American Journal of Obstetrics & Gynecology
Volume 199, Issue 3 , Pages 215-223, September 2008

The early detection of ovarian cancer: from traditional methods to proteomics. Can we really do better than serum CA-125?

  • Vladimir Nossov, MD

      Affiliations

    • Department of Obstetrics and Gynecology, University of California, Los Angeles, Medical Center, Los Angeles, CA
    • ,
  • Malaika Amneus, MD

      Affiliations

    • Department of Obstetrics and Gynecology, University of California, Los Angeles, Medical Center, Los Angeles, CA
    • ,
  • Feng Su, MD

      Affiliations

    • Department of Obstetrics and Gynecology, University of California, Los Angeles, Medical Center, Los Angeles, CA
    • ,
  • Jennifer Lang, MD

      Affiliations

    • Department of Obstetrics and Gynecology, University of California, Los Angeles, Medical Center, Los Angeles, CA
    • ,
  • Jo Marie Tran Janco

      Affiliations

    • Department of Obstetrics and Gynecology, University of California, Los Angeles, Medical Center, Los Angeles, CA
    • ,
  • Srinivasa T. Reddy

      Affiliations

    • Atherosclerosis Research Unit, Department of Medicine/Cardiology, University of California, Los Angeles, CA
    • Department of Molecular and Medical Pharmacology, University of California, Los Angeles, CA
    • ,
  • Robin Farias-Eisner, MD, PhD

      Affiliations

    • Department of Obstetrics and Gynecology, University of California, Los Angeles, Medical Center, Los Angeles, CA
    • Stanford University, Stanford, CA
    • Corresponding Author InformationReprints: Robin Farias-Eisner, MD, PhD, UCLA School of Medicine, Department of Obstetrics and Gynecology, 10833 LeConte Ave, Room 24-137 CHS, Los Angeles, CA 90095-1740

Received 18 January 2008; received in revised form 19 March 2008; accepted 4 April 2008. published online 12 May 2008.

Article Outline

Ovarian cancer is the leading cause of death from gynecologic malignancy in the United States. More than 80% of patients present with advanced disease, with 5 year survival rates between 15% and 45%. In contrast, the survival rate for stage I disease, with malignancy confined to the ovary, is approximately 95%. Given the discrepancy in survival outcomes between early- and late-stage disease, strategies that would allow for the detection of ovarian cancer in its early stages would hold promise to significantly improve the mortality rate from ovarian cancer. Unfortunately, current screening methods for the detection of early stage ovarian cancer are inadequate. However, several recent proteomics-based biomarker discovery projects show promise for the development of highly sensitive and specific markers for gynecological malignancies, including ovarian cancer. In this review, we hope to provide an overview of the early detection ovarian cancer from traditional methods to recent promises in the proteomics pipeline.

Key words: markers, ovarian cancer, proteomics, screening

 

As set forth by the World Health Organization almost 40 years ago, the availability of an acceptable, suitable test capable of identifying disease at an early stage is 1 of the primary requirements for establishing a screening method in asymptomatic populations.1, 2 Despite a very high mortality rate, ovarian cancer is a relatively uncommon disease, with an incidence of approximately 50 per 100,000. Statistical estimates show that an effective ovarian cancer screening test will require a minimum positive predictive value (PPV) of 10%3, 4, 5 and a specificity of greater than 99%, which is unlikely to be achieved by a single test.4, 6 The best studied serum biomarker for ovarian cancer, CA-125, is elevated in approximately 80% of women with advanced ovarian cancer but only 50-60% in patients with early-stage disease.7 Studies show that even when combined with other conventional screening tests, such as ultrasound, CA125 fails to reach the specificity needed for a screening test for early detection. The emergence of new technologies, especially in the field of proteomics, offers new hope for an effective screening method to diagnose ovarian cancer at an early stage.

