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Purpose: Inflammatory breast cancer is a distinct and aggressive form of locally advanced breast cancer with unique clinical and pathological features. Recently, histologic evidence of intense angiogenesis was found in inflammatory breast cancer specimens. The aim of this study was to confirm the angiogenic phenotype of inflammatory breast cancer and to investigate its potential to induce lymphangiogenesis. Experimental Design: Real-time quantitative reverse transcriptase-PCR was used to measure levels of mRNA of tumor angiogenesis and lymphangiogenesis-related factors [vascular endothelial growth factor (VEGF)-A, VEGF-C, VEGF-D, Flt-1, KDR, Flt-4, Ang-1, Ang-2, Tie-1, Tie-2, cyclooxygenase-2, fibroblast growth factor-2 (FGF-2), Egr-1, Prox-1, and LYVE-1] in tumor specimens of 16 inflammatory breast cancer and 20 noninflammatory breast cancer patients. Tissue microarray technology and immunohistochemistry were used to study differential protein expression of some of the angiogenic factors in inflammatory breast cancer and noninflammatory breast cancer. Active lymphangiogenesis was further assessed by measuring lymphatic endothelial cell proliferation. Results: Inflammatory breast cancer specimens had significantly higher mRNA expression levels than noninflammatory breast cancer specimens of the following genes: KDR (P = 0.033), Ang-1, (P = 0.0001), Tie-1 (P = 0.001), Tie-2 (P = 0.001), FGF-2 (P = 0.002), VEGF-C (P = 0.001), VEGF-D (P = 0.012), Flt-4 (P = 0.001), Prox-1 (P = 0.005), and LYVE-1 (P = 0.013). High mRNA levels of FGF-2 and cyclooxygenase-2 corresponded to increased protein expression by immunohistochemistry. Inflammatory breast cancer specimens contained significantly higher fractions of proliferating lymphatic endothelial cells than noninflammatory breast cancer specimens (P = 0.033). Conclusions: Using real-time quantitative reverse transcriptase-PCR and immunohistochemistry, we confirmed the intense angiogenic activity in inflammatory breast cancer and demonstrated the presence of active lymphangiogenesis in inflammatory breast cancer. This may help explain the high metastatic potential of inflammatory breast cancer by lymphatic and hematogenous route. Both pathways are potential targets for the treatment of inflammatory breast cancer.

In this study, a comparative quantitative methylation profiling of inflammatory breast cancer (IBC) and non-IBC was set up for the identification of tumor-specific methylation patterns. Methylation ratios of six genes (DAPK, TWIST, HIN-1, RASSF1A, RARbeta2 and APC) were measured in benign breast tissues (n = 9) and in tumor samples from non-IBC (n = 81) and IBC (n = 19) patients using quantitative methylation-specific PCR. Median methylation ratios observed in breast cancer (n = 100) were significantly higher than those observed in benign breast tissues for five of six genes (TWIST, HIN-1, RASSF1A, RARbeta2 and APC). Only one of the individual genes studied, RARbeta2, showed differential methylation ratios in IBC and non-IBC (p = 0.016). Using the maximal methylation ratio observed in benign breast tissue as a threshold, the methylation frequency of two genes, RARbeta2 and APC, was significantly increased in IBC (n = 19) when compared to non-IBC (n = 81): 53 vs. 23% for RARbeta2 (p = 0.012) and 84 vs. 54% for APC (p = 0.017). Using hierarchical clustering, methylation patterns could not classify breast cancers according to their phenotype. The finding of differential frequencies of methylation in IBC and non-IBC for two out of six genes suggests that gene-specific patterns of methylation could provide a basis for molecular classification of IBC. Testing for additional genes could help to define the IBC phenotype based on patterns of aberrant gene promoter methylation.

