[Show abstract][Hide abstract] ABSTRACT: With expanding biomarker discovery efforts and increasing costs of drug development, it is critical to maximize the value of mass-limited clinical samples. The main limitation of available methods is the inability to isolate and analyze, from a single sample, molecules requiring incompatible extraction methods. Thus, we developed a novel semiautomated method for tissue processing and tissue milling and division (TMAD).
We used a SilverHawk atherectomy catheter to collect atherosclerotic plaques from patients requiring peripheral atherectomy. Tissue preservation by flash freezing was compared with immersion in RNAlater®, and tissue grinding by traditional mortar and pestle was compared with TMAD. Comparators were protein, RNA, and lipid yield and quality. Reproducibility of analyte yield from aliquots of the same tissue sample processed by TMAD was also measured.
The quantity and quality of biomarkers extracted from tissue prepared by TMAD was at least as good as that extracted from tissue stored and prepared by traditional means. TMAD enabled parallel analysis of gene expression (quantitative reverse-transcription PCR, microarray), protein composition (ELISA), and lipid content (biochemical assay) from as little as 20 mg of tissue. The mean correlation was r = 0.97 in molecular composition (RNA, protein, or lipid) between aliquots of individual samples generated by TMAD. We also demonstrated that it is feasible to use TMAD in a large-scale clinical study setting.
The TMAD methodology described here enables semiautomated, high-throughput sampling of small amounts of heterogeneous tissue specimens by multiple analytical techniques with generally improved quality of recovered biomolecules.
[Show abstract][Hide abstract] ABSTRACT: Genome-wide gene expression profiling of whole blood is an attractive method for discovery of biomarkers due to its non-invasiveness, simple clinical site processing and rich biological content. Except for a few successes, this technology has not yet matured enough to reach its full potential of identifying biomarkers useful for clinical prognostic and diagnostic applications or in monitoring patient response to therapeutic intervention. A variety of technical problems have hampered efforts to utilize this technology for identification of biomarkers. One significant hurdle has been the high and variable concentrations of globin transcripts in whole blood total RNA potentially resulting in non-specific probe binding and high background. In this study, we investigated and quantified the power of three whole blood profiling approaches to detect meaningful biological expression patterns.
To compare and quantify the impact of different mitigation technologies, we used a globin transcript spike-in strategy to synthetically generate a globin-induced signature and then mitigate it with the three different technologies. Biological differences, in globin transcript spiked samples, were modeled by supplementing with either 1% of liver or 1% brain total RNA. In order to demonstrate the biological utility of a robust globin artifact mitigation strategy in biomarker discovery, we treated whole blood ex vivo with suberoylanilide hydroxamic acid (SAHA) and compared the overlap between the obtained signatures and signatures of a known biomarker derived from SAHA-treated cell lines and PBMCs of SAHA-treated patients.
We found cDNA hybridization targets detect at least 20 times more specific differentially expressed signatures (2597) between 1% liver and 1% brain in globin-supplemented samples than the PNA (117) or no treatment (97) method at FDR = 10% and p-value < 3x10-3. In addition, we found that the ex vivo derived gene expression profile was highly concordant with that of the previously identified SAHA pharmacodynamic biomarkers.
We conclude that an amplification method for gene expression profiling employing cDNA targets effectively mitigates the negative impact on data of abundant globin transcripts and greatly improves the ability to identify relevant gene expression based pharmacodynamic biomarkers from whole blood.
Full-text · Article · Sep 2010 · Journal of Translational Medicine
[Show abstract][Hide abstract] ABSTRACT: mRNA profiling has become an important tool for developing and validating prognostic assays predictive of disease treatment response and outcome. Archives of annotated formalin-fixed paraffin-embedded tissues (FFPET) are available as a potential source for retrospective studies. Methods are needed to profile these FFPET samples that are linked to clinical outcomes to generate hypotheses that could lead to classifiers for clinical applications.
We developed a two-color microarray-based profiling platform by optimizing target amplification, experimental design, quality control, and microarray content and applied it to the profiling of FFPET samples. We profiled a set of 50 fresh frozen (FF) breast cancer samples and assigned class labels according to the signature and method by van 't Veer et al 1 and then profiled 50 matched FFPET samples to test how well the FFPET data predicted the class labels. We also compared the sorting power of classifiers derived from FFPET sample data with classifiers derived from data from matched FF samples.
