Background: Soluble cytokine receptors and receptor antagonist of proinflammatory cytokines can modify cytokine signaling and may affect cancer risk.

Methods: In a case–cohort study nested within the Women's Health Initiative cohort of postmenopausal women, we assessed the associations of plasma levels of interleukin (IL)-1 receptor antagonist (IL-1Ra) and the soluble receptors of IL-1 (sIL-1R2), IL-6 (sIL-6R and sgp130), and TNF (sTNFR1 and sTNFR2) with risk of colorectal cancer in 433 cases and 821 subcohort subjects. Baseline levels of estradiol, insulin, leptin, IL-6, and TNF-α measured previously were also available for data analysis.

Results: After adjusting for significant covariates, including age, race, smoking, colonoscopy history, waist circumference, and levels of estrogen, insulin, and leptin, relatively high levels of sIL-6R and sIL-1R2 were associated with reduced colorectal cancer risk [HRs comparing extreme quartiles (HRQ4-Q1) for sIL-6R, 0.56; 95% confidence interval (CI), 0.38–0.83; HRQ4-Q1 for sIL-1R2, 0.44; 95% CI, 0.29–0.67]. The associations with IL-1Ra, sgp130, sTNFR1, and sTNFR2 were null. The inverse association of sIL-1R2 with colorectal cancer risk persisted in cases diagnosed ≤5 and >5 years from baseline blood draw; the association with sIL-6R, however, was not evident in the latter group, possibly indicating that relatively low levels of sIL-6R in cases might be due to undiagnosed cancer at the time of blood draw.

Conclusions: High circulating levels of sIL-1R2 may be protective against colorectal carcinogenesis and/or be a marker of reduced risk for the disease.

Impact: sIL-1R2 has potential to be a chemopreventive and/or immunotherapeutic agent in inflammation-related diseases. Cancer Epidemiol Biomarkers Prev; 23(1); 179–88. ©2013 AACR.

Experimental studies have shown that potent proinflammatory cytokines, such as TNF-α, interleukin (IL)-6, and IL-1β, have oncogenic effects (1, 2). However, soluble cytokine receptors or receptor antagonists of these cytokines can modify cytokine signaling and may also affect cancer risk (3, 4). This case–cohort study nested within the Women's Health Initiative Observational Study (WHI-OS) assessed circulating levels of the soluble cytokine receptors and receptor antagonist of these three potent inflammatory cytokines for their associations with risk of colorectal cancer, an inflammation-associated disease (5–7). Specifically, IL-1 receptor antagonist (IL-1Ra) and the soluble receptors of IL-1 (sIL-1R2), IL-6 (sIL-6R and sgp130), and TNF (sTNFR1 and sTNFR2) were examined. With the exception of sTNFR2 (8), none of these analytes have ever been studied for their colorectal cancer associations.

Soluble cytokine receptors can be formed by proteolytic cleavage of cell-surface receptors or by alternative splicing of mRNA that deletes the transmembrane domain of membrane-associated receptors (3). Many soluble cytokine receptors (e.g., sIL-1R2, sTNFR1, and sTNFR2) may act as decoy receptors, block binding of the ligands to cognate functional membrane receptors, and hence inhibit cytokine signaling (4, 9–11). The biologic effects of IL-6 soluble receptors are more complex. IL-6 signaling requires the interaction of IL-6 with its receptor complex consisting of IL-6R and the signal-transducing protein gp130. Although gp130 is ubiquitously expressed, IL-6R is not present on all cells. Nevertheless, IL-6R has a soluble form sIL-6R that binds to IL-6 to form a soluble complex, which binds to cell-surface gp130 on cells that lack the membrane-bound IL-6R and initiates signaling. As such, sIL-6R is thought to be an IL-6 agonist enhancing IL-6 signaling (9). However, there is also a soluble form of gp130. IL-6 can be trapped in the soluble ternary complex with sIL-6R and sgp130, resulting in inhibition of IL-6 signaling (12). IL-1Ra is a naturally occurring receptor antagonist that binds to, without activating, the membrane-bound IL-1 receptors and hence competitively blocks IL-1 binding to its cell-surface receptors (4, 13).

The six analytes were chosen because of their biologic activities that they could modify signaling of the potent inflammatory cytokines. This study tested the hypothesis that the levels of IL-1Ra, sIL-1R2, sgp130, sTNFR1, and sTNFR2 would be inversely associated with colorectal cancer risk, whereas sIL-6R might have the opposite effect. Moreover, we had previously examined the associations of the ligands, IL-6 and TNF-α, with colorectal cancer risk on the same cases and subcohort subjects (7); this present study would have the opportunity to assess how the cytokine ligands and their soluble receptors might act together to affect colorectal cancer risk.

Study population

The WHI-OS is a prospective study of 93,676 postmenopausal women ages 50 to 79 years at recruitment between 1993 and 1998 in the United States (14). At baseline, participants completed epidemiologic questionnaires, and morning, fasting blood samples were collected, centrifuged, frozen on-site at −80°C, and later shipped to the central specimen repository. Diagnosis of colorectal cancer was ascertained by annual self-administered questionnaires and confirmed through centralized review of medical records.

This colorectal cancer study was a component of a case–cohort study in which three cancer outcomes (breast, colorectum, and endometrium) were previously examined for their associations with estradiol, insulin, IL-6, TNF-α, leptin, and other adipokines (7, 15–17). There were 496 cases that had developed an incident primary colorectal cancer by June 2004, after excluding those diagnosed during the first year of follow-up. A subcohort of 892 women was randomly sampled from the WHI-OS participants who had more than 12 months of follow-up and had no history of breast, colorectal, or endometrial cancer at 12 months after study enrollment, regardless of their cancer outcome thereafter. Of these, 433 cases and 821 subcohort members had baseline plasma samples available for the present study and did not have diabetes treatment at the time of blood draw (which would alter levels of insulin and leptin that were included in data analyses described later). There were 353 cases of colon cancer, 78 cases of rectosigmoid junction or rectal cancer, and two cases with unknown location of the colorectal cancer; 96% of the cases were diagnosed as adenocarcinoma.

Laboratory methods

The six analytes in EDTA plasma samples were assayed by the Millipore kits (EMD Millipore). The MILLIPLEX Human Cytokine/Chemokine Panel was used to measure IL-1Ra; sIL-6R, sgp130, sIL-1R2, sTNFR1, and sTNFR2 were measured in a multiplex assay using the MILLIPLEX Human Soluble Cytokine Receptor Panel. The MILLIPLEX assays used the Luminex's color-coded bead-based technology to achieve multiplexing (18).

The analytes were detectable in 99% to 100% of the samples (the lowest detectability was 99.2% for IL-1Ra). The interassay coefficients of variation (CV) in our laboratory, which were determined from four control samples inserted into each of the 42 assay plates run over a period of time by the same technician, were 4.5% for sTNFR2, 5.9% for sTNFR1, 5.5% for sIL-6R, 6.6% for sgp130, 7.1% for sIL-1R2, and 10.7% for IL-1Ra. The 3-year intraclass correlation coefficients (ICC) of the six analytes were estimated from two previous studies. On the basis of three independent plasma samples collected over a 3-year period (baseline, year 1, and year 3) from each of 17 healthy women (19), the ICCs were 0.52 for sIL-6R, 0.63 for sgp130, 0.65 for sTNFR1, and 0.78 for sIL-1R2 (20). In another study, plasma levels of sTNFR2 and IL-1Ra at baseline and year 3 were measured in 148 subjects randomized to the placebo group of the Aspirin/Folate Polyp Prevention Trial (21). The 3-year ICCs were 0.56 for IL-1Ra and 0.72 for sTNFR2 (unpublished data). These ICC data suggest that a single measurement of circulating levels of the analytes under study in the baseline blood sample reflects an individual's average levels over time.

Statistical analyses

From previous studies of this case–cohort study population, we found circulating levels of insulin, leptin, and estradiol to be significantly positively associated with colorectal cancer risk in multivariable analyses (7, 16). These variables were included in the data analyses described here. Although IL-6 and TNF-α were not significant risk factors in prior analyses, they were also included in data analyses, because they are ligands of the soluble receptors under study.

In univariable analyses, the prevalences of established colorectal cancer risk factors and analyte levels in quartiles between cases and subcohort subjects were compared using χ2 test. In the subcohort, we evaluated whether various colorectal cancer risk factors were associated with the analyte levels using Kruskal–Wallis tests, and correlations among the analytes were estimated by Spearman rank correlation coefficients.

