Skip to main content
  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

AACR logo

  • Register
  • Log in
  • My Cart
Advertisement

Main menu

  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

User menu

  • Register
  • Log in
  • My Cart

Search

  • Advanced search
Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

Research Articles

Serum Macrophage Inhibitory Cytokine-1 Concentrations Correlate with the Presence of Prostate Cancer Bone Metastases

Katri S. Selander, David A. Brown, Guillermo Blanco Sequeiros, Mark Hunter, Renee Desmond, Teija Parpala, Juha Risteli, Samuel N. Breit and Arja Jukkola-Vuorinen
Katri S. Selander
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David A. Brown
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Guillermo Blanco Sequeiros
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mark Hunter
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Renee Desmond
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Teija Parpala
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Juha Risteli
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Samuel N. Breit
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Arja Jukkola-Vuorinen
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1158/1055-9965.EPI-06-0841 Published March 2007
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Macrophage-inhibitory cytokine-1 (MIC-1) is a divergent member of the transforming growth factor β superfamily. It is up-regulated by nonsteroidal anti-inflammatory drugs and is highly expressed in human prostate cancer leading to high serum MIC-1 concentrations with advanced disease. A role for MIC-1 has been implicated in the process of early bone formation, suggesting that it may also mediate sclerosis at the site of prostate cancer bone metastases. Consequently, the aim of this study was to retrospectively determine the relationship of serum MIC-1 concentration and other markers related to current and future prostate cancer bone metastasis in a cohort of 159 patients with prostate cancer. Serum markers included cross-linked carboxy-terminal telopeptide of type I collagen, prostate-specific antigen, and amino-terminal propeptide of type I procollagen (PINP). The mean values of all the biomarkers studied were significantly higher in patients with baseline bone metastases (BM+, n = 35), when compared with those without bone metastases (BM−, n = 124). In a multivariate logistic model, both MIC-1 and PINP independently predicted the presence of baseline bone metastasis. Based on receiver operator curve analysis, the best predictor for the presence of baseline bone metastasis was MIC-1, which was significantly better than carboxy-terminal telopeptide of type I collagen, prostate-specific antigen, and PINP. Patients who experienced bone relapse had significantly higher levels of baseline MIC-1 compared with patients who did not (1476.7 versus 988.4; P = 0.03). Current use of acetylsalicylic acid did not influence serum MIC-1 levels in this cohort. Although requiring validation prospectively, these results suggest that serum MIC-1 determination may be a valuable tool for the diagnosis of current and future bone metastases in patients with prostate cancer. (Cancer Epidemiol Biomarkers Prev 2007;16(3):532–7)

  • Prostate cancer
  • Bone metastases
  • MIC-1
  • Organ sites and tumor types
  • Metastasis/metastasis genes/metastasis models
  • Tumor markers and detection of metastasis

Introduction

Macrophage-inhibitory cytokine-1 (MIC-1), also known as PLAB, prostate-derived factor, GDF-15, and NAG-1, is a divergent member of the transforming growth factor β superfamily (1, 2). MIC-1 protein is synthesized as a 308–amino acid propeptide which, when secreted, binds to local extracellular matrix and subsequently becomes cleaved by a furin-like protease. The mature peptide, which is secreted by an alternate pathway, is a 112–amino acid protein which diffuses rapidly into the circulation (1, 3-5). It is likely that extracellular matrix–bound pro–MIC-1 represents a source of local bioactive MIC-1, whereas the secreted mature MIC-1 has more distant effects (6). The nature of the local and remote effects of MIC-1 secretion are not currently clear. However, MIC-1 has been shown by several groups to induce apoptosis and local MIC-1 expression in the stroma of the malignant prostate gland, and has been linked to improved outcome (6).

Although changes in serum MIC-1 levels are associated with a number of disease conditions (7, 8), they are mostly strongly linked to cancer. Increased MIC-1 expression has been documented in a variety of epithelial cancer cell lines, including breast, pancreas, colorectal, and prostate cancers (9-12). Microarray studies have revealed increased expressions of MIC-1 in patients with breast cancer, and serum MIC-1 levels are the best single predictor of the presence of pancreatic carcinoma (11). In colon cancer, increasing MIC-1 expression is associated with the progression of colonic adenomas to invasive cancer and subsequent metastasis, with serum levels at presentation being an independent predictor of subsequent disease-free and overall survival (13). In the case of prostate cancer, serum MIC-1 levels increase with the progression of disease to metastasis (11, 13, 14).

Recently, the MIC-1 gene locus was linked to familial prostate cancer and the most common polymorphism of the MIC-1 gene was associated with a modified risk for the development of prostate cancer (15-18). MIC-1 expression is up-regulated by androgens in murine prostate tissue, but is down-regulated by both androgens and estrogens in the androgen-dependent human LnCaP prostate cancer cell line (2, 19). MIC-1 expression is also increased during the transition from androgen-sensitivity to androgen-independency in an experimental model (20).