When a classifier developed with matched FF samples was applied to FFPET data to assign samples to either "good" or "poor" outcome class labels, the classifier was able to assign the FFPET samples to the correct class label with an average error rate = 12% to 16%, respectively, with an Odds Ratio = 36.4 to 60.4, respectively. A classifier derived from FFPET data was able to predict the class label in FFPET samples (leave-one-out cross validation) with an error rate of approximately 14% (p-value = 3.7 x 10(-7)). When applied to the matched FF samples, the FFPET-derived classifier was able to assign FF samples to the correct class labels with 96% accuracy. The single misclassification was attributed to poor sample quality, as measured by qPCR on total RNA, which emphasizes the need for sample quality control before profiling.
We have optimized a platform for expression analyses and have shown that our profiling platform is able to accurately sort FFPET samples into class labels derived from FF classifiers. Furthermore, using this platform, a classifier derived from FFPET samples can reliably provide the same sorting power as a classifier derived from matched FF samples. We anticipate that these techniques could be used to generate hypotheses from archives of FFPET samples, and thus may lead to prognostic and predictive classifiers that could be used, for example, to segregate patients for clinical trial enrollment or to guide patient treatment.
Full-text · Article · Aug 2009 · Journal of Translational Medicine
[Show abstract][Hide abstract] ABSTRACT: Powerful new approaches to study molecular variation in distinct neuronal populations have recently been developed enabling a more precise investigation of the control of neural circuits involved in complex behaviors such as wake and sleep. We applied laser capture microdissection (LCM) to isolate precise brain nuclei from rat CNS at opposing circadian time points associated with wake and sleep. Discrete anatomical and temporal analysis was performed to examine the extent of variation in the transcriptional control associated with both identifiable anatomical nuclei and with light/dark cycle. Precise isolation of specific brain nuclei regulating sleep and arousal, including the LC, SCN, TMN, VTA, and VLPO, demonstrated robust changes in gene expression. Many of these differences were not observed in previous studies where whole brain lysates or gross dissections were used to probe for changes in gene expression. The robust and differential profiles of genomic data obtained from the approaches used herein underscore the requirement for careful anatomical refinement in CNS gene expression studies designed to understand genomic control within behaviorally-linked, but functionally isolated brain nuclei.
[Show abstract][Hide abstract] ABSTRACT: Blood-based biomarker discovery with gene expression profiling has been hampered by interference from endogenous, highly abundant alpha- and beta-globin transcripts. We describe a means to quantify the interference of globin transcripts on profiling and the effectiveness of globin transcript mitigation by (a) defining and characterizing globin interference, (b) reproducing globin interference with synthetic transcripts, and (c) using ROC curves to measure sensitivity and specificity for a protocol for removing alpha- and beta-globin transcripts.
We collected blood at 2 sites and extracted total RNA in PreAnalytiX PAXgene tubes. As a reference for characterizing interference, we supplemented aliquots of total RNA with synthesized globin transcripts and total RNA from human brain. Selected aliquots were processed with Ambion GLOBINclear to remove globin transcripts. All aliquots were labeled and hybridized to Agilent DNA microarrays by means of pooling schemes designed to quantify the mitigation of globin interference and to titrate gene expression signatures. Quantitative reverse transcription-PCR data were generated for comparison with microarray results.
Our supplementation and pooling strategy for comparing the microarray data among samples demonstrated that mitigation could reduce an interference signature of >1000 genes to approximately 200. Analysis of samples of endogenous globin transcripts supplemented with brain RNA indicated that results obtained with the GLOBINclear treatment approach those of peripheral blood mononuclear cell preparations.
We confirmed that both the absolute concentrations of globin transcripts and differences in transcript concentrations within a sample set are factors that cause globin interference (Genes Immun 2005;6:588-95). The methods and transcripts we have developed may be useful for quantitatively characterizing globin mRNA interference and its mitigation.
