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Molecular analysis of metaplastic breast carcinoma: high EGFR copy number via aneusomy.

ABSTRACT: Metaplastic breast carcinoma, a rare tumor composed of adenocarcinomatous and nonglandular growth patterns, is characterized by a propensity for distant metastases and resistance to standard anticancer therapies. We sought confirmation that this tumor is a basal-like breast cancer, expressing epidermal growth factor receptor (EGFR) and stem cell factor receptor (KIT). EGFR activating mutations and high copy number (associated with response to tyrosine kinase inhibitor gefitinib) and KIT activating mutations (associated with imatinib sensitivity) were then investigated. Seventy-seven metaplastic cases were identified (1976-2006); 38 with tumor blocks available underwent pathologic confirmation before EGFR and KIT immunohistochemical analyses. A tissue microarray of malignant glandular and metaplastic elements was constructed and analyzed immunohistochemically for cytokeratin 5/6, estrogen receptor, progesterone receptor, and p63, and by fluorescence in situ hybridization for EGFR and HER-2/neu. DNA isolated from individual elements was assessed for EGFR and KIT activating mutations. All assessable cases were negative for estrogen receptor, progesterone receptor, and (except one) HER2. The majority were positive for cytokeratin 5/6 (58%), p63 (59%), and EGFR overexpression (66%); 24% were KIT positive. No EGFR or KIT activating mutations were present; 26% of the primary metaplastic breast carcinomas were fluorescence in situ hybridization-positive, displaying high EGFR copy number secondary to aneusomy (22%) and amplification (4%). We report here that metaplastic breast carcinoma is a basal-like breast cancer lacking EGFR and KIT activating mutations but exhibiting high EGFR copy number (primarily via aneusomy), suggesting that EGFR tyrosine kinase inhibitors should be evaluated in this molecular subset of breast carcinomas.

SUBMITTER: Gilbert JA

PROVIDER: S-EPMC2745608 | biostudies-literature | 2008 Apr

REPOSITORIES: biostudies-literature

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Molecular analysis of metaplastic breast carcinoma: high EGFR copy number via aneusomy.

Gilbert Judith A JA Goetz Matthew P MP Reynolds Carol A CA Ingle James N JN Giordano Karin F KF Suman Vera J VJ Blair Hilary E HE Jenkins Robert B RB Lingle Wilma L WL Reinholz Monica M MM Adjei Alex A AA Ames Matthew M MM

Molecular cancer therapeutics 20080401 4

Metaplastic breast carcinoma, a rare tumor composed of adenocarcinomatous and nonglandular growth patterns, is characterized by a propensity for distant metastases and resistance to standard anticancer therapies. We sought confirmation that this tumor is a basal-like breast cancer, expressing epidermal growth factor receptor (EGFR) and stem cell factor receptor (KIT). EGFR activating mutations and high copy number (associated with response to tyrosine kinase inhibitor gefitinib) and KIT activati ...[more]

PMID: 18413808

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Project description:BackgroundMetaplastic breast carcinoma (MpBC) typically consists of carcinoma of no special type (NST) with various metaplastic components. Although previous transcriptomic and proteomic studies have reported subtype-related heterogeneity, the intracase transcriptomic alterations between metaplastic components and paired NST components, which are critical for understanding the pathogenesis underlying the metaplastic processes, remain unclear.MethodsFifty-nine NST components and paired metaplastic components (spindle carcinomatous [SPS], matrix-producing, rhabdoid [RHA], and squamous carcinomatous [SQC] components) were microdissected from specimens obtained from 27 patients with MpBC for gene expression profiling using the NanoString Breast Cancer 360 Panel on a NanoString nCounter FLEX platform. BC360-defined signatures were scored using nSolver software.ResultsHierarchical clustering and principal component analysis revealed a heterogeneous gene expression profile (GEP) corresponding to the NST components, but the GEP of metaplastic components exhibited subtype dependence. Compared with the paired NST components, the SPS components demonstrated the upregulation of genes related to stem cells and epithelial-mesenchymal transition and displayed enrichment in claudin-low and macrophage signatures. Despite certain overlaps in the enriched functions and signatures between the RHA and SPS components, the specific differentially expressed genes differed. We observed the RHA-specific upregulation of genes associated with vascular endothelial growth factor signaling. The chondroid matrix-producing components demonstrated the upregulation of hypoxia-related genes and the downregulation of the immune-related MHC2 signature and the TIGIT gene. In the SQC components, TGF-β and genes associated with cell adhesion were upregulated. The differentially expressed genes among metaplastic components in the 22 MpBC cases with one or predominantly one metaplastic component clustered paired NST samples into clusters with correlation with their associated metaplastic types. These genes could be used to separate the 31 metaplastic components according to respective metaplastic types with an accuracy of 74.2%, suggesting that intrinsic signatures of NST may determine paired metaplastic type. Finally, the EMT activity and stem cell traits in the NST components were correlated with specimens displaying lymph node metastasis.ConclusionsWe presented the distinct transcriptomic alterations underlying metaplasia into specific metaplastic components in MpBCs, which contributes to the understanding of the pathogenesis underlying morphologically distinct metaplasia in MpBCs.