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Conventional Screening Tools 

CA-125 

CA-125 is the most widely studied serum biomarker for ovarian cancer. CA-125 is expressed by fetal amniotic and coelomic epithelium and in adult tissues derived from the coelomic (mesothelial cells of the pleura, pericardium, and peritoneum) and Mullerian (tubal, endometrial, and endocervical) epithelia. By and large, the surface epithelium of normal ovaries does not express CA-125.8 CA-125 contains 2 major antigenic domains, namely, A and B, which bind the monoclonal antibodies OC125 and M11, respectively.9 The original clinical assay for CA-125 utilized the OC125 antibody. The current CA-125 assay, termed CA-125 II assay, quantifies CA-125 levels by utilizing both the OC125 and the M11 antibodies.10 CA-125 levels of less than 35 U/mL are now accepted as normal.11, 12

The initial findings of CA-125 levels greater than 35 U/mL in approximately 83% of patients with epithelial ovarian cancer fueled investigations into the use of CA-125 as a biomarker for ovarian cancer.11, 13 When stratified by disease stage, elevated levels were found in more than 90% of patients with advanced-stage ovarian cancer but in only 50% of patients with stage I disease.9 In addition, elevated levels of CA-125 are more strongly associated with serous, rather than mucinous, tumors.14

Studies utilizing serum obtained from patients prior to the diagnosis of ovarian cancer found that elevated levels of CA-125 levels were detectable in 25% of 59 samples collected 5 years prior to diagnosis.15 This provided hope that CA-125 may be of utility as a prospective marker of disease in the asymptomatic phase. Unfortunately, a few prospective studies indicated the inadequate sensitivity of CA-125 in the setting of ovarian cancer screening in asymptomatic populations.16, 17 The inadequacy of CA-125 alone as a screening test is partially due to the high rate of false-positive values because serum elevations may also be caused by a variety of other conditions including other cancers (pancreatic, breast, bladder, liver, lung); benign conditions such as diverticulitis, liver cirrhosis, endometriosis, uterine fibroids, and benign ovarian lesions; and physiologic conditions such as menstruation and pregnancy.

Ultrasound 

Transvaginal ultrasound allows for detailed imaging of the ovaries and the detection of morphological changes that may signify a developing malignancy. A number of studies considered ultrasound methodology as a candidate-screening tool for the early detection of ovarian cancer.18, 19, 20 In 1 study, autopsy data demonstrated that 56% of postmenopausal women who died of causes other than gynecologic or intraperitoneal cancer had benign adnexal masses less than 5 cm,18 suggesting that screening ultrasounds could result in many false-positives, which is not a desirable situation. Interestingly, another set of studies demonstrated that when an abnormal ultrasound result is obtained; repeat ultrasound 4-6 weeks after the initial screening reduces false-positive rates.19, 20

The complexity of ovarian morphology is of great importance as an indicator of possible malignancy.21, 22 Complex ovarian cysts with wall abnormalities or solid areas are associated with a significant risk of malignancy.19, 23 In agreement with these ultrasonographic findings, when considering gross anatomic changes detected at the time of surgery, papillary projections have the highest correlation with a diagnosis of ovarian malignancy, whereas simple cysts and septal thickness have the lowest correlation.24

Many current screening protocols use a morphological scoring system, which incorporates combinations of many factors such as ovarian volume, outline, presence of papillary projections, and cyst complexity (loculations, wall structure, septae thickness, echogenicity of fluid).25, 26, 27, 28, 29, 30 Ueland et al30 demonstrated a sensitivity of 98.1%, specificity 80.8%, relatively high positive predictive value of 40.9%, and exceptional negative predictive value of 99.7%. However, at this time, no recognized standardized indices exist, making cross-study comparisons difficult.

Doppler studies 

Blood vessels that result from neovascularization in malignancies contain reduced smooth muscle in their walls and therefore provide less resistance to blood flow when compared with vessels in benign ovarian tumors. These altered blood flow patterns are detectable by color-flow Doppler imaging and can be represented as 2 standard measurements: pulsatility index (PI) and resistive index (RI), which have been used as a strategy to identify malignant ovarian tumors in both general and high-risk populations.31, 32, 33, 34

It was hoped that utilizing Doppler imaging as a screening tool would serve as an improvement over traditional ultrasound imaging by improving specificity. However, this has not been confirmed in several studies.30, 32, 35, 36 Whereas there does appear to be an overall difference in the mean PI and RI, with the values in ovarian cancers being lower than the values in benign tumors, there is considerable overlap in the measurements, which prevents reliable differentiation of malignant from benign masses.

