ABSTRACT
CONTEXT: Correct diagnosis of the tissue origin of a metastatic cancer is the first step in disease management, but it is frequently difficult using standard pathologic methods. Microarray-based gene expression profiling has shown great promise as a new tool to address this challenge. OBJECTIVE: Adoption of microarray technologies in the clinic remains limited. We aimed to bridge this technological gap by developing a real-time quantitative polymerase chain reaction (RT-PCR) assay. DESIGN: We constructed a microarray database of 466 frozen and 112 formalin-fixed, paraffin-embedded (FFPE) samples of both primary and metastatic tumors, measuring expression of 22,000 genes. From the microarray database, we used a genetic algorithm to search for gene combinations optimal for multitumor classification. A 92-gene RT-PCR assay was then designed and used to generate a database for 481 frozen and 119 FFPE tumor samples. RESULTS: The microarray-based K-nearest neighbor classifier demonstrated 84% accuracy in classifying 39 tumor types via cross-validation and 82% accuracy in predicting 112 independent FFPE samples. We successfully translated the microarray database to the RT-PCR platform, which allowed an overall success rate of 87% in classifying 32 different tumor classes in the validation set of 119 FFPE tumor samples. CONCLUSIONS: The RT-PCR-based expression assay involving 92 genes represents a powerful tool for accurately and objectively identifying the site of origin for metastatic tumors, especially in the cases of cancer of unknown primary. The assay uses RT-PCR and routine FFPE samples, making it suitable for rapid clinical adoption.
Subject(s)
Gene Expression Profiling , Neoplasm Metastasis/diagnosis , Neoplasm Metastasis/genetics , Neoplasms , Oligonucleotide Array Sequence Analysis/methods , Reverse Transcriptase Polymerase Chain Reaction/methods , Algorithms , Databases, Factual , Female , Humans , Male , Neoplasms/classification , Neoplasms/diagnosis , Neoplasms/geneticsABSTRACT
Human embryonic stem (hES) cells hold promise for generating an unlimited supply of cells for replacement therapies. To characterize hES cells at the molecular level, we obtained 148,453 expressed sequence tags (ESTs) from undifferentiated hES cells and three differentiated derivative subpopulations. Over 32,000 different transcripts expressed in hES cells were identified, of which more than 16,000 do not match closely any gene in the UniGene public database. Queries to this EST database revealed 532 significantly upregulated and 140 significantly downregulated genes in undifferentiated hES cells. These data highlight changes in the transcriptional network that occur when hES cells differentiate. Among the differentially regulated genes are several components of signaling pathways and transcriptional regulators that likely play key roles in hES cell growth and differentiation. The genomic data presented here may facilitate the derivation of clinically useful cell types from hES cells.
Subject(s)
Cell Differentiation/genetics , Expressed Sequence Tags , Gene Expression Profiling , Signal Transduction/genetics , Stem Cells/metabolism , Antigens, CD/genetics , Antigens, CD/physiology , Cell Differentiation/drug effects , Cell Differentiation/physiology , Cell Division/drug effects , Cell Division/genetics , Cell Division/physiology , Cell Line , Cytokine Receptor gp130 , Dimethyl Sulfoxide/pharmacology , Down-Regulation/drug effects , Down-Regulation/genetics , Embryo, Mammalian/cytology , Fibroblast Growth Factors/genetics , Fibroblast Growth Factors/physiology , Gene Expression/drug effects , Gene Library , Growth Substances/pharmacology , Humans , Intercellular Signaling Peptides and Proteins/genetics , Intercellular Signaling Peptides and Proteins/physiology , Interleukin-6 , Leukemia Inhibitory Factor , Membrane Glycoproteins/genetics , Membrane Glycoproteins/physiology , Nodal Protein , Proteins/genetics , Proteins/physiology , Proto-Oncogene Proteins/genetics , Proto-Oncogene Proteins/physiology , RNA/genetics , RNA/isolation & purification , Receptors, Fibroblast Growth Factor/genetics , Receptors, Fibroblast Growth Factor/physiology , Receptors, G-Protein-Coupled/genetics , Receptors, G-Protein-Coupled/physiology , Reverse Transcriptase Polymerase Chain Reaction , Sequence Analysis, DNA , Signal Transduction/physiology , Stem Cells/cytology , Transcription Factors/genetics , Transcription Factors/physiology , Transcription, Genetic/genetics , Transforming Growth Factor beta/genetics , Transforming Growth Factor beta/physiology , Tretinoin/pharmacology , Up-Regulation/drug effects , Up-Regulation/genetics , Wnt ProteinsABSTRACT
Cone arrestin (CAR) is a novel member of the arrestin superfamily expressed in retinal cone photoreceptors and the pineal gland. To understand the regulatory mechanisms controlling its cone- and pineal-specific expression, and to facilitate further functional studies using gene knockout approaches, we characterized the genomic organization and the 5'-flanking region of the mouse CAR (mCAR) gene. The mCAR gene is comprised of 17 exons and 16 introns, encoding five alternatively spliced transcripts. A 215-bp proximal promoter fragment containing a TATA box, an Sp1 site and four cone-rod homeobox-binding sites is sufficient to direct expression in cultured retinoblastoma cells and in cone photoreceptors and the pineal gland in transgenic Xenopus laevis.
