Stephanie Fulmer-Smentek

Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project

Microarray-based expression profiling experiments typically use either a one-color or a two-color design to measure mRNA abundance. The validity of each approach has been amply demonstrated. Here we provide a simultaneous comparison of results from one- and two-color labeling designs, using two independent RNA samples from the Microarray Quality Control (MAQC) project, tested on each of three different microarray platforms. The data were evaluated in terms of reproducibility, specificity, sensitivity and accuracy to determine if the two approaches provide comparable results. For each of the three microarray platforms tested, the results show good agreement with high correlation coefficients and high concordance of differentially expressed gene lists within each platform. Cumulatively, these comparisons indicate that data quality is essentially equivalent between the one- and two-color approaches and strongly suggest that this variable need not be a primary factor in decisions regarding experimental microarray design.

Using RNA sample titrations to assess microarray platform performance and normalization techniques

We have assessed the utility of RNA titration samples for evaluating microarray platform performance and the impact of different normalization methods on the results obtained. As part of the MicroArray Quality Control project, we investigated the performance of five commercial microarray platforms using two independent RNA samples and two titration mixtures of these samples. Focusing on 12,091 genes common across all platforms, we determined the ability of each platform to detect the correct titration response across the samples. Global deviations from the response predicted by the titration ratios were observed. These differences could be explained by variations in relative amounts of messenger RNA as a fraction of total RNA between the two independent samples. Overall, both the qualitative and quantitative correspondence across platforms was high. In summary, titration samples may be regarded as a valuable tool, not only for assessing microarray platform performance and different analysis methods, but also for determining some underlying biological features of the samples.

mRNA and microRNA Expression Profiles of the NCI-60 Integrated with Drug Activities

As part of the Spotlight on Molecular Profiling series, we present here new profiling studies of mRNA and microRNA expression for the 60 cell lines of the National Cancer Institute (NCI) Developmental Therapeutics program (DTP) drug screen (NCI-60) using the 41,000-probe Agilent Whole Human Genome Oligo Microarray and the 15,000-feature Agilent Human microRNA Microarray V2. The expression levels of ∼21,000 genes and 723 human microRNAs were measured. These profiling studies include quadruplicate technical replicates for six and eight cell lines for mRNA and microRNA, respectively, and duplicates for the remaining cell lines. The resulting data sets are freely available and searchable online in our CellMiner database. The result indicates high reproducibility for both platforms and an essential biological similarity across the various cell types. The mRNA and microRNA expression levels were integrated with our previously published 1,429-compound database of anticancer activity obtained from the NCI DTP drug screen. Large blocks of both mRNAs and microRNAs were identified with predominately unidirectional correlations to ∼1,300 drugs, including 121 drugs with known mechanisms of action. The data sets presented here will facilitate the identification of groups of mRNAs, microRNAs, and drugs that potentially affect and interact with one another. Mol Cancer Ther; 9(5); 1080–91. ©2010 AACR.

Abstract 1256: Profiling protein-coding RNA and thousands of large non-coding RNAs from nanogram amounts of total RNA using a single microarray design

Large intergenic non-coding RNAs (lincRNAs) are emerging as key regulators of diverse cellular processes, yet determining the function of individual lincRNAs remains challenging. Recently, more than 8,000 human lincRNAs were annotated and cataloged from more than 4 billion RNA-Seq reads across 24 tissues and cell types by scientists at the Broad Institute of MIT and Harvard. Data from this project indicates that lincRNA expression is highly tissue-specific as compared to protein coding gene expression. As researchers continue to investigate the function of lincRNAs, there is a need for tools that can rapidly and accurately measure the expression of the recently annotated lincRNAs along with mRNA expression. We have previously developed and recently updated the content of the human SurePrint G3 microarrays so that they are comprised of all known protein-coding mRNAs and lincRNAs, to enable systematic profiling and simultaneous detection of coding and non-coding gene expression from a single sample. To demonstrate the utility of the new microarray design we used low nanogram amounts RNA from matched tumor and adjacent normal tissues to produce cyanine-labeled cRNA. The labeled cRNA was applied to the microarrays to detect differences in coding and non-coding gene expression profiles. Using the GeneSpring GX software we are able to identify differentially expressed lincRNAs and protein-coding RNAs in the tumor and normal samples in less than two days. Comparisons of probe signals from technical replicate samples demonstrated high reproducibility with wide dynamic ranges and high sensitivity. Data from the microarrays correlates well with whole transcriptome sequencing of the same matched tumor/normal samples. Using this approach we show that lincRNA expression coincides with key genes known to regulate biological processes involved in cancer progression and this work demonstrates how profiling mRNA and lincRNA from matched tumor and adjacent normal samples can enable researchers to further define the role of lincRNAs in gene regulation. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1256. doi:1538-7445.AM2012-1256