Purpose: A fibrotic focus, the scar-like area found in the center of an invasive breast tumor, is a prognostic parameter associated with an expansive growth pattern, hypoxia, and (lymph)angiogenesis. Little is known about the molecular pathways involved. Experimental Design: Sixty-five patients were selected of whom microarray data of the tumor and H&E slides for histologic analysis were available. The growth pattern and the presence and size of a fibrotic focus were assessed. Differences in biological pathways were identified with global testing. The correlations of growth pattern and fibrotic focus with common breast cancer signatures and with clinicopathologic variables and survival were investigated. Results: Tumors with a large fibrotic focus showed activation of Ras signaling and of the hypoxia-inducible factor-1α pathway. Furthermore, unsupervised hierarchical cluster analysis with hypoxia- and (lymph)angiogenesis-related genes showed that hypoxia-inducible factor-1α, vascular endothelial growth factor A, and carbonic anhydrase 9 were overexpressed. The presence of a fibrotic focus, especially a large fibrotic focus, was associated with the basal-like subtype (P = 0.009), an activated wound-healing signature (P = 0.06), and a poor-prognosis 76-gene signature (P = 0.004). The presence of a fibrotic focus (P = 0.02) and especially of a large fibrotic focus (P = 0.004) was also associated with early development of distant metastasis. Conclusions: Our results sustain the hypothesis that hypoxia-driven angiogenesis is essential in the biology of a fibrotic focus. Ras and Akt might play a role as downstream modulators. Our data furthermore suggest that vascular endothelial growth factor A does not only drive angiogenesis but also lymphangiogenesis in tumors with a fibrotic focus. Our data also show an association between the presence of a fibrotic focus and infaust molecular signatures.

Inflammatory breast cancer (IBC) is the most aggressive form of locally advanced breast cancer (LABC). The IBC phenotype is characterized by an infiltrative growth pattern, increased (lymph)angiogenesis and the propensity to invade dermal lymphatics. In pancreatic cancer, interactions between caveolin-1 and RhoC GTPase, a key molecule in causing the IBC phenotype, regulate tumour cell motility and invasion. In this study we sought to investigate the role of caveolin-1 and -2 in IBC cell lines and in human IBC samples.Differential methylation techniques identified the methylation status of the caveolin-1 and -2 promoters in human mammary epithelial cells (HMECs) and the SUM149 cell line. In cell line experiments, caveolin-1 and -2 mRNA and protein expression were compared in HMECs, MCF10A, the SUM102 non-IBC cell lines and 2 IBC cell lines (SUM149 and SUM190). Furthermore, caveolin-1 and -2 mRNA and protein expression were compared in human IBC and non-IBC samples using cDNA microarray, real-time qRT-PCR and immunohistochemistry. Results were correlated with RhoC protein expression data.In the SUM149 cell line, the caveolin-1 and -2 promoter sites were hypomethylated. A significantly increased expression of caveolin-1 and -2, both at the mRNA and protein level was found in IBC cell lines and in human samples of IBC: caveolin-1 and -2 mRNA were respectively 1.7 (p = 0.02) and 2.2 (p = 0.03) fold more expressed in IBC compared to non IBC and at the protein level, 41.4% of IBC specimens expressed either caveolin-1 or -2, compared to 15.6% of non-IBC specimens (p = 0.03). Furthermore a correlation was found between RhoC protein expression and caveolin-1 (p = 0.1) or caveolin-2 (p = 0.09) or either caveolin-1 or -2 protein expression (p = 0.04).Although considered a tumour suppressor in breast cancer, we demonstrated overexpression of caveolin-1 and -2 in IBC cell lines and in human samples of IBC, most likely due to hypomethylation of their respective promoters. These results confirm the distinct molecular signature of IBC. Our data further suggest interaction between RhoC GTPase and the caveolins in IBC.

