Background: Pathological grade is a useful prognostic factor for stratifying breast cancer patients into favorable (well-differentiated tumors) and less favorable (poorly-differentiated tumors) outcome groups. The current system of tumor grading, however, is highly subjective and a large proportion of tumors are characterized as intermediate-grade, making determination of optimal treatments difficult.Methods: Primary breast tumor specimens from patients diagnosed with well- (n=27) and poorly-differentiated (n=51) invasive ductal carcinoma were obtained from patients enrolled in the Clinical Breast Care Project. Frozen tissues were sectioned and mounted on gold coated MALDI target plates for protein expression profiling. Hematoxylin and eosin (H&E) stained slides were prepared from serial sections for histological characterization. MALDI matrix was deposited as individual spots on the tissue sections in a histology directed manner to assay specific areas and tissue types of interest. Mass spectral data were then acquired from multiple sites across each tissue section.Results: 129 features were observed in well-differentiated and 132 in poorly-differentiated tumors. While the majority of features detected were similar between the two groups, 6 protein features were expressed at significantly lower and 12 at significantly higher levels in the poorly-differentiated tumors, including increased expression of Calgranulin A and Calgizzarin.Conclusions: Protein expression differences detected here suggest that well- and poorly-differentiated invasive breast tumors are molecularly distinct diseases and that these protein changes may contribute to the structural integrity of the tumor cell. In particular, calgranulin A and calgizzarin are members of the S100 protein family, and function in processes such as cell proliferation and differentiation. Further refinement of this differentiation protein signature may not only improve our understanding of the biological processes involved with tumor grade but provide pathologists with new molecular tools to classify breast tumors and reduce the subjectivity associated with current grading criteria.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6126.