In addition, consensus does not exist as to the best parameters for analysis and the most appropriate cutoff values for differentiation of benign from malignant masses. The premise that power Doppler offers a significant advancement over the standard 2-dimensional Doppler examination has been disputed, and its role in ovarian cancer screen has not been firmly established.37, 38, 39

Combined and serial tests 

The use of more than 1 marker has been suggested as a means of increasing sensitivity for the early detection of ovarian cancer, but increased sensitivity is often associated with decreased specificity. Because none of the individual methods for ovarian cancer screening offered acceptable results, an attempt of combining CA-125 levels with ultrasound findings or measuring serial CA-125 levels to increase both positive and negative predictive values has been made. Initially, the specificity of screening with CA-125 was improved by the addition of pelvic ultrasound. When CA-125 was greater than 30, the combination protocol reached a specificity of 99.9% and PPV of 26.8% for detection of ovarian cancer in 22,000 postmenopausal women.3

Patients in the screening group (CA-125 plus pelvic ultrasound for CA-125 greater than 30) also had a survival benefit, compared with those in control group (72.9 vs 41.8 months, respectively).40 To go further and to evaluate individual risk of developing ovarian cancer, a few groups attempted to develop more creative algorithms. The new decision tree was based on the knowledge that CA-125 levels in healthy women do not change or decrease over the time of observation but gradually increase in women developing ovarian cancer. Thus, women with normal values of CA-125, which, however, rise over a period of time, or those with stable high CA-125 levels are both classified as patients at increased risk.17, 41 Sensitivity increased up to 86% with still high specificity (98%). The United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) also used a similar approach.

A few prospective studies have been conducted to evaluate CA-125 and pelvic ultrasounds for screening of women at high risk for ovarian cancer (eg, BRCA mutation carriers),42 but sensitivity and specificity values were below the requirement for an effective screening method. Combinations of methods were studied under different protocols; these methods included serial clinical examinations, CA-125 measurements, and ultrasound. Unfortunately, they were found to be inefficient because many surveillance visits were required, and even then, most selected patients already had advanced stages of ovarian cancer.43

Another aspect to consider is the presence of primary peritoneal cancer in the ovarian cancer-like syndrome, representing 25% of papillary-serous carcinomas of the genital tract in BRCA mutation carriers, compared with 10% in the general population. Typically there are no dominant adnexal masses present despite advanced disease outside the pelvis,44 making screening ultrasound even less useful for detecting early-stage primary peritoneal cancer.

Novel Candidates for Serum Biomarker Screening 

Since traditional screening methods do not provide acceptable specificity and sensitivity (Table), many groups are continuing their quest for discovering novel markers that would help in both early detection and monitoring for recurrence of disease. Similar to screening mammography for early breast cancer detection, simple and cheap tests could help in triaging patients to standard surveillance (for low-risk results), repeated testing (for intermediate risk), or further testing or intervention (for high risk). It is still unclear, however, whether a single marker or panel of markers or more sophisticated computerized algorithm would be required.

TABLE. Summary of selected screening tools for ovarian cancer
Screening modalityStageSensitivity, %Specificity, %Positive predictive value, %Negative predictive value, %Special issues
CA-12564, 91, 94Early stage50-62955770.6Cheap and available in most laboratories. Poor sensitivity in early-stage disease.
Late stage90
Ultrasound26All stages96.87729.499.6Arbitrary cutoff of 3 cm. Low specificity Better suited for differentiation of malignant and benign masses but not for screening.
Ultrasound with Doppler95All stages98879495Operator dependent. Poor reproducibility. Low specificity.
Combination U/S and CA-125 (ROC model)3, 40All stages7899.920.7-26.899.9Better results compared with ultrasound alone or single value of CA-125 with ultrasound.
LPA53, 55Early stage9086.293.391.8Nonspecific elevation in ovarian cancer and other gynecologic cancers. No correlation with disease status.
Late stage98
Johns Hopkins group62Early stage83946014Panel of 4 serum tests, not all available at most laboratories. Still below the desired threshold for screening the general population.
Yale group (6 biomarker panel)63, 64Early stage91.699.497.698.9Panel of 6 serum tests, not all available at most laboratories.
All stages95.3
UCLA group (4 biomarker panel)91Early stage899797.785Panel of 4 serum tests, all available at most laboratories. Sensitivity and specificity even greater for mucinous ovarian tumors. Still below the desired threshold for screening the general population.
Late stage979998.698.1

Nossov. Early detection of ovarian cancer. Am J Obstet Gynecol 2008.