Introduction: MicroRNAs (miRNAs) are a group of small noncoding RNAs involved in the regulation of gene expression. As such, they regulate a large number of cellular pathways, and deregulation or altered expression of miRNAs is associated with tumorigenesis. In the current study, we evaluated the feasibility and clinical utility of circulating miRNAs as biomarkers for the detection and staging of breast cancer. Methods: miRNAs were extracted from a set of 84 tissue samples from patients with breast cancer and eight normal tissue samples obtained after breast-reductive surgery. After reverse transcription and preamplification, 768 miRNAs were profiled by using the TaqMan low-density arrays. After data normalization, unsupervised hierarchical cluster analysis (UHCA) was used to investigate global differences in miRNA expression between cancerous and normal samples. With fold-change analysis, the most discriminating miRNAs between both tissue types were selected, and their expression was analyzed on serum samples from 20 healthy volunteers and 75 patients with breast cancer, including 16 patients with untreated metastatic breast cancer. miRNAs were extracted from 200 mu l of serum, reverse transcribed, and analyzed in duplicate by using polymerase chain reaction (qRT-PCR). Results: UHCA showed major differences in miRNA expression between tissue samples from patients with breast cancer and tissue samples from breast-reductive surgery (P < 0.0001). Generally, miRNA expression in cancerous samples tends to be repressed when compared with miRNA expression in healthy controls (P = 0.0685). The four most discriminating miRNAs by fold-change (miR-215, miR-299-5p, miR-411, and miR-452) were selected for further analysis on serum samples. All miRNAs at least tended to be differentially expressed between serum samples from patients with cancer and serum samples from healthy controls (miR-215, P = 0.094; miR-299-5P, P = 0.019; miR-411, P = 0.002; and miR-452, P = 0.092). For all these miRNAs, except for miR-452, the greatest difference in expression was observed between serum samples from healthy volunteers and serum samples from untreated patients with metastatic breast cancer. Conclusions: Our study provides a basis for the establishment of miRNAs as biomarkers for the detection and eventually staging of breast cancer through blood-borne testing. We identified and tested a set of putative biomarkers of breast cancer and demonstrated that altered levels of these miRNAs in serum from patients with breast cancer are particularly associated with the presence of metastatic disease.

BackgroundIn the present study, we determined the gene hypermethylation profiles of normal tissues adjacent to invasive breast carcinomas and investigated whether these are associated with the gene hypermethylation profiles of the corresponding primary breast tumors.MethodsA quantitative methylation-specific PCR assay was used to analyze the DNA methylation status of 6 genes (DAPK, TWIST, HIN-1, RASSF1A, RARβ2andAPC) in 9 normal breast tissue samples from unaffected women and in 56 paired cancerous and normal tissue samples from breast cancer patients.ResultsNormal tissue adjacent to breast cancer displayed statistically significant differences to unrelated normal breast tissues regarding the aberrant methylation of theRASSF1A(P = 0.03),RARβ2(P = 0.04) andAPC(P = 0.04) genes. Although methylation ratios for all genes in normal tissues from cancer patients were significantly lower than in the cancerous tissue from the same patient (P ≤ 0.01), in general, a clear correlation was observed between methylation ratios measured in both tissue types for all genes tested (P < 0.01). When analyzed as a categorical variable, there was a significant concordance between methylation changes in normal tissues and in the corresponding tumor for all genes tested butRASSF1A. Notably, in 73% of patients, at least one gene with an identical methylation change in cancerous and normal breast tissues was observed.ConclusionsHistologically normal breast tissues adjacent to breast tumors frequently exhibit methylation changes in multiple genes. These methylation changes may play a role in the earliest stages of the development of breast neoplasia.

