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Protein Microarrays for the Detection of Breast Cancer
Background: When cancer is identified at the earliest stages, the probability of cure is very high and therefore diagnostic screening tests that can detect these early stages are crucial. Efforts toward the development of early detection assays for cancers have traditionally depended on single biomarker molecules.
The goal of this project is use the immune system as a biosensor to detect antibodies produced by patients in reaction to proteins overexpressed or mutated in their breast tumors. The PI has developed a high throughput method to clone large numbers of cancer antigens that can be used to recognize the presence of cancer by detecting autoantibodies to tumor proteins in the serum of the test subjects. These antigen biomarkers are cloned without a preconceived notion of their function.
The Aims of this Study are as Follows:
Aim 1. Characterize antigen clones on protein microarrays
Aim 2. Use machine learning techniques such as classification trees and neural networks to develop classifiers able to distinguish women with breast cancer from healthy controls.
Aim 3. Determine the DNA sequence of the antigen marker clones.
Aim 4. Validate the markers on larger breast cancer patient serum sample sets. The reaction of antibodies will be used to identify whether the antigen reactions are indicative of a high likelihood of recurrence in ER negative patients.
Aim 5. Eliminate those antigen clones with a false positive reaction with sera from women with other cancers, inflammatory diseases or benign medical conditions.
Study Design: The essential features of the approach are acknowledging the heterogeneous nature of cancer, departing from the reliance on any single marker for disease detection, and using specialized bioinformatics to interpret the results. In the first phase we isolate and test antigen clones for antibody activity in sera from cohorts of Stage I patients with recurrence, Stage I patients with no recurrence and healthy control serum donors with no history of cancer. Next we will determine their sensitivity, specificity and positive predictive value for detection and prognosis of ER negative breast cancer.
Benefits of the Research: Efforts toward the development of early detection assays for cancers have traditionally depended on single biomarker molecules. Recent technologies have not resulted in non-invasive screening tests suitable for clinical practice. The detection and characterization of breast cancer in a simple serum test will change the face of cancer diagnostics.
Background: When cancer is identified at the earliest stages, the probability of cure is very high and therefore diagnostic screening tests that can detect these early stages are crucial to reduce the morbidity and mortality from that disease. Early detection assays for cancers have traditionally depended on single biomarker molecules.
Objectives: Our goal is the early detection breast tumors exploiting the immune system as a biosensor but using large panels of biomarkers to increase the accuracy.
Specific Aims: The core technology is a newly developed high throughput method to identify large numbers of antigens that can be used to recognize the presence of cancer by detecting antibodies to tumor proteins in the sera of the test subjects. The essential features of the approach are acknowledging the heterogeneous nature of any specific kind of cancer, departing from the reliance on any single marker for disease detection, and using specialized bioinformatics computer techniques to interpret the results. The concept employs pattern recognition of multiple markers as a diagnostic rather than any single marker. This study proposes to investigate a novel serum assay to detect and possibly predict outcomes of breast cancers in asymptomatic women to determine who has cancer and who is healthy and whether those with early stage disease will relapse. This project will focus on estrogen receptor negative breast cancers determining their likelihood of relapse.
Study Design: A unique serum bank makes this project possible. We have developed a specimen bank consisting of primary tissues and sera collected from 1306 patients from 1975 to 1983. Multiple follow-up samples are also available such as at the time of breast cancer recurrence. The data collected include histologic grade, mitotic grade, Estrogen Receptor status, lymph node involvement, family history, and associations with breast cancer recurrence. This project will use a protein microarray approach to more globally study changes in serum antibodies that are indicative of the presence of breast cancer or are specifically found in patients with a poor prognosis in early stage breast cancer. The latter point is made possible by having 10 years of follow-up data on these women.
Potential Outcomes and Benefits of the Research: Our goal is to apply this technology to develop an early detection test for breast cancer in asymptomatic women and develop a novel prognostic approach of staging for women with early stage ER- breast cancer, a disease from which more than 30% of women will relapse in 5 years.