© 2000 by Oxford University Press
Journal of the National Cancer Institute, Vol. 92, No. 23, 1910-1917,
December 6, 2000
© 2000 Oxford University Press
Plasma Insulin-Like Growth Factor-I, Insulin-Like Growth Factor-Binding Proteins, and Prostate Cancer Risk: a Prospective Study
Affiliations of authors: P. Stattin (Department of Urology and Andrology), A. Bylund (Department of Geriatrics), G. Hallmans (Department of Public Health and Clinical Medicine), Umeå University Hospital, Sweden; S. Rinaldi, C. Biessy, E. Riboli, R. Kaaks, International Agency for Research on Cancer, Lyon, France; H. Déchaud, Central Laboratory for Biochemistry, Hôpital de l'Antiquaille, Lyon; U.-H. Stenman, Department of Clinical Chemistry, Helsinki University Central Hospital, Finland; L. Egevad, Department of Pathology, Karolinska Hospital, Stockholm, Sweden.
Correspondence to: Pär Stattin, M.D., Ph.D., Department of Urology and Andrology, Umeå University Hospital, 901 85 Umeå, Sweden (e-mail: par. stattin{at}urologi.umu.se).
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ABSTRACT |
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Background: Recent studies have suggested that men with elevated plasma levels of insulin-like growth factor-I (IGF-I) may have an increased risk of prostate cancer. Furthermore, IGF-binding proteins (IGFBPs) and insulin can modulate the activity of IGF-I. In this study, we sought to determine the role of IGF-I as well as IGFBPs-1, -2, and -3 and insulin as possible etiologic factors for prostate cancer. Methods: We conducted a nested case–control study within the Northern Sweden Health and Disease Cohort Study. We measured levels of IGF-I, IGFBP-1, IGFBP-2, IGFBP-3, and insulin in plasma samples from 149 men who had a diagnosis of prostate cancer between 1 month and 10 years after blood collection and among 298 control men. All statistical tests are two-sided. Results: Case subjects had statistically significantly higher mean levels of IGF-I than control subjects (229 ng/mL; 95% confidence interval [CI] = 218–240 ng/mL] versus 214 ng/mL [95% CI = 208–221 ng/mL]; P = .02) and IGFBP-3 (2611 ng/mL [95% CI = 2518–2704 ng/mL] versus 2498 ng/mL [95% CI = 2437–2560 ng/mL]; P = .04). Conditional logistic regression analyses showed increases in prostate cancer risk with rising levels of IGF-I (Pfor trend = .02) and IGFBP-3 (Pfor trend = .03). In case subjects younger than 59 years at the time of blood collection, the risk associated with increased IGF-I was higher (Pfor trend = .01), whereas the risk associated with increased IGFBP-3 was lower (Pfor trend = .44) than the corresponding risks in the full cohort. Prostate cancer risk was not associated with levels of IGFBP-1, IGFBP-2, or insulin. Conclusions: Prostate cancer risk is increased in men with elevated plasma IGF-I. This association was particularly strong in younger men in this study, suggesting that circulating IGF-I may be specifically involved in the early pathogenesis of prostate cancer.
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INTRODUCTION |
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Insulin-like growth factor-I (IGF-I) may stimulate the development of prostate cancer by stimulating cell proliferation and by inhibiting apoptosis (1,2). In vitro studies (3,4) have demonstrated that prostatic epithelial cells respond to the mitogenic activity of IGF-I. Moreover, in vivo studies have shown that tumors of the prostate cancer cell line PC-3 have a significantly lower proliferation rate in IGF-I-deficient hosts than in IGF-I-expressing hosts (5). In addition, tumor formation induced by injection of fibroblasts in nude mice is inhibited when the fibroblasts have been transfected with an inactivated human IGF-I receptor (6). In men, one prospective cohort study (7) and two case–control studies (8,9) have shown positive associations between prostate cancer risk and circulating IGF-I level.
The bioactivity of IGF-I is determined by circulating levels, as well as the production within tissues, of IGF-I and at least six different IGF-binding proteins (IGFBPs) (1,10). Most of the circulating IGF-I and the IGFBPs-1, -2, and -3 are produced in the liver, and at least 90% of circulating IGF-I is bound to IGFBP-3, the major binding protein in plasma. The main stimulus for synthesis of IGF-I and IGFBP-3 in the liver as well as in other tissues is provided by growth hormone (GH) (1,11). A second level of regulation of IGF-I bioactivity is provided by insulin. Insulin enhances the GH-stimulated synthesis of IGF-I and IGFBP-3. Furthermore, insulin can increase IGF-I bioactivity by decreasing the synthesis and plasma levels of IGFBP-1 and IGFBP-2.
The circulating levels of IGFBPs-1, -2, and -3 vary in response to nutritional status and in response to changes in energy metabolism (11). In the energy-restricted state, which is strongly protective against many forms of tumors, including prostate cancer (12), circulating levels of IGF-I, IGFBP-3, and insulin are decreased, whereas levels of IGFBPs-1 and -2 are increased (11,13). Overeating and obesity, on the other hand, lead to hyperinsulinemia and decreased levels of IGFBPs-1 and -2 (11,14–16) but have little effect on IGF-I and IGFBP-3 levels. In a recent experimental study in nude mice (17), high caloric intake increased both circulating IGF-I levels and the growth of prostatic tumor implants. In addition to nutritional lifestyle factors, genetic predisposition also plays an important role in determining circulating IGF-I and IGFBP-3 levels (18).
In this prospective, population-based, cohort study, we sought to determine the association between prostate cancer risk and plasma levels of IGF-I, IGFBP-1, IGFBP-2, IGFBP-3, and insulin.