Purpose: We hypothesize that a gene expression profile characteristic for inflammatory breast cancer (IBC), an aggressive form of breast cancer associated with rapid cancer dissemination and poor survival, might be related to tumor aggressiveness in non-IBC (nIBC). Experimental Design: RNA from 17 IBC samples and 40 nIBC samples was hybridized onto Affymetrix chips. A gene signature predictive of IBC was identified and applied onto 1,157 nIBC samples with survival data of 881 nIBC samples. Samples were classified as IBC-like or nIBC-like. The IBC signature classification was compared with the classifications according to other prognostically relevant gene signatures and clinicopathologic variables. In addition, relapse-free survival (RFS) was compared by the Kaplan-Meyer method. Results: Classification according to the IBC signature is significantly (P < 0.05) associated with the cell-of-origin subtypes, the wound healing response, the invasive gene signature, the genomic grade index, the fibroblastic neoplasm signature, and the 70-gene prognostic signature. Significant associations (P < 0.01) were found between the IBC signature and tumor grade, estrogen receptor status, ErbB2 status, and patient age at diagnosis. Patients with an IBC-like phenotype show a significantly shorter RFS interval (P < 0.05). Oncomine analysis identified cell motility as an important concept linked with the IBC signature. Conclusions: We show that nIBC carcinomas having an IBC-like phenotype have a reduced RFS interval. This suggests that IBC and nIBC show comparable phenotypic traits, for example augmented cell motility, with respect to aggressive tumor cell behavior. This observation lends credit to the use of IBC to study aggressive tumor cell behavior.

Breast cancer can metastasize via lymphatic and hematogenous pathways. Hypoxia and (lymph)angiogenesis are closely related processes that play a pivotal role in the tumor progression and metastasis. The aim of this study was to compare expression of hypoxia and (lymph)angiogenesis-related genes between primary breast tumors and metastases in different tissues.A gene list of 269 hypoxia and (lymph)angiogenesis-related genes was composed and validated using Onto-Express, Pathway-express and Ingenuity software. The expression of these genes was compared in microarray data of 62 samples of primary tumors and metastases of 31 patients with breast cancer retrieved from Gene Expression Omnibus. Similarity between samples was investigated using unsupervised hierarchical clustering analysis, principal component analysis and permutation testing. Differential gene expression between primary tumors and metastases and between metastases from different organs was analyzed using Kruskall-Wallis and Mann-Whitney statistics.Unsupervised hierarchical cluster analysis demonstrated that hypoxia and (lymph)angiogenesis-related gene expression was more similar between samples from the same patient, than between samples from the same organ. Principal component analysis indicated that 22.7% and 7.0% of the total variation in the gene list was respectively patient and organ related. When differences in gene expression were studied between different organs, liver metastases seemed to differ most from the other secondary sites. Some of the best characterized molecules differentially expressed were VEGFA, PDGFRB, FGF4, TIMP1, TGFB-R1 and collagen 18A1 (precursor of endostatin). To confirm the results of these experiments at the protein level, immunohistochemical experiments were performed with antibodies for VEGFA and MMP-2.Our results suggest that hypoxia and (lymph)angiogenesis-related gene expression is more dependent on the characteristics of the primary tumor than on the characteristics of the organs that bear the metastasis. However, when different organs are compared, the expression in liver metastases differs most from other metastatic sites and primary tumors, possibly due to organ-specific angiogenic and lymphangiogenic responses to metastasis-related hypoxia.

