Gene set analysis of post-lactational mammary gland involution gene signatures in inflammatory and triple-negative breast cancer.

BACKGROUND: Epidemiological studies have found that triple-negative breast cancer (TNBC) and TN inflammatory breast cancer (IBC) are associated with lower frequency and duration of breast-feeding compared to non-TNBC and non-TN IBC, respectively. Limited breast-feeding could reflect abrupt or premature involution and contribute to a "primed" stroma that is permissive to the migration of cancer cells typical of IBC. We hypothesized that gene expression related to abrupt mammary gland involution after forced weaning may be enriched in the tissues of IBC patients and, if so, provide a potential correlation between limited breast-feeding and the development of aggressive breast cancer. METHODS: We utilized the Short Time-series Expression Miner (STEM) program to cluster significant signatures from two independent studies that analyzed gene expression at multiple time-points of mouse mammary gland involution. Using 10 significant signatures, we performed gene ontology analysis and gene set enrichment analysis (GSEA) on training and validation sets from human breast cancer gene expression data to identify specific genes that are enriched in IBC compared to non-IBC and in TN compared to non-TN in IBC and non-IBC groups. RESULTS: Examining the combined data, we identified 10 involution gene clusters (Inv1-10) that share time-dependent regulation after forced weaning. Inv5 was the only cluster significantly enriched in IBC in the training and validation set (nominal p-values <0.05) and only by unadjusted p-values (FDR q-values 0.26 and 0.46 respectively). Eight genes in Inv5 are upregulated in both the training and validation sets in IBC. Combining the training and validation sets, both Inv5 and Inv6 have nominal p-values <0.05 and q-values 0.39 and 0.20, respectively. The time course for both clusters includes genes that change within 12 hours after forced weaning. CONCLUSIONS: Results from this in silico study suggest correlation between molecular events during abrupt involution and aggressive breast cancer. Specifically, candidate genes from Inv5 merit functional investigation regarding the role of limited breast-feeding in IBC development.

Genomic and expression analysis of microdissected inflammatory breast cancer.

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.