Bone metastases are the most common feature of disease dissemination in prostate cancer and may be linked to MIC-1 expression. MIC-1 mRNA is detected in the cartilaginous tissue of rat embryo and ectopically applied MIC-1 also induced early stages of endochondral bone formation (2). Prostate cancer cells known to express high amounts of MIC-1 form sclerotic bone lesions, whereas prostate cancer cells lacking MIC-1 expression produced lytic bone metastases, further supporting a role for MIC-1 in the process of prostate cancer–induced sclerotic bone metastases (20-24).

The aim of this study was to test the hypothesis that there is an association between serum MIC-1 concentrations and the presence of bone metastasis in patients with prostate cancer. Furthermore, we compared serum MIC-1 concentrations with other serum markers associated with bone metastasis. These included cross-linked carboxy-terminal telopeptide of type I collagen (ICTP) and amino-terminal propeptide of type I procollagen (PINP), and prostate-specific antigen (PSA; refs. 25-27). We show a significant relationship between serum MIC-1 concentrations and the presence of bone metastases and show that only serum MIC-1 levels are predictive of future relapse of disease in the bone.

Materials and Methods

Study Population

Male patients that were being treated for prostate cancer (n = 159) at the Department of Oncology, University Hospital of Oulu, Oulu, Finland, were recruited for this study during the years 2001 and 2003. A written, signed consent was obtained from the patients before participating in this study, which was conducted in accordance with the local ethic committees. Blood was drawn from the patients upon their scheduled visits at the clinics, processed, and stored at −80°C until analysis. Serum ICTP, MIC-1, PSA, and PINP concentrations were measured from the same sample. The presence or absence of bone metastasis was detected with native X-ray images and verified with bone scans.

Serum PSA Measurements

Total PSA (ng/L) was measured with AutoDelfia PROSTATUS PSA Free/Total kit, Wallac (Turku, Finland), according to the manufacturer's recommendations (28).

MIC-1 ELISA

The serum concentrations of MIC-1 (pg/mL) were analyzed using a sensitive immunoassay as previously described (7, 29). Data defining the sensitivity and specificity of MIC-1 sandwich ELISA have been published (7, 29). All samples were assayed in duplicate, and the coefficient of variation between samples was <12%.

PINP and ICTP ELISA

The concentration of cross-linked ICTP (μg/L) and amino-terminal PINP (μg/L) were analyzed by specific RIAs, as previously described (30, 31).

Statistical Analyses

The mean levels of the markers were compared between the patients with and without metastasis by Student' t test. Because of the skewness of the distribution of the markers, the data for all markers was transformed to the log scale for analysis. The best predictors of baseline metastases were determined with stepwise discriminatory analysis. The variable selection was based on Wilks' lambda, the likelihood ratio criterion. Variables that met the significance level for the discriminant analysis were considered for inclusion in a multivariate logistic regression model that predicted the probability of the presence of bone metastases. Receiver operator curves (ROC) were constructed for each marker for the prediction of baseline bone metastases and the areas under the curve were computed. The areas under the curves were compared across the four markers by the method of DeLong et al. using the ROC macro which can be downloaded from http://support.sas.com/ctx/samples/index.jsp?sid=520&tab=output. Multivariate analysis of the prognostic factors (biomarkers) for recurrence was based on the Cox proportional hazards model. The graphical plots for ROC curves were generated in PROC LOGISTIC in SAS version 9.1 (32). For all analyses, P < 0.05 was deemed statistically significant.

Results

Patient Characteristics

A summary of the patient characteristics, including previous cancer treatments, are given in Table 1 . Of the studied patients, 124 (78%) did not have bone metastases (BM−) and 35 (22%) did have bone metastasis (BM+) at the time when the blood was drawn. The ages of the patients ranged from 46 to 86 years (mean ± SD, 65 ± 7 years). The mean follow-up time in the whole cohort was 36 ± 7.4 months (mean ± SD, minimum 9 months and maximum 49 months). The mean survival time of the patients during the follow-up was 47.5 months [SE, 0.638; 95% confidence intervals (CI), 46.2-48.7 months]. The mean disease-free survival was 42.6 months (SE, 1.185; 95% CI, 40.3-44.9 months), the median disease-free survival time was 36.0 months. The mean and median times to progression at the various sites were as follows: the mean and median times to bone relapse were 47.5 months (SE, 0.687; 95% CI, 46.1-48.8 months) and 36.9 months, respectively. The mean and median times to local relapse were 48.4 months (SE, 0.494; 95% CI, 47.4-49.3 months) and 37.2 months, respectively. The mean and median times to chemical relapse were 43.9 months (SE, 1.08; 95% CI, 41.7-46.0 months) and 36.0 months, respectively.

View this table:
  • View inline
  • View popup
Table 1.