Abstract 4867: Whole transcript expression microarray profiling of normal colon and adenocarcinoma total RNA

Whole transcript expression profiling by microarray analysis is an important tool for understanding biological mechanisms and development, classifying tissue and tumor types, and identifying indicators for diagnosis and prognosis. This analysis measures the alternative splicing of exons from a given RNA transcript leading to the translation of a variety of proteins from a single RNA transcript. To address the need for whole transcriptome expression profiling from low quantities of total RNA, we have developed an exon expression workflow which includes custom and catalog human, mouse, and rat exon microarrays, a whole transcript labeling method, and analysis software. This fast and simple microarray-based method employs a modified linear amplification procedure to generate Cy-labeled cRNA representing the whole transcript. The labeling method, available in the Low Input Quick Amp Labeling WT Kit (LIQA WT), employs a mixture of oligo dT- and random nucleotide-based T7 promoter primers (WT Primer Mix) resulting in high cRNA yields and specific activities from low RNA inputs. The probes on the human, mouse, and rat SurePrint G3 exon microarrays were designed from the high quality content of the public databases, primarily RefSeq and Ensembl. Exon array results are analyzed for gene and exon-level expression using GeneSpring GX 11.5 software. The exon gene expression workflow allowed whole transcript gene expression profile comparisons to be made in fewer than two days. Comparisons of probe signals from technical replicate samples demonstrated high reproducibility with a wide dynamic range and comparable signals across a broad range of input amounts. High correlations were demonstrated in platform comparisons to both qRT-PCR and RNA-Seq. This new workflow was used to detect alternative splicing of exons between cancerous and normal cells resulting in gene and exon expression profiles consistent with the current literature. These results demonstrate the value of the new exon expression workflow in identifying known exons, alternative start and stop sites, mutually exclusive exons, and cassette exons in cancer research. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4867. doi:10.1158/1538-7445.AM2011-4867

Abstract 3051: mRNA and microRNA expression profiles integrated with drug sensitivities of the NCI-60 human cancer cell lines

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC We present here new NCI-60 profiling studies of mRNA and miRNA expression using the 41,000-probe Agilent Whole Human Genome Oligo Microarray and the 15,000-feature Agilent Human miRNA Microarray V2. Expression levels were determined for ∼21,000 genes and 723 human miRNAs. The resulting data sets are freely available and searchable online at http://discover.nci.nih.gov in our CellMiner relational database package. The profiling included technical replicates, with six and eight cell lines assayed in quadruplicate for mRNA and miRNA, respectively. The remaining cell lines were assayed in duplicate. Our analysis indicates high reproducibility for both platforms and an essential biological similarity across the various cell types. The expression levels were integrated with our previously published 1,429-compound database of anticancer activity in the NCI screen. Large blocks of both mRNAs (∼2000) and miRNAs (∼200) with unidirectional correlation to ∼1300 drugs including 121 drugs with known mechanisms of action were identified. The data sets presented here will facilitate recognition of the groups of mRNAs, miRNAs and drugs that potentially affect and interact with one another. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 3051.

Abstract 4955: Advances in gene expression microarray profiling from small amounts of adenocarcinoma and normal total RNA samples

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC Gene expression profiling by microarray analysis provides an important avenue for understanding biological mechanisms, classifying tissue and tumor types, and identifying signs for diagnosis and prognosis. To address the need for high sensitivity gene expression profiling of low quantities of total RNA, we have developed a modified linear amplification procedure that generates quantities of Cy-labeled cRNA suitable for oligonucleotide microarray experiments from total RNA input amounts as low as 10 nanograms. This new procedure, available in the new Low Input Quick Amp Labeling Kit, employs the AffinityScript Reverse Transcriptase, a mutant MMLV-RT that binds primer-template complexes with 10-fold higher efficiency than wild type MMLV-RT, resulting in increased cDNA yields and improved sensitivity from smaller sample inputs. The protocol uses a single round of IVT amplification without purification of the cDNA product resulting in labeled cRNA in less than one day, enabling gene expression profile comparisons in less than two days. Comparisons of probe signals from technical replicate samples demonstrate high reproducibility with wide dynamic ranges, and generally comparable signals across a broad range of input amounts. This new labeling approach was used to detect differences in gene expression between cancerous and normal cells using new gene expression arrays with updated content resulting in gene expression profiling results consistent with the current literature. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4955.