Multivariable analyses were conducted using Cox proportional hazard regression with robust variance estimation using the Self-Prentice method, which accounts for the case–cohort design in which cases may arise outside of or within the subcohort (22, 23). A base model was first developed to retain only the baseline covariates age (continuous), race (Whites vs. others), and colorectal cancer risk factors that were significant in multivariable analyses in our study population—smoking status (never, former, or current), ever had a colonoscopy, and estrogen level in four categories [serum estradiol in tertiles among women who were not using hormone therapy (<8, 8–13.9, or ≥14 pg/mL) or women using hormone therapy at baseline], waist circumference (continuous), insulin level (continuous), and leptin level (in quartiles due to its nonlinear relationship with colorectal cancer risk). Colorectal cancer risk factors that were not statistically significant in multivariable modeling were excluded from the base model [e.g., use of nonsteroidal antiinflammatory drugs (NSAID) and alcohol, physical activity, family history of colorectal cancer, and folate and red meat intakes per day]. We then assessed the HR for the association of each of the six analytes with colorectal cancer risk adjusting for the base-model covariates. To be robust to any nonlinear effect, all six analytes were categorized and analyzed in quartiles. Trend tests were performed using Wald tests associated with fitting the quartile categories as continuous variables in the regression model.

Although colorectal cancer cases diagnosed within the first year of follow-up were already excluded, sensitivity analyses were conducted to further examine whether reverse-causality might explain the analyte–disease association. Cases were separated into two groups defined by number of years from baseline recruitment to case diagnosis (>1 to 5 years or >5 years). Subcohort members who had >1 year or >5 years of follow-up were included in the corresponding two groups, respectively.

Table 1 shows the demographic factors and established risk factors for colorectal cancer in the cases and the subcohort. Briefly, as compared with the subcohort subjects, cases were older, more likely to be smokers, less physically active, and had higher body mass index (BMI) and waist circumference, with the latter having a stronger association with colorectal cancer than BMI. Cases were less likely to have had a colonoscopy, to have ever used oral contraceptives, and to be a hormone therapy user at baseline. Cases also had higher circulating levels of insulin and leptin and were more likely to have a moderately higher level of estradiol than the subcohort subjects. In terms of the six analytes under study, cases had lower plasma levels of sIL-6R and IL-1R2, but higher levels of sTNFR1 and sTNFR2 than the subcohort subjects. Table 1 also shows that the soluble receptors of IL-6 and TNF-α were circulating at a much higher concentration than their ligands (ng/mL vs. pg/mL).

Table 1.

Baseline characteristics of colorectal cancer cases and subcohort subjects in the WHI

