0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Original Contribution |

Osteopontin as a Potential Diagnostic Biomarker for Ovarian Cancer FREE

Jae-Hoon Kim, MD; Steven J. Skates, PhD; Toshimitsu Uede, MD; Kwong-kwok Wong, PhD; John O. Schorge, MD; Colleen M. Feltmate, MD; Ross S. Berkowitz, MD; Daniel W. Cramer, MD, ScD; Samuel C. Mok, PhD
[+] Author Affiliations

Author Affiliations: Department of Obstetrics and Gynecology, Saint Vincent Hospital and Catholic University of Korea, Suwon, Kyong-Ki-Do, Korea (Dr Kim); Department of Obstetrics, Gynecology, and Reproductive Biology, Brigham and Women's Hospital and Harvard Medical School (Drs Kim, Feltmate, Berkowitz, Cramer, and Mok), Massachusetts General Hospital Biostatistics Center and Harvard Medical School (Dr Skates), Dana-Farber Cancer Institute (Drs Skates, Berkowitz, and Cramer), and Dana-Farber Harvard Cancer Center (Drs Skates, Berkowitz, Cramer, and Mok), Boston, Mass; Institute for Genetic Medicine, Hokkaido University, Sapporo, Hokkaido, Japan (Dr Uede); Department of Pediatrics, Texas Children's Cancer Center, Baylor College of Medicine, Houston (Dr Wong); Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas (Dr Schorge).


JAMA. 2002;287(13):1671-1679. doi:10.1001/jama.287.13.1671.
Text Size: A A A
Published online

Context Development of new biomarkers for ovarian cancer is needed for early detection and disease monitoring. Analyses involving complementary DNA (cDNA) microarray data can be used to identify up-regulated genes in cancer cells, whose products may then be further validated as potential biomarkers.

Objective To describe validation studies of an up-regulated gene known as osteopontin, previously identified using a cDNA microarray system.

Design, Setting, and Participants Experimental and cross-sectional studies were conducted involving ovarian cancer and healthy human ovarian surface epithelial cell lines and cultures, archival paraffin-embedded ovarian tissue collected between June 1992 and June 2001, and fresh tissue and preoperative plasma from 144 patients evaluated for a pelvic mass between June 1992 and June 2001 in gynecologic oncology services at 2 US academic institutions. Plasma samples from 107 women selected from an epidemiologic study of ovarian cancer initiated between May 1992 and March 1997 were used as healthy controls.

Main Outcome Measures Relative messenger RNA expression in cancer cells and fresh ovarian tissue, measured by real-time polymerase chain reaction as 2−ΔΔCT(a quantitative value representing the amount of osteopontin expression); osteopontin production, localized and scored in ovarian healthy and tumor tissue with immunohistochemical studies; and amount of osteopontin in patient vs control plasma, measured using an enzyme-linked immunoassay.

Results The geometric mean for 2−ΔΔCTfor osteopontin expression in 5 healthy ovarian epithelial cell cultures was 4.1 compared with 270.4 in 14 ovarian cancer cell lines (P = .03). The geometric mean 2−ΔΔCTfor osteopontin expression in tissue from 2 healthy ovarian epithelial samples was 9.0 compared with 164.0 in 27 microdissected ovarian tumor tissue samples (P = .06). Immunolocalization of osteopontin showed that tissue samples from 61 patients with invasive ovarian cancer and 29 patients with borderline ovarian tumors expressed higher levels of osteopontin than tissue samples from 6 patients with benign tumors and samples of healthy ovarian epithelium from 3 patients (P = .03). Osteopontin levels in plasma were significantly higher (P<.001) in 51 patients with epithelial ovarian cancer (486.5 ng/mL) compared with those of 107 healthy controls (147.1 ng/mL), 46 patients with benign ovarian disease (254.4 ng/mL), and 47 patients with other gynecologic cancers (260.9 ng/mL).

Conclusions Our findings provide evidence for an association between levels of a biomarker, osteopontin, and ovarian cancer and suggest that future research assessing its clinical usefulness would be worthwhile.

Figures in this Article

Ovarian cancer ranks as the fifth leading cause of death from cancer and has the highest mortality rate among the gynecologic malignancies in the United States.1 Every year approximately 25 000 ovarian cancer cases are newly diagnosed and approximately 15 000 deaths occur secondary to the malignancy.2 This high case-fatality ratio reflects the fact that most ovarian cancer cases are detected at stage III or IV, at which the 5-year survival rate is below 30% compared with 95% with stage I.3 To improve survival, it would be desirable to develop tumor markers that could be used to detect the early stages of the disease.

The development of high-throughput complementary DNA (cDNA) microarray techniques offers great potential for identifying novel and specific biomarkers for the early detection of cancer.46 Using these techniques, potential serum markers for several cancers have been identified.69 In our study with the MICROMAX (PerkinElmer Life Sciences [previously NEN Life Sciences], Boston, Mass) cDNA microarray system using RNA isolated from several ovarian cancer cell lines and healthy human ovarian surface epithelial (HOSE) cell cultures, we identified a spot with an ovarian cancer/HOSE ratio of 184 that corresponded to a protein called osteopontin.6 We present the experimental and clinical studies addressing the potential clinical usefulness of this marker.

Cell Lines and Cultures

All ovarian cancer cell line material was obtained either by scraping the surfaces of healthy ovaries, recovery of material from ascites, or procurement of explanted tissue from solid tumors as described previously.10 Five healthy HOSE cell cultures used in this experiment were HOSE695, HOSE697, HOSE713, HOSE726, and HOSE730. Fourteen ovarian cancer cell lines were used: ALST, CAOV3, DOV13, OVCA3, OVCA420, OVCA429, OVCA432, OVCA433, OVCA633, and SKOV3 originated from serous cystadenocarcinoma; RMUG-L and RMUG-S originated from mucinous cystadenocarcinoma; and RMG-1 and ES-2 originated from clear-cell carcinoma. All cell cultures and cell lines were established in the Laboratory of Gynecologic Oncology, Brigham and Women's Hospital, Boston, Mass, except OVCA3, SKOV3, RMUG-L, RMUG-S, RMG-1, and ES-2, which were purchased from the American Type Culture Collection (Rockville, Md) and the Japanese Collection of Research Bioresources (Tokyo, Japan), respectively.

