Metaplastic breast cancers (MBCs) are aggressive, chemoresistant tumors characterized by lineage plasticity. To advance understanding of their pathogenesis and relatedness to other breast cancer subtypes, twenty-eight MBCs were compared with common breast cancers using comparative genomic hybridization, transcriptional profiling, reverse phase protein arrays and by sequencing for common breast cancer mutations. MBCs demonstrated unique DNA copy number aberrations compared with common breast cancers. PIK3CA mutations were detected in 9/19 MBCs (47.4%) versus 80/232 hormone receptor-positive cancers (34.5%; p=0.32), 17/75 HER2-positive samples (22.7%; p=0.04), 20/240 basal-like cancers (8.3%; p<0.0001) and 0/14 claudin-low tumors (p=0.004). Of 7 PI3K/AKT pathway phosphorylation sites, six were more highly phosphorylated in MBCs than in other breast tumor subtypes. The majority of MBCs displayed mRNA profiles different from those of most common including basal-like cancers. By transcriptional profiling, MBCs and the recently identified claudin-low breast cancer subset constitute related receptor-negative subgroups characterized by low expression of GATA3-regulated genes and of genes responsible for cell-cell adhesion with enrichment for markers linked to stem cell function and epithelial-mesenchymal transition (EMT). In contrast to other breast cancers, claudin-low tumors and most MBCs showed a significant similarity to a “tumorigenic” signature defined using CD44+/CD24breast tumor-initiating stem cell-like cells. MBCs and claudin-low tumors are thus enriched in EMT and stem cell-like features, and may arise from an earlier, more chemoresistant breast epithelial precursor than basal-like or luminal cancers. PIK3CA mutations, EMT and stem cell-like characteristics likely contribute to the poor outcomes of MBC and suggest novel therapeutic targets. INTRODUCTION Metaplastic breast carcinomas (MBCs) are aggressive estrogen receptor (ERα)-negative, progesterone receptor (PR)-negative, HER2-negative (triple-negative) tumors characterized by mesenchymal/sarcomatoid and/or squamous metaplasia of malignant breast epithelium (1-7). Because of limited understanding of their pathogenesis, MBCs are treated in the same fashion as basal-like or triple receptor-negative ductal cancers. However, while neoadjuvant chemotherapy is associated with high pathologic complete response rates in basal-like carcinomas, MBCs are usually chemoresistant (2). Transcriptional profiling has defined breast cancer subtypes (8,9). The origin of luminal A and B tumors appears to be the mammary duct luminal epithelium with concomitant hormone receptor expression. Elevated HER2 expression defines a subgroup with a poor prognosis; however, the responsiveness of this subgroup to trastuzumab improves outcomes (10). In contrast, basal-like cancers likely represent multiple different subtypes arising from distinct precursor cells from those of other cancers. Some basal-like breast cancers likely arise from mammary myoepithelial cells. To date, basal-like cancers have not presented specific therapy targets. As MBCs are triple-negative, they are distinct from luminal and HER2-amplified cancers. As they express some markers associated with basal-like cancers (e.g. epidermal growth factor receptor (EGFR), cytokeratins 5/6), MBCs are proposed to represent a form of basal-like breast cancer. However, distinct clinical features such as chemoresistance suggest that MBCs may represent a unique subtype (2,3). We applied an integrated genomic-proteomic approach to determine mechanisms underlying metaplastic carcinogenesis and MBC chemoresistance along with the relatedness of MBCs to known breast cancer subtypes. Most MBCs showed a unique molecular profile and form a distinct subtype most closely related to a novel subset of receptor-negative breast cancers (claudin-low) characterized by loss of genes involved in cell-cell adhesion. An enrichment for stem cell-like and epithelial-mesenchymal transition (EMT) markers in MBCs (and claudin-low tumors) along with frequent genomic aberrations that activate the phosphatidylinositol-3-kinase (PI3K)/AKT pathway suggest reasons for MBC chemoresistance and that MBCs and claudin-low tumors may arise from more immature precursor cells than other breast cancers. MATERIALS AND METHODS Human tumors Twenty-eight frozen grade 3 MBCs with sarcomatoid (19) or squamous (9) metaplasia were obtained from the Breast Tumor Bank at M.D.Anderson Cancer Center (MDACC) and from a collaborator in Valencia (A.L.). The diagnosis was reconfirmed by pathologists at MDACC (M.G./S.K.) (2,3). Frozen tissue was used for DNA extraction (28 tumors) and, where adequate frozen tumor tissue remained, for RNA and protein extraction (16 MDACC tumors) (11). Three tumor cohorts were used for comparison to MBCs (Supplemental Figure 1). The first cohort, used for comparison of mutation frequency (547 tumors) and functional proteomic profiles (693), was composed of 693 frozen primary breast