RATIONALE: Studying the proteins expressed in tumor tissue samples in the laboratory from patients with cancer may help doctors learn more about biomarkers related to cancer. It may also help doctors predict how patients respond to treatment. PURPOSE: This laboratory study is looking at protein expression in predicting response to treatment using tumor tissue samples from women with stage I, stage II, or stage IIIA breast cancer treated on clinical trial SWOG-9313.
OBJECTIVES: * Assess in-situ protein expression of estrogen receptor (ER), progesterone receptor (PR), HER-2, and p53 by automated quantitative analysis (AQUA™) and multiplexed analysis at 2 markers per slide using tumor tissue from women with stage I, stage II, or stage IIIA breast cancer treated on clinical trial SWOG-9313. * Assess the main effects of ER, PR, HER-2, and p53, as well as interactions to generate classes formed by clustering of biomarkers, on a large breast cancer tissue microarray to predict disease-free and overall survival of patients who received high-dose cyclophosphamide and doxorubicin hydrochloride on clinical trial SWOG-9313. OUTLINE: This is a multicenter study. Patients are stratified according to receptor status and menopausal status. Tumor tissue samples are analyzed by quantitative protein expression analysis (AQUA™, a fluorescent antibody technique) for estrogen receptor, progesterone receptor, p53 and HER-2. AQUA™ is used to assess markers individually and as ratios with the use of clustering algorithms to define reproducible classifications of tissue from patients treated on SWOG-9313 as a function of molecular classification. Results of the AQUA™ testing are compared to immunohistochemistry and fluorescent in situ hybridization (FISH) results obtained on SWOG-9313.
Study Type
OBSERVATIONAL
Enrollment
2,100
Yale Cancer Center
New Haven, Connecticut, United States
In-situ protein expression of estrogen receptor (ER), progesterone receptor (PR), HER-2, and p53 as measured by automated quantitative analysis (AQUA™)
at baseline
Time frame: Retrospectively at baseline
Main effects of ER, PR, HER-2, and p53, as well as interactions to generate classes formed by clustering of biomarkers, on a large breast cancer tissue microarray to predict disease-free and overall survival
at baseline
Time frame: Retrospectively at baseline
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