Biosamples

All patient-derived specimens were collected and archived under protocols approved by the institutional review boards (IRBs) of the parent institutions. Paraffin blocks (n = 99) of ovarian cancer and healthy tissue from the Brigham and Women's Hospital pathology department archives were collected between June 1992 and June 2001, representing a cross-section of histologic types and grades seen at the institution. The blocks were collected under a separate "discarded material" IRB protocol allowing study of such material provided there was linkage only to diagnostic details such as tumor stage and grade. A separate bank of plasma and fresh frozen tissue, representing a different group of patients and for which written informed consent was required, was obtained from 144 women evaluated for a pelvic mass at the practices of 2 oncologists (J.O.S. and R.S.B.) at the Brigham and Women's Hospital between June 1992 and June 2001, and at the University of Texas Southwestern Medical Center, Dallas, between December 2000 and June 2001. The patients represent a cross-section of women seen in these practices and were selected from those women who consented to the protocol and had nonemergent surgery when technical support to collect the specimens was available. The 144 case patients were divided into those with epithelial ovarian tumors (n = 51), other gynecologic cancers (n = 47), and benign disease (n = 46). All tumor tissue contained less than 20% healthy tissue and was collected from the primary ovarian sites and, if possible, metastatic sites. Control plasma specimens (n = 107) were derived from an IRB-approved epidemiologic study of ovarian cancer initiated between May 1992 and March 1997. These controls were selected to match 5-year age groups in cases from 496 plasma specimens still available from an original total of 523 from the epidemiologic study and involved women selected from the general population of Massachusetts and New Hampshire.11,12 A match for all 144 case patients was not sought but the number of controls was chosen to be at least twice as large as the number of individuals in the separate case groups.

For fresh-frozen sections, fresh specimens were embedded in Tissue Tek OCT medium (Miles, Elkhart, Ind), snap-frozen in liquid nitrogen, and stored at –80°C until use. The archival tissues in paraffin blocks were retrieved from pathology files in the Laboratory of Gynecologic Oncology at the Brigham and Women's Hospital. The plasma samples were centrifuged at 2000g at 4°C for 15 minutes. The separated plasma was removed, aliquoted, and frozen at − 80°C for future analysis.

Laser Capture Microdissection

Tissues stored in Tissue Tek OCT (Miles) medium at − 80°C were sectioned at 7 µm in a cryostat (Leica, Allendale, NJ). Sections were mounted on uncoated glass slides and immediately fixed in 70% and 50% ethanol for 30 seconds in each, stained with hematoxylin-eosin, dehydrated in alcohol solutions of increasing concentration, and cleared in xylene for 5 minutes in each. After being air-dried for 3 minutes, the sections were laser microdissected using the PixCell II (Arctarus, Calif). Tissue with morphologically healthy ovarian epithelial cells and malignant epithelial ovarian cancer cells was procured, representing 27 cases with ovarian cancer tissue and 2 cases with healthy ovarian tissue. These samples were selected from enrolled cases with sufficient material for study, representing a range of histologic types.

Real-Time Quantitative Reverse Transcription Polymerase Chain Reaction

Real-time quantitative reverse transcription polymerase chain reaction (RT-PCR) was used for analysis of cell cultures and lines and microdissected fresh tissues. Total RNA extraction and cDNA synthesis were performed as described previously.13 For the quantitative RT-PCR studies, a total of 2 µL of cDNA was used in a 23-µL PCR mix containing 1X SYBR PCR buffer, 3 mM MgCl2, 0.8 mM dNTP, and 0.025 U/µL AmpliTaq Gold (PE Applied Biosystems, Foster City, Calif). Amplification was then performed in duplicate using primer sets, which we developed for osteopontin and were manufactured by and purchased from Sigma Genosys (Woodland, Tex) (forward primer: 5′-AAGCGAGGAGTTGAATGGTGCAT-3′; reverse primer: 5′-TGTGGGTTTCAGCACTCTGCTTCAT-3′) and a housekeeping gene, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), as a control in an ABI PRISM 5700 Sequence Detector (PE Applied Biosystems) with denaturation for 10 minutes at 95°C followed by 40 PCR cycles of denaturation at 95°C for 15 seconds and annealing or extension at 60°C for 1 minute. The ABI5700 system software monitored the changes in fluorescence of SYBR Green I dye in every cycle. The threshold cycle (CT) value for each reaction, reflecting the amount of PCR needed to identify a target gene, and the relative level of osteopontin for each sample were calculated as described.1315 Briefly, GAPDH was used for the normalization of the quantity of RNA used. Its CT value was then subtracted from that of the osteopontin gene to obtain a ΔCT value. The difference (ΔΔCT) between the ΔCT values of the samples for the gene target and the ΔCT value of the calibrator (HOSE697 for cell lines or 741A for tissue) was determined. These calibrators were chosen because they had the lowest expression values for cell lines and tissues, respectively. The relative quantitative value was expressed as 2−ΔΔCT, representing the amount of osteopontin expression (normalized to a reference [endogenous]), relative to the calibrators.15 Specimens were run in duplicate and the values averaged. To confirm the specificity of the PCR reaction, PCR products were electrophoresed on a 1.2% agarose gel.

Immunohistochemistry

The paraffin block specimens used in this experiment were derived from archived tissue (not representing samples from patients contributing fresh specimens) and consisted of tissue from 3 healthy ovaries, 6 benign ovarian tumors (1 serous, 4 mucinous, and 1 mixed), 29 borderline ovarian cancers (13 serous, 14 mucinous, 1 clear cell, and 1 mixed), and 61 invasive ovarian cancers (21 serous, 21 mucinous, 6 endometrioid, 8 clear cell, 2 undifferentiated, and 3 mixed). The archived paraffin blocks were derived from patients having surgery at the Brigham and Women's Hospital. Blocks were selected to represent a cross-section of histologic types and grades, overselecting for early-stage cases. There were 42 blocks containing International Federation of Gynecology and Obstetrics (FIGO) stage I/II tumor and 33 blocks with stage III/IV tumor included in im-munohistochemical studies.

