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Monica Reinholz,
Jeanette Eckel-Passow,
Anderson S Keith,
Yan Asmann,
Michael Zschunke, Ann Oberg,
Ann McCullough,
Amylou Dueck,
Beiyun Chen,
Craig April,
Eliza Wickham-Garcia,
Robert Jenkins,
Julie Cunningham,
Jin Jen,
Edith Perez,
Jian-Bing Fan,
Wilma Lingle
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ABSTRACT: Abstract Background The cDNA-mediated Annealing, extension, Selection and Ligation (DASL) assay has become a suitable gene expression profiling system for degraded RNA from paraffin-embedded tissue. We examined assay characteristics and the performance of the DASL 502-gene Cancer Panelv1 (1.5K) and 24,526-gene panel (24K) platforms at differentiating nine human epidermal growth factor receptor 2- positive (HER2+) and 11 HER2-negative (HER2-) paraffin-embedded breast tumors. Methods Bland-Altman plots and Spearman correlations evaluated intra/inter-panel agreement of normalized expression values. Unequal-variance t-statistics tested for differences in expression levels between HER2 + and HER2 - tumors. Regulatory network analysis was performed using Metacore (GeneGo Inc., St. Joseph, MI). Results Technical replicate correlations ranged between 0.815-0.956 and 0.986-0.997 for the 1.5K and 24K panels, respectively. Inter-panel correlations of expression values for the common 498 genes across the two panels ranged between 0.485-0.573. Inter-panel correlations of expression values of 17 probes with base-pair sequence matches between the 1.5K and 24K panels ranged between 0.652-0.899. In both panels, erythroblastic leukemia viral oncogene homolog 2 (ERBB2) was the most differentially expressed gene between the HER2 + and HER2 - tumors and seven additional genes had p-values < 0.05 and log2 -fold changes > |0.5| in expression between HER2 + and HER2 - tumors: topoisomerase II alpha (TOP2A), cyclin a2 (CCNA2), v-fos fbj murine osteosarcoma viral oncogene homolog (FOS), wingless-type mmtv integration site family, member 5a (WNT5A), growth factor receptor-bound protein 7 (GRB7), cell division cycle 2 (CDC2), and baculoviral iap repeat-containing protein 5 (BIRC5). The top 52 discriminating probes from the 24K panel are enriched with genes belonging to the regulatory networks centered around v-myc avian myelocytomatosis viral oncogene homolog (MYC), tumor protein p53 (TP53), and estrogen receptor α (ESR1). Network analysis with a two-step extension also showed that the eight discriminating genes common to the 1.5K and 24K panels are functionally linked together through MYC, TP53, and ESR1. Conclusions The relative RNA abundance obtained from two highly differing density gene panels are correlated with eight common genes differentiating HER2 + and HER2 - breast tumors. Network analyses demonstrated biological consistency between the 1.5K and 24K gene panels.
BMC Medical Genomics. 01/2010;
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Yan W Asmann,
Eric W Klee,
E Aubrey Thompson,
Edith A Perez,
Sumit Middha, Ann L Oberg,
Terry M Therneau,
David I Smith,
Gregory A Poland,
Eric D Wieben,
Jean-Pierre A Kocher
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ABSTRACT: Massive parallel sequencing has the potential to replace microarrays as the method for transcriptome profiling. Currently there are two protocols: full-length RNA sequencing (RNA-SEQ) and 3'-tag digital gene expression (DGE). In this preliminary effort, we evaluated the 3' DGE approach using two reference RNA samples from the MicroArray Quality Control Consortium (MAQC).