Project description:BackgroundA major challenge in the interpretation of genomic profiling data generated from breast cancer samples is the identification of driver genes as distinct from bystander genes which do not impact tumorigenesis. One way to assess the relative importance of alterations in the transcriptome profile is to combine parallel analyses that assess changes in the copy number alterations (CNAs). This integrated analysis permits the identification of genes with altered expression that map within specific chromosomal regions which demonstrate copy number alterations, providing a mechanistic approach to identify the 'driver genes'.MethodsWe have performed whole genome analysis of CNAs using the Affymetrix 250K Mapping array on 22 infiltrating ductal carcinoma samples (IDCs). Analysis of transcript expression alterations was performed using the Affymetrix U133 Plus2.0 array on 16 IDC samples. Fourteen IDC samples were analyzed using both platforms and the data integrated. We also incorporated data from loss of heterozygosity (LOH) analysis to identify genes showing altered expression in LOH regions.ResultsCommon chromosome gains and amplifications were identified at 1q21.3, 6p21.3, 7p11.2-p12.1, 8q21.11 and 8q24.3. A novel amplicon was identified at 5p15.33. Frequent losses were found at 1p36.22, 8q23.3, 11p13, 11q23, and 22q13. Over 130 genes were identified with concurrent increases or decreases in expression that mapped to these regions of copy number alterations. LOH analysis revealed three tumors with whole chromosome or p arm allelic loss of chromosome 17. Genes were identified that mapped to copy neutral LOH regions. LOH with accompanying copy loss was detected on Xp24 and Xp25 and genes mapping to these regions with decreased expression were identified. Gene expression data highlighted the PPARα/RXRα Activation Pathway as down-regulated in the tumor samples.ConclusionWe have demonstrated the utility of the application of integrated analysis using high resolution CGH and whole genome transcript analysis for detecting driver genes in IDC. The high resolution platform allowed a refined demarcation of CNAs and gene expression profiling provided a mechanism to detect genes directly impacted by the CNA. This is the first report of LOH integrated with gene expression in IDC using a high resolution platform.

Project description:Introduction: A major challenge in the interpretation of genomic profiling data generated from breast cancer samples is the identification of driver genes as distinct from bystander genes which do not impact tumorigenesis. One way to assess the relative importance of alterations in the transcriptome profile is to combine complementary analyses that assess changes in the copy number alterations (CNAs). This integrated analysis permits the identification of genes with altered expression that map within specific chromosomal regions that demonstrate copy number alterations, providing a mechanistic approach to identify the 'driver genes’. Methods: We have performed whole genome analysis of CNAs using the Affymetrix 250K Mapping array on 22 infiltrating ductal carcinoma samples (IDCs). Analysis of transcript expression alterations was performed using the Affymetrix U133 Plus2.0 array on 16 IDC samples. Twelve IDC samples were analyzed using both platforms and the data integrated. We also incorporated data from LOH analysis to identify genes showing loss of expression in LOH regions. Results: Copy number analysis results demarcated smaller boundaries for many previously reported CNAs, and in some cases, the CNAs were defined as more than a single contiguous event. Additionally, we were able to assign driver genes to these commonly reported regions using a rigorous methodology. For example, RAB25 showed a large increased expression in the tumors and mapped to the commonly reported amplification at 1q22. We also identified 5 genes in the 8q24 amplicon and TSEN4 in the 17q25 amplified region. LOH analysis confirmed some previously reported regions, and integration with copy number data determined that the detected LOH were copy neutral events. Finally, we have identified several RXR pathways that demonstrated down-regulation in IDC whose members may represent further targets of therapeutic intervention. Conclusion: We have demonstrated the utility of the application of integrated analysis using high-resolution CGH and whole genome transcript analysis for detecting driver genes in IDC. The high resolution platform allowed a refined demarcation of CNAs, and gene expression profiling provided a mechanism to detect genes directly impacted by the CNA. This is the first report of LOH in IDC using a high resolution platform.

Dataset Information

Molecular analysis of metaplastic breast carcinoma: high EGFR copy number via aneusomy.

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Molecular analysis of metaplastic breast carcinoma: high EGFR copy number via aneusomy.

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