Immunohistochemical studies were performed using the avidin-biotin method, as described previously.13 Sections were incubated with primary mouse monoclonal antibody directed against osteopontin (2 µg/mL) for 60 minutes at 37°C (Immuno-Biological Laboratories [IBL], Gumma, Japan). The control sections were treated in parallel but incubated with normal mouse serum (as a negative control) instead of the primary antibody. All sections were incubated in a moist chamber. Sections were then incubated with a biotinylated secondary antibody for 30 minutes (Vector Laboratories, Burlingame, Calif). After 30 minutes of incubation in avidin-biotin complex, the reaction product was visualized by 3,3-diaminobenzidine tetrahydrochloride (Vector Laboratories). Finally, sections were dehydrated and cleared in ethanol and xylene and mounted in SP15-500 Permount (Fisher Scientific, Pittsburgh, Pa). Representative photomicrographs were recorded by a digital camera (Optronic, Goleta, Calif). Intensity of staining was quantified using a semiquantitative scoring system as described.16

Enzyme-Linked Immunosorbent Assay

Levels of osteopontin in plasma samples were measured with a solid-phase sandwich enzyme-linked immunosorbent assay (ELISA) using a commercially available kit, which has interassay coefficient of variation varying from 0.7% to 2.0% and intraassay coefficient of variation varying from 3.7% to 4.7% depending on the level of the marker (Code No. 17158, IBL). Microplates were first precoated with anti–human osteopontin rabbit IgG (100 µL of 20 µg/mL in 0.1-M carbonate buffer; pH, 9.5) and blocked with 1% bovine serum albumin and 0.05% Tween 20. Plasma and standard osteopontin samples were diluted with 1% bovine serum albumin and 0.05% Tween 20 in phosphate-buffered saline and incubated for 1 hour at 37°C. After 7 washes with 0.05% Tween 20 in phosphate buffer, horseradish peroxidase–labeled conjugated anti–human osteopontin (10A16) mouse monoclonal antibody (100 µL of 2 ng/mL) was added and incubated for 30 minutes at 4°C. After 9 washes, 100 µL of tetramethyl benzidine buffer was added and the signal was allowed to develop for 30 minutes at room temperature. The reaction was stopped with 100 µL of 1 N sulfuric acid. The absorbance at 450 nm was measured by an automatic ELISA reader (Biorad, Hercules, Calif).

Results were converted from the mean absorbance of duplicate wells after subtraction of background values. Recombinant human osteopontin protein (IBL) was used as a standard. The standard curve was prepared simultaneously with the measurement of test samples. Reagent blank, test sample blank, and internal controls of plasma samples were used to normalize osteopontin values obtained from each experiment.

Statistical Analysis

The relative measures of osteopontin expression, 2−ΔΔCT, as measured using RT-PCR in cancer and healthy cells or cancer and healthy tissue were compared with unpaired t tests on log-transformed values. Immunochemistry scores were compared using the nonparametric Kruskal-Wallis test for overall group differences. Osteopontin has plasma levels that range over multiple orders of magnitude; therefore, a logarithmic transformation was used to change to an arithmetic scale. Simultaneously, the transformed data complied more accurately with the assumptions of a Gaussian distribution for residuals in general linear models. Data were summarized with the number of observations, the geometric mean (P values were applied appropriately to differences in the log [osteopontin] levels), the 95% confidence intervals (CIs) for the geometric mean, and the range of the data. The general linear model was used to determine differences in means among groups (eg, diagnostic groups or within ovarian cancers for the histologic groups) and age was added to the model to adjust for any age effects on osteopontin levels. The ELISA levels were compared using the Kruskal-Wallis test or Mann-Whitney U test among groups. The level of critical significance was considered to be P<.05.

For reporting specificity and sensitivity estimates, there are a variety of arbitrary choices, including presenting the full receiver operating characteristic curve, or fixing sensitivity at an arbitrary value and estimating the specificity, or fixing specificity at an arbitrary value and estimating sensitivity. The latter choice was made for this report with a choice of specificity of 80%. First, the nearest cutoff for osteopontin corresponding to this level of specificity is determined, then the sensitivity is estimated as the number of patients with disease for a given subgroup with osteopontin levels exceeding the cutoff divided by the number of patients with disease in the given subgroup. The actual specificity may vary slightly from the target value (80% = 4/5) because the number of case patients is not (in this study) divisible by 5. All analyses were performed using SPSS version 9.0 (SPSS Inc, Chicago, Ill) and S-PLUS (Insightful Inc, Seattle, Wash).

To validate overexpression of osteopontin in ovarian cancer, real-time RT-PCR was applied to an expanded series of ovarian epithelial cell cultures and cancer cell lines and tissues. Based on the ΔΔCT relative to the healthy cell culture, HOSE697, the relative expression levels of osteopontin messenger RNA (mRNA) in other cell lines were calculated (Figure 1). The geometric means of healthy and cancer cell lines were 4.1 and 270.4 (P = .03). Except for CAOV3, OVCA3, OVCA429, and ES-2, the other 10 ovarian cancer cell lines showed high levels of osteopontin expression. There was no significant difference in osteopontin expression among cell lines derived from different histologic subtypes (Figure 1).

Figure 1. Relative Quantitation of Osteopontin in Healthy Ovarian Epithelial Cell Cultures and Malignant Ovarian Epithelial Cancer Cell Lines
Graphic Jump Location
Statistically significant differences were obtained between 5 healthy human ovarian surface epithelial (HOSE) cell cultures, 10 serous-type ovarian cancer cell lines, 2 mucinous-type ovarian cancer cell lines, and 2 clear cell–type ovarian cancer cell lines by unpaired t test (P = .03). Each value was expressed as the mean of duplicate. The referent was HOSE697, considered to have a value of 1.

Osteopontin expression in microdissected ovarian cancer tissues was also examined using real-time RT-PCR with 741A as the reference. Higher osteopontin expression in the 27 ovarian cancer tissues was observed compared with expression in the 2 samples of healthy ovarian surface epithelium. The geometric mean of the 2 groups was 9.0 and 164.0 with logarithmic transformation, respectively. The statistical difference was nonsignificant, perhaps due to the limited number of healthy samples examined (P = .06). There was no significant difference in osteopontin expression among tumors of different subtypes (Figure 2).

Figure 2. Relative Quantitation of Osteopontin in Healthy Ovarian Epithelial Tissues and Malignant Ovarian Epithelial Cancer Tissues
Graphic Jump Location
Expression differences were obtained between samples of 2 healthy ovarian epithelial tissues, 17 serous-type ovarian cancer tissues, 6 mucinous-type ovarian cancer tissues, and 4 endometrioid-type ovarian cancer tissues by unpaired t test (P = .06). Each value was expressed as the mean of duplicate. The referent was 741A, considered to have a value of 1.

