> Research & Grants
> Grants Program
> Research Grants
> Research Grants Awarded
Research Grants Awarded
Identification Of Low Molecular Weight Serum Proteins/Peptides For The Diagnosis Of Breast Cancer Disease
Detection, Diagnosis and Prognosis
Low abundance/low molecular weight serum protein biomarkers (LMPB; <30kDa) will be used for early diagnosis of breast cancer. LMPB include a) intact proteins that may act as signals for cell growth or death (LMSP), b) intact proteins from diseased tissue (LMITP) or c) peptides from this tissue (LMFTP). Identification will require 1) an efficient analysis strategy to detect and characterize the proteins, 2) well characterized patients with well characterized tumors to allow stratification of proteins with specific diagnoses and 3) a set of bioinformatics analysis tools to correlate the presence of LMPB with defined diagnosis categories. We hypothesize that changes in the concentration of small serum proteins or peptides are predictive of the presence of particular cancerous tissue types. LMITP will be isolated from serum of normal and affected individuals with different stages of breast cancer using methodologies developed in this laboratory. These will be analyzed using a MALDI-TOF followed by clustering and model building to identify LMITP that vary in concentration between disease groups. Preliminary results from normal and invasive breast cancer patients indicate that although many LMITP (1kDa-5kDa) were common some were unique to each group. In a second but complementary project, we will perform 2D-DIGE/MS analysis of LMITP obtained by using either acetone precipitation or molecular weight cut off filters. Finally, ELISA will be used to validate potential biomarker(s). WRI is part of the CBCP which includes clinical, molecular and immunological research partners. The clinical arm has provided more than 2,200 serum samples from breast cancer patients over the last five years. The samples also have a vast amount of associated clinical, pathological, treatment and outcome data (900 data fields including up to 7 from 131 possible diagnoses,), which will be used to identify 400-600 samples for the above analyses. Results from LMPB expression analyses will be correlated with the categories of breast cancer to identify LMPB predictive of disease occurrence and potentially outcome. Finally, the effectiveness of the prediction will be assessed using an independent set of 600 samples. Serum analysis will provide a minimally invasive method for early detection of breast cancer. Identification of these potential biomarkers will be the basis for determining if they have any role in immunogenic vaccine development, by the CBCP’s vaccine research division.
Every year about 200,000 women in the US are diagnosed with breast cancer, and ~40,000 women die from this disease. It is now possible to identify biomarkers whose concentration in blood changes in response to disease. We hypothesize that blood (serum) contains biomarkers (small proteins or fragments of protein, known as peptides, released by the breast tumor) that vary with disease type and hence are predictive of the particular cancer. This project will target proteins/peptides that will be far smaller than those currently analyzed. Identification of these biomarkers may be useful for the early diagnosis of breast cancer. We will isolate proteins/peptides from the serum of normal and affected individuals with different stages of breast cancer using specific methodologies developed in this laboratory. These potential biomarkers will be accurately characterized in terms of size using a mass spectrometer which will allow its source to be identified. The biomarkers will then be analyzed by bioinformatics software to correlate discrete biomarkers with specific tumors to identify those that are predictive of specific disease groups. Preliminary results from normal and invasive breast cancer patients indicated that many of the biomarkers were common but some were unique to each disease group. As part of CBCP, WRI has received more than 2,200 serum samples from breast cancer patients who have been treated over the last five years. These samples also have 900 clinical, pathological treatment and outcome data points which will be used to identify 400-600 patient samples for the above analysis. The results of the low molecular biomarker analyses will be correlated with the different categories of breast cancer to identify those which are predictive of breast cancer occurrence and potentially outcome. The effectiveness of the prediction will be assessed using a separate, second set of 600 serum samples. We will also use a number of alternative technologies to purify the differentially expressed biomarkers and we will also use an immunoassay to validate these potential biomarker(s). Since this project aims to identify biomarkers released into blood by the tumor it should provide a minimally-invasive diagnostic test to detect breast cancer. In the future this could be used to develop new therapeutics in collaboration with CBCP’s vaccine research division.