Purpose: Inflammatory breast cancer (IBC) is the most aggressive form of locally advanced breast cancer with high metastatic potential. In a previous study, we showed that IBC is a different form of breast cancer compared with non-IBC by cDNA microarray analysis. A list of 756 genes with significant expression differences between IBC and non-IBC was identified. In-depth functional analysis revealed the presence of a high number of nuclear factor-κB (NF-κB) target genes with elevated expression in IBC versus non-IBC. This led to the hypothesis that NF-κB contributes to the phenotype of IBC. The aim of the present study was to further investigate the role of NF-κB in IBC. Experimental Design: Immunohistochemistry and NF-κB DNA-binding experiments were done for all NF-κB subunits (RelA, RelB, cRel, NFkB1, and NFkB2) using IBC and non-IBC specimens. Transcriptionally active NF-κB dimers were identified by means of coexpression analysis. In addition, quantitative real-time reverse transcription-PCR for eight NF-κB target genes, selected upon a significant, 3-fold gene expression difference between IBC and non-IBC by cDNA microarray analysis, was done. Results: We found a significant overexpression for all of eight selected NF-κB target genes in IBC compared with non-IBC by quantitative real-time reverse transcription-PCR. In addition, we found a statistically elevated number of immunostained nuclei in IBC compared with non-IBC for RelB (P = 0.038) and NFkB1 (P < 0.001). Immunohistochemical data were further validated by NF-κB DNA-binding experiments. Significant correlations between immunohistochemical data and NF-κB DNA binding for RelA, RelB, NFkB1, and NFkB2 were found. Transcriptionally active NF-κB dimers, composed of specific combinations of NF-κB family members, were found in 19 of 44 IBC specimens compared with 2 of 45 non-IBC specimens (P < 0.001). In addition, we found evidence for an estrogen receptor (ER)–mediated inhibition of the NF-κB signaling pathway. NF-κB target genes were significantly elevated in ER− versus ER+ breast tumors. Also, the amount of immunostained nuclei for RelB (P = 0.025) and NFkB1 (P = 0.031) was higher in ER− breast tumors versus ER+ breast tumors. Conclusions: The NF-κB transcription factor pathway probably contributes to the phenotype of IBC and possibly offers new options for treatment of patients diagnosed with this aggressive form of breast cancer.

Inflammatory breast cancer (IBC) is a clinically distinct and aggressive form of locally advanced breast cancer with largely unknown genetic determinants. Overexpression of the RhoC GTPase and of HER2, and decreased ER-expression are involved in IBC. Multimodality treatment has increased survival but prognosis is still poor. Novel molecular targets for improved neoadjuvant treatment are necessary. Using cDNA microarrays, we performed genome-wide expression profiling of pre-treatment tumour samples of 16 patients with IBC and 18 patients with non-stage-matched non-IBC. Rigid clinical diagnostic criteria according to the TNM classification of the American Joint Committee on Cancer were adopted. Unsupervised hierarchical clustering accurately distinguished IBC and non-IBC samples. A set of 50 discriminator genes was identified in a learning group of tumour samples and was successful in diagnosing IBC in a validation group of samples (accuracy of 88%). Exclusion of ER-related or HER2-related genes did not alter this discriminatory accuracy, indicating that the expression of other genes in addition to ER and HER2 characterize the IBC phenotype. The molecular signature of IBC revealed the overexpression of a large number of NF-kappaB target genes, explaining at least part of the aggressive nature of IBC. Successful validation of some of the overexpressed genes by immunohistochemistry or real-time quantitative PCR demonstrated the robustness of the cDNA microarray experiments. The results of our study provide potential targets for the treatment of patients with IBC.

Inflammatory breast cancer (IBC) is an aggressive form of locally advanced breast cancer with high metastatic potential. Most patients have lymph node involvement at the time of diagnosis and 1/3 of the patients have distant metastases. In a previous study, we demonstrated that IBC is a distinct form of breast cancer in comparison with non-IBC. The aim of this study was to investigate the presence of the different molecular subtypes in our data set of 16 IBC and 18 non-IBC specimen. Therefore, we selected an 'intrinsic gene set' of 144 genes, present on our cDNA chips and common to the 'intrinsic gene set' described by Sorlie et al. [PNAS, 2003]. This set of genes was tested for performance in the Norway/Stanford data set by unsupervised hierarchical clustering. Expression centroids were then calculated for the core members of each of the five subclasses in the Norway/Stanford data set and used to classify our own specimens by calculating Spearman correlations between each sample and each centroid. We identified the same cell-of-origin subtypes in IBC as those already described in non-IBC. The classification was in good agreement with immunohistochemical data for estrogen receptor protein expression and cytokeratin 5/6 protein expression. Confirmation was done by an alternative unsupervised hierarchical clustering method. The robustness of this classification was assessed by an unsupervised hierarchical clustering with an alternative gene set of 141 genes related to the cell-of-origin subtypes, selected using a discriminating score and iterative random permutation testing. The contribution of the different cell-of-origin subtypes to the IBC phenotype was investigated by principal component analysis. Generally, the combined ErbB2-overexpressing and basal-like cluster was more expressed in IBC compared to non-IBC, whereas the combined luminal A, luminal B and normal-like cluster was more pronounced in non-IBC compared to IBC. The presence of the same molecular cell-of-origin subtypes in IBC as in non-IBC does not exclude the specific molecular nature of IBC, since gene lists that characterize IBC and non-IBC are entirely different from gene lists that define the different cell-of-origin subtypes, as evidenced by principal component analysis.