Developments in proteomic technology within the past decade opened many doors for development and testing of new biomarkers. Cancer is often referred to as a genetic disease, with genetic alterations leading to the production of abnormal proteins or effecter molecules. The information contained in the expressed protein may be altered by cotranslational and posttranslational events, protein binding, and local microenvironment changes. Proteomic technology aids in the characterization and validation of dysfunctional or altered proteins.45

Delineation of the tumor proteome 

The field of molecular targeted therapy began with assessment of biochemical pathways in cultured cell lines and animal models, with the idea of eventually generalizing the information to human subjects. However, generalization of the conclusions obtained from in vitro and animal experiments to humans was very limited.46, 47, 48 The success of newer amplification reagents coupled with increasing numbers of function-specific antibodies has allowed the development of protein lysate arrays for the analysis of biochemical behavior in tissue samples. Frozen tissue archive samples have been examined for protein pathway profiling and thus characterization of the signalome of ovarian cancer.

These techniques allow global assessment of common biochemical pathways and can be linked to genomic and transcription data.46, 47, 48 Wulfkuhle et al,49 for example, used tissue lysate arrays to describe signal pathway profiles in human ovarian cancers, quantitatively describing protein content and activation state of key signaling pathways in microdissected human epithelial ovarian tissue specimens. The findings of these investigators suggested that variations in molecular signals seemed to be more patient specific than stage specific. This work represents an extension of an approach previously limited to in vitro testing.50

Basic description of techniques 

Among the technologies that have been relatively recently developed are tissue lysate arrays (TLAs), laser capture microdissection (LCM), and mass spectrometry (MS) (matrix-assisted laser desorption and ionization [MALDI] and surface-enhanced laser desorption and ionization [SELDI]). TLAs use multiple tissue lysates arrayed on a single membrane that allows for simultaneous analysis of proteins in multiple samples. LCM allows for the specific selection of cells of interest from tissue sections, allowing analysis of more homogeneous cell populations. MS techniques allow for the rapid and high throughput analysis of the entire protein complement of a biological sample.

These techniques help to obtain significant information from the analysis of very small specimens from patients. Also, they allow detection of low-molecular-weight proteins that were previously difficult to identify. Thus, proteomic technologies therefore offer an opportunity to study and develop new biomarker panels for early diagnosis and to facilitate better understanding of the signaling pathways for various malignant processes. These biomarkers eventually may offer targets for therapeutic intervention of both early and advanced malignancy.

So far, proteomic technology has been used in 2 distinct areas: protein identification and pattern recognition. The ability to sequence peaks previously determined on mass spectrometry now allows the merging of these 2 areas. Anderson et al51 reported a large collaborative effort that resulted in a partial map of the human serum proteome.

New targets for ovarian cancer screening 

An advantage to the use of proteomic technology in the search for ovarian cancer screening methods is the ability to identify many new potential biomarkers present in small amounts in the serum. These biomarkers have the potential, alone or combined with each other or more traditional tests (eg, CA-125), to become an improved tool for the detection of ovarian cancer at early stages. There have emerged many individual biomarkers that are currently being investigated for use in screening by research groups worldwide.

Hellstrom et al52 identified HE4 (Homo sapiens epididymis specific 4) as a potential discriminator for ovarian cancer. HE4 is the product of the WFDC2 gene, which was found, by complementary deoxyribonucleic acid array, to be up-regulated in ovarian cancer. Blinded studies on sera from postmenopausal ovarian cancer patients and unaffected controls showed that HE4 changes were equivalent to CA-125 in terms of differentiating affected from unaffected patients.

In 2002 Urban53 discussed the potential of several biomarkers including macrophage colony-stimulating factor (M-CSF)54 and lysophosphatidic acids (LPA).55 M-CSF is hematopoietic cytokine that is found in serum and is involved in the activation of macrophages. When used alone, M-CSF detects 61-68% of all cases, with specificity for detection of benign tumors around 93%.56 However, the best use of M-CSF as a marker may very well be in conjunction with CA-125.57

One study reported that by using elevation of either CA-125 or M-CSF as the criterion for a positive screening test, 96-98% of ovarian cancers were identified, including 81% of early-stage cases. However, this combination of tests carries low specificity; therefore, its utility is limited: one fifth of healthy women exceed at least 1 of those thresholds.54 LPA is protein that is composed of various lysophosphatidic acids and is thought to play a role in ovarian cancer cell growth. As a marker of ovarian cancer, sensitivity in advanced disease has been reported to be 100%, and in disease confined to 1 ovary sensitivity is 90%. Specificity was also high, in the order of 90% (Table).55

CART analysis (classification and regression tree analysis), which uses the sequential analysis of marker concentrations, was used with 5 markers (CA-125, OVX1, LASA, CA 15-3, CA 72-4) to yield a sensitivity of 90.6% and a specificity of 93.2%.58 Then a subset of 4 markers (CA-125, CA-72-4, CA-15-3, and lipid-associated sialic acid) was analyzed and demonstrated improved sensitivity over CA-125 alone, from 68.4% to 87.5%, while maintaining comparable specificity.59 Crump et al60 reported that an even greater specificity might be attained by using serial values of multiple markers, as in the case of CA-125.