[Show abstract][Hide abstract] ABSTRACT: A data anomaly was observed that affected the uniformity and reproducibility of fluorescent signal across DNA microarrays. Results from experimental sets designed to identify potential causes (from microarray production to array scanning) indicated that the anomaly was linked to a batch process; further work allowed us to localize the effect to the posthybridization array stringency washes. Ozone levels were monitored and highly correlated with the batch effect. Controlled exposures of microarrays to ozone confirmed this factor as the root cause, and we present data that show susceptibility of a class of cyanine dyes (e.g., Cy5, Alexa 647) to ozone levels as low as 5-10 ppb for periods as short as 10-30 s. Other cyanine dyes (e.g., Cy3, Alexa 555) were not significantly affected until higher ozone levels (> 100 ppb). To address this environmental effect, laboratory ozone levels should be kept below 2 ppb (e.g., with filters in HVAC) to achieve high quality microarray data.
Full-text · Article · Oct 2003 · Analytical Chemistry
[Show abstract][Hide abstract] ABSTRACT: The translation elongation machinery in fungi differs from other eukaryotes in its dependence upon eukaryotic elongation factor 3 (eEF3). eEF3 is essential in vivo and required for each cycle of the translation elongation process in vitro. Models predict eEF3 affects the delivery of cognate aminoacyl-tRNA, a function performed by eEF1A, by removing deacylated tRNA from the ribosomal Exit site. To dissect eEF3 function and its link to the A-site activities of eEF1A, we have identified a temperature-sensitive allele of the YEF3 gene. The F650S substitution, located between the two ATP binding cassettes, reduces both ribosome-dependent and intrinsic ATPase activities. In vivo this mutation increases sensitivity to aminoglycosidic drugs, causes a 50% reduction of total protein synthesis at permissive temperatures, slows run-off of polyribosomes, and reduces binding to eEF1A. Reciprocally, excess eEF3 confers synthetic slow growth, increased drug sensitivity, and reduced translation in an allele specific fashion with an E122K mutation in the GTP binding domain of eEF1A. In addition, this mutant form of eEF1A shows reduced binding of eEF3. Thus, optimal in vivo interactions between eEF3 and eEF1A are critical for protein synthesis.
Preview · Article · Mar 2003 · Journal of Biological Chemistry
[Show abstract][Hide abstract] ABSTRACT: A more accurate means of prognostication in breast cancer will improve the selection of patients for adjuvant systemic therapy.
Using microarray analysis to evaluate our previously established 70-gene prognosis profile, we classified a series of 295 consecutive patients with primary breast carcinomas as having a gene-expression signature associated with either a poor prognosis or a good prognosis. All patients had stage I or II breast cancer and were younger than 53 years old; 151 had lymph-node-negative disease, and 144 had lymph-node-positive disease. We evaluated the predictive power of the prognosis profile using univariable and multivariable statistical analyses.
Among the 295 patients, 180 had a poor-prognosis signature and 115 had a good-prognosis signature, and the mean (+/-SE) overall 10-year survival rates were 54.6+/-4.4 percent and 94.5+/-2.6 percent, respectively. At 10 years, the probability of remaining free of distant metastases was 50.6+/-4.5 percent in the group with a poor-prognosis signature and 85.2+/-4.3 percent in the group with a good-prognosis signature. The estimated hazard ratio for distant metastases in the group with a poor-prognosis signature, as compared with the group with the good-prognosis signature, was 5.1 (95 percent confidence interval, 2.9 to 9.0; P<0.001). This ratio remained significant when the groups were analyzed according to lymph-node status. Multivariable Cox regression analysis showed that the prognosis profile was a strong independent factor in predicting disease outcome.
The gene-expression profile we studied is a more powerful predictor of the outcome of disease in young patients with breast cancer than standard systems based on clinical and histologic criteria.
Full-text · Article · Dec 2002 · New England Journal of Medicine
[Show abstract][Hide abstract] ABSTRACT: To identify genes that are differentially over-expressed in Small Cell Lung Carcinoma (SCLC) we have used a combination of suppression subtractive hybridization and cDNA microarray to analyse the expression profiles of 2400 cDNAs clones. Genes that are over-expressed in SCLC were identified using 32 pairs of fluorescence-labeled cDNA samples representing various lung tumors and normal tissues. This comprehensive approach has resulted in the identification of 209 genes that are differentially over-expressed in SCLC. Quantitative real-time PCR was used to further validate the expression of 43 genes in SCLC tumors and various normal tissues. Discussed in this report are nine genes, which showed the most promising SCLC tumor to normal tissue differential expression profiles, including seven known and two novel genes. The large number of differentially expressed genes identified from this analysis and the characterization of these genes will provide valuable information in better understanding the biology of SCLC and help us in developing these gene products as potential targets for diagnostic as well as therapeutic usage.
