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Molecular Network Profiling of DCIS for Patient Stratification and Individualized Therapy
Detection, Diagnosis and Prognosis
Background : In 2005, it is estimated that 54,000 women will be diagnosed with DCIS. Although DCIS itself is noninvasive, women diagnosed with DCIS have a 30-40% chance of developing invasive breast cancer (IBC) if left untreated. Clinically, treatments for DCIS are designed to prevent IBC. Molecular profiling may provide a fingerprint for stratifying patients into appropriate treatment categories and possibly spare patients unnecessary treatment toxicities. Objective /Hypothesis : The objective of this study is to use cDNA gene microarray and reverse phase protein microarray analysis to obtain broad molecular network profiles from breast ductal epithelia, the surrounding stroma and serum obtained from patients with atypical proliferative changes (ADH), DCIS and IBC. Specific Aims : (1) To study the microenvironment disturbances within the DCIS ductal epithelium and stroma (2) To identify potential serum biomarkers in patients with DCIS. (3) To correlate the signaling pathway profiles with known clinical prognostic parameters. Study Design : Tissue samples from patients with ADH, DCIS and IBC will be subjected to Laser Capture Microdissection to obtain tumor tissue, peritumoral stromal tissue and normal samples for comparative gene and protein expression profiling. mRNA and protein samples will be processed for cDNA array gene expression analysis and reverse phase protein microarrays for multiplexed signal network profiling. Concurrent serum samples will be processed for proteomic biomarker discovery. Alterations within intracellular signal pathways and networks profiled in parallel with gene expression and will be evaluated for concordance, and correlation with histologic characteristics and clinical parameters. Potential Outcomes and Benefits of Research : This study of the perturbation of gene and protein molecular networks involved in the malignant transformation of benign breast tissue into DCIS and IBC will help to better understand the signal pathways involved in carcinogenesis. Correlating this data with known clinical prognostic markers may identify novel clinically important prognostic markers. This information may also be able to identify DCIS patients who are at low risk for invasive breast cancer and thus do not need additional therapy after surgery. Most importantly, we may be able to potentially identify new targets for chemoprevention based on the patient’s unique signaling profile disturbance.
In 2005, an estimated 54,000 women will be diagnosed with ductal carcinoma in situ (DCIS), a pre-invasive form of breast cancer. W omen diagnosed with DCIS have a 30-40% chance of developing invasive breast cancer(IBC) if left untreated. Today, the treatment options for women diagnosed with DCIS and other pre-malignant changes are stratified to receive either breast conservation therapy (surgical removal of the tumor with an adequate margin in conjunction with breast radiation therapy) or mastectomy to minimize the risk of recurrent DCIS or IBC. Anti-estrogen hormonal therapy is offered to those patients with estrogen or progesterone receptors on the cancer cells to decrease the risk of future invasive breast cancer development. Further molecular stratification and identification of DCIS patients at risk for IBC will help clinicians to recommend more targeted and individualized therapies and spare patient unnecessary treatments and complications. The objective of this study is to use gene expression technologies and protein identification technologies to build molecular profiles of the tumor cells, surrounding tissues and blood from patients with pre-malignant changes, DCIS and invasive breast cancer. The study's first specific aim is to examine the microenvironment and signaling pathways between the isolated tumor cells and surrounding stromal cells. T hese cell samples will be obtained by laser assisted microdissection and subjected to cDNA microarray gene and reverse phase protein microarray analysis. The second specific aim is to identify selective serum biomarker proteins in the blood of these patients. The third specific aim is to compare these molecular profiles and biomarkers with known clinical prognostic parameters including tumor grade, margin status and hormone receptor status. Potentially, this study of the gene and protein molecular network derangements involved in benign breast disease, DCIS and IBC will help to better understand the pathogenesis of DCIS and IBC. Correlating this compre hensive molecular network profile data with known clinical prognostic markers may identify stronger stratification criteria for DCIS patients at risk for IBC. This will assist clinicians to tailor adjuvant therapies while minimizing morbidity. Most importantly, w e may be able to potentially identify new targets for chemoprevention for patients with DCIS based on their unique molecular network profile.