Biomedical subjects

Federico M Goodsaid

Publications and source records attributed to Federico M Goodsaid.

9 recordsLinked to original sources

PubMed2006

Evaluation of DNA microarray results with quantitative gene expression platforms.

We have evaluated the performance characteristics of three quantitative gene expression technologies and correlated their expression measurements to those of five commercial microarray platforms, based on the MicroArray Quality Control (MAQC) data set. The limit of detection, assay range, precision, accuracy and fold-change correlations were assessed for 997 TaqMan Gene Expression Assays, 205 Standardized RT (Sta)RT-PCR assays and 244 QuantiGene assays. TaqMan is a registered trademark of Roche Molecular Systems, Inc. We observed high correlation between quantitative gene expression values and microarray platform results and found few discordant measurements among all platforms. The main cause of variability was differences in probe sequence and thus target location. A second source of variability was the limited and variable sensitivity of the different microarray platforms for detecting weakly expressed genes, which affected interplatform and intersite reproducibility of differentially expressed genes. From this analysis, we conclude that the MAQC microarray data set has been validated by alternative quantitative gene expression platforms thus supporting the use of microarray platforms for the quantitative characterization of gene expression.

Equipment Design↗

PubMed2006

Rat toxicogenomic study reveals analytical consistency across microarray platforms.

To validate and extend the findings of the MicroArray Quality Control (MAQC) project, a biologically relevant toxicogenomics data set was generated using 36 RNA samples from rats treated with three chemicals (aristolochic acid, riddelliine and comfrey) and each sample was hybridized to four microarray platforms. The MAQC project assessed concordance in intersite and cross-platform comparisons and the impact of gene selection methods on the reproducibility of profiling data in terms of differentially expressed genes using distinct reference RNA samples. The real-world toxicogenomic data set reported here showed high concordance in intersite and cross-platform comparisons. Further, gene lists generated by fold-change ranking were more reproducible than those obtained by t-test P value or Significance Analysis of Microarrays. Finally, gene lists generated by fold-change ranking with a nonstringent P-value cutoff showed increased consistency in Gene Ontology terms and pathways, and hence the biological impact of chemical exposure could be reliably deduced from all platforms analyzed.

Animals↗

PubMed2005

Microarray scanner calibration curves: characteristics and implications.

BACKGROUND: Microarray-based measurement of mRNA abundance assumes a linear relationship between the fluorescence intensity and the dye concentration. In reality, however, the calibration curve can be nonlinear. RESULTS: By scanning a microarray scanner calibration slide containing known concentrations of fluorescent dyes under 18 PMT gains, we were able to evaluate the differences in calibration characteristics of Cy5 and Cy3. First, the calibration curve for the same dye under the same PMT gain is nonlinear at both the high and low intensity ends. Second, the degree of nonlinearity of the calibration curve depends on the PMT gain. Third, the two PMTs (for Cy5 and Cy3) behave differently even under the same gain. Fourth, the background intensity for the Cy3 channel is higher than that for the Cy5 channel. The impact of such characteristics on the accuracy and reproducibility of measured mRNA abundance and the calculated ratios was demonstrated. Combined with simulation results, we provided explanations to the existence of ratio underestimation, intensity-dependence of ratio bias, and anti-correlation of ratios in dye-swap replicates. We further demonstrated that although Lowess normalization effectively eliminates the intensity-dependence of ratio bias, the systematic deviation from true ratios largely remained. A method of calculating ratios based on concentrations estimated from the calibration curves was proposed for correcting ratio bias. CONCLUSION: It is preferable to scan microarray slides at fixed, optimal gain settings under which the linearity between concentration and intensity is maximized. Although normalization methods improve reproducibility of microarray measurements, they appear less effective in improving accuracy.

Calibration↗

PubMed2005

Cross-platform comparability of microarray technology: intra-platform consistency and appropriate data analysis procedures are essential.

BACKGROUND: The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630-631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676-5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology. RESULTS: We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall. CONCLUSION: Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control.

Databases, Genetic↗

PubMed2004

Quantitative gene expression analysis in a nonhuman primate model of antibiotic-induced nephrotoxicity.