Baseline characteristicsCases (n = 433) n (%)Subcohort (n = 814)an (%)P
Age (y) 
 50–54 33 (7.6) 130 (16.0) <0.001b 
 55–56 141 (32.6) 350 (43.0)  
 65–74 201 (46.4) 283 (34.8)  
 75–79 58 (13.4) 51 (6.3)  
Race-ethnicity 
 White 375 (87.0) 695 (85.7) 0.127 
 Black 35 (8.1) 54 (6.7)  
 Other 21 (4.9) 62 (7.6)  
Smoking status 
 Never 194 (45.51) 432 (53.7) 0.009b 
 Former 200 (47.0) 323 (40.2)  
 Current 32 (7.5) 49 (6.1)  
Used NSAID for ≥2 weeks 178 (41.1) 298 (36.6) 0.120 
Ever used oral contraceptives 130 (30.0) 336 (41.3) <0.001b 
Hormone therapy use at baseline 
 No 280 (64.7) 445 (54.7) 0.002b 
 Estrogen + progesterone 67 (15.5) 182 (22.4)  
 Estrogen alone 86 (19.9) 186 (22.9)  
Family history of colorectal cancer 
 No 315 (72.7) 627 (77.0) 0.246 
 Yes 81 (18.7) 128 (15.7)  
 Don't know 37 (8.5) 59 (7.2)  
Ever had colonoscopy 209 (49.0) 456 (56.4) 0.012 
Had polyps removed among those ever had colonoscopy 47 (23.0) 78 (17.6) 0.101 
Alcohol servings per week 
 0 178 (41.2) 319 (39.2) 0.291b 
 0.1–1. 56 125 (28.9) 224 (27.6)  
 ≥1.57 129 (29.9) 270 (33.2)  
Total folate intake (μg) per kcal per day 
 <0.30 124 (28.7) 195 (24.0) 0.136b 
 0.30–0.40 105 (24.3) 204 (25.1)  
 0.41–0.58 97 (22.5) 205 (25.2)  
 ≥0.59 106 (24.5) 210 (25.8)  
Red meat intake (medium serving) per kcal per day × 103 
 <0.20 111 (25.7) 209 (25.7) 0.714b 
 0.20–0.34 111 (25.7) 204 (25.1)  
 0.35–0.52 112 (25.9) 202 (24.8)  
 ≥0.53 98 (22.7) 199 (24.5)  
BMI (kg/m2
 <25 149 (35.0) 316 (39.8) 0.028b 
 25–29.9 151 (35.5) 288 (36.3)  
 ≥30 126 (29.6) 190 (23.9)  
Waist circumference (cm) 
 <74.6 67 (15.5) 196 (24.2) <0.001b 
 74.6–81.9 91 (21.0) 185 (22.8)  
 82.0–91.4 124 (28.6) 219 (27.0)  
 ≥91.5 151 (34.9) 210 (25.9)  
Physical activity (MET/wk) 
 <3.8 124 (28.9) 203 (25.2) 0.030b 
 3.8–9.9 110 (25.6) 200 (24.8)  
 10.0–19.9 113 (26.3) 201 (24.9)  
 ≥20 82 (19.2) 203 (25.2)  
Serum estradiol (pg/mL)c 
 <8 72 (26.5) 146 (33.4)  
 8–13.9 103 (37.8) 132 (30.2) 0.018 
 ≥14 97 (35.7) 159 (36.4) 0.271 
Serum insulin (μU/mL) 
 <3.2 73 (17.2) 193 (24.2) <0.001b 
 3.2–4.9 92 (21.7) 189 (23.7)  
 5.0–8.2 107 (25.2) 202 (25.4)  
 ≥8.3 153 (36.0) 213 (26.7)  
Plasma leptin (ng/mL) 
 <7.4 82 (19.0) 213 (26.2) 0.001b 
 7.4–15.0 120 (27.8) 209 (25.7)  
 15.1–25.5 88 (20.4) 201 (24.7)  
 ≥25.6 142 (32.9) 191 (23.5)  
Plasma IL-6 (pg/mL) 
 <0.93 87 (20.2) 205 (26.0) 0.001b 
 0.93–1.47 98 (22.8) 207 (26.3)  
 1.48–2.31 121 (28.1) 200 (25.4)  
 ≥2.32 124 (28.8) 176 (22.3)  
Plasma TNF-α (pg/mL) 
 <1.82 99 (23.1) 196 (24.8) 0.147b 
 1.82–2.62 103 (24.0) 205 (25.9)  
 2.63–3.62 106 (24.7) 203 (25.6)  
 ≥3.63 121 (28.2) 188 (23.7)  
Plasma levels of six analytes under study 
sgp130 (ng/mL) 
 <146.2 99 (22.9) 203 (24.9) 0.697b 
 146.2–172.1 110 (25.4) 208 (25.6)  
 172.2–200.0 123 (28.4) 199 (24.5)  
 ≥200.1 101 (23.3) 204 (25.1)  
sIL-6R (ng/mL) 
 <16.7 126 (29.1) 207 (25.4) 0.023b 
 16.7–21.1 116 (26.8) 198 (24.3)  
 21.2–25.4 105 (24.3) 204 (25.1)  
 ≥25.5 86 (19.9) 205 (25.2)  
sIL-1R2 (ng/mL) 
 <5.8 130 (30.0) 197 (24.2) 0.019b 
 5.8–7.3 101 (23.3) 209 (25.7)  
 7.4–9.1 122 (28.2) 208 (25.6)  
 ≥9.2 80 (18.5) 200 (24.6)  
IL-1Ra (pg/mL) 
 <15.5 112 (25.9) 204 (25.1) 0.911b 
 15.5–24.1 98 (22.6) 205 (25.2)  
 24.2–38.8 118 (27.3) 206 (25.3)  
 ≥38.9 105 (24.3) 199 (24.5)  
sTNFR1 (ng/mL) 
 <1.0 82 (18.9) 210 (25.8) 0.005b 
 1.0–1.2 108 (24.9) 204 (25.1)  
 1.3–1.5 117 (27.0) 203 (24.9)  
 ≥1.6 126 (29.1) 197 (24.2)  
sTNFR2 (ng/mL) 
 <3.8 81 (18.7) 214 (26.3) 0.012b 
 3.8–4.4 112 (25.9) 207 (25.4)  
 4.5–5.4 132 (30.5) 203 (24.9)  
 ≥5.5 108 (24.9) 190 (23.3)  
Baseline characteristicsCases (n = 433) n (%)Subcohort (n = 814)an (%)P
Age (y) 
 50–54 33 (7.6) 130 (16.0) <0.001b 
 55–56 141 (32.6) 350 (43.0)  
 65–74 201 (46.4) 283 (34.8)  
 75–79 58 (13.4) 51 (6.3)  
Race-ethnicity 
 White 375 (87.0) 695 (85.7) 0.127 
 Black 35 (8.1) 54 (6.7)  
 Other 21 (4.9) 62 (7.6)  
Smoking status 
 Never 194 (45.51) 432 (53.7) 0.009b 
 Former 200 (47.0) 323 (40.2)  
 Current 32 (7.5) 49 (6.1)  
Used NSAID for ≥2 weeks 178 (41.1) 298 (36.6) 0.120 
Ever used oral contraceptives 130 (30.0) 336 (41.3) <0.001b 
Hormone therapy use at baseline 
 No 280 (64.7) 445 (54.7) 0.002b 
 Estrogen + progesterone 67 (15.5) 182 (22.4)  
 Estrogen alone 86 (19.9) 186 (22.9)  
Family history of colorectal cancer 
 No 315 (72.7) 627 (77.0) 0.246 
 Yes 81 (18.7) 128 (15.7)  
 Don't know 37 (8.5) 59 (7.2)  
Ever had colonoscopy 209 (49.0) 456 (56.4) 0.012 
Had polyps removed among those ever had colonoscopy 47 (23.0) 78 (17.6) 0.101 
Alcohol servings per week 
 0 178 (41.2) 319 (39.2) 0.291b 
 0.1–1. 56 125 (28.9) 224 (27.6)  
 ≥1.57 129 (29.9) 270 (33.2)  
Total folate intake (μg) per kcal per day 
 <0.30 124 (28.7) 195 (24.0) 0.136b 
 0.30–0.40 105 (24.3) 204 (25.1)  
 0.41–0.58 97 (22.5) 205 (25.2)  
 ≥0.59 106 (24.5) 210 (25.8)  
Red meat intake (medium serving) per kcal per day × 103 
 <0.20 111 (25.7) 209 (25.7) 0.714b 
 0.20–0.34 111 (25.7) 204 (25.1)  
 0.35–0.52 112 (25.9) 202 (24.8)  
 ≥0.53 98 (22.7) 199 (24.5)  
BMI (kg/m2
 <25 149 (35.0) 316 (39.8) 0.028b 
 25–29.9 151 (35.5) 288 (36.3)  
 ≥30 126 (29.6) 190 (23.9)  
Waist circumference (cm) 
 <74.6 67 (15.5) 196 (24.2) <0.001b 
 74.6–81.9 91 (21.0) 185 (22.8)  
 82.0–91.4 124 (28.6) 219 (27.0)  
 ≥91.5 151 (34.9) 210 (25.9)  
Physical activity (MET/wk) 
 <3.8 124 (28.9) 203 (25.2) 0.030b 
 3.8–9.9 110 (25.6) 200 (24.8)  
 10.0–19.9 113 (26.3) 201 (24.9)  
 ≥20 82 (19.2) 203 (25.2)  
Serum estradiol (pg/mL)c 
 <8 72 (26.5) 146 (33.4)  
 8–13.9 103 (37.8) 132 (30.2) 0.018 
 ≥14 97 (35.7) 159 (36.4) 0.271 
Serum insulin (μU/mL) 
 <3.2 73 (17.2) 193 (24.2) <0.001b 
 3.2–4.9 92 (21.7) 189 (23.7)  
 5.0–8.2 107 (25.2) 202 (25.4)  
 ≥8.3 153 (36.0) 213 (26.7)  
Plasma leptin (ng/mL) 
 <7.4 82 (19.0) 213 (26.2) 0.001b 
 7.4–15.0 120 (27.8) 209 (25.7)  
 15.1–25.5 88 (20.4) 201 (24.7)  
 ≥25.6 142 (32.9) 191 (23.5)  
Plasma IL-6 (pg/mL) 
 <0.93 87 (20.2) 205 (26.0) 0.001b 
 0.93–1.47 98 (22.8) 207 (26.3)  
 1.48–2.31 121 (28.1) 200 (25.4)  
 ≥2.32 124 (28.8) 176 (22.3)  
Plasma TNF-α (pg/mL) 
 <1.82 99 (23.1) 196 (24.8) 0.147b 
 1.82–2.62 103 (24.0) 205 (25.9)  
 2.63–3.62 106 (24.7) 203 (25.6)  
 ≥3.63 121 (28.2) 188 (23.7)  
Plasma levels of six analytes under study 
sgp130 (ng/mL) 
 <146.2 99 (22.9) 203 (24.9) 0.697b 
 146.2–172.1 110 (25.4) 208 (25.6)  
 172.2–200.0 123 (28.4) 199 (24.5)  
 ≥200.1 101 (23.3) 204 (25.1)  
sIL-6R (ng/mL) 
 <16.7 126 (29.1) 207 (25.4) 0.023b 
 16.7–21.1 116 (26.8) 198 (24.3)  
 21.2–25.4 105 (24.3) 204 (25.1)  
 ≥25.5 86 (19.9) 205 (25.2)  
sIL-1R2 (ng/mL) 
 <5.8 130 (30.0) 197 (24.2) 0.019b 
 5.8–7.3 101 (23.3) 209 (25.7)  
 7.4–9.1 122 (28.2) 208 (25.6)  
 ≥9.2 80 (18.5) 200 (24.6)  
IL-1Ra (pg/mL) 
 <15.5 112 (25.9) 204 (25.1) 0.911b 
 15.5–24.1 98 (22.6) 205 (25.2)  
 24.2–38.8 118 (27.3) 206 (25.3)  
 ≥38.9 105 (24.3) 199 (24.5)  
sTNFR1 (ng/mL) 
 <1.0 82 (18.9) 210 (25.8) 0.005b 
 1.0–1.2 108 (24.9) 204 (25.1)  
 1.3–1.5 117 (27.0) 203 (24.9)  
 ≥1.6 126 (29.1) 197 (24.2)  
sTNFR2 (ng/mL) 
 <3.8 81 (18.7) 214 (26.3) 0.012b 
 3.8–4.4 112 (25.9) 207 (25.4)  
 4.5–5.4 132 (30.5) 203 (24.9)  
 ≥5.5 108 (24.9) 190 (23.3)  

Abbreviation: MET, metabolic equivalent of task.

aExcluding seven cases in the subcohort.

bP value for trend.

cAmong women not using hormone therapy at baseline.

Several of the demographic and lifestyle variables in Table 1 remained to be associated with colorectal cancer risk in multivariable analyses. Associations of the six analytes with these significant baseline risk factors for colorectal cancer are shown in Table 2. Sgp130, sTNFR1, and sTNFR2 increased with age. None was related to cigarette smoking. Use of hormone therapy was associated with reduced levels of all six analytes. Greater adiposity was associated with higher levels of IL-1Ra, sTNFR1, and sTNFR2. Concentrations of sIL-1R2, IL-1Ra, sTNFR1, and sTNFR2 increased with circulating levels of obesity-related factors (insulin and leptin).

Table 2.