Patient characteristics

MIC-1 Serum Levels are Associated with Bone Metastatic Prostate Cancer

The mean values of all the studied biomarkers (ICTP, MIC-1, PSA, and PINP) were statistically significantly higher in the group of patients that had bone metastases (n = 35) at the time point when the blood samples were drawn, as compared with those that did not have bone metastases (n = 124) at the same time point (Table 2 ). Among the patients who experienced bone relapse (n = 7) during the follow-up (until June 2006), the baseline MIC-1 levels were significantly higher than those who did not (P = 0.03). There was a trend toward higher levels of MIC-1 among patients with local relapse compared with those without, but the differences were not significant. Baseline levels of the other measured markers were not significantly different between no-relapse and relapse groups for any site. It has been suggested that MIC-1 production in some colon cancer cells lines is regulated by nonsteroidal anti-inflammatory drugs. These drugs regulate MIC-1 expression independently of cyclooxygenase inhibition (10, 33). There were 25 patients listed as acetylsalicylic acid (Primaspan) users in this cohort. There were no significant differences in baseline serum levels of the biomarkers (MIC-1, ICTP, and PSA) among patients who used acetylsalicylic acid versus those who did not, stratified by metastasis status at baseline (data not shown). Only PINP had a slight difference in baseline mean levels for acetylsalicylic acid users versus nonusers (42.7 ± 23.4 versus 33.4 ± 19.4; P = 0.04) among those with no baseline metastasis.

View this table:
  • View inline
  • View popup
Table 2.

Descriptive statistics of biomarker levels at baseline for patients with prostate cancer (n = 159)

MIC-1 Serum Levels at Presentation are Associated with Tumor Grade

There were significant differences in MIC-1 at baseline by tumor grade, not stratifying by baseline metastasis. Grade 3 tumors had MIC-1 values that were significantly higher (mean, 2,326.1) than the lower grades (mean, 2,054.1 and 761.5 for grades 2 and grade 1, P = 0.002 and P < 0.0001, respectively). Similarly, Gleason scored tumors of 8 to 10 had significantly higher MIC-1 serum levels (2,647.2) compared with Gleason score 7 (mean, 1,101.4) and Gleason score 2 to 6 (mean, 756.9; P = 0.0003 and P < 0.0001, respectively).

Initial Serum MIC-1 Level Independently Predicts Bone Metastatic Disease in Prostate Cancer

Results of the stepwise discriminate analysis showed that only PINP, MIC-1, and PSA were significantly related to baseline metastasis in bone. In a multivariate logistic model, both MIC-1 (risk ratios, 7.38; 95% CI, 3.57-15.4; P ≤ 0.0001) and PINP (risk ratios, 3.27; 95% CI, 1.39-7.72; P = 0.007) significantly predicted the presence of baseline prostate cancer bone metastasis. PSA levels and ICTP levels were not significant in the adjusted analyses. There was no significant effect of acetylsalicylic acid usage (P = 0.54) in a model with MIC-1 predicting baseline metastasis.

Bone or Local Relapse by Proportional Hazard Regression

Results of the Cox regression showed that MIC-1 was borderline significantly related to future bone relapse. In a multivariable model predicting bone relapse with MIC-1, the hazard ratio was 1.88 (95% CI, 0.91-3.88; P = 0.09). Thus, higher serum MIC concentrations were associated with higher risk of bone relapse. In a model predicting local relapses, MIC-1 was not significant (hazard ratio, 1.92; 95% CI, 0.73-5.05; P = 0.19).

Serum MIC-1 Is the Best Diagnostic Marker of Bone Metastatic Disease in Prostate Cancer

ROC analyses were done for each serum marker for the prediction of the presence of bone metastasis. The areas under the curve, SEs, and 95% CIs are given in Table 3 for patients presenting with metastasis for each marker. The ROC curves for the baseline presence of bone metastasis for each biomarker are also shown (Figs. 1 – 4 ). Serum MIC-1 level was the best diagnostic marker of bone metastatic disease (Fig. 3, c = 0.9215) which was significantly better than ICTP (Fig. 1, c = 0.813; P = 0.005), PSA (Fig. 4, c = 0.7126; P = 0.002) and PINP (Fig. 2, c = 0.7982; P = 0.03), as judged by the DeLong test of equality of areas (32).

View this table:
  • View inline
  • View popup
Table 3.

ROC curve areas and 95% CI for prediction of bone metastases

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

ROC curve for the prediction of bone metastasis among patients with prostate cancer by ICTP.

Figure 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2.

ROC curve for the prediction of bone metastasis among patients with prostate cancer by PINP.

Figure 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 3.

ROC curve for the prediction of bone metastasis among patients with prostate cancer by MIC-1.

Figure 4.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 4.

ROC curve for the prediction of bone metastasis among patients with prostate cancer by PSA.