[Show abstract][Hide abstract] ABSTRACT: Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70-80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases ('poor prognosis' signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.
[Show abstract][Hide abstract] ABSTRACT: Signal transduction pathways with shared components must be insulated from each other to avoid the inappropriate activation of multiple pathways by a single stimulus. Scaffold proteins are thought to contribute to this specificity by binding select substrates.
We have studied the ability of scaffold proteins to influence signaling by the yeast kinase Ste11, a MAPKKK molecule that participates in three distinct MAP kinase pathways: mating, filamentation, and HOG. We used protein fusions to force Ste11 to associate preferentially with a subset of its possible binding partners in vivo, including Ste5, Ste7, and Pbs2. Signaling became confined to a particular pathway when Ste11 was covalently attached to these scaffolds or substrates. This pathway bias was conferred upon both stimulus-activated and constitutively active forms of Ste11. We also used membrane-targeted derivatives of the mating pathway scaffold, Ste5, to show that stimulus-independent signaling initiated by this scaffold remained pathway specific. Finally, we demonstrate that loss of pathway insulation has a negative physiological consequence, as nonspecific activation of both the HOG and mating pathways interfered with proper execution of the mating pathway.
The signaling properties of these kinase fusions support a model in which scaffold proteins dictate substrate choice and promote pathway specificity by presenting preferred substrates in high local concentration. Furthermore, insulation is inherent to scaffold-mediated signaling and does not require that signaling be initiated by pathway-specific stimuli or activator proteins. Our results give insight into the mechanisms and physiological importance of pathway insulation and provide a foundation for the design of customized signaling proteins.
[Show abstract][Hide abstract] ABSTRACT: Starvation for amino acids induces Gcn4p, a transcriptional activator of amino acid biosynthetic genes in Saccharomyces cerevisiae. In an effort to identify all genes regulated by Gcn4p during amino acid starvation, we performed cDNA microarray analysis. Data from 21 pairs of hybridization experiments using two different strains derived from S288c revealed that more than 1,000 genes were induced, and a similar number were repressed, by a factor of 2 or more in response to histidine starvation imposed by 3-aminotriazole (3AT). Profiling of a gcn4Delta strain and a constitutively induced mutant showed that Gcn4p is required for the full induction by 3AT of at least 539 genes, termed Gcn4p targets. Genes in every amino acid biosynthetic pathway except cysteine and genes encoding amino acid precursors, vitamin biosynthetic enzymes, peroxisomal components, mitochondrial carrier proteins, and autophagy proteins were all identified as Gcn4p targets. Unexpectedly, genes involved in amino acid biosynthesis represent only a quarter of the Gcn4p target genes. Gcn4p also activates genes involved in glycogen homeostasis, and mutant analysis showed that Gcn4p suppresses glycogen levels in amino acid-starved cells. Numerous genes encoding protein kinases and transcription factors were identified as targets, suggesting that Gcn4p is a master regulator of gene expression. Interestingly, expression profiles for 3AT and the alkylating agent methyl methanesulfonate (MMS) overlapped extensively, and MMS induced GCN4 translation. Thus, the broad transcriptional response evoked by Gcn4p is produced by diverse stress conditions. Finally, profiling of a gcn4Delta mutant uncovered an alternative induction pathway operating at many Gcn4p target genes in histidine-starved cells.
Full-text · Article · Aug 2001 · Molecular and Cellular Biology
[Show abstract][Hide abstract] ABSTRACT: We describe a flexible system for gene expression profiling using arrays of tens of thousands of oligonucleotides synthesized in situ by an ink-jet printing method employing standard phosphoramidite chemistry. We have characterized the dependence of hybridization specificity and sensitivity on parameters including oligonucleotide length, hybridization stringency, sequence identity, sample abundance, and sample preparation method. We find that 60-mer oligonucleotides reliably detect transcript ratios at one copy per cell in complex biological samples, and that ink-jet arrays are compatible with several different sample amplification and labeling techniques. Furthermore, results using only a single carefully selected oligonucleotide per gene correlate closely with those obtained using complementary DNA (cDNA) arrays. Most of the genes for which measurements differ are members of gene families that can only be distinguished by oligonucleotides. Because different oligonucleotide sequences can be specified for each array, we anticipate that ink-jet oligonucleotide array technology will be useful in a wide variety of DNA microarray applications.