Associations of soluble cytokine receptors and receptor antagonist with significant risk factors of colorectal cancer among subcohort subjects in the WHI

sgp130 (ng/mL)sIL-6R (ng/mL)sIL-1R2 (ng/mL)IL-1Ra (pg/mL)sTNFR1 (ng/mL)sTNFR2 (ng/mL)
NMedianIQRMedianIQRMedianIQRMedianIQRMedianIQRMedianIQR
Age 
 <55 131 163 134 193 20.4 15.8 25.8 7.2 5.3 9.0 24.0 14.7 45.1 1.1 1.0 1.4 4.1 3.4 4.9 
 55–64 351 171 146 195 21.1 16.5 25.0 7.2 5.8 9.2 24.1 15.6 36.7 1.2 1.0 1.5 4.3 3.6 5.2 
 65–74 287 176 150 205 21.5 17.7 26.1 7.5 5.9 9.2 24.3 15.5 39.4 1.4 1.1 1.7 4.8 4.1 5.8 
 ≥75 52 180 160 201 22.4 16.8 27.4 7.6 6.2 9.4 24.5 15.7 38.5 1.4 1.2 1.8 5.2 4.5 6.5 
P 0.010   0.391   0.448   0.975   <0.0001   <0.0001   
Smoking 
 Never 437 175 149 202 21.5 17.1 25.1 7.2 5.8 9.0 24.1 15.9 39.7 1.3 1.0 1.6 4.6 3.8 5.5 
 Former 323 169 143 195 20.8 16.7 25.6 7.6 5.9 9.4 25.3 15.4 39.2 1.2 1.0 1.6 4.4 3.7 5.3 
 Current 50 173 150 195 20.8 14.9 27.7 8.4 6.0 10.0 19.8 11.6 29.8 1.2 1.0 1.4 4.3 3.8 5.4 
P 0.262   0.916   0.049   0.122   0.685   0.173   
Hormone therapy at baseline 
 No 450 179 153 207 21.6 17.2 26.3 7.8 6.1 9.4 25.6 16.5 41.7 1.3 1.1 1.6 4.7 3.8 5.5 
 Yes 370 166 141 186 20.4 16.1 24.6 7.0 5.5 8.7 22.8 14.3 35.0 1.2 1.0 1.5 4.3 3.6 5.2 
P <0.0001   0.009   <0.0001   0.006   0.001   0.002   
Colonoscopy ever 
 No 355 171 144 200 21.2 16.5 26.2 7.7 5.9 9.4 24.1 15.3 38.5 1.2 1.0 1.6 4.4 3.6 5.3 
 Yes 460 174 149 201 21.3 16.9 25.1 7.2 5.7 9.0 24.1 15.4 38.5 1.3 1.0 1.6 4.6 3.8 5.5 
P 0.148   0.828   0.151   0.631   0.156   0.086   
Waist circumference 
 <74.6 199 175 146 203 20.5 15.9 25.4 7.3 5.8 9.0 19.6 12.6 33.0 1.2 0.9 1.4 4.2 3.6 4.9 
 74.6–81.9 186 168 141 189 20.8 16.5 25.6 6.9 5.4 8.4 24.2 15.1 36.4 1.2 1.0 1.5 4.3 3.6 5.2 
 82–91.4 220 175 155 205 22.2 17.8 25.9 7.8 6.1 9.5 25.6 15.6 38.2 1.3 1.1 1.5 4.5 3.9 5.5 
 ≥91.5 212 168 141 203 20.6 17.0 25.2 7.8 5.9 9.5 27.9 18.2 44.5 1.4 1.1 1.7 5.0 4.2 5.9 
P 0.011   0.187   0.000   <0.0001   <0.0001   <0.0001   
Estradiol (pg/mL)a 
 <8 147 186 150 213 23.1 19.1 27.3 8.3 6.4 9.8 25.7 17.7 46.8 1.3 1.1 1.5 4.6 4.0 5.6 
 8–13.9 134 173 152 201 21.7 16.5 26.0 7.9 6.2 9.4 24.7 15.6 36.7 1.3 1.1 1.7 4.6 3.7 5.3 
 ≥14 161 179 153 209 20.4 16.8 25.2 7.3 5.7 9.2 26.7 16.5 43.3 1.3 1.0 1.7 4.8 3.8 5.7 
P 0.230   0.014   0.045   0.439   0.903   0.279   
Insulin (μU/mL) 
 <3.2 196 175 146 202 20.3 16.2 25.2 7.0 5.6 8.6 21.7 12.9 35.8 1.1 0.9 1.4 4.1 3.5 4.9 
 3.2–4.9 191 172 146 199 21.1 15.8 25.1 7.2 5.8 8.6 22.0 14.0 32.0 1.3 1.1 1.6 4.4 3.8 5.4 
 5.0–8.2 203 172 141 203 22.0 17.2 26.1 7.7 6.1 9.1 22.2 14.7 35.2 1.3 1.1 1.5 4.5 3.7 5.3 
 ≥8.3 214 172 150 196 21.5 17.3 26.0 7.9 6.1 9.8 30.9 19.7 51.2 1.4 1.1 1.7 5.0 4.1 6.1 
P 0.988   0.163   0.003   <0.0001   <0.0001   <0.0001   
Leptin (ng/mL) 
 <7.4 216 171 142 193 20.5 15.8 25.4 7.0 5.5 8.4 22.2 13.6 35.7 1.2 1.0 1.4 4.3 3.6 5.0 
 7.4–15.0 210 171 149 204 21.4 16.9 25.6 7.2 5.7 9.1 23.5 15.3 34.5 1.2 1.0 1.5 4.3 3.6 5.2 
 15.1–25.5 203 172 147 201 21.3 17.2 26.1 7.4 6.1 9.1 23.4 15.1 40.2 1.3 1.1 1.6 4.3 3.7 5.3 
 ≥25.6 192 174 149 202 21.7 16.6 25.5 8.2 6.0 9.7 27.9 18.2 47.9 1.4 1.1 1.7 5.1 4.3 5.9 
P 0.665   0.538   0.001   0.001   <0.0001   <0.0001   
sgp130 (ng/mL)sIL-6R (ng/mL)sIL-1R2 (ng/mL)IL-1Ra (pg/mL)sTNFR1 (ng/mL)sTNFR2 (ng/mL)
NMedianIQRMedianIQRMedianIQRMedianIQRMedianIQRMedianIQR
Age 
 <55 131 163 134 193 20.4 15.8 25.8 7.2 5.3 9.0 24.0 14.7 45.1 1.1 1.0 1.4 4.1 3.4 4.9 
 55–64 351 171 146 195 21.1 16.5 25.0 7.2 5.8 9.2 24.1 15.6 36.7 1.2 1.0 1.5 4.3 3.6 5.2 
 65–74 287 176 150 205 21.5 17.7 26.1 7.5 5.9 9.2 24.3 15.5 39.4 1.4 1.1 1.7 4.8 4.1 5.8 
 ≥75 52 180 160 201 22.4 16.8 27.4 7.6 6.2 9.4 24.5 15.7 38.5 1.4 1.2 1.8 5.2 4.5 6.5 
P 0.010   0.391   0.448   0.975   <0.0001   <0.0001   
Smoking 
 Never 437 175 149 202 21.5 17.1 25.1 7.2 5.8 9.0 24.1 15.9 39.7 1.3 1.0 1.6 4.6 3.8 5.5 
 Former 323 169 143 195 20.8 16.7 25.6 7.6 5.9 9.4 25.3 15.4 39.2 1.2 1.0 1.6 4.4 3.7 5.3 
 Current 50 173 150 195 20.8 14.9 27.7 8.4 6.0 10.0 19.8 11.6 29.8 1.2 1.0 1.4 4.3 3.8 5.4 
P 0.262   0.916   0.049   0.122   0.685   0.173   
Hormone therapy at baseline 
 No 450 179 153 207 21.6 17.2 26.3 7.8 6.1 9.4 25.6 16.5 41.7 1.3 1.1 1.6 4.7 3.8 5.5 
 Yes 370 166 141 186 20.4 16.1 24.6 7.0 5.5 8.7 22.8 14.3 35.0 1.2 1.0 1.5 4.3 3.6 5.2 
P <0.0001   0.009   <0.0001   0.006   0.001   0.002   
Colonoscopy ever 
 No 355 171 144 200 21.2 16.5 26.2 7.7 5.9 9.4 24.1 15.3 38.5 1.2 1.0 1.6 4.4 3.6 5.3 
 Yes 460 174 149 201 21.3 16.9 25.1 7.2 5.7 9.0 24.1 15.4 38.5 1.3 1.0 1.6 4.6 3.8 5.5 
P 0.148   0.828   0.151   0.631   0.156   0.086   
Waist circumference 
 <74.6 199 175 146 203 20.5 15.9 25.4 7.3 5.8 9.0 19.6 12.6 33.0 1.2 0.9 1.4 4.2 3.6 4.9 
 74.6–81.9 186 168 141 189 20.8 16.5 25.6 6.9 5.4 8.4 24.2 15.1 36.4 1.2 1.0 1.5 4.3 3.6 5.2 
 82–91.4 220 175 155 205 22.2 17.8 25.9 7.8 6.1 9.5 25.6 15.6 38.2 1.3 1.1 1.5 4.5 3.9 5.5 
 ≥91.5 212 168 141 203 20.6 17.0 25.2 7.8 5.9 9.5 27.9 18.2 44.5 1.4 1.1 1.7 5.0 4.2 5.9 
P 0.011   0.187   0.000   <0.0001   <0.0001   <0.0001   
Estradiol (pg/mL)a 
 <8 147 186 150 213 23.1 19.1 27.3 8.3 6.4 9.8 25.7 17.7 46.8 1.3 1.1 1.5 4.6 4.0 5.6 
 8–13.9 134 173 152 201 21.7 16.5 26.0 7.9 6.2 9.4 24.7 15.6 36.7 1.3 1.1 1.7 4.6 3.7 5.3 
 ≥14 161 179 153 209 20.4 16.8 25.2 7.3 5.7 9.2 26.7 16.5 43.3 1.3 1.0 1.7 4.8 3.8 5.7 
P 0.230   0.014   0.045   0.439   0.903   0.279   
Insulin (μU/mL) 
 <3.2 196 175 146 202 20.3 16.2 25.2 7.0 5.6 8.6 21.7 12.9 35.8 1.1 0.9 1.4 4.1 3.5 4.9 
 3.2–4.9 191 172 146 199 21.1 15.8 25.1 7.2 5.8 8.6 22.0 14.0 32.0 1.3 1.1 1.6 4.4 3.8 5.4 
 5.0–8.2 203 172 141 203 22.0 17.2 26.1 7.7 6.1 9.1 22.2 14.7 35.2 1.3 1.1 1.5 4.5 3.7 5.3 
 ≥8.3 214 172 150 196 21.5 17.3 26.0 7.9 6.1 9.8 30.9 19.7 51.2 1.4 1.1 1.7 5.0 4.1 6.1 
P 0.988   0.163   0.003   <0.0001   <0.0001   <0.0001   
Leptin (ng/mL) 
 <7.4 216 171 142 193 20.5 15.8 25.4 7.0 5.5 8.4 22.2 13.6 35.7 1.2 1.0 1.4 4.3 3.6 5.0 
 7.4–15.0 210 171 149 204 21.4 16.9 25.6 7.2 5.7 9.1 23.5 15.3 34.5 1.2 1.0 1.5 4.3 3.6 5.2 
 15.1–25.5 203 172 147 201 21.3 17.2 26.1 7.4 6.1 9.1 23.4 15.1 40.2 1.3 1.1 1.6 4.3 3.7 5.3 
 ≥25.6 192 174 149 202 21.7 16.6 25.5 8.2 6.0 9.7 27.9 18.2 47.9 1.4 1.1 1.7 5.1 4.3 5.9 
P 0.665   0.538   0.001   0.001   <0.0001   <0.0001   

