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Expression Analysis of Microdissected Inflammatory Breast Cancer

ABSTRACT: 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 examined microdissected IBC tumor cells compared to microdissected nIBC tumor cells matched based on estrogen and HER-2/neu receptor status. Gene expression profiling of 20 inflammatory breast cancer (IBC), 20 non-IBC and 5 normal was studied.

ORGANISM(S): Homo sapiens

SUBMITTER: Woodward WA

PROVIDER: S-ECPF-GEOD-45581 | biostudies-other | 2013 Apr

REPOSITORIES: biostudies-other

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Genomic and expression analysis of microdissected inflammatory breast cancer.

Project description: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. 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 publicly available data. 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 publicly available data (100 %). An IBC enriched genomic data set accurately identified 10/16 cases in the validation data set. 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. Inflammatory breast cancer comparative genomic hybridization data are presented, but a validated genomic data set that identifies IBC is not demonstrated.

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Expression Analysis of Microdissected Inflammatory Breast Cancer

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Gene-expression profiling of microdissected breast cancer microvasculature identifies distinct tumor vascular subtypes.

Project description:Angiogenesis represents a potential therapeutic target in breast cancer. However, responses to targeted antiangiogenic therapies have been reported to vary among patients. This suggests that the tumor vasculature may be heterogeneous and that an appropriate choice of treatment would require an understanding of these differences.To investigate whether and how the breast tumor vasculature varies between individuals, we isolated tumor-associated and matched normal vasculature from 17 breast carcinomas by laser-capture microdissection, and generated gene-expression profiles. Because microvessel density has previously been associated with disease course, tumors with low (n = 9) or high (n = 8) microvessel density were selected for analysis to maximize heterogeneity for this feature.We identified differences between tumor and normal vasculature, and we describe two subtypes present within tumor vasculature. These subtypes exhibit distinct gene-expression signatures that reflect features including hallmarks of vessel maturity. Potential therapeutic targets (MET, ITGAV, and PDGFR?) are differentially expressed between subtypes. Taking these subtypes into account has allowed us to derive a vascular signature associated with disease outcome.Our results further support a role for tumor microvasculature in determining disease progression. Overall, this study provides a deeper molecular understanding of the heterogeneity existing within the breast tumor vasculature and opens new avenues toward the improved design and targeting of antiangiogenic therapies.

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Distinct molecular phenotype of inflammatory breast cancer compared to non-inflammatory breast cancer using Affymetrix-based genome-wide gene-expression analysis.

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