Discussion

In this retrospective study of 159 patients, serum MIC-1 level was independently associated with tumor grade and independently predictive of the presence of bone metastasis. Comparison of serum MIC-1 level with other markers shown to predict the presence of bone metastasis in prostate cancer, PINP, ICTP, and PSA (34, 35) by ROC analysis confirmed the superior diagnostic capacity of serum MIC-1 determination. The reason for the superior performance of serum MIC-1 compared with other markers of prostate cancer bone metastases is unclear at the moment, but it may be due to the participation of MIC-1 in the process of sclerosis that is associated with bone metastatic prostate cancer (34-37). However, the particular role for MIC-1 in the pathogenesis of prostate cancer needs to be clarified in animal studies.

Increased serum MIC-1 concentrations were significantly associated with increasing grade and Gleason's score. These findings, which suggest that increased serum MIC-1 concentrations are associated with advanced disease in prostate cancer, are in line with previous findings (11, 35, 38-40) MIC-1 was also the only marker studied that was capable of predicting the future occurrence of bone metastases. Because of the retrospective nature of this study, and the small number of patients that developed bone metastasis throughout the course of the study, further prospective studies in larger cohorts are required to confirm our results (40).

Acetylsalicylic acid, a nonsteroidal anti-inflammatory drug, has been shown to up-regulate MIC-1 in human colon cancer cells (33). It is not known whether acetylsalicylic acid also affects MIC-1 secretion in patients with cancer. We did not, however, detect differences between serum MIC-1 concentrations in patients that were taking acetylsalicylic acid, as compared with those that do not take this drug. Although the number of patients on acetylsalicylic acid was small, our findings do suggest that this frequently used drug does not interfere with the clinical use of serum MIC-1 measurements. There are also other drugs that regulate MIC-1 expression in cancer cells (41). Such drugs are not, however, typically used to treat prostate cancer (42-46).

The biomarkers used in this study represent different biological aspects in the pathophysiology of prostate cancer. PINP and ICTP are products of collagen metabolism, and their increased serum concentrations typically reflect pathologic bone turnover in cancer metastases to bone (38, 47-51). MIC-1 and PSA are derived from malignant cells (52, 53). Apart from possibly reflecting tumor volume within the system, both these proteins may also affect the behavior of the cancer cells. For example PSA, as a kallikrein protease, may regulate prostate cancer cell invasion in a zinc ion–dependent fashion (54). PSA expression, in addition to human kallikrein 4, may also mediate epithelial-mesenchymal transition of prostate cancer cells, further suggesting that PSA may also have a functional role in the progression of prostate cancer through the promotion of tumor cell migration (53). The effects of MIC-1 on cancer cells have been described to be of dual nature. In one hand, MIC-1 promotes invasiveness via up-regulating the urokinase-type plasminogen activator (55). MIC-1 has also been shown to decrease cell adhesion and to induce apoptosis in prostate cancer cells (19). In this light, the increased MIC-1 secretion which has been seen in association with prostate cancer progression is unclear. It may, however, be related to acquired insensitivity to the apoptosis-inducing effects of MIC-1. Similar insensitivity to the growth-inhibitory effects of other members of the transforming growth factor β family has been detected in various cancer cells, and this effect has been attributed to mutations in their receptors. These issues will be solved once the currently unknown cellular receptor for MIC-1 is characterized (56-58). Taken together, in addition to their roles as biomarkers, PSA and MIC-1 may exhibit important functional roles in prostate cancer progression at the cellular level.

The process of bone metastasis involves escape from the primary site, and homing at and growing in bone (59). Although growing in bone, metastatic cancer cells secrete various factors that influence the behavior of the surrounding bone cells in the bone microenvironment. More specifically, breast cancer cells typically secrete factors that activate the bone-resorbing osteoclasts, which results in osteolysis at the site of metastases (59). Prostate cancer bone metastases typically involve osteoblast activation, resulting in the formation of new bone (36). Despite the increased serum MIC-1 concentrations in patients with prostate cancer with bone metastases, the possible role of MIC-1 in their pathophysiology is currently unclear. Whether or not MIC-1 actually stimulates osteoblasts and participates in the formation of sclerotic bone metastases remains to be clarified in animal models of prostate cancer bone metastases, in which the metastasis-associated sclerosis is compared between prostate cancer cells that express various amounts and forms of MIC-1.

In conclusion, we show here that serum MIC-1 concentrations exhibit significant correlation with the presence of bone metastasis in patients with prostate cancer. In this regard, MIC-1 outperformed ICTP and PSA, of which especially the latter is typically clinically used in following the disease course. Furthermore, of the studied biomarkers, only serum MIC-1 exhibited significant prognostic value for future relapse in bone. These findings suggest that MIC-1 may be a helpful, new clinical tool in the clinical management of patients with prostate cancer.

Acknowledgments

Kari Mononen (R.N.) is acknowledged for gathering the clinical data.

Footnotes

  • Grant support: National Health and Medical Research Council Australia, New South Wales Health Research and Development Infrastructure grant (S. Breit), and by a grant from UAB Core Center for Musculoskeletal Disorders (5P30 AR46031-05, K.S. Selander).

