Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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A Supervised Risk Predictor of Breast Cancer Based on Biological Subtypes

ABSTRACT: Purpose: The biological subtypes of breast cancer designated as Luminal A, Luminal B, HER2+/ER-, and Basal-like are clinically important for prognosis and planning treatment strategies. Recognizing that there is a continuum in both the spectrum of breast cancer disease and the risk of survival, we sought to develop a clinical test for the biological subtypes using a supervised risk classier.Methods: Microarray and real-time quantitative RT-PCR (qRT-PCR) data from 189 samples, procured as fresh-frozen and formalin-fixed, paraffin-embedded tissues, were used to statistically select prototypical samples and genes for the biological subtypes of breast cancer. Predictions for biological subtype and risk of recurrence were determined for different stages of disease, treatments, and across analytical platforms. Results: The biological subtype predictions on a large combined microarray test set showed prognostic significance across all patients (1244 subjects; p<0.0001), on node negative patients with no adjuvant systemic therapy (738 subjects; p<0.0001), and on patients treated with endocrine therapy (404 subjects; p=0.001). Analysis of a neoadjuvant chemotherapy study revealed a high pathologic complete response (pCR) rate in HER2+/ER- and Basal-like patients. The subtype and risk predications were also highly significant when using the qRT-PCR assay from archived FFPE breast cancers. Conclusion: Our risk predictor based on distance to biological subtype centroids provides a continuous risk score that applies to all stages of breast cancer given current therapies. The assay can be performed using archived breast tissues and a real-time qRT-PCR assay, thus facilitating application to retrospective cohorts and clinical samples. Keywords: reference x sample Comparison of reference samples against treatment

ORGANISM(S): Homo sapiens

SUBMITTER: Charles Perou

PROVIDER: E-GEOD-10886 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Supervised risk predictor of breast cancer based on intrinsic subtypes.

Parker Joel S JS Mullins Michael M Cheang Maggie C U MC Leung Samuel S Voduc David D Vickery Tammi T Davies Sherri S Fauron Christiane C He Xiaping X Hu Zhiyuan Z Quackenbush John F JF Stijleman Inge J IJ Palazzo Juan J Marron J S JS Nobel Andrew B AB Mardis Elaine E Nielsen Torsten O TO Ellis Matthew J MJ Perou Charles M CM Bernard Philip S PS

Journal of clinical oncology : official journal of the American Society of Clinical Oncology 20090209 8

<h4>Unlabelled</h4>PURPOSE To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression-based "intrinsic" subtypes luminal A, luminal B, HER2-enriched, and basal-like. METHODS A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated ...[more]

PMID: 19204204

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Project description:Metaplastic breast cancers (MBC) are aggressive, chemoresistant tumors characterized by lineage plasticity. To advance understanding of their pathogenesis and relatedness to other breast cancer subtypes, 28 MBCs were compared with common breast cancers using comparative genomic hybridization, transcriptional profiling, and reverse-phase protein arrays and by sequencing for common breast cancer mutations. MBCs showed unique DNA copy number aberrations compared with common breast cancers. PIK3CA mutations were detected in 9 of 19 MBCs (47.4%) versus 80 of 232 hormone receptor-positive cancers (34.5%; P = 0.32), 17 of 75 HER-2-positive samples (22.7%; P = 0.04), 20 of 240 basal-like cancers (8.3%; P < 0.0001), and 0 of 14 claudin-low tumors (P = 0.004). Of 7 phosphatidylinositol 3-kinase/AKT pathway phosphorylation sites, 6 were more highly phosphorylated in MBCs than in other breast tumor subtypes. The majority of MBCs displayed mRNA profiles different from those of the 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-to-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(+)/CD24(-) breast 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. Comparison of reference samples against treatment

Project description:Introduction: In breast cancers, the basal-like subtype has high levels of genomic instability relative to other breast cancer subtypes with many basal-like-specific regions of aberration. There is evidence that this genomic instability extends to smaller scale genomic aberrations as well, as shown by a previously described micro-event in the PTEN gene in the Basal-like SUM149 breast cancer cell line. Methods: We sought to identify if small regions of genomic change exist by using a high density, gene centric Comparative Genomic Hybridizations (CGH) array on both cell lines and primary tumors. A custom Agilent tiling array for CGH (244,000 probes, 200bp tiling resolution) was created to identify small regions of genomic change and was focused on previously identified basal-like-specific, and general cancer genes. Tumor genomic DNA from 94 patients and 2 breast cancer cell lines was labeled and hybridized to these arrays. Aberrations were called using SWITCHdna and the smallest 25% of SWITCHdna-defined genomic segments being called micro-aberrations (<64 contiguous probes, ~ <15kb). Results: Our data showed that primary tumor breast cancer genomes frequently contained areas of small-scale copy number gains and losses, termed micro-aberrations, which are undetectable using lower-density genome-wide platforms. The basal-like subtype exhibited the highest incidence of these events. These micro-aberrations sometimes altered expression of the involved gene as suggested by data from microarray and mRNA-seq studies. We confirmed the presence of the PTEN micro-amplification in SUM149 and by mRNA-seq showed that this resulted in loss of expression of all exons downstream of this event. Micro-aberrations disproportionately affected the 5’ regions of the affected genes, including the promoter region, and a high frequency of micro-aberrations was associated with poor survival outcomes. Conclusion: Using a high probe density, gene-centric aCGH microarray, we present evidence of small-scale genomic aberrations that contribute to gene inactivation, and thus, genomic instability and tumor formation through a mechanism not detected using conventional copy number analyses. reference x sample

Dataset Information

A Supervised Risk Predictor of Breast Cancer Based on Biological Subtypes

Publications

Supervised risk predictor of breast cancer based on intrinsic subtypes.

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