Abbreviation: IQR, interquartile range.

aAmong women not using hormone therapy at baseline.

Table 3 shows the correlations among the analytes and the ligands IL-6 and TNF-α. The highest correlations were between sTNFR1 and sTNFR2 (r = 0.51) and between TNF-α and sTNFR2 (r = 0.43). The ratios of soluble receptors to their ligands (e.g., sIL-6R/IL-6) were not meaningful indices, because they merely reflected the ligand levels and were highly correlated with them (∣r∣ > 0.80).

Table 3.

Spearman rank correlations among soluble cytokine receptors, receptor antagonist, their ligands, and ratios of receptor to ligand (P values shown in parentheses)

sIL-6RsIL-1R2IL-1RasTNFR1sTNFR2IL-6TNF-αsgp130/IL-6sIL6R/IL-6sTNFR1/TNFsTNFR2/TNF
sgp130 0.17 (<0.0001) 0.26 (<0.0001) 0.03 (0.331) 0.17 (<0.0001) 0.19 (<0.0001) −0.01 (0.875) 0.06 (0.085) 0.32 (<0.0001) 0.08 (0.032) 0.03 (0.363) 0.03 (0.436) 
sIL-6R  0.18 (<0.0001) 0.06 (0.098) 0.19 (<0.0001) 0.20 (<0.0001) 0.06 (0.099) 0.13 (0.0002) 0.01 (0.836) 0.33 (<0.0001) −0.03 (0.392) −0.04 (0.321) 
sIL-1R2   0.10 (0.004) 0.12 (0.001) 0.10 (0.006) 0.03 (0.331) 0.06 (0.104) 0.05 (0.186) 0.03 (0.334) 0.03 (0.448) 0.01 (0.866) 
IL1RA    0.18 (<0.0001) 0.18 (<0.0001) 0.14 (0.0001) 0.10 (0.006) −0.12 (0.001) −0.10 (0.004) −0.02 (0.670) −0.02 (0.535) 
sTNFR1     0.51 (<0.0001) 0.24 (<0.0001) 0.26 (<0.0001) −0.17 (<0.0001) −0.14 (<0.0001) 0.28 (<0.0001) 0.00 (0.978) 
sTNFR2      0.30 (<0.0001) 0.43 (<0.0001) −0.23 (<0.0001) −0.19 (<0.0001) −0.14 (0.0001) 0.07 (0.052) 
IL-6       0.23 (<0.0001) 0.93 (<0.0001) 0.90 (<0.0001) −0.08 (0.025) −0.09 (0.010) 
TNF-α        −0.21 (<0.0001) −0.17 (<0.0001) 0.80 (<0.0001) 0.84 (<0.0001) 
sgp130/IL-6         0.87 (<0.0001) 0.09 (0.009) 0.10 (0.005) 
sIL6R/IL-6          0.07 (0.055) 0.07 (0.035) 
sTNFR1/TNF           0.82 (<0.0001) 
sIL-6RsIL-1R2IL-1RasTNFR1sTNFR2IL-6TNF-αsgp130/IL-6sIL6R/IL-6sTNFR1/TNFsTNFR2/TNF
sgp130 0.17 (<0.0001) 0.26 (<0.0001) 0.03 (0.331) 0.17 (<0.0001) 0.19 (<0.0001) −0.01 (0.875) 0.06 (0.085) 0.32 (<0.0001) 0.08 (0.032) 0.03 (0.363) 0.03 (0.436) 
sIL-6R  0.18 (<0.0001) 0.06 (0.098) 0.19 (<0.0001) 0.20 (<0.0001) 0.06 (0.099) 0.13 (0.0002) 0.01 (0.836) 0.33 (<0.0001) −0.03 (0.392) −0.04 (0.321) 
sIL-1R2   0.10 (0.004) 0.12 (0.001) 0.10 (0.006) 0.03 (0.331) 0.06 (0.104) 0.05 (0.186) 0.03 (0.334) 0.03 (0.448) 0.01 (0.866) 
IL1RA    0.18 (<0.0001) 0.18 (<0.0001) 0.14 (0.0001) 0.10 (0.006) −0.12 (0.001) −0.10 (0.004) −0.02 (0.670) −0.02 (0.535) 
sTNFR1     0.51 (<0.0001) 0.24 (<0.0001) 0.26 (<0.0001) −0.17 (<0.0001) −0.14 (<0.0001) 0.28 (<0.0001) 0.00 (0.978) 
sTNFR2      0.30 (<0.0001) 0.43 (<0.0001) −0.23 (<0.0001) −0.19 (<0.0001) −0.14 (0.0001) 0.07 (0.052) 
IL-6       0.23 (<0.0001) 0.93 (<0.0001) 0.90 (<0.0001) −0.08 (0.025) −0.09 (0.010) 
TNF-α        −0.21 (<0.0001) −0.17 (<0.0001) 0.80 (<0.0001) 0.84 (<0.0001) 
sgp130/IL-6         0.87 (<0.0001) 0.09 (0.009) 0.10 (0.005) 
sIL6R/IL-6          0.07 (0.055) 0.07 (0.035) 
sTNFR1/TNF           0.82 (<0.0001) 

NOTE: Correlations >0.4 were bolded.

