Purpose: The presence of disseminated tumor cells (DTC) in the bone marrow of breast cancer patients is an acknowledged independent prognostic factor.The biological metastatic potential of these cells has not yet been shown. The presence of putative breast cancer stem cells is shown both in primary tumors and distant metastases. These cells with a CD44 + CD24À/low phenotype represent a minor population in primary breast cancer and are associated with self-renewal and tumorigenic potential. Recognizing the potential effect of prevalence of putative stem cells among DTC, we evaluated the bone marrow DTC. Experimental Design: We employed the double/triple-staining immunohistochemistry protocol and modified the established bone marrow cytokeratin (CK) staining protocol by adding steps for additional antigens, CD44 and/or CD24. We evaluated 50 bone marrow specimens, previously categorized as CK + from early breast cancer patients. CK + cells were examined for CD44 and CD24 expression by light microscopy, fluorescence microscopy, and spectral imaging. Results: We detected the putative stem cell^like phenotype in all CK + specimens. The mean prevalence of putative stem/progenitor cells was 72% and median prevalence was 65% (range, 33-100%) among the overall DTC per patient, compared with primary tumors where this phenotype is reported in <10% of cells.Conclusions: This is the first evidence of the existence of the putative stem-like phenotype within the DTC in bone marrow in early breast cancer patients. All patients had a putative stem cell phenotype among the DTC and most individual DTC showed such phenotype. Future molecular characterization of these cells is warranted.

Background: Spectral imaging extends the capabilities of biological and clinical studies to simultaneously study multiple features such as organelles and proteins qualitatively and quantitatively. Spectral imaging combines two well-known scientific methodologies, namely spectroscopy and imaging, to provide a new advantageous tool. The need to measure the spectrum at each point of the image requires combining dispersive optics with the more common imaging equipment, and introduces constrains as well. Methods and Results: The principles of spectral imaging and a few representative applications are described. Spectral imaging analysis is necessary because the complex data structure cannot be analyzed visually. A few of the

Accurate classification is essential for understanding the pathophysiology of a disease and can inform therapeutic choices. For hematopoietic malignancies, a classification scheme based on the phenotypic similarity between tumor cells and normal cells has been successfully used to define tumor subtypes; however, use of normal cell types as a reference by which to classify solid tumors has not been widely emulated, in part due to more limited understanding of epithelial cell differentiation compared with hematopoiesis. To provide a better definition of the subtypes of epithelial cells comprising the breast epithelium, we performed a systematic analysis of a large set of breast epithelial markers in more than 15,000 normal breast cells, which identified 11 differentiation states for normal luminal cells. We then applied information from this analysis to classify human breast tumors based on normal cell types into 4 major subtypes, HR0-HR3, which were differentiated by vitamin D, androgen, and estrogen hormone receptor (HR) expression. Examination of 3,157 human breast tumors revealed that these HR subtypes were distinct from the current classification scheme, which is based on estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Patient outcomes were best when tumors expressed all 3 hormone receptors (subtype HR3) and worst when they expressed none of the receptors (subtype HR0). Together, these data provide an ontological classification scheme associated with patient survival differences and provides actionable insights for treating breast tumors.