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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.

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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.

 

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MHC class I-presented lung cancer-associated tumor antigens identified by immunoproteomics analysis are targets for cancer-specific T cell response.

J Proteomics. 2011 May 1;74(5):728-43. doi: 10.1016/j.jprot.2011.02.020. Epub 2011 Mar 11.

Shetty V1, Sinnathamby G, Nickens Z, Shah P, Hafner J, Mariello L, Kamal S, Vlahović G, Lyerly HK, Morse MA, Philip R.

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

Abstract

The development of potent cancer vaccines for common malignancies such as lung cancer requires identification of suitable target antigens. We hypothesized that peptide epitopes naturally presented by MHC class I molecules on the surface of cancer cells would be the most relevant targets. We used LC/MS/MS analysis and identified 68 MHC class I-presented peptides from lung cancer cells. Using the criteria of strong consensus for HLA-A2 binding and relevance of the source proteins to malignant phenotype, we selected 8 peptides for functional characterization. These peptides, with a range of binding affinities, were confirmed to stabilize HLA-A2 molecules and were used to activate peptide-specific CTLs that efficiently recognized lung tumor cells. No correlation between the transcript levels of the source proteins and the extent of peptide-specific T cell recognition of lung cancer cells was observed. Furthermore, the peptide specific CTLs failed to recognize HLA-A2+ normal lung cells despite expression of the mRNA encoding the source proteins from which the peptides were derived. We conclude that MHC class I associated peptide epitopes are a more relevant source of authentic tumor antigens than over-expressed proteins and the identified peptides may be used as antigens for therapeutic vaccine strategies to treat lung cancer.

Copyright © 2011 Elsevier B.V. All rights reserved.

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Shared immunoproteome for ovarian cancer diagnostics and immunotherapy: potential theranostic approach to cancer.

J Proteome Res. 2007 Jul;6(7):2509-17. Epub 2007 Jun 5.

Philip R1, Murthy S, Krakover J, Sinnathamby G, Zerfass J, Keller L, Philip M.

1Immunotope Inc., The Pennsylvania Biotechnology Center, 3805 Old Easton Road, Doylestown, Pennsylvania 18902, USA.

Abstract

Elimination of cancer through early detection and treatment is the ultimate goal of cancer research and is especially critical for ovarian and other forms of cancer typically diagnosed at very late stages that have very poor response rates. Proteomics has opened new avenues for the discovery of diagnostic and therapeutic targets. Immunoproteomics, which defines the subset of proteins involved in the immune response, holds considerable promise for providing a better understanding of the early-stage immune response to cancer as well as important insights into antigens that may be suitable for immunotherapy. Early administration of immunotherapeutic vaccines can potentially have profound effects on prevention of metastasis and may potentially cure through efficient and complete tumor elimination. We developed a mass-spectrometry-based method to identify novel autoantibody-based serum biomarkers for the early diagnosis of ovarian cancer that uses native tumor-associated proteins immunoprecipitated by autoantibodies from sera obtained from cancer patients and from cancer-free controls to identify autoantibody signatures that occur at high frequency only in cancer patient sera. Interestingly, we identified a subset of more than 50 autoantigens that were also processed and presented by MHC class I molecules on the surfaces of ovarian cancer cells and thus were common to the two immunological processes of humoral and cell-mediated immunity. These shared autoantigens were highly representative of families of proteins with roles in key processes in carcinogenesis and metastasis, such as cell cycle regulation, cell proliferation, apoptosis, tumor suppression, and cell adhesion. Autoantibodies appearing at the early stages of cancer suggest that this detectable immune response to the developing tumor can be exploited as early-stage biomarkers for the development of ovarian cancer diagnostics. Correspondingly, because the T-cell immune response depends on MHC class I processing and presentation of peptides, proteins that go through this pathway are potential candidates for the development of immunotherapeutics designed to activate a T-cell immune response to cancer. To the best of our knowledge, this is the first comprehensive study that identifies and categorizes proteins that are involved in both humoral and cell-mediated immunity against ovarian cancer, and it may have broad implications for the discovery and selection of theranostic molecular targets for cancer therapeutics and diagnostics in general.

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