The results of age-adjusted as well as multivariable adjusted analyses are shown in Table 4. After adjusting for the significant covariates in the base model (including age, race, smoking status, ever had colonoscopy, estrogen level, waist circumference, insulin level, and leptin level), two soluble cytokine receptors, sIL-6R and sIL-1R2, were inversely associated with colorectal cancer risk, with HRs comparing extreme quartiles (HRQ4-Q1) of 0.56 for sIL-6R [95% confidence interval (CI), 0.38–0.83; Ptrend = 0.007] and 0.44 for sIL-1R2 (95% CI, 0.29–0.67; Ptrend = 0.0004); sTNFR1 and sTNRF2 were no longer significantly associated with colorectal cancer risk. When all the six analytes and the ligands IL-6 and TNF-α were analyzed simultaneously, sIL-6R and sIL-1R2 remained significant (Table 4). In a saturated model, we adjusted for all the established risk factors, by including covariates that were not statistically associated with colorectal cancer into the base model (e.g., use of NSAIDs and alcohol, physical activity, family history of colorectal cancer, and folate and red meat intakes per day), and similar results were obtained (data not shown).

Table 4.

HRs for the associations of soluble cytokine receptors and receptor antagonist with colorectal cancer risk

Q1Q2Q3Q4P for trend
sgp130 (ng/mL) <146.2 146.2–172.1 172.2–200.0 ≥200.1  
# cases/# subcohort 99/204 110/209 123/199 101/209  
 Age 1.04 (0.74–1.47) 1.17 (0.83–1.65) 0.90 (0.63–1.27) 0.694 
 Base modela 1.05 (0.72–1.53) 1.05 (0.71–1.54) 0.94 (0.64–1.37) 0.754 
 Base + other receptors + ligandsb 1.19 (0.80–1.76) 1.14 (0.74–1.75) 1.12 (0.72–1.75) 0.654 
sIL-6R (ng/mL) <16.7 16.7–21.1 21.2–25.4 ≥25.5  
# cases/# subcohort 126/207 116/202 105/205 86/207  
 Age 0.86 (0.62–1.20) 0.78 (0.55–1.09) 0.58 (0.41–0.83) 0.002 
 Base modela 0.82 (0.56–1.21) 0.82 (0.55–1.21) 0.56 (0.38–0.83) 0.007 
 Base + other receptors + ligandsb 0.82 (0.55–1.23) 0.82 (0.54–1.26) 0.59 (0.38–0.90) 0.022 
sIL-1R2 (ng/mL) <5.8 5.8–7.3 7.4–9.1 ≥9.2  
# cases/# subcohort 130/202 101/209 122/210 80/200  
 Age 0.73 (0.52–1.02) 0.85 (0.62–1.18) 0.59 (0.41–0.84) 0.014 
 Base modela 0.69 (0.47–1.01) 0.79 (0.55–1.13) 0.44 (0.29–0.67) <0.001 
 Base + other receptors + ligandsb 0.68 (0.45–1.03) 0.79 (0.53–1.16) 0.44 (0.28–0.71) 0.003 
IL-1Ra (pg/mL) <15.5 15.5–24.1 24.2–38.8 ≥38.9  
# cases/# subcohort 112/206 98/207 118/207 105/201  
 Age 0.86 (0.61–1.22) 1.05 (0.75–1.46) 0.93 (0.66–1.30) 0.942 
 Base modela 0.72 (0.48–1.06) 0.79 (0.54–1.16) 0.73 (0.49–1.10) 0.227 
 Base + other receptors + ligandsb 0.80 (0.52–1.23) 0.78 (0.52–1.16) 0.84 (0.54–1.31) 0.420 
sTNFR1 (ng/mL) <1.0 1.0–1.2 1.3–1.5 ≥1.6  
# cases/# subcohort 82/211 108/206 117/204 126/200  
 Age 1.23 (0.86–1.75) 1.33 (0.94–1.90) 1.42 (0.99–2.03) 0.054 
 Base modela 1.11 (0.74–1.66) 1.31 (0.88–1.95) 1.03 (0.68–1.56) 0.766 
 Base + other receptors + ligandsb 1.16 (0.74–1.81) 1.56 (0.98–2.49) 1.29 (0.80–2.10) 0.191 
sTNFR2 (ng/mL) <3.8 3.8–4.4 4.5–5.4 ≥5.5  
# cases/# subcohort 81/214 112/208 132/206 108/193  
 Age 1.26 (0.88–1.80) 1.42 (1.00–2.02) 1.14 (0.79–1.64) 0.428 
 Base modela 1.10 (0.74–1.62) 1.20 (0.81–1.79) 0.82 (0.53–1.28) 0.441 
 Base + other receptors + ligandsb 1.05 (0.69–1.59) 1.27 (0.79–2.04) 0.90 (0.52–1.56) 0.893 
Q1Q2Q3Q4P for trend
sgp130 (ng/mL) <146.2 146.2–172.1 172.2–200.0 ≥200.1  
# cases/# subcohort 99/204 110/209 123/199 101/209  
 Age 1.04 (0.74–1.47) 1.17 (0.83–1.65) 0.90 (0.63–1.27) 0.694 
 Base modela 1.05 (0.72–1.53) 1.05 (0.71–1.54) 0.94 (0.64–1.37) 0.754 
 Base + other receptors + ligandsb 1.19 (0.80–1.76) 1.14 (0.74–1.75) 1.12 (0.72–1.75) 0.654 
sIL-6R (ng/mL) <16.7 16.7–21.1 21.2–25.4 ≥25.5  
# cases/# subcohort 126/207 116/202 105/205 86/207  
 Age 0.86 (0.62–1.20) 0.78 (0.55–1.09) 0.58 (0.41–0.83) 0.002 
 Base modela 0.82 (0.56–1.21) 0.82 (0.55–1.21) 0.56 (0.38–0.83) 0.007 
 Base + other receptors + ligandsb 0.82 (0.55–1.23) 0.82 (0.54–1.26) 0.59 (0.38–0.90) 0.022 
sIL-1R2 (ng/mL) <5.8 5.8–7.3 7.4–9.1 ≥9.2  
# cases/# subcohort 130/202 101/209 122/210 80/200  
 Age 0.73 (0.52–1.02) 0.85 (0.62–1.18) 0.59 (0.41–0.84) 0.014 
 Base modela 0.69 (0.47–1.01) 0.79 (0.55–1.13) 0.44 (0.29–0.67) <0.001 
 Base + other receptors + ligandsb 0.68 (0.45–1.03) 0.79 (0.53–1.16) 0.44 (0.28–0.71) 0.003 
IL-1Ra (pg/mL) <15.5 15.5–24.1 24.2–38.8 ≥38.9  
# cases/# subcohort 112/206 98/207 118/207 105/201  
 Age 0.86 (0.61–1.22) 1.05 (0.75–1.46) 0.93 (0.66–1.30) 0.942 
 Base modela 0.72 (0.48–1.06) 0.79 (0.54–1.16) 0.73 (0.49–1.10) 0.227 
 Base + other receptors + ligandsb 0.80 (0.52–1.23) 0.78 (0.52–1.16) 0.84 (0.54–1.31) 0.420 
sTNFR1 (ng/mL) <1.0 1.0–1.2 1.3–1.5 ≥1.6  
# cases/# subcohort 82/211 108/206 117/204 126/200  
 Age 1.23 (0.86–1.75) 1.33 (0.94–1.90) 1.42 (0.99–2.03) 0.054 
 Base modela 1.11 (0.74–1.66) 1.31 (0.88–1.95) 1.03 (0.68–1.56) 0.766 
 Base + other receptors + ligandsb 1.16 (0.74–1.81) 1.56 (0.98–2.49) 1.29 (0.80–2.10) 0.191 
sTNFR2 (ng/mL) <3.8 3.8–4.4 4.5–5.4 ≥5.5  
# cases/# subcohort 81/214 112/208 132/206 108/193  
 Age 1.26 (0.88–1.80) 1.42 (1.00–2.02) 1.14 (0.79–1.64) 0.428 
 Base modela 1.10 (0.74–1.62) 1.20 (0.81–1.79) 0.82 (0.53–1.28) 0.441 
 Base + other receptors + ligandsb 1.05 (0.69–1.59) 1.27 (0.79–2.04) 0.90 (0.52–1.56) 0.893 

aBase model included the following baseline covariates: age, race, smoking status, ever had colonoscopy, estrogen level, waist circumference, insulin level, and leptin level.

bBase model covariates + sgp130 + sIL-6R + sIL-1R2 + IL-1Ra + sTNFR1 + sTNFR2 + IL-6 + TNF-α.