Osteopontin protein levels in paraffin block sections of 3 healthy tissues, 6 benign ovarian tumors, 29 borderline ovarian cancers, and 61 invasive ovarian cancers were assessed via immunohistochemistry studies. Osteopontin immunoreactivity was not observed in epithelium and stroma of the healthy ovarian tissues (score 0). Most positive staining observed in cancer tissues was localized to the cellular membrane and cytoplasm, extracellular matrix component, or psammoma bodies with some variations by histologic subtypes. Serous types mainly showed immunopositivity in psammoma bodies with occasional or focal cytoplasmic staining. Immunopositivity in mucinous type was localized to the cytoplasmic, especially pericytoplasmic, region. Abundantly stained extracellular materials suggested that osteopontin was secreted from mucinous ovarian cancer cells. Endometrioid and clear cell subtypes showed focal cytoplasmic localization (Figure 3).

Figure 3. Immunolocalization of Osteopontin in Healthy and Malignant Ovarian Tissues
Graphic Jump Location
Osteopontin expression is indicated by brown staining and was immunolocalized using an anti-osteopontin monoclonal antibody and an avidin-biotin peroxidase complex method with diaminobenzidine as the chromogen. The sections were counterstained with hematoxylin. A, Healthy ovarian surface epithelial cells with no expression of osteopontin. B, Endometrioid cystadenocarcinoma with osteopontin expression in cancer cells. C, Borderline mucinous tumor with osteopontin expression in cell membrane and cytoplasmic area. D, Invasive mucinous cystadenocarcinoma. E, Serous cystadenocarcinoma with osteopontin expression in psamomma body. F, Serous cystadenocarcinoma with osteopontin expression in cancer cells.

The immunostaining scores in tissue sections from healthy ovary, benign ovarian tumor, borderline ovarian tumor, and invasive ovarian cancer were 0.0 (95% CI, 0.0-0.0), 0.7 (95% CI, 0.0-1.8), 2.2 (95% CI, 1.5-2.9), and 2.1 (95% CI, 1.7-2.6), respectively (Table 1). The difference among diagnostic groups was statistically significant (P = .03) as well as the differences among histologic groups (P = .01) with mucinous cases having higher expression. Among the cancer (borderline and invasive) group, there was no significant difference in osteopontin immunoreactivity among different grades and stages.

Table Graphic Jump LocationTable 1. Expression of Osteopontin in Relation to Histopathologic Characteristics in Immunohistochemical Analyses*

Finally, we examined osteopontin levels in plasma samples obtained from 107 healthy controls, 46 patients with benign disease, 47 patients with gynecologic cancers other than ovarian cancers, and 51 patients with ovarian cancer using ELISA. The mean ages for the groups by category were 50.8 years for healthy, 54.6 years for benign disease, 50.9 years for other gynecologic cancers, and 55.4 years for ovarian cancer. Because the age difference between the ovarian cancer patients and healthy controls was marginally significant (P = .04), P values for the differences among mean (logarithm) osteopontin levels are presented from linear models that include a term for age.

The mean osteopontin level for all of the patients was 230.9 ng/mL (95% CI, 130.2-409.3 ng/mL) and in the categories of healthy controls, benign disease, other gynecologic cancers, and ovarian cancer, the mean levels were 147.1 ng/mL (95% CI, 99.4-217.7 ng/mL), 254.4 ng/mL (95% CI, 148.2-436.7 ng/mL), 260.9 ng/mL (95% CI, 127.8-532.7 ng/mL), and 486.5 ng/mL (95% CI, 315.0-751.4 ng/mL), respectively (Figure 4). The difference in osteopontin level between ovarian cancer cases and healthy controls was statistically significant (P<.001) (Table 2). There were no significant differences among histologic types (P = .11), different histologic grades (P = .26), and stages (P = .17) of ovarian cancer (Table 2).

Figure 4. Osteopontin Levels in Case Patients Within 4 Diagnostic Categories
Graphic Jump Location
The box is bounded above and below by the 75th and 25th percentiles and the median is the line in the box. Whiskers are drawn to the nearest value not beyond a standard span from the quartiles; points beyond (outliers) are drawn individually, where the standard span is 1.5 × (interquartile range).
Table Graphic Jump LocationTable 2. Preoperative Osteopontin Levels in Patients With Ovarian Cancer vs Those of Controls and Patients With Benign or Other Gynecologic Disease*

Using a cutoff value of 252 ng/mL, the specificity was 80.4% and the sensitivity point estimates for the detection of early-stage (I/II) and late-stage (III/IV) ovarian cancer were 80.4% and 85.4%, respectively.

Because of the tendency for ovarian cancer to produce clinical symptoms at a late stage, there is a need for better early detection methods. Although a number of tumor markers have been identified and studied for ovarian cancer,1722 a useful screening marker for ovarian cancer has not been clearly established. The most widely researched marker, CA125, has shown some value in postmenopausal women in pilot screening studies but sensitivity for early-stage disease before clinical detection remains questionable.23 Thus, a marker of advanced disease may not translate well to identification of early asymptomatic disease.

One approach to meeting the need for new markers is the use of cDNA microarray technology to identify up-regulating genes in ovarian cancer cells or tissues. Previously, we described the cDNA MICROMAX microarray system to identify up- or down-regulated genes in ovarian cancer using RNA pooled from several healthy HOSE cell cultures and ovarian cancer cell lines.6 We described herein the additional studies necessary to establish the potential clinical relevance of one of the markers identified, osteopontin.

Osteopontin is an acidic, calcium-binding glycophosphoprotein that is found in all body fluids and in the extracellular matrix components.2429 The molecular weight is 44 kd to 66 kd, depending on species and cell types.2429 Osteopontin has been referred to as pp69, 44-kd bone phosphoprotein, 2ar, Eta-1, transformation associated phosphoprotein 1, and 2B7.2429 It can function both as a cell adhesion protein and as a cytokine for several integrins and CD44.30,31 Furthermore, it has been shown to be involved in inflammation, especially in regulation of macrophages,3237 tumorigenesis,28,3845 and dystrophic calcification.3941,46

To further examine osteopontin's clinical potential, it was first necessary to show that osteopontin is expressed in individual cell lines and in actual cancer tissue. A technique involving real-time RT-PCR was used to measure gene expression in cells or tissue. Our study demonstrated that osteopontin was expressed in a number of ovarian cancer cell lines different from the ones previously used in the microarray experiment.6 We next used real-time RT-PCR with actual ovarian cancer tissue to demonstrate that expression was not an artifact associated with the culturing of ovarian cancer cells in vitro. Real-time RT-PCR applied to microdissected ovarian cancer tissue also demonstrated increased osteopontin mRNA expression in the cancer tissue compared with healthy tissue, though the difference was not statistically significant. Another method for demonstrating expression is to use immunohistochemical studies to examine protein expression assessed through staining of tumor or healthy ovarian tissue. This technique offers the advantage of being able to use material archived in tumor blocks but does require the existence of an antibody to the overexpressed protein, which in this case was available.

