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Autoantibody biomarkers identified by proteomics methods distinguish ovarian cancer from non-ovarian cancer with various CA-125 levels.

J Cancer Res Clin Oncol. 2013 Oct;139(10):1757-70. doi: 10.1007/s00432-013-1501-6. Epub 2013 Sep 3.

Karabudak AA1, Hafner J, Shetty V, Chen S, Secord AA, Morse MA, Philip R.

Abstract

PURPOSE:

CA-125 has been a valuable marker for detecting ovarian cancer, however, it is not sensitive enough to detect early-stage disease and not specific to ovarian cancer. The purpose of our study was to identify autoantibody markers that are specific to ovarian cancer regardless of CA-125 levels.

METHODS:

Top-down and iTRAQ quantitative proteomics methods were used to identify high-frequency autoantibodies in ovarian cancer. Protein microarrays comprising the recombinant autoantigens were screened using serum samples from various stages of ovarian cancer with diverse levels of CA-125 as well as benign and healthy controls. ROC curve and dot blot analyses were performed to validate the sensitivity and specificity of the autoantibody markers.

RESULTS:

The proteomics methodologies identified more than 60 potential high-frequency autoantibodies in ovarian cancer. Individual serum samples from ovarian cancer stages I-IV compared to control samples that were screened on a microarray containing native recombinant autoantigens revealed a panel of stage I high-frequency autoantibodies. Preliminary ROC curve and dot blot analyses performed with the ovarian cancer samples showed higher specificity and sensitivity as compared to CA-125. Three autoantibody markers exhibited higher specificity in various stages of ovarian cancer with low and normal CA-125 levels.

CONCLUSIONS:

Proteomics technologies are suitable for the identification of protein biomarkers and also the identification of autoantibody biomarkers when combined with protein microarray screening. Using native recombinant autoantigen arrays to screen autoantibody markers, it is possible to identify markers with higher sensitivity and specificity than CA-125 that are relevant to early detection of ovarian cancer.

PMID:
23999876
[PubMed – indexed for MEDLINE]
PMCID:
PMC3832954

Free PMC Article

Investigation of ovarian cancer associated sialylation changes in N-linked glycopeptides by quantitative proteomics.

Clin Proteomics. 2012 Aug 2;9(1):10. doi: 10.1186/1559-0275-9-10.

Shetty V1, Hafner J, Shah P, Nickens Z, Philip R.

1Immunotope, Inc,, 3805 Old Easton Road, Doylestown, PA, 18902, USA.

Abstract

BACKGROUND:

In approximately 80% of patients, ovarian cancer is diagnosed when the patient is already in the advanced stages of the disease. CA125 is currently used as the marker for ovarian cancer; however, it lacks specificity and sensitivity for detecting early stage disease. There is a critical unmet need for sensitive and specific routine screening tests for early diagnosis that can reduce ovarian cancer lethality by reliably detecting the disease at its earliest and treatable stages.

RESULTS:

In this study, we investigated the N-linked sialylated glycopeptides in serum samples from healthy and ovarian cancer patients using Lectin-directed Tandem Labeling (LTL) and iTRAQ quantitative proteomics methods. We identified 45 N-linked sialylated glycopeptides containing 46 glycosylation sites. Among those, ten sialylated glycopeptides were significantly up-regulated in ovarian cancer patients’ serum samples. LC-MS/MS analysis of the non-glycosylated peptides from the same samples, western blot data using lectin enriched glycoproteins of various ovarian cancer type samples, and PNGase F (+/-) treatment confirmed the sialylation changes in the ovarian cancer samples.

CONCLUSION:

Herein, we demonstrated that several proteins are aberrantly sialylated in N-linked glycopeptides in ovarian cancer and detection of glycopeptides with abnormal sialylation changes may have the potential to serve as biomarkers for ovarian cancer.

Pubmed Link

Quantitative immunoproteomics analysis reveals novel MHC class I presented peptides in cisplatin-resistant ovarian cancer cells.

J Proteomics. 2012 Jun 18;75(11):3270-90. doi: 10.1016/j.jprot.2012.03.044. Epub 2012 Apr 3.

Shetty V1, Nickens Z, Testa J, Hafner J, Sinnathamby G, Philip R.

1Immunotope, Inc., 3805 Old Easton Road, Doylestown, PA 18902, United States.

 

Abstract

Platinum-based chemotherapy is widely used to treat various cancers including ovarian cancer. However, the mortality rate for patients with ovarian cancer is extremely high, largely due to chemo-resistant progression in patients who respond initially to platinum based chemotherapy. Immunotherapy strategies, including antigen specific vaccines, are being tested to treat drug resistant ovarian cancer with variable results. The identification of drug resistant specific tumor antigens would potentially provide significant improvement in effectiveness when combined with current and emerging therapies. In this study, using an immunoproteomics method based on iTRAQ technology and an LC-MS platform, we identified 952 MHC class I presented peptides. Quantitative analysis of the iTRAQ labeled MHC peptides revealed that cisplatin-resistant ovarian cancer cells display increased levels of MHC peptides derived from proteins that are implicated in many important cancer pathways. In addition, selected differentially presented epitope specific CTL recognize cisplatin-resistant ovarian cancer cells significantly better than the sensitive cells. These over-presented, drug resistance specific MHC class I associated peptide antigens could be potential targets for the development of immunotherapeutic strategies for the treatment of ovarian cancer including the drug resistant phenotype.

Copyright © 2012 Elsevier B.V. All rights reserved.

 

Pubmed Link