There were no significant interactions among the soluble cytokine receptors, receptor antagonist, IL-6, and TNF-α (data not shown), or between the study analytes and colorectal cancer risk factors (e.g., waist circumference, insulin, and hormone therapy, etc.). Results were similar when data were stratified by NSAID status at baseline (used regularly for ≥ 2 weeks or not) or when the 78 rectosigmoid junction or rectal cancer cases were excluded (data not shown).

When colorectal cancer cases were stratified by the number of years from baseline blood collection to case diagnosis in a sensitivity analysis (Table 5), sIL-6R was inversely associated with colorectal cancer risk only in those diagnosed between >1 to 5 years of baseline, but not in the cases diagnosed >5 years after baseline. In contrast, the inverse association between sIL-1R2 and colorectal cancer risk persisted regardless of the year of diagnosis (the last case was diagnosed 8.2 years after baseline in the study population reported here).

Table 5.

HRs for the associations of sIL-6R and sIL-1R2 with colorectal cancer risk stratified by the number of years from baseline recruitment to case diagnosis

Q1Q2Q3Q4P for trend
sIL-6R (ng/mL) <16.7 16.7–21.1 21.2–25.4 ≥25.5  
 Cases diagnosed >1 to 5 years after baseline      
  # cases/# subcohort 96/196 88/195 73/188 52/198  
  Base + other receptors + ligandsa 0.87 (0.57–1.34) 0.77 (0.49–1.21) 0.50 (0.31–0.79) 0.003 
 Cases diagnosed >5 years after baseline      
  # cases/# subcohort 21/159 19/163 26/155 29/173  
  Base + other receptors + ligandsa 0.59 (0.24–1.44) 1.01 (0.44–2.31) 0.90 (0.41–1.98) 0.835 
sIL-1R2 (ng/mL) <5.8 5.8–7.3 7.4–9.1 ≥9.2  
 Cases diagnosed >1 to 5 years after baseline      
  # cases/# subcohort 94/188 69/197 89/201 57/191  
  Base + other receptors + ligandsa 0.72 (0.46–1.12) 0.91 (0.60–1.37) 0.49 (0.30–0.80) 0.019 
 Cases diagnosed >5 years after baseline      
  # cases/# subcohort 30/157 22/165 24/173 19/155  
  Base + other receptors + ligandsa 0.55 (0.24–1.23) 0.36 (0.14–0.91) 0.26 (0.09–0.77) 0.013 
Q1Q2Q3Q4P for trend
sIL-6R (ng/mL) <16.7 16.7–21.1 21.2–25.4 ≥25.5  
 Cases diagnosed >1 to 5 years after baseline      
  # cases/# subcohort 96/196 88/195 73/188 52/198  
  Base + other receptors + ligandsa 0.87 (0.57–1.34) 0.77 (0.49–1.21) 0.50 (0.31–0.79) 0.003 
 Cases diagnosed >5 years after baseline      
  # cases/# subcohort 21/159 19/163 26/155 29/173  
  Base + other receptors + ligandsa 0.59 (0.24–1.44) 1.01 (0.44–2.31) 0.90 (0.41–1.98) 0.835 
sIL-1R2 (ng/mL) <5.8 5.8–7.3 7.4–9.1 ≥9.2  
 Cases diagnosed >1 to 5 years after baseline      
  # cases/# subcohort 94/188 69/197 89/201 57/191  
  Base + other receptors + ligandsa 0.72 (0.46–1.12) 0.91 (0.60–1.37) 0.49 (0.30–0.80) 0.019 
 Cases diagnosed >5 years after baseline      
  # cases/# subcohort 30/157 22/165 24/173 19/155  
  Base + other receptors + ligandsa 0.55 (0.24–1.23) 0.36 (0.14–0.91) 0.26 (0.09–0.77) 0.013 

aBase model covariates (age, race, smoking status, ever had colonoscopy, estrogen level, waist circumference, insulin level, and leptin level) + sgp130 + sIL-6R + sIL-1R2 + IL-1Ra + sTNFR1 + sTNFR2 + IL-6 + TNF-α.

In this study, we found high levels of sIL-1R2, but not IL-1Ra, to be associated with a reduced risk of colorectal cancer. IL-1 signaling can be inhibited by its receptor antagonist (IL-1Ra) and soluble type I and type II IL-1 receptors (sIL-1R1 and sIL-1R2; refs. 4, 13). We measured sIL-1R2 instead of sIL-1R1, because sIL-1R2 is the dominant soluble receptor and has greater affinity for IL-1 than sIL-R1 (4, 24). sIL-1R2 functions as a molecular decoy that prevents interaction of IL-1 with the signal-transducing type I receptor. Our finding of the inverse association between colorectal cancer risk and sIL-1R2 is consistent with the results of a study on Crohn's disease, an inflammatory bowel disease associated with high risk of colorectal cancer, in which both circulating and mucosal sIL-1R2 levels were significantly higher in healthy controls than patients and treatment with corticosteroids induced a significant increase in sIL-1R2 (25). In accord with our present findings, in our previous study of patients with a history of colorectal adenoma, we did not observe any effects of IL-1Ra on adenoma recurrence (21).

Laboratory studies have shown that a very high concentration of sIL-1R2 relative to IL-1 is required to block IL-1 biologic activity, as affinity of the soluble receptor is generally weaker than that of the membrane-bound receptor (4). We did not measure IL-1β in this study, because of its low circulating level. In a pilot study of 25 EDTA plasma samples from postmenopausal women, 36% of the samples had IL-1β levels below the assay limit of detection of 0.06 pg/mL (MILLIPLEX High Sensitivity Human Cytokine Panel), and the median level among samples with a detectable level was 1.2 pg/mL. On the other hand, in the subcohort of this study, the median sIL-1R2 level was 7,385 pg/mL. It then seems that the circulating concentration of sIL-1R2 greatly exceeds that of IL-1β. As such, the ratio of sIL-1R2 to IL-1β levels, even if data on IL-1β were available in our study, would not be a useful indicator for the level of free IL-1β in circulation.

Although we found that a low level of sIL-6R was associated with increased colorectal cancer risk, this inverse association was only seen in the cases diagnosed in the first 5 years, suggesting the relatively low levels of sIL-6R in the baseline blood samples of cases might have arisen as a result of undiagnosed colorectal neoplasia at the time of the blood draw. A previous study of colorectal tumor tissue also indicated that sIL-6R level could be a marker for tumor growth (26). Specifically, this study showed that a low level of sIL-6R expression in tumor correlated with increased IL-6 expression and with disease progression, inferring consumption of sIL-6R by increased binding with IL-6 in the cancer stroma may favor tumor growth (26).

We did not find any associations of sTNFR1 and sTNFR2 with colorectal cancer. Similarly, there were no effects of sTNFR2 on adenoma recurrence in our previous study of patients with a history of colorectal adenoma (21). Contrarily, the Nurses' Health Study found that increased sTNFR2 levels were associated with colorectal cancer risk (8). One possible explanation for this discrepancy is the fact that the assays used for sTNFR2 were different between this study and those used in the Nurses' Health Study.

Similar to the situation of sIL-1R2 and IL-1β, the circulating concentrations of soluble receptors of IL-6 and TNF-α were several thousand-folds greater than those of the ligands (ng vs. pg). As such, their ratios (e.g., sIL-6R/IL-6 or sTNFR1/TNF-α) were not meaningful indices to make any biologic inferences. Although one of the study goals was to examine how the cytokine ligands and their soluble receptors might act together to affect colorectal cancer risk, we could not assess this effectively. Nevertheless, we did not observe any interactive effects between the soluble receptors and their ligands on colorectal cancer risk.

Our study has other limitations. The mechanisms of regulation of circulating sIL-1R2 are unclear. The inverse association between sIL-1R2 and colorectal cancer risk might have been confounded by unmeasured protective factors for colorectal cancer that stimulate the release of sIL-1R2. Moreover, circulating levels of the soluble cytokine receptors and receptor antagonist may not reflect tissue levels. Finally, our results are not necessarily generalizable to men or to premenopausal women.

It is unlikely that our results were confounded by NSAID use, although close to 40% of the study population had used an NSAID regularly for 2 weeks or more at baseline. NSAID use was not associated with colorectal cancer risk in multivariate analyses in our study population. Even when NSAID use was added into the regression model, similar results were obtained. Moreover, there is no evidence in the literature to indicate that NSAID use affects the levels of soluble cytokine receptors and receptor antagonists. In fact, our previous data from an aspirin clinical trial demonstrated that low-dose aspirin had no effects on the circulating levels of sTNFR2 and IL-1Ra (21).

