Abstract P6-04-10: Genetic Discrimination of Aggressive from Indolent DCIS
Authors: Ellsworth RE , Deyarmin B , Patney HL , Shriver CD , Ellison K , Thornton JD , Dang H , Tafra L , Cheng Z , Rosman M. 
Published: April 2011

Background: Treatment options for DCIS vary from surgical excision with or without radiation and/or chemopreventive therapy, or mastectomy. Intuitively, more aggressive treatment options should lead to improved survival rates, however, studies have shown no difference in breast cancer mortality between women treated with wide excision only versus those with excision plus radiation and treatments can be costly, lengthy and associated with side effects. To avoid over-treating women with indolent disease, while intensively treating women with aggressive disease, new molecular tools must be developed to supplement pathological information to classify DCIS lesions and predict clinical outcome.

Methods: Formalin-fixed paraffin-embedded (FFPE) pure DCIS biopsy specimens were collected from the pathology archives of the Anne Arundel Medical Center. Samples included those with poor prognosis characterized by either recurrence of DCIS or progression to invasive cancer (n=7) and those good prognosis, having ≥5-year disease-free survival (n=10). RNA was isolated after laser-microdissection of pure tumor cells and hybridized to Breast Cancer DSA™ microarrays (Almac Diagnostics). S-way ANOVA was used to account for batch effects and then Support Vector Machine (SVM) was used to identify candidate genes effective at discriminating good from poor prognosis DCIS. Pathway analysis was performed using MetaCore (GeneGeo).

Results: 328 genes were found to be differentially expressed between good and poor prognosis specimens (P&lt;0.01). Preliminary analysis with SVM found that a 70-gene candidate signature from these 328 genes wasoptimal under the tested conditions for discriminating favorable from poor prognosis DCIS. This candidate signature included genes such as MEF2C, PTK2 and ZBTB2. Pathway analysis revealed that genes involved in cytoskeleton modeling, apoptosis and survival, DNA damage repair and cell adhesion are expressed at lower levels in poor prognosis DCIS while those involved in cell cycle, immune response and cell proliferation are expressed at higher levels.

Conclusions: While studies have attempted to identify molecular profiles associated with aggressive DCIS by comparing DCIS co-occurring with invasive disease to pure DCIS, to our knowledge, this is the first study that identified a candidate molecular signature of prognosis in pure DCIS. Although many of the 70 genes found to differ between favorable and poor prognosis DCIS have not been previously associated with breast cancer or have unknown function, MEF2C and PTK2 have been implicated in invasion and migration, while ZBTB2 is a master regulator of p53 and stimulates cellular proliferation. These data demonstrate aggressive DCIS do differ from indolent DCIS at the genetic level and that these differences may be useful in developing molecular tools to classify DCIS lesions and guide appropriate treatment.

Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P6-04-10.