Our immunohistochemistry results suggested that different histologic subtypes of ovarian cancer have different osteopontin expression patterns. In serous ovarian cancer, high levels of osteopontin were localized to the psamomma bodies, which are laminated calcified concretions commonly found in serous cancers. Curiously, the cancer cells expressed low levels of osteopontin protein, yet the real-time RT-PCR data on cell lines and microdissected tumors showed relatively high levels of osteopontin mRNA in the majority of samples of serous cancer cells. The discrepancy between osteopontin mRNA and protein levels may be explained by the fact that osteopontin protein may be actively secreted by serous epithelial cancer cells and, subsequently, translocated to the psammoma bodies resulting in calcium phosphate deposition. Recently, osteopontin mRNA has also been detected in CD68 protein macrophages infiltrating serous ovarian cancer tissues,40 suggesting that tumor-infiltrating macrophages may also secrete osteopontin and are involved in the generation of psammoma bodies in serous cancers. A recent study of osteopontin expression in 16 serous borderline ovarian tumors and 14 serous invasive ovarian carcinomas showed a significantly higher level of expression in borderline tumors than carcinomas, suggesting that osteopontin may be important for the pathogenesis of serous borderline tumors.41

In contrast to serous-type ovarian cancer, higher osteopontin protein levels were detected in the cytoplasm of mucinous-type ovarian cancer cells, suggesting active osteopontin protein synthesis in these cells. Different osteopontin expression patterns in different histologic subtypes of cancer have also been described in lung and esophageal cancers.47,48 Osteopontin overexpression has been demonstrated in immunohistochemical studies of a number of other cancers including cancer of prostate, breast, and stomach.4145

Clearly, any proposed tumor marker must be identifiable in blood or other readily accessed biological samples. Using ELISA, we measured osteopontin levels in preoperative plasma from patients with epithelial ovarian cancer and plasma from healthy controls. Preoperative osteopontin levels were significantly higher in women with ovarian cancer compared with those in women not having ovarian cancer or those with benign pelvic disease. In addition, osteopontin levels were significantly higher in patients with ovarian cancer than in patients with other types of gynecologic cancers (cervix and endometrium). We also observed no significant difference in osteopontin levels as assessed via ELISA among serous, mucinous, clear cell, and endometrioid types of ovarian cancer, suggesting that osteopontin may be useful in detecting most subtypes of ovarian cancer. We believe preoperative sensitivity estimates may be sufficiently high to encourage pilot clinical screening studies, which would include osteopontin in a panel of putative early detection markers to obtain estimates of screening sensitivity and specificity. The crucial issue to be addressed is the sensitivity of a panel of biomarkers for detecting early-stage ovarian cancer or for screening subjects who would have been clinically detected in late-stage disease. Sensitivity estimates based on preoperative samples from clinically detected patients, either early- or late-stage disease, are no substitute for estimates obtained from prospectively conducted clinical trials and are at best a guide as to which markers to test in such a trial.

In conclusion, this investigation has demonstrated the potential value of the cDNA microarray analysis in identifying overexpressed genes in ovarian cancer and its subsequent link to a protein measurable in plasma. The findings suggest evidence for an association between plasma levels of osteopontin and ovarian cancer, pointing to a rationale for further research assessing potential clinical usefulness.