Full-text · Article · May 2001 · Nature Biotechnology
[Show abstract][Hide abstract] ABSTRACT: The most important product of the sequencing of a genome is a complete, accurate catalogue of genes and their products, primarily messenger RNA transcripts and their cognate proteins. Such a catalogue cannot be constructed by computational annotation alone; it requires experimental validation on a genome scale. Using 'exon' and 'tiling' arrays fabricated by ink-jet oligonucleotide synthesis, we devised an experimental approach to validate and refine computational gene predictions and define full-length transcripts on the basis of co-regulated expression of their exons. These methods can provide more accurate gene numbers and allow the detection of mRNA splice variants and identification of the tissue- and disease-specific conditions under which genes are expressed. We apply our technique to chromosome 22q under 69 experimental condition pairs, and to the entire human genome under two experimental conditions. We discuss implications for more comprehensive, consistent and reliable genome annotation, more efficient, full-length complementary DNA cloning strategies and application to complex diseases.
[Show abstract][Hide abstract] ABSTRACT: Expression profiling using DNA microarrays holds great promise for a variety of research applications, including the systematic characterization of genes discovered by sequencing projects. To demonstrate the general usefulness of this approach, we recently obtained expression profiles for nearly 300 Saccharomyces cerevisiae deletion mutants. Approximately 8% of the mutants profiled exhibited chromosome-wide expression biases, leading to spurious correlations among profiles. Competitive hybridization of genomic DNA from the mutant strains and their isogenic parental wild-type strains showed they were aneuploid for whole chromosomes or chromosomal segments. Expression profile data published by several other laboratories also suggest the use of aneuploid strains. In five separate cases, the extra chromosome harboured a close homologue of the deleted gene; in two cases, a clear growth advantage for cells acquiring the extra chromosome was demonstrated. Our results have implications for interpreting whole-genome expression data, particularly from cells known to suffer genomic instability, such as malignant or immortalized cells.
[Show abstract][Hide abstract] ABSTRACT: Ascertaining the impact of uncharacterized perturbations on the cell is a fundamental problem in biology. Here, we describe how a single assay can be used to monitor hundreds of different cellular functions simultaneously. We constructed a reference database or "compendium" of expression profiles corresponding to 300 diverse mutations and chemical treatments in S. cerevisiae, and we show that the cellular pathways affected can be determined by pattern matching, even among very subtle profiles. The utility of this approach is validated by examining profiles caused by deletions of uncharacterized genes: we identify and experimentally confirm that eight uncharacterized open reading frames encode proteins required for sterol metabolism, cell wall function, mitochondrial respiration, or protein synthesis. We also show that the compendium can be used to characterize pharmacological perturbations by identifying a novel target of the commonly used drug dyclonine.
[Show abstract][Hide abstract] ABSTRACT: Genome-wide transcript profiling was used to monitor signal transduction during yeast pheromone response. Genetic manipulations allowed analysis of changes in gene expression underlying pheromone signaling, cell cycle control, and polarized morphogenesis. A two-dimensional hierarchical clustered matrix, covering 383 of the most highly regulated genes, was constructed from 46 diverse experimental conditions. Diagnostic subsets of coexpressed genes reflected signaling activity, cross talk, and overlap of multiple mitogen-activated protein kinase (MAPK) pathways. Analysis of the profiles specified by two different MAPKs-Fus3p and Kss1p-revealed functional overlap of the filamentous growth and mating responses. Global transcript analysis reflects biological responses associated with the activation and perturbation of signal transduction pathways.
[Show abstract][Hide abstract] ABSTRACT: Genome-wide transcript profiling was used to monitor signal transduction during yeast pheromone response. Genetic manipulations
allowed analysis of changes in gene expression underlying pheromone signaling, cell cycle control, and polarized morphogenesis.
A two-dimensional hierarchical clustered matrix, covering 383 of the most highly regulated genes, was constructed from 46
diverse experimental conditions. Diagnostic subsets of coexpressed genes reflected signaling activity, cross talk, and overlap
of multiple mitogen-activated protein kinase (MAPK) pathways. Analysis of the profiles specified by two different MAPKs—Fus3p
and Kss1p—revealed functional overlap of the filamentous growth and mating responses. Global transcript analysis reflects
biological responses associated with the activation and perturbation of signal transduction pathways.