Gene expression profiles in hepatocellular carcinoma: not yet there.
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Biomedical subjects
Publications and source records attributed to Elisa Wurmbach.
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DNA microarray analysis has been used to investigate relative changes in the level of gene expression in the CNS, including changes that are associated with disease, injury, psychiatric disorders, drug exposure or withdrawal, and memory formation. We have used oligonucleotide microarrays to identify hypothalamic genes that respond to nutritional manipulation. In addition to commonly used microarray analysis based on criteria such as fold-regulation, we have also found that simply carrying out multiple t tests then sorting by P value constitutes a highly reliable method to detect true regulation, as assessed by real-time polymerase chain reaction (PCR), even for relatively low abundance genes or relatively low magnitude of regulation. Such analyses directly suggested novel mechanisms that mediate effects of nutritional state on neuroendocrine function and are being used to identify regulated gene products that may elucidate the metabolic pathology of obese ob/ob, lean Vgf-/Vgf-, and other models with profound metabolic impairments.
Most neuropharmacological agents and many drugs of abuse modulate the activity of heptahelical G-protein-coupled receptors. Although the effects of these ligands result from changes in cellular signaling, their neurobehavioral activity may not correlate with results of in vitro signal transduction assays. 5-Hydroxytryptamine 2A receptor (5-HT2AR) partial agonists that have similar pharmacological profiles differ in the behavioral responses they elicit. In vitro studies suggest that different agonists acting at the same receptor may establish distinct patterns of signal transduction. Testing this hypothesis in the brain requires a global signal transduction assay that is applicable in vivo. To distinguish the cellular effects of the different 5-HT2AR agonists, we developed an assay for global signal transduction on the basis of high throughput quantification of rapidly modulated transcripts. Study of the responses to agonists in human embryonic kidney 293 cells stably expressing 5-HT2ARs demonstrated that each agonist elicits a distinct transcriptome fingerprint. We therefore studied behavioral and cortical signal transduction responses in wild-type and 5-HT2AR null-mutant mice. The hallucinogenic chemicals (+/-)-2,5-dimethoxy-4-iodoamphetamine (DOI) and lysergic acid diethylamide (LSD) stimulated a head-twitch behavioral response that was not observed with the nonhallucinogenic lisuride hydrogen maleate (LHM) and was absent in receptor null-mutant mice. We also found that DOI, LSD, and LHM each induced distinct transcriptome fingerprints in somatosensory cortex that were absent in 5-HT2AR null-mutants. Moreover, DOI and LSD showed similarities in the transcriptome fingerprints obtained that were not observed with the behaviorally inactive drug LHM. Our results demonstrate that chemicals acting at the 5-HT2AR induce specific cellular response patterns in vivo that are reflected in unique changes in the somatosensory cortex transcriptome.
We describe detailed protocols and results with an integrated platform for studying relative transcript expression, including microarray design and fabrication, analysis and calibration algorithms, and high throughput quantitative real-time PCR. This approach optimizes sensitivity and accuracy while controlling the cost of experiments. A high quality cDNA array was fabricated using a restricted number of carefully selected transcripts with each clone printed in triplicate. This focused array facilitated both repeated measurement and replicate experiments. Following normalization and differential expression analysis, we found that experiments with this array identified differentially expressed transcripts with a high degree of accuracy and with high sensitivity to low levels of differential expression. Using a calibration algorithm improved the accuracy of the array in quantifying the relative level of transcript expression. All differentially expressed transcripts identified by the array were independently tested using high throughput quantitative real-time PCR assays. This approach reliably identified transcripts having as low as 1.3-fold differences in transcript expression between RNA samples from treatment- and control groups and was applicable to highly heterogenous tissue sources such as hypothalamus and cerebral cortex.
We compared the accuracy of microarray measurements obtained with oligonucleotide arrays (GeneChip, Affymetrix) with a laboratory-developed cDNA array by assaying test RNA samples from an experiment using a paradigm known to regulate many genes measured on both arrays. We selected 47 genes represented on both arrays, including both known regulated and unregulated transcripts, and established reference relative expression measurements for these genes in the test RNA samples using quantitative reverse transcriptase real-time PCR (QRTPCR) assays. The validity of the reproducible (average coefficient of variation = 11.8%) QRTPCR measurements were established through application of a new mathematical model. The performance of both array platforms in identifying regulated and non-regulated genes was identical. With either platform, 16 of 17 definitely regulated genes were correctly identified, and no definitely unregulated transcript was falsely identified as regulated. Accuracy of the fold-change measurements obtained with each platform was assessed by determining measurement bias. Both platforms consistently underestimate the relative changes in mRNA expression between experimental and control samples. The bias observed with cDNA arrays was predictable for fold-changes <250-fold by QRTPCR and could be corrected by the calibration function F(c) = F(a(cDNA))(q), where F(a(cDNA)) is the microarray-determined fold-change comparing experimental with control samples, q is the correction factor and F(c) is the calibrated value. The bias observed with the commercial oligonucleotide arrays was less predictable and calibration was unfeasible. Following calibration, fold-change measurements generated by custom cDNA arrays were more accurate than those obtained by commercial oligonucleotide arrays. Our study demonstrates systematic bias of microarray measurements and identifies a calibration function that improves the accuracy of cDNA array data.
Microarray-based genomic techniques allow the simultaneous determination of relative levels of expression of a large number of genes. Studies of the transcriptome in complex neurobiological systems are uniquely demanding due to the heterogeneous nature of these cells. Most brain regions contain a large variety of cell populations that are closely intermingled. The expression of any specific gene may be restricted to a subpopulation of cells, and changes in gene expression may occur in only a small fraction of the cells expressing that transcript. Due to this dilution effect, many genes of interest are expected to have relatively low levels of expression in tissue homogenates. Furthermore, biologically significant differences in expression may result in only small fold-changes. Therefore genomic approaches using brain dissections must be optimized to identify potentially regulated transcripts and differential expression should be confirmed using quantitative assays. We evaluated the effects of increasing tissue complexity on detection of regulated transcripts in focused microarray studies using a mouse cell line, mouse hypothalamus and mouse cortex. Regulated transcripts were confirmed by quantitative real-time PCR. As tissue complexity increased, distinguishing significantly regulated genes from background variation became increasingly more difficult. However, we found that cDNA microarray studies using regional brain dissections and appropriate numbers of replicates could identify genes showing less than 2-fold regulation and that most regulated genes identified fell within this range.
The initial waves of gene induction caused by GnRH in the LbetaT2 gonadotrope cell line have recently been identified using microarrays. We now investigate the relationship of the concentration of GnRH to the level of biosynthesis induced. Using an optimized custom cDNA microarray, we show that a large number of genes are induced in a concentration-dependent fashion. Detailed time course studies of the induction of six induced transcripts using quantitative real-time PCR suggest that the amplitude, but not the temporal pattern, depends on the concentration of GnRH. The early genes appear to show a delay in gene induction, followed by a linear phase of increase. The relationship of rate of synthesis and GnRH concentration was studied by mathematical modeling of the induction of two genes, gly96 and tis11. In both cases, only the rates of increase, but not the lag times, are influenced by the concentration of GnRH exposure. Western blot analyses for c-Jun and Egr1 show that the levels of nuclear protein for these transcription factors also depend on the concentration of GnRH. These studies indicate that, despite the complex signaling network connecting the receptor to the activated genes, the biosynthetic rate of RNA polymerase at induced genes is correlated with the concentration of GnRH at the GnRH receptor.