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METHODS |
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Northern Sweden Health and Disease Cohort Study
Men are recruited to the Northern Sweden Health and Disease Cohort Study through the Västerbotten Intervention Project (VIP) and the Northern Sweden part of the World Health Organization (WHO) study for Monitoring of Trends and Cardiovascular Disease Study (MONICA). VIP is an ongoing population-based, intervention study initiated in 1985 that aims to decrease mortality due to cardiovascular disease and cancer by advocating a healthy diet and lifestyle to the general public. VIP invites all persons residing in the county of Västerbotten (total population, 260 000) to participate in a health survey when they reach the ages of 30, 40, 50, and 60 years. In March 1999, a total of 26 856 men had participated in VIP (19). MONICA includes 2704 men, recruited in 1986, 1990, and 1994, who are also a population-based sample from the counties of Västerbotten and Norrbotten (19).
In both projects, subjects were asked to complete a self-administered questionnaire that included questions about demographic, medical, and lifestyle characteristics. In addition, we recorded the subjects' height and weight (recorded to the closest 0.2 kg and cm, respectively) and drew a 20-mL blood sample from each subject at study entry. Because blood samples were collected from most participants in the morning, fasting time before blood donation was more than 8 hours in 60% of the cohort, 4–8 hours in 36%, and less than 4 hours in 4%. The blood was collected in one heparin tube and one EDTA tube, centrifuged at 1500g for 15 minutes at ambient temperature, separated as plasma and buffy coat, frozen at -20 °C or -80 °C, and transferred within 1 week of collection to a -80 °C central storage facility. The methods for collection of anthropometric measurements, as well as for the collection, processing, and storage of blood samples, were identical in the MONICA and VIP projects. All participants signed an informed consent form. The study was approved by the Ethical Committee of Umeå University Hospital. So far, no additional blood samples have been collected for analysis from any of the study subjects.
Case Ascertainment and Control Selection
All incident cases of prostate cancer and deaths that occurred in the cohort were identified by linkage with cancer and all-cause mortality registries, respectively, using an individual identification number as the identity link. Approximately 97% of the cases have been estimated to be ascertained through such registries (20). We identified 166 incident cases of prostate cancer by March 1999, of which 17 were excluded because insufficient plasma samples remained. The remaining 149 prostate cancer case subjects were included in this study. The time between blood donation and cancer diagnosis ranged from less than 1 month to 10 years (median, 3.85 years). Of the 149 case subjects, 126 (85%) were diagnosed more than 1 year after blood donation, 115 (77%) were diagnosed more than 2 years, and 70 (47%) were diagnosed more than 4 years. Two control subjects per case subject were randomly selected from all of the cohort members who were still alive and free of cancer at the time of diagnosis of the case subject. Control subjects were matched to the case subject by age (±1 year), date (±1 year) the health survey was completed, and town or village of residency.
Additional information on tumor classification was obtained from the Local Primary Prostate Cancer Registry (21). However, because this registry has only been in operation since 1992 and has a delay of approximately 1 year from the time of diagnosis to final registration, clinical data on tumor classification were extracted directly from patient medical records for tumors diagnosed before 1992 or after 1997. Tumor stage and differentiation were evaluated according to the classifications of the Union Internationale Contre le Cancer in 1992 (22) and the WHO, respectively (23). The presence of lymph node metastases was evaluated by histologic examination of obturator lymph nodes obtained by surgery. The presence of bone metastases was evaluated by a radionuclide scan. In most case subjects, tumors were localized and either highly or intermediately differentiated. Among the case subjects, 10 men had nonpalpable tumors detected by transurethral resection (seven T1a and three T1b tumors), 53 had nonpalpable tumors detected by prostate-specific antigen (PSA)-driven biopsies (T1c), 61 had palpable tumors that were confined to the prostate (T2), 16 had locally advanced tumors (T3 and T4), and five had tumors that were not locally staged (Tx). Lymph node metastases were present in six case subjects (4%), bone metastases were present in 14 (9%), and poorly differentiated tumors were present in 19 (13%). No formal screening for prostate cancer was performed during the study period in the region. However, the distribution of tumors by stage suggests that many of the tumors may have been found through informal screening on the initiative of the patient himself or of his physician.
Biochemical Assays
Serum levels of PSA in blood drawn shortly before the diagnostic biopsies were determined by either the Tandem-R PSA assay (Hybritech, Inc, San Diego, CA) or the IMx PSA assay (Abbot Laboratories, Abbott Park, IL). The correlation coefficient between the two assays was .990 [IMx PSA assay value = (1.22 x Tandem-R PSA value) - 2.80) (24).
The concentrations of insulin, IGF-I, IGFBP-1, IGFBP-2, and IGFBP-3 were measured in EDTA-treated plasma from baseline blood collection. Insulin, IGF-I, and IGFBPs-1 and -3 were measured by double-antibody, immunoradiometric assays, while IGFBP-2 was measured by a single-antibody radioimmunoassay. Reagents were obtained from Sanofi Diagnostics Pasteur (Marnes la Coquette, France) for insulin assays, from Immunotech (Marseille, France) for IGF-I and IGFBP-3 assays, and from Diagnostic Systems Laboratories (Webster, TX) for IGFBP-1 and IGFBP-2 assays. The protocol for the IGF-I assay included an acid–ethanol extraction step to release IGF-I from its binding proteins. All assays were performed by laboratory personnel who were blinded as to the case–control status of the plasma samples. Samples from matched study subjects were always analyzed together in the same batch. For quality control, all batches included three control samples containing known amounts of the specific peptide. The mean intra-assay coefficients of variation calculated from these control samples were 4.2%, 13.5%, 2.9%, 2.5%, and 3.3% for insulin, IGF-I, and IGFBPs-1, -2, and -3, respectively.