In summary, our data suggest that high circulating levels of sIL-1R2 may be protective against colorectal carcinogenesis or be a marker for reduced colorectal cancer risk. Further investigations of this soluble cytokine receptor are warranted for its potential as a risk-prediction marker or as an immunologic agent for chemoprevention and therapy of colorectal cancer.

No potential conflicts of interest were disclosed.

Conception and design: G.Y.F. Ho, H.D. Strickler, M. Cushman

Development of methodology: X. Xue, A.I. Phipps, M. Cushman

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): G.Y.F. Ho, S.L. Zheng, L. Tinker, S. Wassertheil-Smoller, H.D. Strickler, M. Cushman

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): G.Y.F. Ho, T. Wang, J. Xu, X. Xue, U. Peters, A.I. Phipps, H.D. Strickler, M.J. Gunter

Writing, review, and/or revision of the manuscript: G.Y.F. Ho, T. Wang, L. Tinker, J. Xu, T.E. Rohan, S. Wassertheil-Smoller, L.H. Augenlicht, U. Peters, A.I. Phipps, H.D. Strickler, M.J. Gunter, M. Cushman

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): G.Y.F. Ho

Study supervision: G.Y.F. Ho, S. Wassertheil-Smoller, M. Cushman

The authors thank Elaine Cornell and Danielle Parent for conducting the laboratory measurements and Dan Wang for assistance in data analyses.

This work was supported by grant R01 CA122654 awarded to G.Y.F. Ho from the National Cancer Institute, NIH. The WHI program is funded by the National Heart, Lung, and Blood Institute, NIH, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Philip
M
,
Rowley
DA
,
Schreiber
H
. 
Inflammation as a tumor promoter in cancer induction
.
Semin Cancer Biol
2004
;
14
:
433
9
.
2.
Smyth
MJ
,
Cretney
E
,
Kershaw
MH
,
Hayakawa
Y
. 
Cytokines in cancer immunity and immunotherapy
.
Immunol Rev
2004
;
202
:
275
93
.
3.
Levine
SJ
. 
Molecular mechanisms of soluble cytokine receptor generation
.
J Biol Chem
2008
;
283
:
14177
81
.
4.
Yang
Y
,
Bin
W
,
Aksoy
MO
,
Kelsen
SG
. 
Regulation of interleukin-1beta and interleukin-1beta inhibitor release by human airway epithelial cells
.
Eur Respir J
2004
;
24
:
360
6
.
5.
Pohl
C
,
Hombach
A
,
Kruis
W
. 
Chronic inflammatory bowel disease and cancer
.
Hepatogastroenterol
2000
;
47
:
57
70
.
6.
Tsilidis
KK
,
Branchini
C
,
Guallar
E
,
Helzlsouer
KJ
,
Erlinger
TP
,
Platz
EA
. 
C-reactive protein and colorectal cancer risk: a systematic review of prospective studies
.
Int J Cancer
2008
;
123
:
1133
40
.
7.
Ho
GY
,
Wang
T
,
Gunter
MJ
,
Strickler
HD
,
Cushman
M
,
Kaplan
RC
, et al
Adipokines linking obesity with colorectal cancer risk in postmenopausal women
.
Cancer Res
2012
72
:
3029
37
.
8.
Chan
AT
,
Ogino
S
,
Giovannucci
EL
,
Fuchs
CS
. 
Inflammatory markers are associated with risk of colorectal cancer and chemopreventive response to anti-inflammatory drugs
.
Gastroenterol
2011
;
140
:
799
808
.
9.
Scheller
J
,
Ohnesorge
N
,
Rose-John
S
. 
Interleukin-6 trans-signalling in chronic inflammation and cancer
.
Scand J Immunol
2006
;
63
:
321
9
.
10.
Kohno
T
,
Brewer
MT
,
Baker
SL
,
Schwartz
PE
,
King
MW
,
Hale
KK
, et al
A second tumor necrosis factor receptor gene product can shed a naturally occurring tumor necrosis factor inhibitor
.
Proc Natl Acad Sci U S A
1990
;
87
:
8331
5
.
11.
Van Zee
KJ
,
Kohno
T
,
Fischer
E
,
Rock
CS
,
Moldawer
LL
,
Lowry
SF
. 
Tumor necrosis factor soluble receptors circulate during experimental and clinical inflammation and can protect against excessive tumor necrosis factor a in vitro and in vivo
.
Proc Natl Acad Sci U S A
1992
;
89
:
4845
9
.
12.
Knupfer
H
,
Preiss
R
. 
sIL-6R: more than an agonist
?
Immunol Cell Biol
2008
;
86
:
87
91
.
13.
Arend
WP
,
Guthridge
CJ
. 
Biological role of interleukin 1 receptor antagonist isoforms
.
Ann Rheum Dis
2000
;
59
Suppl 1
:
i60
4
.
14.
Anderson
GL
,
Manson
J
,
Wallace
R
,
Lund
B
,
Hall
D
,
Davis
C
, et al
Implementation of the Women's Health Initiative Study Design
.
Ann Epidemiol
2003
;
13
:
S5
17
.
15.
Gunter
MJ
,
Hoover
DR
,
Yu
H
,
Wassertheil-Smoller
S
,
Manson
JE
,
Li
J
, et al
A prospective evaluation of insulin and insulin-like growth factor-I as risk factors for endometrial cancer
.
Cancer Epidemiol Biomarkers Prev
2008
;
17
:
921
9
.
16.
Gunter
MJ
,
Hoover
DR
,
Yu
H
,
Wassertheil-Smoller
S
,
Rohan
TE
,
Manson
JE
, et al
Insulin, insulin-like growth factor-I, endogenous estradiol, and risk of colorectal cancer in postmenopausal women
.
Cancer Res
2008
;
68
:
329
37
.
17.
Gunter
MJ
,
Hoover
DR
,
Yu
H
,
Wassertheil-Smoller
S
,
Rohan
TE
,
Manson
JE
, et al
Insulin, insulin-like growth factor-I, and risk of breast cancer in postmenopausal women
.
J Natl Cancer Inst
2009
;
101
:
48
60
.
18.
Luminex. xMAP Technology
.
[cited 2013 October 8]; Available from
: http://www.luminexcorp.com/TechnologiesScience/xMAPTechnology/
19.
Kaplan
RC
,
Ho
GY
,
Xue
X
,
Rajpathak
S
,
Cushman
M
,
Rohan
TE
, et al
Within-individual stability of obesity-related biomarkers among women
.
Cancer Epidemiol Biomarkers Prev
2007
;
16
:
1291
3
.
20.
Agalliu
I
,
Xue
X
,
Cushman
M
,
Cornell
E
,
Hsing
AW
,
Kaplan
RC
, et al
Detectability and reproducibility of plasma levels of chemokines and soluble receptors
.
Results Immunol
2013
;
3
:
79
84
.
21.
Ho
GY
,
Xue
X
,
Cushman
M
,
McKeown-Eyssen
G
,
Sandler
RS
,
Ahnen
DJ
, et al
Antagonistic effects of aspirin and folic acid on inflammation markers and subsequent risk of recurrent colorectal adenomas
.
J Natl Cancer Inst
2009
;
101
:
1650
4
.
22.
Self
SG
,
Prentice
RL
. 
Asymptotic distribution theory and efficiency results for case-cohort studies
.
Ann Stat
1988
;
16
:
64
81
.
23.
Barlow
WE
,
Ichikawa
L
,
Rosner
D
,
Izumi
S
. 
Analysis of case-cohort designs
.
J Clin Epidemiol
1999
;
52
:
1165
72
.
24.
Fernandez-Botran
R
,
Crespo
FA
,
Sun
X
. 
Soluble cytokine receptors in biological therapy
.
Expert Opin Biol Ther
2002
;
2
:
585
605
.
25.
Gustot
T
,
Lemmers
A
,
Louis
E
,
Nicaise
C
,
Quertinmont
E
,
Belaiche
J
, et al
Profile of soluble cytokine receptors in Crohn's disease
.
Gut
2005
;
54
:
488
95
.
26.
Okugawa
Y
,
Miki
C
,
Toiyama
Y
,
Yasuda
H
,
Yokoe
T
,
Saigusa
S
, et al
Loss of tumoral expression of soluble IL-6 receptor is associated with disease progression in colorectal cancer
.
Br J Cancer
2010
;
103
:
787
95
.