Greenlee RT, Murray T, Bolden S, Wingo PA. Cancer statistics.  CA Cancer J Clin.2000;50:7-33.
Landis SH, Murray T, Bolden S, Wingo PA. Cancer statistics, 1999.  CA Cancer J Clin.1999;49:8-31.
Ries LA, Kosary CL, Hankey BF.  et al.  SEER Cancer Statistic Review, 1973-1995. Bethesda, Md: National Cancer Institute; 1998.
Sgroi DC, Teng S, Robinson G.  et al.  In vivo gene expression profile analysis of human breast cancer progression.  Cancer Res.1999;59:5656-5661.
Villaret DB, Wang T, Dillon D.  et al.  Identification of genes overexpressed in head and neck squamous cell carcinoma using a combination of complementary DNA subtraction and microarray analysis.  Laryngoscope.2000;110:374-381.
Wong KK, Cheng RS, Mok SC. Identification of differentially expressed genes from ovarian cancer cells by MICROMAX cDNA microarray system.  Biotechniques.2001;30:670-675.
Bull JH, Ellison G, Patel A.  et al.  Identification of potential diagnostic markers of prostate cancer and prostatic intraepithelial neoplasia using cDNA microarray.  Br J Cancer.2001;84:1512-1519.
Kononen J, Bubendorf L, Kallioniemi A.  et al.  Tissue microarrays for high-throughput molecular profiling of tumor specimens.  Nat Med.1998;4:844-847.
Dhanasekaran SM, Barrette TR, Ghosh D.  et al.  Delineation of prognostic biomarkers in prostate cancer.  Nature.2001;412:822-826.
Tsao SW, Mok SC, Fey EG.  et al.  Characterization of human ovarian surface epithelial cells immortalized by human papilloma viral oncogenes (HPV-E6E7 ORFs).  Exp Cell Res.1995;218:499-507.
Cramer DW, Kuper H, Harlow BL, Titus-Ernstoff L. Carotenoids, antioxidants and ovarian cancer risk in pre- and postmenopausal women.  Int J Cancer.2001;94:128-134.
Cramer DW, Greenberg ER, Titus-Ernstoff L.  et al.  A case-control study of galactose consumption and metabolism in relation to ovarian cancer.  Cancer Epidemiol Biomarkers Prev.2000;9:95-101.
Mok SC, Chao J, Skates S.  et al.  Prostasin, a potential serum marker for ovarian cancer.  J Natl Cancer Inst.2001;93:1458-1464.
Heid CA, Stevens J, Livak L, Williams IM. Real time quantitative PCR.  Genome Res.1996;6:986-994.
 Absolute and relative quantitation. In: GeneAmp 5700 User's Manual. Foster City, Calif: PE Applied Biosystems; 1998:A9-A11.
Chan WY, Cheung KK, Schorge JO.  et al.  Bcl-2 and p53 protein expression, apoptosis, and p53 mutation in human epithelial ovarian cancers.  Am J Pathol.2000;156:409-417.
Xu Y, Shen Z, Wiper DW.  et al.  Lysophosphatidic acid as a potential biomarker for ovarian and other gynecologic cancers.  JAMA.1998;280:719-723.
Tuxen MK, Soletormos G, Petersen PH.  et al.  Assessment of biological variation and analytical imprecision of CA 125, CEA, and TPA in relation to monitoring of ovarian cancer.  Gynecol Oncol.1999;74:12-22.
Sandmaier BM, Oparin DV, Holmberg LA.  et al.  Evidence of a cellular immune response against sialyl-Tn in breast and ovarian cancer patients after high-dose chemotherapy, stem cell rescue, and immunization with Theratope STn-KLH cancer vaccine.  J Immunother.1999;22:54-66.
Luo LY, Katsaros D, Scorilas A.  et al.  Prognostic value of human kallikrein 10 expression in epithelial ovarian carcinoma.  Clin Cancer Res.2001;7:2372-2379.
Negishi Y, Iwabuchi H, Sakunaga H.  et al.  Serum and tissue measurements of CA72-4 in ovarian cancer patients.  Gynecol Oncol.1993;48:148-154.
Hogdall CK, Mogensen O, Tabor A.  et al.  The role of serum tetranectin, CA 125, and a combined index as tumor markers in women with pelvic tumors.  Gynecol Oncol.1995;56:22-28.
Jacobs IJ, Skates SJ, MacDonald N.  et al.  Screening for ovarian cancer: a pilot randomised controlled trial.  Lancet.1999;353:1207-1210.
Chackalaparampil I, Banerjee D, Poirier Y, Mukherjee BB. Altered processing of a major secreted phosphoprotein correlates with tumorigenicity in Rous sarcoma virus-transformed mammalian cells.  J Virol.1985;53:841-850.
Prince CW, Oosawa T, Butler WT.  et al.  Isolation, characterization, and biosynthesis of a phosphorylated glycoprotein from rat bone.  J Biol Chem.1987;262:2900-2907.
Smith JH, Denhardt DT. Molecular cloning of a tumor promoter-inducible mRNA found in JB6 mouse epidermal cells: induction is stable at high, but not at low, cell densities.  J Cell Biochem.1987;34:13-22.
Patarca R, Freeman GJ, Singh RP.  et al.  Structural and functional studies of the early T lymphocyte activation 1 (Eta-1) gene.  J Exp Med.1989;170:145-161.
Senger DR, Perruzzi CA, Papadopoulos A. Elevated expression of secreted phosphoprotein I (osteopontin, 2ar) as a consequence of neoplastic transformation.  Anticancer Res.1989;9:1291-1299.
Giachelli C, Bae N, Lombardi D.  et al.  Molecular cloning and characterization of 2B7, a rat mRNA which distinguishes smooth muscle cell phenotypes in vitro and is identical to osteopontin (secreted phosphoprotein I, 2aR).  Biochem Biophys Res Commun.1991;177:867-873.
Liaw L, Skinner MP, Raines EW.  et al.  The adhesive and migratory effects of osteopontin are mediated via distinct cell surface integrins.  J Clin Invest.1995;95:713-724.
Weber GF, Ashkar S, Glimcher MJ, Cantor H. Receptor-ligand interaction between CD44 and osteopontin (Eta-1).  Science.1996;271:509-512.
Giachelli CM, Lombardi D, Johnson RJ.  et al.  Evidence for a role of osteopontin in macrophage infiltration in response to pathological stimuli in vivo.  Am J Pathol.1998;152:353-358.
Crawford HC, Matrisian LM, Liaw L. Distinct roles of osteopontin in host defense activity and tumor survival during squamous cell carcinoma progression in vivo.  Cancer Res.1998;58:5206-5215.
Nau GJ, Guilfoile P, Chupp GL.  et al.  A chemoattractant cytokine associated with granulomas in tuberculosis and silicosis.  Proc Natl Acad Sci U S A.1997;94:6414-6419.
Singh RP, Patarca R, Schwartz J.  et al.  Definition of a specific interaction between the early T lymphocyte activation 1 (Eta-1) protein and murine macrophages in vitro and its effect upon macrophages in vivo.  J Exp Med.1990;171:1931-1942.
Hwang SM, Lopez CA, Heck DE.  et al.  Osteopontin inhibits induction of nitric oxide synthase gene expression by inflammatory mediators in mouse kidney epithelial cells.  J Biol Chem.1994;269:711-715.
McKee MD, Nanci A. Secretion of osteopontin by macrophages and its accumulation at tissue surfaces during wound healing in mineralized tissues.  Anat Rec.1996;245:394-409.
Shijubo N, Uede T, Kon S.  et al.  Vascular endothelial growth factor and osteopontin in stage I lung adenocarcinoma.  Am J Respir Crit Care Med.1999;160:1269-1273.
Tunio GM, Hirota S, Nomura S, Kitamura Y. Possible relation of osteopontin to development of psammoma bodies in human papillary thyroid cancer.  Arch Pathol Lab Med.1998;122:1087-1090.
Maki M, Hirota S, Kaneko Y, Morohoshi T. Expression of osteopontin messenger RNA by macrophages in ovarian serous papillary cystadenocarcinoma.  Pathol Int.2000;50:531-535.
Tiniakos DG, Yu H, Liapis H. Osteopontin expression in ovarian carcinomas and tumors of low malignant potential (LMP).  Hum Pathol.1998;29:1250-1254.
Thalmann GN, Sikes RA, Devoll RE.  et al.  Osteopontin: possible role in prostate cancer progression.  Clin Cancer Res.1999;5:2271-2277.
Kim YW, Park YK, Lee J.  et al.  Expression of osteopontin and osteonectin in breast cancer.  J Korean Med Sci.1998;13:652-657.
Tuck AB, O'Malley FP, Singhal H.  et al.  Osteopontin expression in a group of lymph node negative breast cancer patients.  Int J Cancer.1998;79:502-508.
Ue T, Yokozaki H, Kitadai Y.  et al.  Co-expression of osteopontin and CD44v9 in gastric cancer.  Int J Cancer.1998;79:127-132.
Giachelli CM, Liaw L, Murry CE.  et al.  Osteopontin expression in cardiovascular diseases.  Ann N Y Acad Sci.1995;760:109-126.
Casson AG, Wilson SM, McCart JA.  et al.  ras mutation and expression of the ras-regulated genes osteopontin and cathepsin L in human esophageal cancer.  Int J Cancer.1997;72:739-745.
Zhang J, Takahashi K, Takahashi F.  et al.  Differential osteopontin expression in lung cancer.  Cancer Lett.2001;171:215-222.

