inflammation in human carcinogenesis. These inflammatory markers may assist as early predictors of cancer risk in the general population.
  45 in total

Review 1.  Neopterin as a marker for immune system activation.

Authors:  C Murr; B Widner; B Wirleitner; D Fuchs
Journal:  Curr Drug Metab       Date:  2002-04       Impact factor: 3.731

2.  Kynurenine pathway metabolites in humans: disease and healthy States.

Authors:  Yiquan Chen; Gilles J Guillemin
Journal:  Int J Tryptophan Res       Date:  2009-01-08

3.  Association of inflammatory markers with colorectal cancer incidence in the atherosclerosis risk in communities study.

Authors:  Anna E Prizment; Kristin E Anderson; Kala Visvanathan; Aaron R Folsom
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2011-01-07       Impact factor: 4.254

Review 4.  The Hordaland Homocysteine Study: a community-based study of homocysteine, its determinants, and associations with disease.

Authors:  Helga Refsum; Eha Nurk; A David Smith; Per M Ueland; Clara G Gjesdal; Ingvar Bjelland; Aage Tverdal; Grethe S Tell; Ottar Nygård; Stein E Vollset
Journal:  J Nutr       Date:  2006-06       Impact factor: 4.798

5.  Tryptophan degradation in patients with gynecological cancer correlates with immune activation.

Authors:  Katharina Schroecksnadel; Christiana Winkler; Lothar C Fuith; Dietmar Fuchs
Journal:  Cancer Lett       Date:  2004-12-08       Impact factor: 8.679

6.  Hydroxyamidine inhibitors of indoleamine-2,3-dioxygenase potently suppress systemic tryptophan catabolism and the growth of IDO-expressing tumors.

Authors:  Holly K Koblish; Michael J Hansbury; Kevin J Bowman; Gengjie Yang; Claire L Neilan; Patrick J Haley; Timothy C Burn; Paul Waeltz; Richard B Sparks; Eddy W Yue; Andrew P Combs; Peggy A Scherle; Kris Vaddi; Jordan S Fridman
Journal:  Mol Cancer Ther       Date:  2010-02-02       Impact factor: 6.261

7.  Clinical value of serum neopterin, tissue polypeptide-specific antigen and CA19-9 levels in differential diagnosis between pancreatic cancer and chronic pancreatitis.

Authors:  Renata Talar-Wojnarowska; Anita Gasiorowska; Marek Olakowski; Andrzej Lekstan; Paweł Lampe; Ewa Malecka-Panas
Journal:  Pancreatology       Date:  2011-01-18       Impact factor: 3.996

Review 8.  New promises for manipulation of kynurenine pathway in cancer and neurological diseases.

Authors:  Gabriele Costantino
Journal:  Expert Opin Ther Targets       Date:  2009-02       Impact factor: 6.902

9.  Tobacco smoking and cancer: a meta-analysis.

Authors:  Sara Gandini; Edoardo Botteri; Simona Iodice; Mathieu Boniol; Albert B Lowenfels; Patrick Maisonneuve; Peter Boyle
Journal:  Int J Cancer       Date:  2008-01-01       Impact factor: 7.396

10.  Prognostic value of indoleamine 2,3-dioxygenase expression in colorectal cancer: effect on tumor-infiltrating T cells.

Authors:  Gerald Brandacher; Alexander Perathoner; Ruth Ladurner; Stefan Schneeberger; Peter Obrist; Christiana Winkler; Ernst R Werner; Gabriele Werner-Felmayer; Helmut G Weiss; Georg Göbel; Raimund Margreiter; Alfred Königsrainer; Dietmar Fuchs; Albert Amberger
Journal:  Clin Cancer Res       Date:  2006-02-15       Impact factor: 12.531

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  14 in total

1.  Associations between intake of fish and n-3 long-chain polyunsaturated fatty acids and plasma metabolites related to the kynurenine pathway in patients with coronary artery disease.

Authors:  Therese Karlsson; Elin Strand; Jutta Dierkes; Christian A Drevon; Jannike Øyen; Øivind Midttun; Per M Ueland; Oddrun A Gudbrandsen; Eva Ringdal Pedersen; Ottar Nygård
Journal:  Eur J Nutr       Date:  2015-10-19       Impact factor: 5.614

2.  Serum Immune System Biomarkers Neopterin and Interleukin-10 Are Strongly Related to Tryptophan Metabolism in Healthy Young Adults.

Authors:  Oana M Deac; James L Mills; Clair M Gardiner; Barry Shane; Louise Quinn; Øivind Midttun; Adrian McCann; Klaus Meyer; Per M Ueland; Ruzong Fan; Zhaohui Lu; Lawrence C Brody; Anne M Molloy
Journal:  J Nutr       Date:  2016-08-03       Impact factor: 4.798

3.  Cationic Dendrimers for siRNA Delivery: An Overview of Methods for In Vitro/In Vivo Characterization.

Authors:  Erik Laurini; Suzana Aulic; Domenico Marson; Maurizio Fermeglia; Sabrina Pricl
Journal:  Methods Mol Biol       Date:  2021

4.  The Dietary Inflammatory Index Is Associated with Prostate Cancer Risk in French Middle-Aged Adults in a Prospective Study.