  • 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.

  • Note: K.S. Selander, D.A. Brown, G.B. Sequeiros, and A. Jukkola-Vuorinen contributed equally to this work.

    • Accepted December 15, 2006.
    • Received October 4, 2006.
    • Revision received December 6, 2006.

References

  1. ↵
    Bootcov MR, Bauskin AR, Valenzuela S, et al. MIC-1, a novel macrophage inhibitory cytokine, is a divergent member of the TGF-β superfamily. Proc Natl Acad Sci U S A 1997;94:11514–9.
    OpenUrlAbstract/FREE Full Text
  2. ↵
    Paralkar VM, Vail AL, Grasser WA, et al. Cloning and characterization of a novel member of the transforming growth factor-β/bone morphogenetic protein family. J Biol Chem 1998;273:13760–7.
    OpenUrlAbstract/FREE Full Text
  3. ↵
    Fairlie WD, Zhang HP, Wu WM, et al. The propeptide of the transforming growth factor-β superfamily member, macrophage inhibitory cytokine-1 (MIC-1), is a multifunctional domain that can facilitate protein folding and secretion. J Biol Chem 2001;276:16911–8.
    OpenUrlAbstract/FREE Full Text
  4. Fairlie WD, Moore AG, Bauskin AR, Russell PK, Zhang HP, Breit SN. MIC-1 is a novel TGF-β superfamily cytokine associated with macrophage activation. J Leukoc Biol 1999;65:2–5.
    OpenUrlAbstract
  5. ↵
    Bauskin AR, Zhang HP, Fairlie WD, et al. The propeptide of macrophage inhibitory cytokine (MIC-1), a TGF-β superfamily member, acts as a quality control determinant for correctly folded MIC-1. EMBO J 2000;19:2212–20.
    OpenUrlAbstract
  6. ↵
    Bauskin AR, Brown DA, Junankar S, et al. The propeptide mediates formation of stromal stores of PROMIC-1: role in determining prostate cancer outcome. Cancer Res 2005;65:2330–6.
    OpenUrlAbstract/FREE Full Text
  7. ↵
    Brown DA, Breit SN, Buring J, et al. Concentration in plasma of macrophage inhibitory cytokine-1 and risk of cardiovascular events in women: a nested case-control study. Lancet 2002;359:2159–63.
    OpenUrlCrossRefPubMed
  8. ↵
    Tong S, Marjono B, Brown DA, et al. Serum concentrations of macrophage inhibitory cytokine 1 (MIC 1) as a predictor of miscarriage. Lancet 2004;363:129–30.
    OpenUrlCrossRefPubMed
  9. ↵
    Wollmann W, Goodman ML, Bhat-Nakshatri P, et al. The macrophage inhibitory cytokine integrates AKT/PKB and MAP kinase signaling pathways in breast cancer cells. Carcinogenesis 2005;26:900–7.
    OpenUrlAbstract/FREE Full Text
  10. ↵
    Iczkowski KA, Pantazis CG. Overexpression of NSAID-activated gene product in prostate cancer. Int J Surg Pathol 2003;11:159–66.
    OpenUrlAbstract/FREE Full Text
  11. ↵
    Welsh JB, Sapinoso LM, Kern SG, et al. Large-scale delineation of secreted protein biomarkers overexpressed in cancer tissue and serum. Proc Natl Acad Sci U S A 2003;100:3410–5.
    OpenUrlAbstract/FREE Full Text
  12. ↵
    Welsh JB, Sapinoso LM, Su AI, et al. Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer. Cancer Res 2001;61:5974–8.
    OpenUrlAbstract/FREE Full Text
  13. ↵
    Brown DA, Ward RL, Buckhaults P, et al. MIC-1 serum level and genotype: associations with progress and prognosis of colorectal carcinoma. Clin Cancer Res 2003;9:2642–50.
    OpenUrlAbstract/FREE Full Text
  14. ↵
    Thomas R, True LD, Lange PH, Vessella RL. Placental bone morphogenetic protein (PLAB) gene expression in normal, pre-malignant and malignant human prostate: relation to tumor development and progression. Int J Cancer 2001;93:47–52.
    OpenUrlCrossRefPubMed
  15. ↵
    Lindmark F, Zheng SL, Wiklund F, et al. H6D polymorphism in macrophage-inhibitory cytokine-1 gene associated with prostate cancer. J Natl Cancer Inst 2004;96:1248–54.
    OpenUrlAbstract/FREE Full Text
  16. Hsieh CL, Oakley-Girvan I, Balise RR, et al. A genome screen of families with multiple cases of prostate cancer: evidence of genetic heterogeneity. Am J Hum Genet 2001;69:148–58.
    OpenUrlCrossRefPubMed
  17. Wiklund F, Gillanders EM, Albertus JA, et al. Genome-wide scan of Swedish families with hereditary prostate cancer: suggestive evidence of linkage at 5q11.2 and 19p13.3. Prostate 2003;57:290–7.
    OpenUrlCrossRefPubMed
  18. ↵
    Hayes VM, Severi G, Southey MC, et al. Macrophage inhibitory cytokine-1 H6D polymorphism, prostate cancer risk, and survival. Cancer Epidemiol Biomarkers Prev 2006;15:1223–5.
    OpenUrlAbstract/FREE Full Text
  19. ↵
    Liu T, Bauskin AR, Zaunders J, et al. Macrophage inhibitory cytokine 1 reduces cell adhesion and induces apoptosis in prostate cancer cells. Cancer Res 2003;63:5034–40.
    OpenUrlAbstract/FREE Full Text
  20. ↵