Figures

Figure 1. Relative Quantitation of Osteopontin in Healthy Ovarian Epithelial Cell Cultures and Malignant Ovarian Epithelial Cancer Cell Lines
Graphic Jump Location
Statistically significant differences were obtained between 5 healthy human ovarian surface epithelial (HOSE) cell cultures, 10 serous-type ovarian cancer cell lines, 2 mucinous-type ovarian cancer cell lines, and 2 clear cell–type ovarian cancer cell lines by unpaired t test (P = .03). Each value was expressed as the mean of duplicate. The referent was HOSE697, considered to have a value of 1.
Figure 2. Relative Quantitation of Osteopontin in Healthy Ovarian Epithelial Tissues and Malignant Ovarian Epithelial Cancer Tissues
Graphic Jump Location
Expression differences were obtained between samples of 2 healthy ovarian epithelial tissues, 17 serous-type ovarian cancer tissues, 6 mucinous-type ovarian cancer tissues, and 4 endometrioid-type ovarian cancer tissues by unpaired t test (P = .06). Each value was expressed as the mean of duplicate. The referent was 741A, considered to have a value of 1.
Figure 3. Immunolocalization of Osteopontin in Healthy and Malignant Ovarian Tissues
Graphic Jump Location
Osteopontin expression is indicated by brown staining and was immunolocalized using an anti-osteopontin monoclonal antibody and an avidin-biotin peroxidase complex method with diaminobenzidine as the chromogen. The sections were counterstained with hematoxylin. A, Healthy ovarian surface epithelial cells with no expression of osteopontin. B, Endometrioid cystadenocarcinoma with osteopontin expression in cancer cells. C, Borderline mucinous tumor with osteopontin expression in cell membrane and cytoplasmic area. D, Invasive mucinous cystadenocarcinoma. E, Serous cystadenocarcinoma with osteopontin expression in psamomma body. F, Serous cystadenocarcinoma with osteopontin expression in cancer cells.
Figure 4. Osteopontin Levels in Case Patients Within 4 Diagnostic Categories
Graphic Jump Location
The box is bounded above and below by the 75th and 25th percentiles and the median is the line in the box. Whiskers are drawn to the nearest value not beyond a standard span from the quartiles; points beyond (outliers) are drawn individually, where the standard span is 1.5 × (interquartile range).

Tables

Table Graphic Jump LocationTable 1. Expression of Osteopontin in Relation to Histopathologic Characteristics in Immunohistochemical Analyses*
Table Graphic Jump LocationTable 2. Preoperative Osteopontin Levels in Patients With Ovarian Cancer vs Those of Controls and Patients With Benign or Other Gynecologic Disease*