The baseline PSA levels in plasma samples of both case and control subjects were determined by time-resolved immunofluorometric assays (Prostatus PSA; Wallac, Turku, Finland). The analytic detection limit of the assay was 0.01 ng/mL; for values between 0.2 and 100 ng/mL, the inter-assay and intra-assay coefficients of variation were between 2% and 4%.
Statistical Analyses
Age-adjusted Pearson coefficients of correlation were used to examine the cross-sectional relationships between serum insulin, IGF-I, and the IGFBPs and between each of those peptides and body height, weight, and body mass index (BMI) (BMI = weight/height2).
A paired Student's t test was used to test for mean differences between anthropometric measurements and hormone levels of the case subjects and the mean values of the two control subjects who had been matched to each case subject. Conditional logistic regression models were used to calculate odds ratios (ORs) for disease by quartile or tertile levels of insulin, IGF-I, and IGFBPs-1, -2, and -3. Quartiles were used for full cohort analyses, whereas tertiles were used for the subgroup analysis of young patients (<59 years) because of the relatively small number of men in this subgroup. Cut points for quartiles and tertiles were determined on variable distributions of case and control subjects combined. Ninety-five percent confidence intervals (CIs) were computed using the standard errors of the pertinent regression coefficients, assuming a normal probability distribution for the estimated coefficients. Likelihood ratio tests for linear trends in risk with increasing levels of the various peptides were performed on the original, continuous variables. All statistical tests and corresponding P values were two-sided.
Multivariate conditional logistic regression analysis was used to estimate ORs adjusted for possible confounding factors other than those controlled for by matching. Potential confounding factors included BMI and smoking status at the time of blood donation. In addition, risk associated with different levels of IGF-I was estimated after adjustment for levels of each of the IGFBPs. Each of the various adjustments for potential confounding factors was made by a two-step procedure. First, in a multiple linear regression model, values for a specific peptide were regressed on the confounding variables (smoking status, BMI, and IGFBP level), and the residuals of this regression were categorized into quartiles or tertiles. Second, ORs were estimated for the quartiles or tertiles of the residuals by multivariate conditional logistic regression models. The same two-step procedure was also used to estimate ORs for each of the IGFBPs adjusted for levels of IGF-I. The "PHREG" procedure for proportional hazards' regression in the Statistical Analysis System (SAS Institute, Cary, NC) was used to perform all logistic regression analyses.
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RESULTS |
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Baseline Characteristics
Case and control subjects differed in several baseline characteristics (Table 1
). Mean plasma levels for case subjects were statistically significantly higher than those for control subjects for IGF-I (229.0 [95% CI = 217.7–240.3] versus 214.4 [95% CI = 207.8–220.9] ng/mL; P = .02) and IGFBP-3 (2611 [95% CI = 2518–2704] versus 2498 [95% CI = 2437–2560] ng/mL; P = .04). Case subjects also had higher mean levels of insulin (8.41 [95% CI = 6.58–10.24] versus 7.93 [95% CI = 6.92–8.94] pmol/mL; P = .62) and lower mean levels of IGFBP-1 (39.50 [95% CI = 35.61–43.39] versus 43.02 [95% CI = 39.80–46.24] ng/mL; P = .19) and IGFBP-2 (653.3 [95% CI = 529.3–714.2] versus 671.9 [95% CI = 621.7–722.1] ng/mL; P = .55) than control subjects, but none of these differences were statistically significant. Case subjects were statistically significantly taller than control subjects; the ORs for prostate cancer risk over increasing quartiles of height (Pfor trend = .048) were 1.00 (referent), 1.27 (95% CI = 0.74–2.21), 0.73 (95% CI = 0.40–1.34), and 1.48 (95% CI = 0.87–2.50). However, in contrast to some previous studies (25,26), we found that both groups of subjects had a similar BMI; the ORs for prostate cancer risk for increasing quartiles of BMI (Pfor trend = .69) were 1.00 (referent), 1.38 (95% CI = .79–2.42), 1.18 (95% CI = 0.68–2.05), and 1.32 (95% CI = 0.77–2.26). Although several previous studies (27–29) have shown weak associations between prostate cancer risk and smoking, we found only modest and statistically nonsignificant differences between the case and control subjects in this study with regard to the percentages of current smokers, ex-smokers, and never smokers (Table 1).
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At initial blood donation, plasma PSA levels were statistically significantly higher (P = .012) in case subjects than in control subjects (Table 1
). Eighty percent of the case subjects and 20% of the control subjects had plasma PSA levels above 4.0 ng/mL at the time of initial blood donation. At the time of prostate cancer diagnosis, plasma PSA values for case subjects had risen further (25th, 50th, and 75th percentiles were 6.3, 12.0, and 22.8 ng/mL, respectively). Cross-sectional Interrelationships
We combined the data from case and control subjects to examine the cross-sectional interrelationships between the plasma peptide levels, body height, and BMI after adjustment for age at sampling and case–control status (Table 2). All correlation coefficients were similar in the case and control groups with the exception of height, which was weakly correlated with IGF-I (r = .19) and IGFBP-3 (r = .20) levels in the case subjects but not in the control subjects (r = -.01 and .04), respectively. In both groups combined, there were positive correlations between plasma levels of IGF-I and IGFBP-3 (r = .59), between plasma levels of IGFBP-1 and IGFBP-2 (r = .36), and between BMI and plasma levels of insulin (r = .27). However, BMI and insulin levels both correlated inversely with plasma levels of IGFBP-1 (r = -.38 and r = -.21, respectively) and IGFBP-2 (r = -.46 and r = -.25, respectively). Plasma PSA levels at baseline for case and control subjects and at the time of diagnosis (case subjects only) did not correlate with height, BMI, or levels of insulin, IGF-I, or IGFBPs.