    Karan D, Kelly DL, Rizzino A, Lin MF, Batra SK. Expression profile of differentially-regulated genes during progression of androgen-independent growth in human prostate cancer cells. Carcinogenesis 2002;23:967–75.
    OpenUrlAbstract/FREE Full Text
  21. Thalmann GN, Anezinis PE, Chang SM, et al. Androgen-independent cancer progression and bone metastasis in the LNCaP model of human prostate cancer. Cancer Res 1994;54:2577–81.
    OpenUrlAbstract/FREE Full Text
  22. Thalmann GN, Sikes RA, Wu TT, et al. LNCaP progression model of human prostate cancer: androgen-independence and osseous metastasis. Prostate 2000;44:91–103.
    OpenUrlCrossRefPubMed
  23. Burton DW, Geller J, Yang M, et al. Monitoring of skeletal progression of prostate cancer by GFP imaging, X-ray, and serum OPG and PTHrP. Prostate 2005;62:275–81.
    OpenUrlCrossRefPubMed
  24. ↵
    Fisher JL, Schmitt JF, Howard ML, Mackie PS, Choong PF, Risbridger GP. An in vivo model of prostate carcinoma growth and invasion in bone. Cell Tissue Res 2002;307:337–45.
    OpenUrlCrossRefPubMed
  25. ↵
    Koizumi M, Yonese J, Fukui I, Ogata E. The serum level of the amino-terminal propeptide of type I procollagen is a sensitive marker for prostate cancer metastasis to bone. BJU Int 2001;87:348–51.
    OpenUrlCrossRefPubMed
  26. Tamada T, Sone T, Tomomitsu T, Jo Y, Tanaka H, Fukunaga M. Biochemical markers for the detection of bone metastasis in patients with prostate cancer: diagnostic efficacy and the effect of hormonal therapy. J Bone Miner Metab 2001;19:45–51.
    OpenUrlCrossRefPubMed
  27. ↵
    Rudnicki M, Jensen LT, Iversen P. Collagen derived serum markers in carcinoma of the prostate. Scand J Urol Nephrol 1995;29:317–21.
    OpenUrlPubMed
  28. ↵
    Zhu L, Leinonen J, Zhang WM, Finne P, Stenman UH. Dual-label immunoassay for simultaneous measurement of prostate-specific antigen (PSA)-α1-antichymotrypsin complex together with free or total PSA. Clin Chem 2003;49:97–103.
    OpenUrlAbstract/FREE Full Text
  29. ↵
    Brown DA, Bauskin AR, Fairlie WD, et al. Antibody-based approach to high-volume genotyping for MIC-1 polymorphism. Biotechniques 2002;33:118–20.
    OpenUrlPubMed
  30. ↵
    Risteli J, Elomaa I, Niemi S, Novamo A, Risteli L. Radioimmunoassay for the pyridinoline cross-linked carboxy-terminal telopeptide of type I collagen: a new serum marker of bone collagen degradation. Clin Chem 1993;39:635–40.
    OpenUrlAbstract/FREE Full Text
  31. ↵
    Melkko J, Kauppila S, Niemi S, et al. Immunoassay for intact amino-terminal propeptide of human type I procollagen. Clin Chem 1996;42:947–54.
    OpenUrlAbstract/FREE Full Text
  32. ↵
    DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988;44:837–45.
    OpenUrlCrossRefPubMed
  33. ↵
    Baek SJ, Kim KS, Nixon JB, Wilson LC, Eling TE. Cyclooxygenase inhibitors regulate the expression of a TGF-β superfamily member that has proapoptotic and antitumorigenic activities. Mol Pharmacol 2001;59:901–8.
    OpenUrlAbstract/FREE Full Text
  34. ↵
    Akimoto S, Furuya Y, Akakura K, Ito H. Comparison of markers of bone formation and resorption in prostate cancer patients to predict bone metastasis. Endocr J 1998;45:97–104.
    OpenUrlPubMed
  35. ↵
    Demers LM, Costa L, Lipton A. Biochemical markers and skeletal metastases. Cancer 2000;88:2919–26.
    OpenUrlCrossRefPubMed
  36. ↵
    Green JR. Skeletal complications of prostate cancer: pathophysiology and therapeutic potential of bisphosphonates. Acta Oncol 2005;44:282–92.
    OpenUrlPubMed
  37. ↵
    Loberg RD, Logothetis CJ, Keller ET, Pienta KJ. Pathogenesis and treatment of prostate cancer bone metastases: targeting the lethal phenotype. J Clin Oncol 2005;23:8232–41.
    OpenUrlAbstract/FREE Full Text
  38. ↵
    Diaz-Martin MA, Traba ML, De La Piedra C, Guerrero R, Mendez-Davila C, De La Pena EG. Aminoterminal propeptide of type I collagen and bone alkaline phosphatase in the study of bone metastases associated with prostatic carcinoma. Scand J Clin Lab Invest 1999;59:125–32.
    OpenUrlCrossRefPubMed
  39. Nakamura T, Scorilas A, Stephan C, et al. Quantitative analysis of macrophage inhibitory cytokine-1 (MIC-1) gene expression in human prostatic tissues. Br J Cancer 2003;88:1101–4.
    OpenUrlCrossRefPubMed
  40. ↵
    Brown DA, Stephan C, Ward RL, et al. Measurement of serum levels of macrophage inhibitory cytokine 1 combined with prostate-specific antigen improves prostate cancer diagnosis. Clin Cancer Res 2006;12:89–96.
    OpenUrlAbstract/FREE Full Text
  41. ↵