Authors:  Laurie Graffouillère; Mélanie Deschasaux; François Mariotti; Lola Neufcourt; Nitin Shivappa; James R Hébert; Michael D Wirth; Paule Latino-Martel; Serge Hercberg; Pilar Galan; Chantal Julia; Emmanuelle Kesse-Guyot; Mathilde Touvier
Journal:  J Nutr       Date:  2016-03-09       Impact factor: 4.798

5.  Circulating markers of cellular immune activation in prediagnostic blood sample and lung cancer risk in the Lung Cancer Cohort Consortium (LC3).

Authors:  Joyce Y Huang; Tricia L Larose; Hung N Luu; Renwei Wang; Anouar Fanidi; Karine Alcala; Victoria L Stevens; Stephanie J Weinstein; Demetrius Albanes; Neil E Caporaso; Mark P Purdue; Regina G Ziegler; Neal D Freedman; Qing Lan; Ross L Prentice; Mary Pettinger; Cynthia A Thomson; Qiuyin Cai; Jie Wu; William J Blot; Xiao-Ou Shu; Wei Zheng; Alan A Arslan; Anne Zeleniuch-Jacquotte; Loïc Le Marchand; Lynn R Wilkens; Christopher A Haiman; Xuehong Zhang; Meir J Stampfer; Jiali Han; Graham G Giles; Allison M Hodge; Gianluca Severi; Mikael Johansson; Kjell Grankvist; Arnulf Langhammer; Kristian Hveem; Yong-Bing Xiang; Hong-Lan Li; Yu-Tang Gao; Kala Visvanathan; Per M Ueland; Øivind Midttun; Arve Ulvi; Julie E Buring; I-Min Lee; Howard D Sesso; J Michael Gaziano; Jonas Manjer; Caroline Relton; Woon-Puay Koh; Paul Brennan; Mattias Johansson; Jian-Min Yuan
Journal:  Int J Cancer       Date:  2019-07-22       Impact factor: 7.396

6.  A prospective study of the immune system activation biomarker neopterin and colorectal cancer risk.

Authors:  Krasimira Aleksandrova; Shu-Chun Chuang; Heiner Boeing; Hui Zuo; Grethe S Tell; Tobias Pischon; Mazda Jenab; Bas Bueno-de-Mesquita; Stein Emil Vollset; Øivind Midttun; Per Magne Ueland; Veronika Fedirko; Mattias Johansson; Elisabete Weiderpass; Gianluca Severi; Antoine Racine; Marie-Christine Boutron-Ruault; Rudolf Kaaks; Tilman Kühn; Anne Tjønneland; Kim Overvad; J Ramón Quirós; Paula Jakszyn; María-José Sánchez; Miren Dorronsoro; Maria-Dolores Chirlaque; Eva Ardanaz; Kay-Tee Khaw; Nicholas J Wareham; Ruth C Travis; Antonia Trichopoulou; Pagona Lagiou; Dimitrios Trichopoulos; Domenico Palli; Sabina Sieri; Rosario Tumino; Salvatore Panico; Anne M May; Richard Palmqvist; Ingrid Ljuslinder; So Yeon J Kong; Heinz Freisling; Marc J Gunter; Yunxia Lu; Amanda J Cross; Elio Riboli; Paolo Vineis
Journal:  J Natl Cancer Inst       Date:  2015-02-23       Impact factor: 13.506

7.  A prospective study of pre-diagnostic circulating tryptophan and kynurenine, and the kynurenine/tryptophan ratio and risk of glioma.

Authors:  Claudine M Samanic; Yiyang Yue; David J Cote; Meir J Stampfer; Molin Wang; Adrian McCann; Øivind Midttun; Per Magne Ueland; Stephanie A Smith-Warner; Kathleen M Egan
Journal:  Cancer Epidemiol       Date:  2021-12-03       Impact factor: 2.984

8.  Predictive and prognostic role of serum neopterin and tryptophan breakdown in prostate cancer.

Authors:  Renate Pichler; Josef Fritz; Isabel Heidegger; Eberhard Steiner; Zoran Culig; Helmut Klocker; Dietmar Fuchs
Journal:  Cancer Sci       Date:  2017-04-12       Impact factor: 6.716

9.  A prospective evaluation of serum kynurenine metabolites and risk of pancreatic cancer.

Authors:  Joyce Y Huang; Lesley M Butler; Øivind Midttun; Arve Ulvik; Renwei Wang; Aizhen Jin; Yu-Tang Gao; Per M Ueland; Woon-Puay Koh; Jian-Min Yuan
Journal:  PLoS One       Date:  2018-05-07       Impact factor: 3.240

10.  Plasma Biomarkers of Inflammation, the Kynurenine Pathway, and Risks of All-Cause, Cancer, and Cardiovascular Disease Mortality: The Hordaland Health Study.

Authors:  Hui Zuo; Per M Ueland; Arve Ulvik; Simone J P M Eussen; Stein E Vollset; Ottar Nygård; Øivind Midttun; Despoina Theofylaktopoulou; Klaus Meyer; Grethe S Tell
Journal:  Am J Epidemiol       Date:  2016-01-27       Impact factor: 4.897

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