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Smoking affects many metabolic pathways. We found that smoking status was statistically significantly associated with BMI (25.3 kg/m2 ± 3.2 in current smokers, 27.2 kg/m2 ± 3.6 in ex-smokers, and 26.4 kg/m2 ± 3.8 in never smokers; P = .002) and plasma insulin levels (9.9 pmol/mL ± 14.1 in current smokers, 9.1 pmol/mL ± 12.1 in ex-smokers, and 6.8 pmol/mL ± 5.1 in never smokers; P = .02). In addition, smoking status was also statistically significantly associated with levels of IGFBP-2 (833 ± 473 ng/mL in current smokers, 611 ± 376 ng/mL in ex-smokers, and 633 ± 392 ng/mL in never smokers; P = .0002) but not with levels of IGFBP-1 (45.1 ± 26.1 ng/mL in current smokers, 41.9 ± 27.6 ng/mL in ex-smokers, and 39.8 ± 25.1 ng/mL in never smokers; P = .30). Smoking status did not show any associations at all with levels of IGF-I or IGFBP-3.
Logistic Regression Analyses of Prostate Cancer Risk
Prostate cancer risk in relation to plasma levels of IGF-I, IGFBP1–3, and insulin was analyzed by logistic regression analyses. We found a statistically significant trend of prostate cancer risk with increasing levels of IGF-I (Pfor trend = .02) and IGFBP-3 (Pfor trend = .03) as continuous variables. These increases in risk were reflected in ORs of 1.57 (95% CI = 0.88–2.81) and 1.56 (95% CI = 0.86–2.83) for top quartiles relative to the bottom quartiles of IGF-I and IGFBP-3, respectively (Table 3). Plasma levels of insulin and the insulin-regulated IGFBPs-1 and -2 did not show any statistically significant relationship with prostate cancer risk. Adjustment for BMI and smoking status did not materially alter the associations of IGF-I and IGFBP-3 with prostate cancer risk (Table 3). The association of prostate cancer risk with IGF-I and IGFBP-3 levels as continuous variables remained statistically significant after adjusting for height (Pfor trend = .03 and Pfor trend = .04, respectively). However, the OR estimates, after adjusting for height, moving from the bottom to the top quartile were somewhat lower for IGF-I (1.00 (referent), 0.80 [95% CI = 0.48–1.45], 1.27 [95% CI = 0.72–2.23], and 1.39 [95% CI = 0.75–2.55]) but did not change substantially for IGFBP-3 (1.00 (referent), 1.52 [95% CI = 0.85–2.72], 1.45 [95% CI = 0.79–2.65], and 1.60 [95% CI = 0.86–2.95]). Adjustment for IGFBP-3 levels, which were positively related to both IGF-I levels and prostate cancer risk, also practically cancelled the association of IGF-I levels to risk (Table 3). Conversely, adjustment for IGF-I levels abolished the association of prostate cancer risk with IGFBP-3 levels.
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Lagtime, Tumor Characteristics, and Age
To investigate the influence of time between blood collection and diagnosis on OR estimates, we excluded the 34 case subjects whose diagnosis of prostate cancer was made less than 2 years after the time of blood collection (and their matched control subjects). In this restricted analysis, the associations of risk with total IGF-I and IGFBP-3 levels was stronger compared with the full-cohort analysis. OR estimates for increasing quartiles of IGF-I were 1.00 (referent), 1.18 (95% CI = 0.61–2.26), 1.68 (95% CI = 0.88–3.21), and 2.18 (95% CI = 1.09–4.36); Pfor trend = .003); for increasing quartiles of IGFBP-3, OR estimates were 1.00 (referent), 1.53 (95% CI = 0.78–3.00), 1.68 (95% CI = 0.87–3.26), and 1.74 (95% CI = 0.85–3.52); Pfor trend = .02). Excluding the 39 control subjects who had baseline plasma PSA levels above 4.0 ng/mL did not materially alter any of the above OR estimates.
To examine whether the presence of patients with large tumors had a strong influence on the OR estimates, we excluded from our analysis the 44 case subjects who had large (T3–T4) tumors, lymph node or bone metastases, or poorly differentiated tumors. We found that the exclusion of these subjects did not substantially alter OR estimates for IGF-I levels compared with the full cohort analysis (ORs = 1.00 (referent), 1.24 [95% CI = 0.61–2.49], 1.98 [95% CI = 1.01–3.85], and 1.66 [95% CI = 0.83–3.31]; Pfor trend = .05) but led to lower OR estimates for IGFBP-3 (1.00 [referent], 1.58 [95% CI = 0.81–3.05], 1.24 [95% CI = 0.64–2.40], and 1.35 [95% CI = 0.69–2.64]; Pfor trend = .11). In each of these restricted analyses, levels of insulin, IGFBP-1, and IGFBP-2 remained unassociated with prostate cancer risk.