    Martinez JM, Sali T, Okazaki R, et al. Drug-induced expression of nonsteroidal anti-inflammatory drug-activated gene/macrophage inhibitory cytokine-1/prostate-derived factor, a putative tumor suppressor, inhibits tumor growth. J Pharmacol Exp Ther 2006;318:899–906.
    OpenUrlAbstract/FREE Full Text
  42. ↵
    Lee SH, Kim JS, Yamaguchi K, Eling TE, Baek SJ. Indole-3-carbinol and 3,3′-diindolylmethane induce expression of NAG-1 in a p53-independent manner. Biochem Biophys Res Commun 2005;328:63–9.
    OpenUrlCrossRefPubMed
  43. Wilson LC, Baek SJ, Call A, Eling TE. Nonsteroidal anti-inflammatory drug-activated gene (NAG-1) is induced by genistein through the expression of p53 in colorectal cancer cells. Int J Cancer 2003;105:747–53.
    OpenUrlCrossRefPubMed
  44. Bottone FG, Baek SJ, Nixon JB, Eling TE. Diallyl disulfide (DADS) induces the antitumorigenic NSAID-activated gene (NAG-1) by a p53-dependent mechanism in human colorectal HCT 116 cells. J Nutr 2002;132:773–8.
    OpenUrlAbstract/FREE Full Text
  45. Baek SJ, Wilson LC, Eling TE. Resveratrol enhances the expression of non-steroidal anti-inflammatory drug-activated gene (NAG-1) by increasing the expression of p53. Carcinogenesis 2002;23:425–34.
    OpenUrlAbstract/FREE Full Text
  46. ↵
    Baek SJ, Kim JS, Jackson FR, Eling TE, McEntee MF, Lee SH. Epicatechin gallate-induced expression of NAG-1 is associated with growth inhibition and apoptosis in colon cancer cells. Carcinogenesis 2004;25:2425–32.
    OpenUrlAbstract/FREE Full Text
  47. ↵
    de la Piedra C, Castro-Errecaborde NA, Traba ML, et al. Bone remodeling markers in the detection of bone metastases in prostate cancer. Clin Chim Acta 2003;331:45–53.
    OpenUrlCrossRefPubMed
  48. Jukkola A, Bloigu R, Holli K, et al. Postoperative PINP in serum reflects metastatic potential and poor survival in node-positive breast cancer. Anticancer Res 2001;21:2873–6.
    OpenUrlPubMed
  49. Ylisirniö S, Sassi ML, Risteli J, Turpeenniemi-Hujanen T, Jukkola A. Serum type I collagen degradation markers, ICTP and CrossLaps, are factors for poor survival in lung cancer. Anticancer Res 1999;19:5577–81.
    OpenUrlPubMed
  50. Luftner D, Jozereau D, Schildhauer S, et al. PINP as serum marker of metastatic spread to the bone in breast cancer patients. Anticancer Res 2005;25:1491–9.
    OpenUrlPubMed
  51. ↵
    Tähtelä R, Tholix E. Serum concentrations of type I collagen carboxyterminal telopeptide (ICTP) and type I procollagen carboxy- and aminoterminal propeptides (PICP, PINP) as markers of metastatic bone disease in breast cancer. Anticancer Res 1996;16:2289–93.
    OpenUrlPubMed
  52. ↵
    Karan D, Chen SJ, Johansson SL, et al. Dysregulated expression of MIC-1/PDF in human prostate tumor cells. Biochem Biophys Res Commun 2003;305:598–604.
    OpenUrlCrossRefPubMed
  53. ↵
    Veveris-Lowe TL, Lawrence MG, Collard RL. Kallikrein 4 (hK4) and prostate-specific antigen (PSA) are associated with the loss of E-cadherin and an epithelial-mesenchymal transition (EMT)-like effect in prostate cancer cells. Endocr Relat Cancer 2005;12:631–43.
    OpenUrlAbstract/FREE Full Text
  54. ↵
    Ishii K, Otsuka T, Iguchi K, et al. Evidence that the prostate-specific antigen (PSA)/Zn2+ axis may play a role in human prostate cancer cell invasion. Cancer Lett 2004;207:79–87.
    OpenUrlCrossRefPubMed
  55. ↵
    Lee DH, Yang Y, Lee SJ, et al. Macrophage inhibitory cytokine-1 induces the invasiveness of gastric cancer cells by up-regulating the urokinase-type plasminogen activator system. Cancer Res 2003;63:4648–55.
    OpenUrlAbstract/FREE Full Text
  56. ↵
    Zhang Q, Rubenstein JN, Jang TL, et al. Insensitivity to transforming growth factor-β results from promoter methylation of cognate receptors in human prostate cancer cells (LNCaP). Mol Endocrinol 2005;19:2390–9.
    OpenUrlCrossRefPubMed
  57. Schiemann WP, Rotzer D, Pfeifer WM, et al. Transforming growth factor-β (TGF-β)-resistant B cells from chronic lymphocytic leukemia patients contain recurrent mutations in the signal sequence of the type I TGF-β receptor. Cancer Detect Prev 2004;28:57–64.
    OpenUrlCrossRefPubMed
  58. ↵
    Kim IY, Lee DH, Lee DK, et al. Decreased expression of bone morphogenetic protein (BMP) receptor type II correlates with insensitivity to BMP-6 in human renal cell carcinoma cells. Clin Cancer Res 2003;9:6046–51.
    OpenUrlAbstract/FREE Full Text
  59. ↵
    Käkönen SM, Mundy GR. Mechanisms of osteolytic bone metastases in breast carcinoma. Cancer 2003;97:834–9.
    OpenUrlCrossRefPubMed
View Abstract
PreviousNext
Back to top
Cancer Epidemiology Biomarkers & Prevention: 16 (3)
March 2007
Volume 16, Issue 3
  • Table of Contents
  • Table of Contents (PDF)