Preliminary data on a panel of 5 serum tumor markers (CA-125, HER-2/neu, urinary gonadotropin peptide, lipid-associated sialic acid, and Dianon marker 70/K) that were tracked over 6 years of follow-up of 1257 healthy women at high risk of ovarian cancer suggests that individual screening guidelines may be developed with the potential to improve the early detection of ovarian cancer.60 Lu et al61 have reported that several sets of potential markers, determined by recursive-descent partition analysis (RDPA), reverse transcription–polymerase chain reaction, and immunohistochemistry, when used in different combinations, were able to distinguish tumors of different histology from normal ovarian surface cells. These combinations of markers could potentially identify more than 99% of all epithelial ovarian cancers despite their heterogeneity.61 However, as promising as this may sound, the serum determination of these markers was never studied.

Zhang et al62 reported on 3 biomarkers found in a 5-center case-control study encompassing 153 patients with invasive epithelial ovarian cancer, 42 with other ovarian cancers, 166 with benign pelvic masses, and 142 healthy women. The biomarkers were identified as apolipoprotein A1, a truncated form of transthyretin (both are down-regulated in cancer), and a cleavage fragment of inter–alpha-trypsin inhibitor heavy-chain H4 (up-regulated in cancer). For the detection of early-stage invasive epithelial ovarian cancer, the combination of these 3 biomarkers in combination with CA-125 gained a higher sensitivity and specificity than CA-125 alone.62

Leiser and colleagues63, 64 presented a panel of biomarkers that exhibited the same pattern of expression in both the Multiplex and the enzyme-linked immunosrobent assay (ELISA) systems. None of the biomarkers individually (leptin, prolactin, osteopontin, IGF-II, macrophage inhibitory factor, and CA-125) was able to adequately differentiate between control samples and ovarian cancer samples. However, the combination of the 6 markers provided improved differentiation.

The Multiplex results were analyzed using 3 different classification algorithms to evaluate the accuracy of classification. Logistic regression was then selected for the validation analysis. In the validation set, 2 of 85 patients with ovarian cancer were misclassified (2.35%). In the healthy control group, none of the patients were misclassified (0%). On further testing, 1 of 365 healthy samples was misclassified, for a specificity of 99.67%. Four of 160 ovarian cancer samples were misclassified, for a sensitivity of 97.5%. With respect to stage, of 37 stage I/II samples, 4 were misclassified (89% accuracy), and all 123 stage III/IV samples were correctly classified (100% accuracy). The positive predictive value for the test population was 99.97%, with a negative predictive value of 99.7%.

The biomarker panel, as a screening test, thus was reported to be associated with high sensitivity (97.5%) and specificity (99.7%), although those numbers were not stage specific and the detection rate for early stage ovarian cancers was still below cutoffs for an effective screening test.

Other groups have explored potential biomarkers for disease recurrence, such as osteopontin (OPN),65 which has been previously reported to be associated with breast and prostate cancers.66 Schorge et al67 demonstrated that OPN was useful as an adjunct to CA-125 in a prospective analysis of ovarian cancer recurrence following primary therapy. Although OPN did not surpass CA-125 as a monitoring test, the rise of OPN was earlier in recurrence than CA-125.

Ye et al68 screened a group of 80 cancer patients and 9 healthy controls with SELDI-MS to identify putative biomarkers for ovarian cancer. They identified a candidate biomarker peak at approximately 11,700 kDa that appeared to be increased in cancer patients when compared with controls. The peak was subsequently identified to be the alpha chain of haptoglobin. Rai et al69 used the immobilized metal affinity chromatography (IMAC)-Ni chip surface for profiling of plasma from ovarian cancer patients and selected seven candidate biomarkers and subsequently characterized 3 of them. These biomarkers were identified as transferrin, haptoglobin precursor fragment, and the immunoglobulin heavy chain.