Previous studies (7,8) have shown contradictory data on the influence of age on the association between IGF-I levels and prostate cancer risk. In our study, most (80%) of the case subjects diagnosed with prostate cancer were aged 59–60 years or older at the time of the health survey, while 20% were men aged 58 years or younger. There were two clusters in age distribution because of the recruitment at even decades: 74% of the men were aged 59–60 years, and 15% of the men were aged 49–50 years. Men younger than 59 years had significantly higher IGF-I levels than did men older than 59 years (231 ng/mL ± 63 versus 209 ng/mL ± 60; P<.005). The difference in mean IGF-I levels between case and control subjects was larger in younger men (269 ng/mL ± 76 versus 228 ng/mL ± 54; P = .007) than in older men (219 ± 65 versus 211 ± 58 ng/mL; P = .25). When we restricted our logistic regression analyses to men below age 59 years at study entry, a strong positive trend in risk was found for increasing tertiles of IGF-I but not for increasing tertiles of IGFBP-3. Furthermore, adjustment for IGFBP-3 levels did not diminish the association of prostate cancer risk with IGF-I levels in these younger men. In contrast, adjustment for IGF-I levels caused IGFBP-3 levels to be negatively associated with prostate cancer risk, although the trend was not statistically significant (Table 4).
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DISCUSSION |
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In this prospective cohort study, we observed an increase in prostate cancer risk with rising levels of circulating IGF-I and IGFBP-3. In subgroup analyses, we observed a particularly strong association between prostate cancer risk and IGF-I levels in men who were younger than 59 years at recruitment. Plasma levels of insulin and IGFBPs-1 and -2, which are themselves negatively regulated by insulin, were not associated with any increase or decrease in prostate cancer risk, either in the whole cohort or in subgroups.
Methodologic Considerations
A methodologic strength of our study is that blood samples were obtained before cancer diagnosis, which makes it unlikely that levels of IGF-I, IGFBPs, or insulin had been affected by alterations in metabolism that might be caused by the presence of an advanced prostate tumor. This conclusion is corroborated by the fact that OR estimates remained unchanged after we excluded either those case subjects whose cancer was diagnosed less than 2 years after blood donation or those with large, metastasized, or poorly differentiated tumors. Furthermore, the prospective design of our study, which included a complete follow-up for cancer incidence, minimized the possibility of any bias that might have been caused by systematic case–control differences in blood sample collection, processing, and storage or by selection of case and control subjects from different source populations. Several studies (7,30,31) have shown that blood levels of IGF-I and IGFBP-3 have relatively low within-subject variation over time, so that measurements in a single blood sample should provide a reliable indicator of a subject's habitual blood concentrations of these peptides over time periods up to at least 1 year.
Influence of IGF-I and IGFBP-3 on Prostate Cancer Development
The positive association that we have observed between plasma IGF-I levels and prostate cancer risk is consistent with similar findings from a prospective cohort study of U.S. male physicians (7) and two case-control studies (8,9). It is interesting that recent prospective cohort studies have also shown that increases in the risks of colon (32) and breast (33) cancers are associated with elevated plasma IGF-I levels. Together, these findings suggest that an elevation of plasma IGF-I levels might be a common risk factor for different forms of cancer. The observed increase in total plasma IGF-I concentrations in men developing prostate cancer may reflect a relative elevation of pituitary secretion of GH, which provides the main stimulus for synthesis of IGF-I and IGFBP-3 in the liver as well as in other tissues (1,11).
Our findings of increased prostate cancer risk in men with elevated IGFBP-3 levels are inconsistent with results obtained in other studies. Neither the Physicians' Health Study (7) nor one case–control study (8) found an association between prostate cancer risk and total IGFBP-3 levels. Furthermore, in the Physicians' Health Study, the association of risk with IGF-I levels was considerably stronger when IGF-I levels were adjusted for levels of IGFBP-3, whereas levels of IGFBP-3 itself were found to be significantly inversely related to risk when adjusted for IGF-I (7). In our study, adjustment for IGFBP-3 levels reduced the association of risk with IGF-I levels in a full cohort analysis but did not affect this association when the analysis was restricted to younger men. We observed an inverse, but statistically nonsignificant, association of risk with IGFBP-3 levels only in younger men when IGFBP-3 levels were adjusted for IGF-I levels. In addition to revealing that younger men have a higher risk of prostate cancer as IGF-I levels increase, our data show that younger men had higher mean IGF-I levels than older men. Pituitary GH secretion, plasma IGF-I levels, and the IGF-I/IGFBP-3 ratio all peak during adolescence and then gradually decline with age (34–37). Furthermore, many epidemiologic studies (25,26,38–40), including ours, have shown positive associations of prostate cancer risk with adult height, which may be a possible marker of bioavailable IGF-I levels during the prepubertal and adolescent growth spurt. Therefore, it seems likely that the OR estimates of prostate cancer for quartiles of IGF-I corrected for height in our analysis were most likely overadjusted. Taken together, these various observations fit a model in which prostate cancer risk is specifically increased in men who have elevated IGF-I levels at a young age and whose IGF-I levels, therefore, show a stronger age-related decline than do those in men with lower initial IGF-I levels. Elevated IGF-I levels during adolescence and early adulthood may favor the development of early (pre) neoplastic lesions, which may progress into clinically manifest cancers much later in life.
Insulin, IGFBP-1, and IGFBP-2
Circulating levels of IGF-I and IGFBPs-1, -2, and -3 are regulated by both GH and insulin. GH provides the main stimulus for the synthesis of IGF-I and IGFBP-3, whereas insulin can increase IGF-I bioactivity by inhibiting the synthesis of IGFBPs-1 and -2. It is interesting that we found that plasma levels of insulin and the insulin-dependent IGFBPs -1 and -2 were not related to prostate cancer risk. It is unlikely that an OR of any importance would have been missed because of random errors in the measurements of peptide levels. Most (96%) blood samples were collected at least 4 hours after last consumption of any food or drink, an interval that is usually sufficient for levels of insulin and IGFBP-1 to return to fasting levels. Previous studies (31,41) have shown that measurements of insulin, IGFBP-1, and IGFBP-2 levels, especially in blood from fasting individuals, generally show relatively little intraindividual variation over time, suggesting that a single blood sample is adequate to test for associations with cancer risk in epidemiologic studies. Furthermore, we found no association between prostate cancer risk and high BMI, which is a major determinant of hyperinsulinemia and decreased IGFBP-1 and IGFBP-2 levels. This absence of association fits with results from many (27,39,42,43), although not all (25,26), epidemiologic studies on BMI and prostate cancer risk.