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for sharing this Cancer Epidemiology, Biomarkers & Prevention article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Serum Macrophage Inhibitory Cytokine-1 Concentrations Correlate with the Presence of Prostate Cancer Bone Metastases
(Your Name) has forwarded a page to you from Cancer Epidemiology, Biomarkers & Prevention
(Your Name) thought you would be interested in this article in Cancer Epidemiology, Biomarkers & Prevention.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Serum Macrophage Inhibitory Cytokine-1 Concentrations Correlate with the Presence of Prostate Cancer Bone Metastases
Katri S. Selander, David A. Brown, Guillermo Blanco Sequeiros, Mark Hunter, Renee Desmond, Teija Parpala, Juha Risteli, Samuel N. Breit and Arja Jukkola-Vuorinen
Cancer Epidemiol Biomarkers Prev March 1 2007 (16) (3) 532-537; DOI: 10.1158/1055-9965.EPI-06-0841

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Serum Macrophage Inhibitory Cytokine-1 Concentrations Correlate with the Presence of Prostate Cancer Bone Metastases
Katri S. Selander, David A. Brown, Guillermo Blanco Sequeiros, Mark Hunter, Renee Desmond, Teija Parpala, Juha Risteli, Samuel N. Breit and Arja Jukkola-Vuorinen
Cancer Epidemiol Biomarkers Prev March 1 2007 (16) (3) 532-537; DOI: 10.1158/1055-9965.EPI-06-0841
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF
Advertisement

Related Articles

Cited By...

More in this TOC Section

  • Urinary Melatonin in Relation to Breast Cancer Risk
  • Endometrial Cancer and Ovarian Cancer Cross-Cancer GWAS
  • Risk Factors of Subsequent CNS Tumor after Pediatric Cancer
Show more Research Articles
  • Home
  • Alerts
  • Feedback
  • Privacy Policy
Facebook   Twitter   LinkedIn   YouTube   RSS

Articles

  • Online First
  • Current Issue
  • Past Issues

Info for

  • Authors
  • Subscribers
  • Advertisers
  • Librarians

About Cancer Epidemiology, Biomarkers & Prevention

  • About the Journal
  • Editorial Board
  • Permissions
  • Submit a Manuscript
AACR logo

Copyright © 2021 by the American Association for Cancer Research.

Cancer Epidemiology, Biomarkers & Prevention
eISSN: 1538-7755
ISSN: 1055-9965

Advertisement