Abstract

Abstract Purpose: Different molecular subtypes of breast cancer are believed to have different degrees of molecular heterogeneity. However, the heterogeneity of breast cancer subtypes has not been formally compared. The goal of this analysis was to develop metrics of global transcriptional heterogeneity, compare heterogeneity across breast cancer subtypes and assess whether heterogeneity metrics correlate with sensitivity to chemotherapy in basal-like cancers. Methods: Affymetrix U133A gene expression data from 836 breast cancers (basal n = 219, HER2-like n = 147, luminal A n = 343, luminal B n = 127) were analyzed. Among the basal-like cancers, 128 received neoadjuvant chemotherapy (pathologic complete response, pCR, n = 44; residual disease, RD, n = 94). Molecular class was assigned by the PAM50 classifier. We used the average pairwise Pearson distance, the sum of eigenvalues of the correlation matrix and multi-dimensional scaling dispersions of the probe set expression values to quantify heterogeneity. Distribution of each metric within the different subtypes was estimated from 500 bootstrapped cohorts of 80 cases in each subtype. We used analysis of variance (ANOVA) to evaluate the significance of the differences in heterogeneity between subtypes. Results: All three heterogeneity metrics yielded concordant results. Within subtypes, heterogeneity was greatest in basal-like cancers followed by HER2-like, luminal B and luminal A (see figure). Luminal A cancers were distinctly less heterogeneous than the rest. Basal-like cancers with RD were more heterogeneous than those with pCR. The best metric to separate basal tumors with pCR versus RD was the sum of eigenvalues shown below. Conclusion: Breast cancer molecular subtypes differ in transcriptional heterogeneity. Luminal A cancers have the lowest within group heterogeneity while basal like cancers have the highest. Among the basal-like cancers, those with high chemotherapy sensitivity (pCR) are more homogeneous than those with RD suggesting that transcriptional heterogeneity might be contributing to increased resistance to therapy in this subgroup. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P4-06-05.

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