Purpose Inflammatory breast cancer (IBC) is a unique clinical entity characterized by rapid onset of erythema and swelling of the breast often without an obvious breast mass. Many studies have examined and compared gene expression between IBC and non-IBC (nIBC), repeatedly finding clusters associated with receptor subtype, but no consistent gene signature associated with IBC has been validated. Here we compared microdissected IBC tumor cells to microdissected nIBC tumor cells matched based on estrogen and HER-2/neu receptor status. Methods Gene expression analysis and comparative genomic hybridization were performed. An IBC gene set and genomic set were identified using a training set and validated on the remaining data. The IBC gene set was further tested using data from IBC consortium samples and publically available data. Results Receptor driven clusters were identified in IBC; however no IBC-specific gene signature was identified. Fifteen genes were correlated between increased genomic copy number and gene overexpression data. An expression-guided gene set upregulated in the IBC training set clustered the validation set into two clusters independent of receptor subtype but segregated only 75% of samples in each group into IBC or nIBC. In a larger consortium cohort and in published data the gene set failed to optimally enrich for IBC samples. However, this gene set had a high negative predictive value for excluding the diagnosis of IBC in publically available data (100%). An IBC enriched genomic data set accurately identified 10/16 cases in the validation data set. Conclusions Even with microdissection, no IBC-specific gene signature distinguishes IBC from nIBC. Using microdissected data, a validated gene set was identified that is associated with IBC tumor cells. IBC comparative genomic hybridization data are presented, but a validated genomic data set that identifies IBC is not demonstrated.

Real-time reverse transcriptase -polymerase chain reaction (RT -PCR) is a technique with the potential of improving the quantification of disseminated epithelial cells (DEC) in haematological tissues due to its exquisite sensitivity. This sensitivity may lead to false positivity. Immunocytochemistry (ICC) is regarded as the standard methodology to diagnose DEC. In this study, detection with ICC was compared with quantitative real-time RT -PCR for CK-19 and mammaglobin (hMAM) mRNA in bone marrow (BM) of patients with metastatic breast cancer (MBC). Bone marrow was aspirated from 14 control patients and from 29 patients with MBC. Mononuclear cells (MNC) were isolated. Immunostaining was carried out with the Epimet kit. Quantitative PCR was performed on the ABI Prism 7700. The CK-19 and hMAM mRNA quantities were normalised against b-Actin and calculated relative to a calibrator sample (relative gene expression). All controls were negative by ICC and for hMAM expression measured by RT -PCR, whereas the median RGE value for CK-19 was 0.57. For the MBC patients, the median RGE for hMAM was 0 and 10 out of 25 (40%) tested positive. Median RGE for CK-19 was 2.9 and 20 out of 25 (80%) tested positive. With ICC, the median value was 1 stained cell per sample, and 15 out of 24 (62%) samples were positive. A correlation was observed between CK-19 and hMAM expression (r ¼ 0.7; P ¼ 0.0003), and between hMAM expression and ICC (r ¼ 0.6; P ¼ 0.003). CK-19 expression and ICC (r ¼ 0.9; Po0.0001) showed the strongest correlation. Reverse transcriptase -polymerase chain reaction for CK-19 resulted in a higher number of positive BM samples of patients with MBC than ICC. Since an excellent correlation is observed between ICC and RT -PCR, and RT -PCR is probably more sensitive with the advantage of being less observer dependent and thus also more easy to automate, we consider our quantitative real-time RT -PCR method as validated for the detection of DEC in the bone marrow of breast cancer patients.