tumors obtained under IRB-approved protocols from MDACC. These tumors were subdivided into clinically-defined subtypes as described previously (Table 1) (12). A second cohort of 145 primary breast tumors was used for comparison to MBC gene copy number profiles herein (13,14). A third cohort (Lineberger Comprehensive Cancer Center (LCCC)) of 184 breast tumors and 9 normal breast tissues was used for comparison with MBC transcriptional profiles (8,9,15). There were no statistically significant differences in the proportion of patients with tumors of different stages between the cohorts. Comparative genomic hybridization (CGH) CGH profiles from the 28 MBCs were generated at Lawrence Berkeley National Laboratory (LBNL) using single nucleotide polymorphism (SNP)-based GeneChip® Human Mapping 50K Sty arrays (Affymetrix, Santa Clara, CA) and compared to BACCGH profiles of primary breast tumors previously generated and processed (J.F.) at LBNL using HumArray1.14/HumArray2.0 (13,14,16-18). MBC 50K data are available. For comparison with LBNL tumors, the 28 MBC SNP chips were mapped to BAC resolution. This approach has been validated by comparing data derived using both platforms to analyze breast cancer cell lines (not shown). LBNL tumors were remapped to the May04 freeze from UCSC and regions around each BAC clone were defined as within a half distance to each neighboring clone or to the beginning or end of the i ftp://beamish.lbl.gov/njwang/ chromosome if telomeric. A median expression value was then obtained for SNPs in each BAC region. Missing values were assigned if <5 SNPs mapped to a particular region. Each array was recentered to have a median of 0. The resulting values were segmented using Circular Binary Segmentation (CBS) followed by a merge-level procedure to combine segmented levels across the genome. Each missing value was assigned the value of its corresponding segment. Gain/loss events and fraction of genome altered were calculated. After this resolution reduction (median=18 SNPs/BAC;mean=30), the mean variability estimate was 0.25. Similar analyses beginning with the CBS steps were performed on the original dChip processed data. We used a Fisher’s test to measure the difference in copy number at probes on each side of genes encoding PI3K/AKT pathway components. These p-values were used to fit a beta-uniform mixture (BUM) model to determine significance at a given false discovery rate (FDR). To directly compare the 50K SNP and older BAC platforms, DNA extracted from five MBCs was also run using the BAC platform. This confirmed a high concordance for the matched data derived from the two platforms (not shown). Detection of mutations DNA was extracted from 547 MDACC breast tumors along with 14 LCCC claudin-low breast tumors and 19 MBCs with sufficient remaining DNA for mutation detection (9,11,12). Following whole genome amplification, p53/PTEN genes were resequenced (19). CTNNB1 exon 3 (the most common site of mutations) was amplified from genomic DNA using a forward primer located at the 5' portion and a reverse primer at the 3' end of the exon. A tumor sample with a known CTNNB1 mutation was amplified and sequenced in parallel with tumor samples as a positive control. A SNP-based approach (Sequenom (San Diego, CA) MassArray) was used to detect mutations in PIK3CA, KRAS and E17K mutations in the AKT1/2/3 genes (12,20). This approach is unsuitable for detection of mutations that are not ‘hot spot’ mutations but is particularly suitable to mutation detection in breast cancer where stromal ‘contamination’ is prevalent (21). Reverse phase protein lysate array (RPPA) RPPA was applied with the antibodies in Supplemental Table 1 to compare PI3K/AKT and mitogen activated protein kinase (MAPK) pathway activation in protein lysates derived from 16 MBCs versus 693 common breast cancers (Supplemental Table 2) (2225). The expression of each antibody in a sample was corrected for protein loading using the average expression levels of all probed proteins. Transcriptional profiling Total RNA was isolated by phenol-chloroform extraction (Trizol, GIBCO/BRL), and mRNA was purified by either magnetic separation using Dynabeads (Dynal) or the Invitrogen FastTrack 2.0 Kit. Twelve of 16 MBC RNA samples with RNA integrity numbers (RINs)>6 were assayed on Agilent oligomicroarrays at LCCC and compared with a published Agilent microarray data set also previously assayed and processed (C.M.P.) at LCCC (8,9,15). The microarray and clinical data are available at UNC Microarray Database and in the Gene Expression Omnibus (GSE10885). Expression Analysis Systematic Explorer (EASE) was applied to perform functional analysis of gene lists. Mapping gene expression onto regions of MBC copy number change Using a Significance Analysis of Microarray (SAM)-defined list of MBC-defining genes, we determined the chromosomal location of each gene to link with the CGH data. Probes with an undefined chromosomal positi
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