Proteomics is the study of the structure and function of proteins. Proteins are vital parts of living organisms, as they are the main components of the physiological metabolic pathways of cells. The term "proteomics" was coined to make an analogy with genomics, the study of the genes. Proteomics differs from genomics mostly because an organism's genome is rather constant, while a proteome differs from cell to cell and constantly changes through its biochemical interactions with the genome and the environment. One organism has radically different protein expression in different parts of its body, different stages of its life cycle and different environmental conditions.

Investigational and Not Medically Necessary: 

Analysis of proteomic patterns for screening or diagnosis of disease is considered investigational and not medically necessary.

There has been considerable publicity regarding the potential role for proteomics for cancer screening and detection (Conrads, 2003; Wu, 2002; Zhu, 2003). Petricoin and colleagues studied proteomics for ovarian cancer detection in women considered at high risk of ovarian cancer. They reported on the technical feasibility of proteomic screening in a test series of serum from 50 women with and 50 women without ovarian cancer (Petricoin, 2002). The spectra of proteins were analyzed by an iterative searching algorithm that identified a cluster pattern that segregated those with ovarian cancer from those without ovarian cancer. This discovered pattern was then used to classify an independent set of 116 masked serum samples; 50 from women with ovarian cancer, and 66 from unaffected women or those with non-malignant conditions. Individuals without cancer were considered at high risk, due either to familial breast or cancer syndrome or the presence of BRCA 1 or BRCA 2 mutations. All 50 with ovarian cancer were correctly identified, including the 18 with stage I cancer. Of the 66 benign cases, 63 were identified as not cancer, yielding a sensitivity of 100% and a positive predictive value of 94%. The authors note that while a positive predictive value of 94% may be acceptable for those high-risk women, in the larger population of average-risk women the positive predictive value must be close to 100% to avoid a high number of false positives, which in turn would generate additional work up. One of the key outcomes of an ovarian cancer screening test is the ability to identify Stage I ovarian cancer that is potentially curable with surgery. The above study only included 18 women with Stage I ovarian cancer. The authors state that an important future goal is the confirmation of the diagnostic performance of proteomic screening for the prospective detection of Stage I ovarian cancer in trials of both high- and low-risk women. Such trials are currently underway at the National Cancer Institute.

The OvaCheck^® test (Correlogic Systems, Inc., Rockville, MD) is based on proteomic patterns detected in the serum, which are further analyzed with the use of a mass spectrometer to profile a population of proteins based on their size and electrical charge. This type of analysis contains thousands of data points, which undergo further sophisticated computer analysis using specially developed algorithmic software to identify a pattern that is consistent with ovarian cancer. The U.S. Food and Drug Administration (FDA) has requested additional data to review as part of the pre marketing approval process (PMA). It should also be noted that the technology used in the Petricoin study (Petricoin, 2002) is not the same as the technology proposed for the OvaCheck test.

Other comments and correspondence in the literature also question the statistical analysis and other technical issues in the Petricoin study (Diamandis, 2002; 2004). In February 2004, the Society of Gynecologic Oncologists (SGO) released the following statement:

The Society of Gynecologic Oncologists (SGO) recognizes the importance of accurate early detection biomarkers for ovarian cancer. For this reason SGO reviewed the literature regarding OvaCheck, a serum based diagnostic test for ovarian cancer. In the opinion of SGO, more research is needed to validate the test's effectiveness before offering it to the public. SGO is committed to actively following and contributing to this vitally important research. As physicians who care only for women with gynecologic cancer, our hope is that these cancers can either be prevented or detected early. Because no test now exists to routinely detect ovarian cancer in its earliest and most curable stage, we will await the results of further clinical validation of OvaCheck with great interest.

The Agency for Healthcare Research and Quality (AHRQ, 2006) addressed the use of proteomic testing for ovarian cancer in their Genomic Tests for Ovarian Cancer Detection and Management. They found that the proteomic studies reviewed showed good discrimination for the particular protein profile studied however, recurrent technical/methodology variance and small sample sizes (as compared with the prevalence of ovarian cancer) limits the ability to draw conclusions about clinical applications of proteomic testing for ovarian cancer.