It is difficult to explain why only the absolute level of circulating IGF-I is related to prostate cancer risk, while an increase in IGF-I bioactivity that may result from insulin-induced reductions in IGFBP-1 and IGFBP-2 levels apparently is not. First, it is only partially understood how IGF-I bioactivity within the prostate is quantitatively determined by the concentrations of IGF-I and IGFBPs. For example, although reductions in levels of IGFBPs-1, -2, or -3 are generally thought to increase IGF-I bioactivity, some in vitro studies (10,44) have shown that these IGFBPs can sometimes actually potentiate IGF-I receptor binding and action, depending on their concentrations relative to those of IGF-I and on the cell type studied. Second, the relative concentrations of IGF-I and IGFBPs in the circulation may differ from those in the prostate gland because some of the circulating IGFBPs can diffuse more easily through the endothelial barrier than others and because IGF-I and IGFBPs may also be synthesized in the prostate. Furthermore, circulating levels of IGF-I and IGFBPs may also reflect the levels of synthesis of these peptides within the prostate itself because the same factors (e.g., GH and insulin) that regulate the synthesis of these peptides within the liver also regulate their synthesis within the prostate.
Implications for Prevention
Prostate cancer incidence rates vary widely between high-risk areas, such as the United States and Scandinavia, and lowrisk areas, such as Northern Africa or Southeast Asia. In high-risk areas, average body height and prostate cancer incidence rates have increased in parallel since the early 1900s, and growth rates during puberty and adolescence are related to levels of IGF-I. These observations, together with our results, would suggest that elevated IGF-I levels might provide a physiologic link between a Western lifestyle that is characterized by an energy-dense diet and an increased risk of prostate cancer. However, although chronic energy restriction has been shown to decrease circulating IGF-I levels, obesity, which is a reflection of long-term positive energy balance, is not related to an increase in IGF-I levels compared with the normally nourished but nonobese state (11). In addition to (or possibly in interaction with) nutritional lifestyle, genetic predisposition has been shown to determine a large part (30%–60%) of variation in circulating IGF-I levels (45–48). Identification of the nutritional and genetic factors that may cause the interindividual variations in IGF-I levels is an important area for future research.
In conclusion, our results indicate that elevated plasma IGF-I levels may be an important factor in the etiology of prostate cancer. In contrast, high levels of plasma insulin and insulin-induced reductions in IGFBP levels do not appear to be related to prostate cancer development. Studies on factors influencing plasma levels of IGF-I may provide insights that could be used in the design of novel preventive and therapeutic strategies against prostate cancer.
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NOTES |
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Supported by grants from The Swedish Cancer Society, The Lions Research Foundation, Umeå, Sweden, and The Medical Faculty, Umeå University.
We thank all of the participants in the VIP and MONICA projects; Åsa Ågren and Charlotte Ingri for their assistance in project coordination and data handling; and David Achaintre, Beatrice Vozar, and Francine Claustrat for their help with laboratory assays.
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Manuscript received March 29, 2000; revised September 18, 2000; accepted September 25, 2000.
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J. A. M. J. L. Janssen, M. F. Wildhagen, K. Ito, B. G. Blijenberg, R. H. N. van Schaik, M. J. Roobol, H. A. P. Pols, S. W. J. Lamberts, and F. H. Schroder Circulating Free Insulin-Like Growth Factor (IGF)-I , Total IGF-I, and IGF Binding Protein-3 Levels Do Not Predict the Future Risk to Develop Prostate Cancer: Results of a Case-Control Study Involving 201 Patients within a Population-Based Screening with a 4-Year Interval J. Clin. Endocrinol. Metab., September 1, 2004; 89(9): 4391 - 4396. [Abstract] [Full Text] [PDF]
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 P. Stattin, S. Rinaldi, C. Biessy, U.-H. Stenman, G. Hallmans, and R. Kaaks High Levels of Circulating Insulin-Like Growth Factor-I Increase Prostate Cancer Risk: A Prospective Study in a Population-Based Nonscreened Cohort J. Clin. Oncol., August 1, 2004; 22(15): 3104 - 3112. [Abstract] [Full Text] [PDF]
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 L. Peng, P. J. Malloy, and D. Feldman Identification of a Functional Vitamin D Response Element in the Human Insulin-Like Growth Factor Binding Protein-3 Promoter Mol. Endocrinol., May 1, 2004; 18(5): 1109 - 1119. [Abstract] [Full Text] [PDF]
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K. Wolk, S. C. Larsson, B. Vessby, A. Wolk, and K. Brismar Metabolic, Anthropometric, and Nutritional Factors as Predictors of Circulating Insulin-Like Growth Factor Binding Protein-1 Levels in Middle-Aged and Elderly Men J. Clin. Endocrinol. Metab., April 1, 2004; 89(4): 1879 - 1884. [Abstract] [Full Text] [PDF]
