Use of a Single-Chain Antibody Library for Ovarian Cancer Biomarker Discovery |
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Authors: | Arturo B. Ramirez Christian M. Loch Yuzheng Zhang Yan Liu Xiaohong Wang Elizabeth A. Wayner Jonathon E. Sargent Sahar Sibani Eugenie Hainsworth Eliseo A. Mendoza Ralph Eugene Joshua LaBaer Nicole D. Urban Martin W. McIntosh Paul D. Lampe |
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Affiliation: | From the ‡Molecular Diagnostics Program, Public Health Sciences and ;‖Antibody Development Shared Resources, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109.;**Biodesign Institute, Arizona State University, Tempe, Arizona 85287, and ;§LifeSesnors, Inc., Malvern, Pennsylvania 19355 |
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Abstract: | The discovery of novel early detection biomarkers of disease could offer one of the best approaches to decrease the morbidity and mortality of ovarian and other cancers. We report on the use of a single-chain variable fragment antibody library for screening ovarian serum to find novel biomarkers for the detection of cancer. We alternately panned the library with ovarian cancer and disease-free control sera to make a sublibrary of antibodies that bind proteins differentially expressed in cancer. This sublibrary was printed on antibody microarrays that were incubated with labeled serum from multiple sets of cancer patients and controls. The antibodies that performed best at discriminating disease status were selected, and their cognate antigens were identified using a functional protein microarray. Overexpression of some of these antigens was observed in cancer serum, tumor proximal fluid, and cancer tissue via dot blot and immunohistochemical staining. Thus, our use of recombinant antibody microarrays for unbiased discovery found targets for ovarian cancer detection in multiple sample sets, supporting their further study for disease diagnosis.Despite many advances in the treatment of cancer, early detection and tumor removal remains the best prospect for overcoming disease. Ovarian cancer is an excellent example of the potential prognostic value of early detection because diagnosis at a localized stage has a 5-year survival rate of 93%. However, only 19% of cases are diagnosed at this stage, and by the time the disease has evolved to an advanced stage, the 5-year survival rate drops to 31% (1).Much effort has been expended to find early detection markers of ovarian cancer, and some success has been achieved. Most notable is CA125, the only approved marker for the detection of recurrence of ovarian cancer (2). Other leading targets are mesothelin and HE4, which have been examined by several groups for their efficacy as early detection markers (3–8). Nevertheless, several conditions necessitate the discovery of more specific and sensitive ovarian cancer markers: the heterogeneity of this disease, the ambiguity of its symptoms, its low incidence in the general population, and the low sensitivity and specificity of currently available markers.One of the difficulties in finding markers in blood is the complexity of the plasma/serum proteome, estimated in the tens to hundreds of thousands of proteins, as well as its large range in constituent protein concentrations, which can span 12 orders of magnitude (9). However, along with its easy accessibility, the fact that blood is in contact with virtually every tissue and contains tissue- and tumor-derived proteins makes it a preferred source for disease biomarker discovery.Our previous results (10, 11) and those of others (12–14) using high density, full-length IgG antibody microarrays to validate and discover cancer serum biomarkers demonstrated that this platform is valuable for simultaneously comparing the levels of hundreds of proteins on dozens of serum samples from cancer patients and healthy controls. We confirmed overexpression of CA125, mesothelin, and HE4 in ovarian cancer samples using this high density microarray platform, validating our array methodology for measurement of cancer serum biomarkers and yielding new putative biomarkers for this disease (10, 11).Previously reported approaches are typically limited to a few hundred antibodies. The methodology reported here allows us to exploit the specific advantages of antibodies as high affinity capture reagents to detect differential expression of thousands of tumor biomarkers using a diverse (2 × 108 binding agents) single-chain variable fragment antibody (scFv)1 library for detection of ovarian cancer markers in serum, tumor cyst fluid, and ascites fluid. Our results build on previous reports of phage display library microarrays to discover autoantibody (15–18) and other protein (12, 19, 20) cancer biomarkers. Our scFv are high affinity capture reagents consisting of the variable regions of human antibody heavy and light chains joined by a flexible linker peptide. These recombinant antibodies are able to recognize a wide variety of antigens, including many previously thought difficult, such as self-antigens and proteins that are not normally immunogenic in animals (21–24). Using a highly diverse recombinant antibody library, one has the ability to overcome the complexity of the serum proteome. It has been calculated that for an immune repertoire to be complete (at least one antibody in the repertoire has reasonable affinity for every epitope possible in nature) it requires a diversity of at least 106 antibodies (25). The reported diversity of our scFv library exceeds this value by 100-fold (21).To enrich for antibodies that differentiate disease status, we performed a selection or panning of the naïve library for proteins that are differentially expressed in cyst fluid, ascites fluid, or serum of cancer patients with respect to healthy serum. We printed this sublibrary on activated hydrogel slides that were queried with three different sets of labeled case and control sera to further select those that discriminate cancer status in a statistically significant manner. Next, we identified some of the targets that bind to the individual scFv using high density nucleic acid programmable protein arrays (NAPPAs) expressing a total of over 7000 proteins. Finally, we validated the effectiveness of the selection process by confirming overexpression of these targets in cancer serum, cyst fluid, and ascites fluid as well as in tumor sections. |
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