References

Greenlee RT, Murray T, Bolden S, Wingo PA. Cancer statistics.  CA Cancer J Clin.2000;50:7-33.
Landis SH, Murray T, Bolden S, Wingo PA. Cancer statistics, 1999.  CA Cancer J Clin.1999;49:8-31.
Ries LA, Kosary CL, Hankey BF.  et al.  SEER Cancer Statistic Review, 1973-1995. Bethesda, Md: National Cancer Institute; 1998.
Sgroi DC, Teng S, Robinson G.  et al.  In vivo gene expression profile analysis of human breast cancer progression.  Cancer Res.1999;59:5656-5661.
Villaret DB, Wang T, Dillon D.  et al.  Identification of genes overexpressed in head and neck squamous cell carcinoma using a combination of complementary DNA subtraction and microarray analysis.  Laryngoscope.2000;110:374-381.
Wong KK, Cheng RS, Mok SC. Identification of differentially expressed genes from ovarian cancer cells by MICROMAX cDNA microarray system.  Biotechniques.2001;30:670-675.
Bull JH, Ellison G, Patel A.  et al.  Identification of potential diagnostic markers of prostate cancer and prostatic intraepithelial neoplasia using cDNA microarray.  Br J Cancer.2001;84:1512-1519.
Kononen J, Bubendorf L, Kallioniemi A.  et al.  Tissue microarrays for high-throughput molecular profiling of tumor specimens.  Nat Med.1998;4:844-847.
Dhanasekaran SM, Barrette TR, Ghosh D.  et al.  Delineation of prognostic biomarkers in prostate cancer.  Nature.2001;412:822-826.
Tsao SW, Mok SC, Fey EG.  et al.  Characterization of human ovarian surface epithelial cells immortalized by human papilloma viral oncogenes (HPV-E6E7 ORFs).  Exp Cell Res.1995;218:499-507.
Cramer DW, Kuper H, Harlow BL, Titus-Ernstoff L. Carotenoids, antioxidants and ovarian cancer risk in pre- and postmenopausal women.  Int J Cancer.2001;94:128-134.
Cramer DW, Greenberg ER, Titus-Ernstoff L.  et al.  A case-control study of galactose consumption and metabolism in relation to ovarian cancer.  Cancer Epidemiol Biomarkers Prev.2000;9:95-101.
Mok SC, Chao J, Skates S.  et al.  Prostasin, a potential serum marker for ovarian cancer.  J Natl Cancer Inst.2001;93:1458-1464.
Heid CA, Stevens J, Livak L, Williams IM. Real time quantitative PCR.  Genome Res.1996;6:986-994.
 Absolute and relative quantitation. In: GeneAmp 5700 User's Manual. Foster City, Calif: PE Applied Biosystems; 1998:A9-A11.
Chan WY, Cheung KK, Schorge JO.  et al.  Bcl-2 and p53 protein expression, apoptosis, and p53 mutation in human epithelial ovarian cancers.  Am J Pathol.2000;156:409-417.
Xu Y, Shen Z, Wiper DW.  et al.  Lysophosphatidic acid as a potential biomarker for ovarian and other gynecologic cancers.  JAMA.1998;280:719-723.
Tuxen MK, Soletormos G, Petersen PH.  et al.  Assessment of biological variation and analytical imprecision of CA 125, CEA, and TPA in relation to monitoring of ovarian cancer.  Gynecol Oncol.1999;74:12-22.
Sandmaier BM, Oparin DV, Holmberg LA.  et al.  Evidence of a cellular immune response against sialyl-Tn in breast and ovarian cancer patients after high-dose chemotherapy, stem cell rescue, and immunization with Theratope STn-KLH cancer vaccine.  J Immunother.1999;22:54-66.
Luo LY, Katsaros D, Scorilas A.  et al.  Prognostic value of human kallikrein 10 expression in epithelial ovarian carcinoma.  Clin Cancer Res.2001;7:2372-2379.
Negishi Y, Iwabuchi H, Sakunaga H.  et al.  Serum and tissue measurements of CA72-4 in ovarian cancer patients.  Gynecol Oncol.1993;48:148-154.
Hogdall CK, Mogensen O, Tabor A.  et al.  The role of serum tetranectin, CA 125, and a combined index as tumor markers in women with pelvic tumors.  Gynecol Oncol.1995;56:22-28.
Jacobs IJ, Skates SJ, MacDonald N.  et al.  Screening for ovarian cancer: a pilot randomised controlled trial.  Lancet.1999;353:1207-1210.
Chackalaparampil I, Banerjee D, Poirier Y, Mukherjee BB. Altered processing of a major secreted phosphoprotein correlates with tumorigenicity in Rous sarcoma virus-transformed mammalian cells.  J Virol.1985;53:841-850.
Prince CW, Oosawa T, Butler WT.  et al.  Isolation, characterization, and biosynthesis of a phosphorylated glycoprotein from rat bone.  J Biol Chem.1987;262:2900-2907.
Smith JH, Denhardt DT. Molecular cloning of a tumor promoter-inducible mRNA found in JB6 mouse epidermal cells: induction is stable at high, but not at low, cell densities.  J Cell Biochem.1987;34:13-22.
Patarca R, Freeman GJ, Singh RP.  et al.  Structural and functional studies of the early T lymphocyte activation 1 (Eta-1) gene.  J Exp Med.1989;170:145-161.
Senger DR, Perruzzi CA, Papadopoulos A. Elevated expression of secreted phosphoprotein I (osteopontin, 2ar) as a consequence of neoplastic transformation.  Anticancer Res.1989;9:1291-1299.
Giachelli C, Bae N, Lombardi D.  et al.  Molecular cloning and characterization of 2B7, a rat mRNA which distinguishes smooth muscle cell phenotypes in vitro and is identical to osteopontin (secreted phosphoprotein I, 2aR).  Biochem Biophys Res Commun.1991;177:867-873.
Liaw L, Skinner MP, Raines EW.  et al.  The adhesive and migratory effects of osteopontin are mediated via distinct cell surface integrins.  J Clin Invest.1995;95:713-724.
Weber GF, Ashkar S, Glimcher MJ, Cantor H. Receptor-ligand interaction between CD44 and osteopontin (Eta-1).  Science.1996;271:509-512.
Giachelli CM, Lombardi D, Johnson RJ.  et al.  Evidence for a role of osteopontin in macrophage infiltration in response to pathological stimuli in vivo.  Am J Pathol.1998;152:353-358.
Crawford HC, Matrisian LM, Liaw L. Distinct roles of osteopontin in host defense activity and tumor survival during squamous cell carcinoma progression in vivo.  Cancer Res.1998;58:5206-5215.
Nau GJ, Guilfoile P, Chupp GL.  et al.  A chemoattractant cytokine associated with granulomas in tuberculosis and silicosis.  Proc Natl Acad Sci U S A.1997;94:6414-6419.
Singh RP, Patarca R, Schwartz J.  et al.  Definition of a specific interaction between the early T lymphocyte activation 1 (Eta-1) protein and murine macrophages in vitro and its effect upon macrophages in vivo.  J Exp Med.1990;171:1931-1942.
Hwang SM, Lopez CA, Heck DE.  et al.  Osteopontin inhibits induction of nitric oxide synthase gene expression by inflammatory mediators in mouse kidney epithelial cells.  J Biol Chem.1994;269:711-715.
McKee MD, Nanci A. Secretion of osteopontin by macrophages and its accumulation at tissue surfaces during wound healing in mineralized tissues.  Anat Rec.1996;245:394-409.
Shijubo N, Uede T, Kon S.  et al.  Vascular endothelial growth factor and osteopontin in stage I lung adenocarcinoma.  Am J Respir Crit Care Med.1999;160:1269-1273.
Tunio GM, Hirota S, Nomura S, Kitamura Y. Possible relation of osteopontin to development of psammoma bodies in human papillary thyroid cancer.  Arch Pathol Lab Med.1998;122:1087-1090.
Maki M, Hirota S, Kaneko Y, Morohoshi T. Expression of osteopontin messenger RNA by macrophages in ovarian serous papillary cystadenocarcinoma.  Pathol Int.2000;50:531-535.
Tiniakos DG, Yu H, Liapis H. Osteopontin expression in ovarian carcinomas and tumors of low malignant potential (LMP).  Hum Pathol.1998;29:1250-1254.
Thalmann GN, Sikes RA, Devoll RE.  et al.  Osteopontin: possible role in prostate cancer progression.  Clin Cancer Res.1999;5:2271-2277.
Kim YW, Park YK, Lee J.  et al.  Expression of osteopontin and osteonectin in breast cancer.  J Korean Med Sci.1998;13:652-657.
Tuck AB, O'Malley FP, Singhal H.  et al.  Osteopontin expression in a group of lymph node negative breast cancer patients.  Int J Cancer.1998;79:502-508.
Ue T, Yokozaki H, Kitadai Y.  et al.  Co-expression of osteopontin and CD44v9 in gastric cancer.  Int J Cancer.1998;79:127-132.
Giachelli CM, Liaw L, Murry CE.  et al.  Osteopontin expression in cardiovascular diseases.  Ann N Y Acad Sci.1995;760:109-126.
Casson AG, Wilson SM, McCart JA.  et al.  ras mutation and expression of the ras-regulated genes osteopontin and cathepsin L in human esophageal cancer.  Int J Cancer.1997;72:739-745.
Zhang J, Takahashi K, Takahashi F.  et al.  Differential osteopontin expression in lung cancer.  Cancer Lett.2001;171:215-222.
CME
Also Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
Your answers have been saved for later.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 285

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Collections
PubMed Articles