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 P.-S. Leung, W. J. Aronson, T. H. Ngo, L. A. Golding, and R. J. Barnard Exercise alters the IGF axis in vivo and increases p53 protein in prostate tumor cells in vitro J Appl Physiol, February 1, 2004; 96(2): 450 - 454. [Abstract] [Full Text] [PDF]
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 Y. Daaka G Proteins in Cancer: The Prostate Cancer Paradigm Sci. Signal., January 20, 2004; 2004(216): re2 - re2. [Abstract] [Full Text] [PDF]
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D. Gunnell, S. E. Oliver, J. L. Donovan, T. J. Peters, D. Gillatt, R. Persad, F. C. Hamdy, D. E. Neal, and J. M. P. Holly Do Height-Related Variations in Insulin-Like Growth Factors Underlie the Associations of Stature with Adult Chronic Disease? J. Clin. Endocrinol. Metab., January 1, 2004; 89(1): 213 - 218. [Abstract] [Full Text] [PDF]
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R. K. Nam, W. W. Zhang, J. Trachtenberg, M. A. S. Jewett, M. Emami, D. Vesprini, W. Chu, M. Ho, J. Sweet, A. Evans, et al. Comprehensive Assessment of Candidate Genes and Serological Markers for the Detection of Prostate Cancer Cancer Epidemiol. Biomarkers Prev., December 1, 2003; 12(12): 1429 - 1437. [Abstract] [Full Text] [PDF]
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 K. Song, S. C. Cornelius, M. Reiss, and D. Danielpour Insulin-like Growth Factor-I Inhibits Transcriptional Responses of Transforming Growth Factor-{beta} by Phosphatidylinositol 3-Kinase/Akt-dependent Suppression of the Activation of Smad3 but Not Smad2 J. Biol. Chem., October 3, 2003; 278(40): 38342 - 38351. [Abstract] [Full Text] [PDF]
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P. Stattin and R. Kaaks Re: Insulin Resistance and Prostate Cancer Risk J Natl Cancer Inst, July 16, 2003; 95(14): 1086 - 1087. [Full Text] [PDF]
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K. Woodson, J. A. Tangrea, M. Pollak, T. D. Copeland, P. R. Taylor, J. Virtamo, and D. Albanes Serum Insulin-like Growth Factor I: Tumor Marker or Etiologic Factor? A Prospective Study of Prostate Cancer among Finnish Men Cancer Res., July 15, 2003; 63(14): 3991 - 3994. [Abstract] [Full Text] [PDF]
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T. H. Ngo, R. J. Barnard, P. Cohen, S. Freedland, C. Tran, F. deGregorio, Y. I. Elshimali, D. Heber, and W. J. Aronson Effect of Isocaloric Low-fat Diet on Human LAPC-4 Prostate Cancer Xenografts in Severe Combined Immunodeficient Mice and the Insulin-like Growth Factor Axis Clin. Cancer Res., July 1, 2003; 9(7): 2734 - 2743. [Abstract] [Full Text] [PDF]
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T. H. Ngo, R. J. Barnard, P.-S. Leung, P. Cohen, and W. J. Aronson Insulin-Like Growth Factor I (IGF-I) and IGF Binding Protein-1 Modulate Prostate Cancer Cell Growth and Apoptosis: Possible Mediators for the Effects of Diet and Exercise on Cancer Cell Survival Endocrinology, June 1, 2003; 144(6): 2319 - 2324. [Abstract] [Full Text] [PDF]
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R. O. Roberts, D. J. Jacobson, C. J. Girman, T. Rhodes, G. G. Klee, M. M. Lieber, and S. J. Jacobsen Insulin-like Growth Factor I, Insulin-like Growth Factor Binding Protein 3, and Urologic Measures of Benign Prostatic Hyperplasia Am. J. Epidemiol., May 1, 2003; 157(9): 784 - 791. [Abstract] [Full Text] [PDF]
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A. E. Paradis, P. W. Kantoff, E. Giovannucci, M. J. Stampfer, and J. Ma Association between the Met326Ile Polymorphism of the p85{alpha} Regulatory Subunit of Phosphatidylinositol 3-Kinase and Prostate Cancer Risk: A Prospective Study Cancer Epidemiol. Biomarkers Prev., February 1, 2003; 12(2): 172 - 173. [Full Text] [PDF]
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 K. D. Burroughs, J. Oh, J. C. Barrett, and R. P. DiAugustine Phosphatidylinositol 3-Kinase and Mek1/2 Are Necessary for Insulin-Like Growth Factor-I-Induced Vascular Endothelial Growth Factor Synthesis in Prostate Epithelial Cells: A Role for Hypoxia-Inducible Factor-1? Mol. Cancer Res., February 1, 2003; 1(4): 312 - 322. [Abstract] [Full Text] [PDF]
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R. A. Krajcik, N. D. Borofsky, S. Massardo, and N. Orentreich Insulin-like Growth Factor I (IGF-I), IGF-binding Proteins, and Breast Cancer Cancer Epidemiol. Biomarkers Prev., December 1, 2002; 11(12): 1566 - 1573. [Abstract] [Full Text] [PDF]
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H. Yu, F. Jin, X.-O. Shu, B. D. L. Li, Q. Dai, J.-R. Cheng, H. J. Berkel, and W. Zheng Insulin-like Growth Factors and Breast Cancer Risk in Chinese Women Cancer Epidemiol. Biomarkers Prev., August 1, 2002; 11(8): 705 - 712. [Abstract] [Full Text] [PDF]
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A. R. Kristal, J. H. Cohen, P. Qu, and J. L. Stanford Associations of Energy, Fat, Calcium, and Vitamin D with Prostate Cancer Risk Cancer Epidemiol. Biomarkers Prev., August 1, 2002; 11(8): 719 - 725. [Abstract] [Full Text] [PDF]