Gene expression patterns using microarrays have been described for rodent models of nephrotoxicity. To determine if significant gene expression changes previously identified have application across multiple species, we studied quantitative gene expression changes in the kidneys of female cynomolgus monkeys after exposure to two nephrotoxicants. Animals were dosed with the aminoglycoside gentamicin (10 mg/kg), the experimental oligosaccharide antibiotic everninomicin (30 or 60 mg/kg), or a combination of gentamicin (10 mg/kg) and everninomicin (30 mg/kg) for 7 days. Monkeys receiving these drugs in combination developed renal lesions as early as Day 1. By Day 7, monkeys dosed with 60 mg/kg everninomicin alone also developed renal lesions, while the group exposed to both compounds had more extensive renal damage. The modulation of several genes previously reported to be associated with nephrotoxicity in rodent models was confirmed using quantitative real-time PCR. Among these, waf-1, matrix metalloproteinase-9, and vimentin exhibited changes consistent with the definition of a genomic indicator of toxicity. In addition, we identified three early gene biomarkers that may be predictive of drug-induced nephrotoxicity: clusterin, osteopontin, and hepatitis A virus cellular receptor-1. Logistic regression demonstrated a high degree of correlation between changes in gene expression and the probability of the development of histopathologic lesions. These results are the first confirming rodent gene expression changes associated with nephrotoxicity in a nonhuman primate model and provide preliminary evidence for identifying early gene expression changes predicting the onset of drug-induced renal tubular damage in cynomolgus monkeys.

Aminoglycosides↗

PubMed2004

Quantitative PCR deconstruction of discrepancies between results reported by different hybridization platforms.

Differences in hybridization platforms used in gene array analysis experiments can lead to significant differences in hybridization results. In this study we used quantitative reverse transcription-polymerase chain reaction (qRT-PCR) to investigate discrepant results between the National Institute of Environmental Health Sciences cDNA and Affymetrix oligo platforms used to evaluate hepatic gene expression changes in rats exposed to methapyrilene. Caldesmon cDNA platform hybridization results showed decreases in gene expression levels for the high-dose methapyrilene 7-day pooled samples compared with their controls. By contrast, the Affymetrix oligonucleotide platform showed increases in expression levels for these samples. Quantitative gene expression measurements provide an explanation for the discrepancies observed for these samples. In the case of caldesmon, there is a 74-base sequence in the cDNA clone that is absent in the Affymetrix sequence. The amplicon based on the cDNA clone shows > 100-fold suppression relative to the day 7 high-dose methapyrilene-pooled control. These data demonstrate the importance of using a "gold standard," such as qRT-PCR to confirm key hybridization results as well as to understand the sources of discrepancies resulting from different hybridization platforms.

Animals↗

PubMed2003

Assessment of temporal biochemical and gene transcription changes in rat liver cytochrome P450: utility of real-time quantitative RT-PCR.

PURPOSE: A conventional approach to assess cytochrome P450 (CYP) induction in preclinical animal models involves daily dosing for a least a week followed by Western blot and/or enzyme activity analysis. To evaluate the potential benefit of a third more specific and sensitive assay, real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), with the objective of reducing the duration of the conventional 1-week study, we simultaneously assessed gene expression by qRT-PCR along with Western blots and enzyme activity assays as a time course in an in vivo model. METHODS: Rats were dosed daily for 8 days with model inducers of CYP1A, CYP2B, CYP3A, or CYP4A. Liver P450 levels were measured after 0.5, 1, 2, 4, and 8 days of dosing by qRT-PCR, Western blot, and enzyme activity. RESULTS: CYP1A, CYP3A, and CYP4A genes were maximally induced very rapidly (0.5-1 day), whereas the CYP2B gene was maximally induced after a lag time of 4 days. In all cases, fold changes in induction detected by qRT-PCR were greater than fold changes in protein levels and enzyme activities. CONCLUSIONS: Maximal persistent and larger fold changes observed by qRT-PCR either preceded or occurred simultaneously with maximal sustained fold changes in protein levels as measured by Western blots and enzyme activity assays. Our data show that qRT-PCR provides increased sensitivity and specificity over conventional assays and may be key information for reliable assessment of drug-related changes in CYP induction during the transition from discovery to toxicology studies.

Animals↗

PubMed2003

Genomic biomarkers of toxicity.

The difference between measuring changes in gene expression levels in a toxicogenomics study and actually achieving reduced drug development costs is in the knowledge of which gene expression changes are predictive of toxicity. Whether the cost savings are in high-throughput screening, in discovery or in preclinical, testing, the application of genomics, proteomics or metabonomics will require a clear understanding of what these methods actually measure. Results of studies published over the past year have set valuable benchmarks for genomic studies, transforming this technology into a source of candidates for validation as predictive biomarkers of toxicity. This review will summarize some of the publications that have achieved this transformation, and the steps that are still needed for the implementation of predictive tests derived from these genomic biomarkers of toxicity.

Carrier Proteins↗

PubMedDate not supplied

Identification and measurement of genomic biomarkers of nephrotoxicity.

An accelerated pace for drug discovery and development requires the application of measurements of novel parameters for drug-induced toxicity. Genomic biomarkers can contribute to this process as indicators or predictors of toxicity. Transcript levels for genes such as the kidney injury molecule have been identified and evaluated as genomic biomarkers of nephrotoxicity.

Animals↗