We are analyzing https://link.springer.com/article/10.1186/1471-2164-7-127.

Title:
Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms | BMC Genomics
Description:
Background Gene expression profiling has been used to define molecular phenotypes of complex diseases such as breast cancer. The luminal A and basal-like subtypes have been repeatedly identified and validated as the two main subtypes out of a total of five molecular subtypes of breast cancer. These two are associated with distinctly different gene expression patterns and more importantly, a significant difference in clinical outcome. To further validate and more thoroughly characterize these two subtypes at the molecular level in tumors at an early stage, we report a gene expression profiling study using three different DNA microarray platforms. Results Expression data from 20 tumor biopsies of early stage breast carcinomas were generated on three different DNA microarray platforms; Applied Biosystems Human Genome Survey Microarrays, Stanford cDNA Microarrays and Agilent
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Keywords {🔍}

genes, expression, gene, subtypes, breast, cancer, microarray, pubmed, tumors, tumor, analysis, luminal, article, basallike, google, scholar, platforms, samples, cas, data, human, identified, molecular, applied, set, sample, correlation, biosystems, file, signature, subtype, figure, performed, taqman, genome, analyzed, microarrays, cdna, array, distinct, protein, additional, study, pathway, cell, agilent, pathways, clustering, central, carcinomas,

Topics {✒️}

genome-wide gene-expression profiles taqman real-time pcr real-time pcr reactions real-time pcr validation expression-based prognostic assay performed real-time pcr red-black-green color scale rikshospitalet-radiumhospitalet medical center celera-assembled human genome real-time pcr gene expression-based classification tetra-span membrane protein fatty acid/lipid metabolism rna interference-mediated silencing print-tip loess normalization article download pdf digoxigenin-utp labeled crna distinct molecular mechanisms distinct biological entities full size image breast-cancer cells purified clinically relevant subtypes c-myc-responsive gene affymetrix probe sets tailor-made therapeutic strategies full size table ten-fold cross validation applied biosystems microarrays p21-mediated signaling pathway molecular basis underlying cell cycle-signaling pathways f-box proteins skp2 molecular mechanisms descriptive human genome microarrays average expression profile biological pathways underlying related subjects gene expression profiling protein classification system norwegian research council full access hierarchical clustering analysis multiple platform data including quantitative pcr 60-mer oligo microarray privacy choices/manage cookies distinct expression patterns cdna microarray analysis messageamp amplification kit human breast cancer

Schema {🗺️}

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         headline:Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms
         description:Gene expression profiling has been used to define molecular phenotypes of complex diseases such as breast cancer. The luminal A and basal-like subtypes have been repeatedly identified and validated as the two main subtypes out of a total of five molecular subtypes of breast cancer. These two are associated with distinctly different gene expression patterns and more importantly, a significant difference in clinical outcome. To further validate and more thoroughly characterize these two subtypes at the molecular level in tumors at an early stage, we report a gene expression profiling study using three different DNA microarray platforms. Expression data from 20 tumor biopsies of early stage breast carcinomas were generated on three different DNA microarray platforms; Applied Biosystems Human Genome Survey Microarrays, Stanford cDNA Microarrays and Agilent's Whole Human Genome Oligo Microarrays, and the resulting gene expression patterns were analyzed. Both unsupervised and supervised analyses identified the different clinically relevant subtypes of breast tumours, and the results were consistent across all three platforms. Gene classification and biological pathway analyses of the genes differentially expressed between the two main subtypes revealed different molecular mechanisms descriptive of the two expression-based subtypes: Signature genes of the luminal A subtype were over-represented by genes involved in fatty acid metabolism and steroid hormone-mediated signaling pathways, in particular estrogen receptor signaling, while signature genes of the basal-like subtype were over-represented by genes involved in cell proliferation and differentiation, p21-mediated pathway, and G1-S checkpoint of cell cycle-signaling pathways. A minimal set of 54 genes that best discriminated the two subtypes was identified using the combined data sets generated from the three different array platforms. These predictor genes were further verified by TaqMan® Gene Expression assays. We have identified and validated the two main previously defined clinically relevant subtypes, luminal A and basal-like, in a small set of early stage breast carcinomas. Signature genes characterizing these two subtypes revealed that distinct molecular mechanisms might have been pre-programmed at an early stage in different subtypes of the disease. Our results provide further evidence that these breast tumor subtypes represent biologically distinct disease entities and may require different therapeutic strategies. Finally, validated by multiple gene expression platforms, including quantitative PCR, the set of 54 predictor genes identified in this study may define potential prognostic molecular markers for breast cancer.
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            Gene Expression Assay
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            Microbial Genetics and Genomics
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         Microarray Platform
         Gene Expression Assay
         Predictor Gene
         Intrinsic Gene
         Distinct Disease Entity
         Life Sciences
         general
         Microarrays
         Proteomics
         Animal Genetics and Genomics
         Microbial Genetics and Genomics
         Plant Genetics and Genomics
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      name:Department of Genetics, Institute for Cancer Research, Rikshospitalet-Radiumhospitalet Medical Center, Oslo, Norway
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