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S. Chang, X. Wu, H. Yu, and M. R. Spitz Plasma Concentrations of Insulin-like Growth Factors among Healthy Adult Men and Postmenopausal Women: Associations with Body Composition, Lifestyle, and Reproductive Factors Cancer Epidemiol. Biomarkers Prev., August 1, 2002; 11(8): 758 - 766. [Abstract] [Full Text] [PDF]
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J. M. Chan, M. J. Stampfer, J. Ma, P. Gann, J. M. Gaziano, M. Pollak, and E. Giovannucci Insulin-Like Growth Factor-I (IGF-I) and IGF Binding Protein-3 as Predictors of Advanced-Stage Prostate Cancer J Natl Cancer Inst, July 17, 2002; 94(14): 1099 - 1106. [Abstract] [Full Text] [PDF]
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R. E. Schoen, J. Schragin, J. L. Weissfeld, F. L. Thaete, R. W. Evans, C. J. Rosen, and L. H. Kuller Lack of Association between Adipose Tissue Distribution and IGF-1 and IGFBP-3 in Men and Women Cancer Epidemiol. Biomarkers Prev., June 1, 2002; 11(6): 581 - 586. [Abstract] [Full Text] [PDF]
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 R Palmqvist, G Hallmans, S Rinaldi, C Biessy, R Stenling, E Riboli, and R Kaaks Plasma insulin-like growth factor 1, insulin-like growth factor binding protein 3, and risk of colorectal cancer: a prospective study in northern Sweden Gut, May 1, 2002; 50(5): 642 - 646. [Abstract] [Full Text] [PDF]
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S. F. Shariat, D. J. Lamb, M. W. Kattan, C. Nguyen, J. Kim, J. Beck, T. M. Wheeler, and K. M. Slawin Association of Preoperative Plasma Levels of Insulin-Like Growth Factor I and Insulin-Like Growth Factor Binding Proteins-2 and -3 With Prostate Cancer Invasion, Progression, and Metastasis J. Clin. Oncol., February 1, 2002; 20(3): 833 - 841. [Abstract] [Full Text] [PDF]
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 R. D. Klein and S. M. Fischer Black tea polyphenols inhibit IGF-I-induced signaling through Akt in normal prostate epithelial cells and Du145 prostate carcinoma cells Carcinogenesis, January 1, 2002; 23(1): 217 - 221. [Abstract] [Full Text] [PDF]
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L. Chen, M. Stacewicz-Sapuntzakis, C. Duncan, R. Sharifi, L. Ghosh, R. v. Breemen, D. Ashton, and P. E. Bowen Oxidative DNA Damage in Prostate Cancer Patients Consuming Tomato Sauce-Based Entrees as a Whole-Food Intervention J Natl Cancer Inst, December 19, 2001; 93(24): 1872 - 1879. [Abstract] [Full Text] [PDF]
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P. Stattin, U.-H. Stenman, E. Riboli, G. Hallmans, and R. Kaaks Ratios of IGF-I, IGF Binding Protein-3, and Prostate-Specific Antigen in Prostate Cancer Detection J. Clin. Endocrinol. Metab., December 1, 2001; 86(12): 5745 - 5748. [Abstract] [Full Text] [PDF]
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A. Hoeflich, R. Reisinger, H. Lahm, W. Kiess, W. F. Blum, H. J. Kolb, M. M. Weber, and E. Wolf Insulin-like Growth Factor-binding Protein 2 in Tumorigenesis: Protector or Promoter? Cancer Res., December 1, 2001; 61(24): 8601 - 8610. [Full Text] [PDF]
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R. Kaaks, S. Rinaldi, A. Lukanova, A. Akhmedkhanov, A. Zeleniuch-Jacquotte, and P. Toniolo Correspondence re: Giovannucci et al., A Prospective Study of Plasma Insulin-like Growth Factor-1 and Binding Protein-3 and Risk of Colorectal Neoplasia in Women. Cancer Epidemiol. Biomark. Prev., 9: 345-349, 2000 Cancer Epidemiol. Biomarkers Prev., October 1, 2001; 10(10): 1103 - 1104. [Full Text] [PDF]
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 W Zumkeller IGFs and IGFBPs: surrogate markers for diagnosis and surveillance of tumour growth? Mol. Pathol., October 1, 2001; 54(5): 285 - 288. [Abstract] [Full Text] [PDF]
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 S. Gupta, K. Hastak, N. Ahmad, J. S. Lewin, and H. Mukhtar Inhibition of prostate carcinogenesis in TRAMP mice by oral infusion of green tea polyphenols PNAS, August 10, 2001; (2001) 171326098. [Abstract] [Full Text] [PDF]
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T. Nickerson, F. Chang, D. Lorimer, S. P. Smeekens, C. L. Sawyers, and M. Pollak In Vivo Progression of LAPC-9 and LNCaP Prostate Cancer Models to Androgen Independence Is Associated with Increased Expression of Insulin-like Growth Factor I (IGF-I) and IGF-I Receptor (IGF-IR) Cancer Res., August 1, 2001; 61(16): 6276 - 6280. [Abstract] [Full Text] [PDF]
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N. E. Allen and T. J. Key Re: Plasma Insulin-Like Growth Factor-I, Insulin-Like Growth Factor-Binding Proteins, and Prostate Cancer Risk: a Prospective Study J Natl Cancer Inst, April 18, 2001; 93(8): 649 - 650. [Full Text] [PDF]
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S. Gupta, K. Hastak, N. Ahmad, J. S. Lewin, and H. Mukhtar Inhibition of prostate carcinogenesis in TRAMP mice by oral infusion of green tea polyphenols PNAS, August 28, 2001; 98(18): 10350 - 10355. [Abstract] [Full Text] [PDF]
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