A more recent study by Riaz and colleagues (2010) investigated the use of proteomics to indentify urinary biomarkers in individuals with type 2 diabetes. This study involved 100 subjects with type 2 diabetes and 50 age- and gender-matched healthy controls. Urinary protein samples from all participants were analyzed by first phase chromatofocusing chromatography and then reverse-phase chromatography for the second phase. This was followed by mass spectrometric analysis. Proteins that were found to vary in subjects versus controls were then determined by enzyme-linked immunosorbent assay. The authors reported significant decreases in transthyretin and haptoglobin precursor, and significant increases in the levels of albumin, zinc a2 glycoprotein, retinol binding protein 4, and E-cadherin in subjects with diabetes. No data were presented addressing the use of this information in the clinical setting, and at this time no such evidence has been published.

Currently, the use of proteomic analysis is in clinical trials and testing is not commercially available. Additionally, there are no published, large randomized controlled trials demonstrating that the use of proteomic analysis for screening or detection of disease improves clinical outcomes.

Genetic mutations do not reflect the complicated interactions between individual cells, tissue and organs. Proteins are the functional units of cells and represent the end product of the interactions among the underlying genes. Therefore, recent research interest has increased in the pattern of proteins associated with disease. This field may be referred to as proteomics (to distinguish it from genomics) and is defined as the study of all protein forms expressed within an organism as a function of time, age, state, and external factors. Proteomics unravel biochemical and physiological mechanisms of complex multivariate diseases at the functional molecular level. The discipline of proteomics has been initiated to complement physical genomic research.

One research application of proteomics has been the identification of a pattern of proteins detected in a given fluid, such as body fluid or serum that is associated with an underlying cancer. Essentially, the identification of patterns of proteins in the serum could function as serum tumor marker, similar in concept to the more familiar prostate specific antigen (PSA) or CA-125, which are used in the detection and monitoring of prostate and ovarian cancer, respectively. This type of proteomic profiling has also been referred to as a "protein fingerprint."

Use of proteomic patterns in serum to identify ovarian cancer is one of the first clinical applications of proteomics and is the result of a joint project initiated between the National Cancer Institute and the U.S. Food and Drug Administration (FDA) to develop proteomics for cancer screening and diagnosis.  

Proteomic analysis is also being studied for neurological diseases such as brain damage, stroke, Alzheimer's, depression and Parkinson's disease. Other areas of interest are:

• Cardiac ischemia and cardiomyopathy;
• Solid organ transplant rejection; 
• Diabetes and obesity; 
• Oncology for screening and disease identification of lung, colon, prostate and breast cancers.

Algorithm: A set of mathematical rules for solving complex problems with the aid of computer technology.

Proteomics: The study of molecules in the functional protein pathways of normal or diseased states.

Screening: Checking or testing for disease when there are no symptoms.

Serum: The clear portion of any body fluid, in this case the clear portion of blood.

The following codes for treatments and procedures applicable to this document are included below for informational purposes.  Inclusion or exclusion of a procedure, diagnosis or device code(s) does not constitute or imply member coverage or provider reimbursement policy. Please refer to the member's contract benefits in effect at the time of service to determine coverage or non-coverage of these services as it applies to an individual member. 

When Services are Investigational and Not Medically Necessary:
When the code describes a procedure indicated in the Position Statement section as investigational and not medically necessary.

Peer Reviewed Publications:

1. Bast RC Jr, Brewer M, Zou C, et al. Prevention and early detection of ovarian cancer: mission impossible? Recent Results Cancer Res 2007; 174:91-100.
2. Chung L, Clifford D, Buckley M, Baxter RC. Novel biomarkers of human growth hormone action from serum proteomic profiling using protein chip mass spectrometry. J Clin Endocrinol Metab. 2006; 91(2):671-677. 
3. Conrads TP, Zhou M, Petricoin EF 3rd, et al. Cancer diagnosis using proteomic patterns. Expert Rev Mol Diagn. 2003; 3(4):411-420.
4. Conrads TP, Fusaro VS, Ross S, et al. High-resolution serum proteomic features for ovarian cancer detection. Endocr Relat Cancer. 2004; 11(2):163–178.
5. Diamandis EP. Analysis of serum proteomic patterns for early cancer diagnosis: drawing attention to potential problems. J Natl Cancer Inst. 2004; 96(5):353-356.
6. Diamandis EP. Proteomic patterns in serum and identification of ovarian cancer. Lancet 2002; 360(9327):169-171.
7. Parikh AA, Johnson JC, Merchant NB. Genomics and proteomics in predicting cancer outcomes. Surg Oncol Clin N Am. 2008; 17(2):257-277
8. Petricoin EF, Ardekani AM, Hitt BA, et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet. 2002; 359(9306):572-577.
9. Riaz S, Alam SS, Srai SK, et al. Proteomic identification of human urinary biomarkers in diabetes mellitus type 2. Diabetes Technol Ther. 2010; 12(12):979-988.
10. Rosenblatt KP, Bryant-Greenwood P, Killian JK, et al. Serum proteomics in cancer diagnosis and management. Annu Rev Med. 2004; 55:97-112.
11. Stone JH, Rajapakse VN, Hoffman GS, et al. A serum proteomic approach to gauging the state of remission in Wegener's granulomatosis. Arthritis Rheum. 2005; 52(3):902-910.
12. Tchabo NE, Liel MS, Kohn EC. Applying proteomics in clinical trials: assessing the potential and practical limitations in ovarian cancer.  J Pharmacogenomics. 2005; 5(3):141-148.
13. Wu W, Hu W, Kavanagh JJ. Proteomics in cancer research. Int J Gynecol Cancer. 2002; 12(5):409-423.
14. Ye B, Skates S, Mok SC, et al. Proteomic-based discovery and characterization of glycosylated eosinophil-derived neurotoxin and COOH-terminal osteopontin fragments for ovarian cancer in urine. Clin Cancer Res. 2006; 12(2):432-441.
15. Zakharchenko O, Greenwood C, Lewandowska A, et al. Meta-data analysis as a strategy to evaluate individual and common features of proteomic changes in breast cancer. Cancer Genomics Proteomics. 2011; 8(1):1-14.
16. Zhang Z, Bast RC Jr, Yu Y, et al. Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer. Cancer Res. 2004; 64(16):5882-5890.
17. Zhu W, Wang X, Ma Y, et al. Detection of cancer-specific markers amid massive mass spectral data. Proc Natl Acad Sci, USA. 2003; 100(25):14666-14671.

Government Agency, Medical Society and Other Authoritative Publications: 

1. Agency for Healthcare Research and Quality (AHRQ). Genomic Tests for Ovarian Cancer Detection and Management. Evidence Report/Technology Assessments No. 145. October 2006. Available at: http://www.ahrq.gov/downloads/pub/evidence/pdf/genomicovc/genovc.pdf. Accessed on May 26, 2011.
2. National Cancer Institutes (NCI). Questions and Answers: Distinction Between the NCI/FDA Ovarian Cancer Proteomics Research Program and Diagnostic Tests by Private Industry (e.g. OvaCheck ™). Available at: http://home.ccr.cancer.gov/ncifdaproteomics/pdf/OvaCheckQandA.pdf. Accessed on May 26, 2011.
3. Society of Gynceologic Oncologists (SGO), Chicago, Illinois, Press release: Society of Gynecologic Oncologists statement regarding OvaCheck^®. February 7, 2004. Available at: http://www.sgo.org/WorkArea/showcontent.aspx?id=954. Accessed on May 26, 2011.

1. American Cancer Society. Overview: Ovarian cancer. Last revised October 13, 2010. Available at: http://www.cancer.org/docroot/CRI/CRI_2_1x.asp?rnav=criov&dt=33. Accessed on May 26, 2011.
2. National Library of Medicine. Medical Encyclopedia: Ovarian Cancer. December 28, 2010. Available at: http://www.nlm.nih.gov/medlineplus/ency/article/000889.htm. Accessed on May 26, 2011.

OvaCheck^®
Serum-Based Diagnostic Test for Ovarian Cancer

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