Purpose: At the time of diagnosis, metastatic dissemination of tumor cells via the lymphatic system has occurred in nearly all patients with inflammatory breast cancer (IBC). The objective of this study was twofold: (a) to determine which is the most suitable marker of lymph vessels in primary breast tumors and (b) to compare histomorphometric lymph vessel variables in IBC and non-IBC. Experimental Design: Serial sections of 10 IBCs and 10 non-IBCs were immunostained for D2-40, LYVE-1, podoplanin, and PROX-1. Relative lymph vessel area, lymph vessel perimeters, and counts and lymphatic endothelial cell proliferation (LECP) were then measured in D2-40/Ki-67 double-immunostained sections of 10 normal breast tissues, 29 IBCs, and 56 non-IBCs. Results: D2-40 was the most suitable antibody for staining peritumoral and intratumoral lymph vessels. D2-40-stained intratumoral lymph vessels were present in 80% of non-IBCs and 82.8% of IBCs (P = 0.76). In non-IBC, lymph vessels located in the tumor parenchyma were smaller and less numerous than those at the tumor periphery (P < 0.0001) whereas in IBC, intratumoral and peritumoral variables were not significantly different. The mean relative tumor area occupied by lymph vessels was larger in IBC than in non-IBC (P = 0.01). LECP at the tumor periphery was higher in IBC than in non-IBC: median LECP was 5.74% in IBC versus 1.83% in non-IBC (P = 0.005). Conclusions: The high LECP in IBC suggests that lymphangiogenesis contributes to the extensive lymphatic spread of IBC.

Background Abnormal DNA methylation is well established for breast cancer and contributes to its progression by silencing tumor suppressor genes. DNA methylation profiling platforms might provide an alternative approach to expression microarrays for accurate breast tumor subtyping. We sought to determine whether the distinction of the inflammatory breast cancer (IBC) phenotype from the non-IBC phenotype by transcriptomics could be sustained by methylomics. Methodology/Principal Findings We performed methylation profiling on a cohort of IBC (N = 19) and non-IBC (N = 43) samples using the Illumina Infinium Methylation Assay. These results were correlated with gene expression profiles. Methylation values allowed separation of breast tumor samples into high and low methylation groups. This separation was significantly related to DNMT3B mRNA levels. The high methylation group was enriched for breast tumor samples from patients with distant metastasis and poor prognosis, as predicted by the 70-gene prognostic signature. Furthermore, this tumor group tended to be enriched for IBC samples (54% vs. 24%) and samples with a high genomic grade index (67% vs. 38%). A set of 16 CpG loci (14 genes) correctly classified 97% of samples into the low or high methylation group. Differentially methylated genes appeared to be mainly related to focal adhesion, cytokine-cytokine receptor interactions, Wnt signaling pathway, chemokine signaling pathways and metabolic processes. Comparison of IBC with non-IBC led to the identification of only four differentially methylated genes (TJP3, MOGAT2, NTSR2 and AGT). A significant correlation between methylation values and gene expression was shown for 4,981 of 6,605 (75%) genes. Conclusions/Significance A subset of clinical samples of breast cancer was characterized by high methylation levels, which coincided with increased DNMT3B expression. Furthermore, an association was observed with molecular signatures indicative of poor patient prognosis. The results of the current study also suggest that aberrant DNA methylation is not the main force driving the molecular biology of IBC.