Gene Expression Profiling for Molecular Characterization of Inflammatory Breast Cancer and Prediction of Response to Chemotherapy

Abstract

Inflammatory breast cancer (IBC) is a rare but aggressive form of breast cancer with a 5-year survival limited to ϳ40%. Diagnosis, based on clinical and/or pathological criteria, may be difficult. Optimal systemic neoadjuvant therapy and accurate predictors of pathological response have yet to be defined for increasing response rate and survival. Using DNA microarrrays containing ϳ8,000 genes, we profiled breast cancer samples from 81 patients, including 37 with IBC and 44 with noninflammatory breast cancer (NIBC). Global unsupervised hierarchical clustering was able to some extent to distinguish IBC and NIBC cases and revealed subclasses of IBC. Supervised analysis identified a 109-gene set the expression of which discriminated IBC from NIBC samples. This molecular signature was validated in an independent series of 26 samples, with an overall performance accuracy of 85%. Discriminator genes were associated with various cellular processes possibly related to the aggressiveness of IBC, including signal transduction, cell motility, adhesion, and angiogenesis. A similar approach, with leave-one-out cross-validation, identified an 85-gene set that divided IBC patients with significantly different pathological complete response rate (70% in one group and 0% in the other group). These results show the potential of gene expression profiling to contribute to a better understanding of IBC, and to provide new diagnostic and predictive factors for IBC, as well as for potential therapeutic targets.

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

“…Therefore, efforts were undertaken to gain deeper insights at molecular level into the biology of IBC. Hence, it was demonstrated that IBC shows a distinct gene-expression profile compared to non-IBC (Bertucci et al, 2004;Van Laere et al, 2005). In the present study, this observation was confirmed in a platform-independent manner, using both principal component analysis and unsupervised hierarchical clustering.…”

“…At biological level, increased angiogenesis in breast tumours from patients with IBC was demonstrated in several independent studies (Colpaert et al, 2003;Van der Auwera et al, 2004). Using cDNA microarrays, Bertucci et al (2004) and Van Laere et al (2005) identified gene-expression signatures associated with the IBC phenotype. Using the same expression data sets, both studies demonstrated the presence of the same cell-of-origin breast cancer subtypes in IBC (Bertucci et al, 2005;Van Laere et al, 2006a), as was originally described for non-IBC (Perou et al, 2000).…”

Differences in survival among women with stage III inflammatory and noninflammatory locally advanced breast cancer appear early

“…Using cDNA microarrays, distinct gene expression signatures of IBC have also been identified. 25 At the biological level, several studies have also demonstrated increased angiogenesis in IBC. 26 As such, there are currently several prospective studies evaluating inhibitors of angiogenesis (eg, bevacizumab) for the treatment of IBC.…”

Genetic profiling of chromosome 1 in breast cancer: mapping of regions of gains and losses and identification of candidate genes on 1q

“…of expression levels of one gene in subgroup 1, M2 and S2 in subgroup 2. Confidence levels were calculated by performing 1200 iterative random permutations per gene as described previously (Bertucci et al, 2004). Significance threshold for expression differences was DSX0.32 corresponding to o0.01 false positive.…”