A recent report by Yu et al70 described proteomic analysis on 61 serum samples from 32 ovarian cancer patients and 29 healthy subjects. The results revealed 5 potential biomarkers, with peaks at 2085, 5881, 7564, 9422, and 6044 Da. The protein expression pattern of these putative biomarkers, used together, separated ovarian cancer from healthy samples with a sensitivity of 96.7%, specificity of 96.7%, and positive predictive value of 96.7%.

In studies by Petricoin et al,71 a proteomic signature for ovarian cancer was derived using SELDI-MS. The resultant model signature pattern was then tested against 116 masked samples and yielded 100% sensitivity, 95% specificity, and a 94% PPV in the test set. Conrads et al72 analyzed these proteins along with additional serum samples using an ABI qStar quadrapole (OqTOF) mass spectrometer (Applied Biosystems, Foster City, CA). Four different models were generated using the genetic algorithm and other bioinformatics approaches. Each was tested against a set of samples that was doubly blinded. All models achieved sensitivity and specificity of 100%. These initial data have spurred interest in further investigation and will be utilized in ongoing clinical trials in the United States and internationally. The serum bank amassed by the UKCTOCS will be studied using a number of methods, including mass spectrometry proteomic signature testing.

Our group reported several candidate biomarkers that were found by using a strong anion-exchange surface chip. The biomarkers were arranged into 3 panels containing 4-5 potential markers each; all were individually able to effectively separate benign and ovarian neoplasia with sensitivities and specificities ranging from 72% to 95%. In combination, they correctly diagnosed 41 of 44 blinded test samples: 21 of 22 malignant ovarian neoplasms (10 of 11 stage I/II ovarian cancers, 11 of 11 stage III/IV ovarian cancers), 6 of 6 neoplasms of low malignant potential, 5 of 6 benign tumors, and 9 of 10 healthy control samples.73 Using micro–liquid chromatography and tandem mass spectrometry, we identified 5 m/z peaks as transthyretin (TTR; 13.9 kDa, TTR fragment 12.9 kDa), beta-hemoglobin (Hb; 15.9 kDa), apolipoprotein A1 (Apo A1; 28 kDa) and transferrin (TF; 79 kDa).

Further work74 confirmed the differential expression of TTR, Hb, Apo A1, and TF by Western and/or ELISA methods. Multivariate analyses resulted in improving the detection of early-stage ovarian tumors (low malignant potential and malignant; receiver operating characteristic [ROC] 0.933) as compared with cancer antigen CA-125 alone (ROC 0.833). Addition of CA-125 in the multivariate analysis improved the ROC to 0.959. Multivariate analysis including only the mucinous subtype of early-stage ovarian tumors showed the marker panel to greatly improve the detection of disease (ROC 0.959) as compared with CA-125 alone (ROC 0.613). Interestingly, the addition of CA-125 to the other markers did not improve the detection of mucinous tumors (ROC 0.955). We concluded that TTR, Hb, Apo A1, and TF, when combined with CA-125, should significantly improve the detection of early-stage ovarian cancer (Table).73, 74

There have already been described associations between ovarian cancer and each of the 3 biomarkers separately: ApoA-1, TTR, and TF.75, 76 ApoA-1 is the major protein constituent of high-density lipoprotein (HDL). Prior reports have described decreased ApoA-1 in the serum of patients with ovarian cancer77 as well as patients with atherosclerosis.78 Changes in serum lipids and lipoproteins in association with cancer have been reported in numerous studies.79, 80, 81 The mechanism behind the observed association remains unclear, although 1 proposed theory involves free radical–mediated damage to cellular membranes, resulting in lipid peroxidation.

One byproduct of lipid degradation is malondiadlehyde (MDA), which appears to be promutagenic as an MDA-deoxyribonucleic acid adduct, inducing mutations in both oncogenes and tumor suppressor genes.82 TTR is secreted binding protein that functions to transport serum thyroxine, triiodothyronine, and retinol (vitamin A). TTR levels have been reported to be inversely correlated to tumor volume in ovarian cancer.83

Additionally, immunohistochemistry studies have shown decreased levels of cellular retinol binding proteins in ovarian cancer.69 TF (m/z peak of 79 kDa) is an iron-binding transport protein, responsible for shuttling iron from sites of absorption and heme degradation to areas of storage and utilization,84, 85 and has been previously reported to be decreased in the serum of patients with ovarian cancer.86 All 3 of these proteins have been shown to play an important role in oxidative stress, for which there is much evidence supporting a link to carcinogenesis.87, 88, 89, 90

