Patent Application
20150362497
Ovarian cancer is the fifth leading cause of cancer-related mortality of women in the U.S., with over 15,000 deaths per year. Early diagnosis is associated with improved overall survival; however, the majority of patients are currently diagnosed with advanced disease. The five-year survival rate for late-stage ovarian cancer remains less than 30%.
Despite the identification of serum CA 125 as a biomarker for ovarian cancer in 1983, there are currently no screening biomarkers recommended for use for the general population. The utility of CA 125 as a screening test is limited by a low sensitivity of 50% for early stage disease at 99% specificity.
Combining CA 125 with transvaginal ultrasound (TVUS) increased the specificity of detection in the UKCTOCS large-scale screening trial. In a recent joint validation study of 28 potential markers for detecting ovarian cancer in blood, the most accurate marker remains CA 125, followed closely by HE4. Panels of markers demonstrated only marginal improvements over CA 125 alone for the early detection of disease.
A recent study showed that the addition of CEA and VCAM-1 to CA 125 and HE4 increased the sensitivity of detection of stage I and II ovarian cancer to 86% at 98% specificity, but this remains to be confirmed in a blinded validation study using prediagnostic sera.
Protein overexpression or mutation can also lead to the spontaneous development of autoantibodies (AAb) in the sera of patients with cancer. Tumor antigen-specific AAb have been identified in the sera of patients with cancer, including patients with early-stage disease. p53-specific AAb, which are associated with p53 mutation and resultant protein stabilization, have been detected in early-stage ovarian cancer. p53-specific AAb have also been detected in 41.7% of patients with serous ovarian cancer at 91.7% specificity. Unlike CA 125 and HE4, p53-AAb were associated with improved survival.
However, identification and utilization of other biomarkers for detection of early stage ovarian cancer remains elusive.
Methods to identify antibody signatures in early-stage breast cancer using Nucleic Acid Protein Programmable Arrays (NAPPA) have been developed. Diagnostic test kits and personalized medicine determinations, such as the identification of biomarkers for the early detection of ovarian cancer, also are disclosed.
A novel protein microarray technology NAPPA, which are generated by printing full-length cDNAs encoding the target proteins at each feature of the array, was used. The proteins are then transcribed and translated by a cell-free system and immobilized in situ using epitope tags fused to the proteins. Sera are added, and bound IgG is detected by standard secondary reagents.
These and other aspects of the invention will be apparent upon reference to the following detailed description and figures. To that end, any patent and other documents cited herein are hereby incorporated by reference in their entirety.
Embodiments described herein relate to methods for identifying autoantibodies as potential biomarkers for the early detection of ovarian cancer, as well as to kits for utilizing said autoantibodies as diagnostic biomarkers and for personalized medicine/therapeutics assessment.
Protein microarrays displaying full-length candidate antigens have been developed and sequentially screened to select candidate autoantibody biomarkers. Sera from patients with ovarian cancer were found to contain autoantibodies (AAb) to tumor-derived proteins. Thus, to detect AAb, high-density programmable protein microarrays (NAPPA) expressing 5,177 candidate tumor antigens are probed with sera from patients with serous ovarian cancer and healthy controls, bound IgG measured.
In one embodiment, a set of 741 antigens was selected and probed with an independent set of sera from serous ovarian cancer patients and matched controls. Twelve potential autoantigens were identified with sensitivities ranging from 13-22% at >93% specificity. Surprisingly, many of these twelve autoantigens are not known to previously have been associated with ovarian cancer.
The objective of this study was to identify novel AAb biomarkers for the detection of serous ovarian cancer. To profile the ovarian cancer immune response, NAPPA microarrays displaying 5,177 full-length candidate antigens were generated using cDNAs derived from the DNASU Plasmid Repository at Arizona State University. These cDNAs were all sequence-verified, full length, wild-type genes fused in frame with either a C-terminal GST tag or N-terminal FLAG tag in a vector optimized for mammalian protein expression.
The cDNAs were printed on amine-treated glass slides with anti-tag antibodies at a high density (up to 2300 antigens/slide; 3 slides/gene set) using a Genetix QArray2 with 300 pm solid tungsten pins. Proteins were expressed and captured in situ on the arrays using a coupled in vitro transcription-translation system derived from rabbit reticulocyte lysate. Protein expression was confirmed by probing the arrays with anti-tag antibodies. For detecting antibodies, the arrays were incubated with serum diluted in 5% PBS mile with 0.2% Tween 20 overnight and detected with anti-human IgG-HRP with Tyramide. Slides were scanned with a Perkin Elmer ProScanArray HT and the images quantitated using ArrayPro software.
A sequential screening strategy was used to select candidate AAb biomarkers to limit the false discovery rate inherent to large-scale proteomic screening.
First, 34 cases of serous ovarian cancer and 30 age-matched healthy controls (Cohort 1) were screened on 5,177 candidate tumor antigens. Each array was normalized by first removing the background signal estimated by the first quartile of the non-spots and then log-transforming the median-scaled raw intensities to bring the data to the same scale and stabilize the variance across the range of signals.
Candidate antigens from the initial 5,177 antigens were selected if they met two different criteria: 1) comparison of the 95th percentiles of the cases and controls using quantile regression and 2) comparison of the proportion of cases with intensities above the 95th percentile of controls to the expected number seen by chance using binomial tests. Using these criteria, 741 antigens were selected for further testing.
Second, 60 cases and 60 healthy controls (Cohort 2) were screened on the 741 antigens, which were printed in duplicate on the arrays. Following the use of spot-level quality control procedures, the arrays were similarly normalized and analyzed using receiver operator characteristic (ROC) curve analysis. Specifically, we tested the hypothesis that the partial area under the ROC curve (PAUC) in the region where the specificity >95% exceeds 0.00125, which is the PAUC for a non-informative diagnostic test. We computed q-values and identified 12 potential AAb biomarkers that were statistically significant with a false discovery rate threshold of 15% (Table 1).
Descriptions of these biomarkers, their amino acid sequences and their nucleic acid sequences are provided in Table 2. Third, an independent assay (Luminex bead array) was used to display these autoantigens, and sera from women in Cohort 2 was re-screened. Finally, a smaller set of 7 autoantigens was displayed and screened with sera from an independent set (Cohort 3) of non-serous cancers (n=30), false-negative CA 125 (n=20), benign ovarian disease (n=30), and healthy controls (n=30).
The twelve biomarkers for ovarian cancer can be utilized on an array or other substrate as a diagnostic test in which sera from a patient is tested for ovarian cancer autoantibodies.
The claims are not meant to be limited to the materials and methods, embodiments, and examples described herein.
This application claims priority to U.S. provisional patent Application No. 61/759,047 filed on Jan. 31, 2013, which is incorporated by reference herein in its entirety.
This invention was made with government support under CA117374 awarded by The National Institutes of Health. The U.S. government has certain rights in the invention.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2014/013809 | 1/30/2014 | WO | 00 |
| Number | Date | Country | |
|---|---|---|---|
| 61759047 | Jan 2013 | US |