In more recent experiments,91 study samples were taken from the serum of 392 patients in total, 82 with no ovarian pathology, 24 with benign ovarian tumors, 85 with tumors of low malignant potential (LMP), 126 with early-stage ovarian cancer (ESOC), and 75 with late stage ovarian cancer (LSOC). CA-125 levels alone distinguished controls from tumors of LMP with a sensitivity of 62% and controls from ESOC with a sensitivity of 76%. When ovarian cancer subtypes were evaluated, CA-125 levels separated controls from LMP and ESOC of the mucinous type with sensitivities of 46% and 47%, respectively. On reanalysis of the 392 patient serum samples utilizing ApoA-1, TTR, and TF in combination with CA-125, there was a 29% improvement in sensitivity for the detection of tumors of LMP and a 13% improvement in sensitivity for the detection of ESOC. For the mucinous subtype of ovarian cancer, there was an improvement in the sensitivity for detection of LMP by 44% and ESOC by 48%.

Furthermore, to evaluate these markers in an independent study population, postdiagnostic, pretreatment serum samples from the National Cancer Institute Immunodiagnostic Serum Bank were studied. Levels of various posttranslational forms of transthyretin and apolipoprotein A1 were measured in addition to CA-125. The mean levels of 5 of the 6 forms of TTR studied were significantly lower in samples from ovarian cancer patients as compared with controls. When using TTR and ApoA-1 alone, specificity for detection of ovarian cancer was high, 96.5%, but sensitivity was low, 52.4%. A class prediction algorithm using all forms of the markers, CA-125, and age maintained high specificity, 94.3%, but still had relatively low sensitivity, 78.6%.91

These results warrant further studies to evaluate the role of these biomarkers in the early detection of ovarian cancer. These data suggest that ApoA-1, TTR, and TF, when analyzed collectively, are unique to ovarian cancer and thus provide for the first time a disease-specific multiple marker panel for the early detection of ovarian cancer. In combination with CA-125 in a multivariate predictive model, ApoA-1, TTR, and TF have the potential to improve specificity and sensitivity for the early detection of ovarian cancer over CA-125 alone, particularly for the mucinous histopathologic subtype. Further elucidation of the mechanisms and pathways by which ApoA-1, TTR, and TF participate in or signify the development of ovarian cancer will be important and also may ultimately provide targets for therapeutic intervention.

Conclusion 

The problem of ovarian cancer, with its high mortality and lack of effective screening tests, has spurred numerous investigators to develop novel approaches for early detection and therapeutics. Despite significant advances in the understanding of the biology of ovarian cancer, there is still minimal, if any, improvement in the mortality rate seen. Routine screening tests, such as serum CA-125, ultrasound, or in combination, aimed at the early detection of ovarian cancer, when it still can potentially be cured, are neither specific nor sensitive enough. Proteomic techniques have yielded new putative biomarkers for ovarian cancer that may be of significant clinical importance.

There has been significant criticism in the literature of the proteomics approach to the detection of ovarian cancer, mainly because of the lack of identification of key peaks,92 lack of cross-validation of the identified protein and peptide peaks, difficulty in reproduction of the results using varied bioinformatics, and lack of incorporation of existing putative markers, such as CA-125. With the use of MALDI-quadropole-MS and publishing of sequencing information,93 the identification of key peaks has greatly improved. Validation of the peaks that have been identified is ongoing and will provide important biologic insight into disease state and its local microenvironment. Despite criticisms, proteomic approaches offer a promising arena of investigation. There is increasing support for their role in developing screening and diagnostic tests as well as in eliciting mechanisms of carcinogenesis.

Proteomics has now advanced past theoretical method. Attempts have been made toward prospective clinical trials for some of previously reported biomarkers. To date, however, we still do not have adequate screening tools for early detection of ovarian cancer that will significantly decrease morbidity and mortality by diagnosing disease at a curable stage. Proteomic technology has great potential to augment traditional screening tools and increase specificity and sensitivity to levels acceptable for a screening method.

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Acknowledgment 

The authors thank Gina Farias-Eisner for editing our manuscript.

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PII: S0002-9378(08)00400-6

doi:10.1016/j.ajog.2008.04.009

American Journal of Obstetrics & Gynecology
Volume 199, Issue 3 , Pages 215-223, September 2008

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