Using Brain RNA sample from multiple runs, we demonstrated that the transcript profiles from 3' DGE were highly reproducible between technical and biological replicates from libraries constructed by the same lab and even by different labs, and between two generations of Illumina's Genome Analyzers. Approximately 65% of all sequence reads mapped to mitochondrial genes, ribosomal RNAs, and canonical transcripts. The expression profiles of brain RNA and universal human reference RNA were compared which demonstrated that DGE was also highly quantitative with excellent correlation of differential expression with quantitative real-time PCR. Furthermore, one lane of 3' DGE sequencing, using the current sequencing chemistry and image processing software, had wider dynamic range for transcriptome profiling and was able to detect lower expressed genes which are normally below the detection threshold of microarrays.
3' tag DGE profiling with massive parallel sequencing achieved high sensitivity and reproducibility for transcriptome profiling. Although it lacks the ability of detecting alternative splicing events compared to RNA-SEQ, it is much more affordable and clearly out-performed microarrays (Affymetrix) in detecting lower abundant transcripts.
BMC Genomics 11/2009; 10:531. · 4.07 Impact Factor
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Aaron L Sarver,
Amy J French,
Pedro M Borralho,
Venugopal Thayanithy, Ann L Oberg,
Kevin A T Silverstein,
Bruce W Morlan,
Shaun M Riska,
Lisa A Boardman,
Julie M Cunningham,
Subbaya Subramanian,
Liang Wang,
Tom C Smyrk,
Cecilia M P Rodrigues,
Stephen N Thibodeau,
Clifford J Steer
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ABSTRACT: Colon cancer arises from the accumulation of multiple genetic and epigenetic alterations to normal colonic tissue. microRNAs (miRNAs) are small, non-coding regulatory RNAs that post-transcriptionally regulate gene expression. Differential miRNA expression in cancer versus normal tissue is a common event and may be pivotal for tumor onset and progression.
To identify miRNAs that are differentially expressed in tumors and tumor subtypes, we carried out highly sensitive expression profiling of 735 miRNAs on samples obtained from a statistically powerful set of tumors (n = 80) and normal colon tissue (n = 28) and validated a subset of this data by qRT-PCR.
Tumor specimens showed highly significant and large fold change differential expression of the levels of 39 miRNAs including miR-135b, miR-96, miR-182, miR-183, miR-1, and miR-133a, relative to normal colon tissue. Significant differences were also seen in 6 miRNAs including miR-31 and miR-592, in the direct comparison of tumors that were deficient or proficient for mismatch repair. Examination of the genomic regions containing differentially expressed miRNAs revealed that they were also differentially methylated in colon cancer at a far greater rate than would be expected by chance. A network of interactions between these miRNAs and genes associated with colon cancer provided evidence for the role of these miRNAs as oncogenes by attenuation of tumor suppressor genes.
Colon tumors show differential expression of miRNAs depending on mismatch repair status. miRNA expression in colon tumors has an epigenetic component and altered expression that may reflect a reversion to regulatory programs characteristic of undifferentiated proliferative developmental states.
BMC Cancer 11/2009; 9:401. · 3.01 Impact Factor
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Julie M Cunningham, Ann L Oberg,
Pedro M Borralho,
Betsy T Kren,
Amy J French,
Liang Wang,
Brian M Bot,
Bruce W Morlan,
Kevin A T Silverstein,
Rod Staggs,
Yan Zeng,
Anne-Francoise Lamblin,
Christopher A Hilker,
Jian-Bing Fan,
Clifford J Steer,
Stephen N Thibodeau
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ABSTRACT: MicroRNAs (miRNAs) are a class of approximately 22 nucleotide long, widely expressed RNA molecules that play important regulatory roles in eukaryotes. To investigate miRNA function, it is essential that methods to quantify their expression levels be available.
We evaluated a new miRNA profiling platform that utilizes Illumina's existing robust DASL chemistry as the basis for the assay. Using total RNA from five colon cancer patients and four cell lines, we evaluated the reproducibility of miRNA expression levels across replicates and with varying amounts of input RNA. The beta test version was comprised of 735 miRNA targets of Illumina's miRNA profiling application.
Reproducibility between sample replicates within a plate was good (Spearman's correlation 0.91 to 0.98) as was the plate-to-plate reproducibility replicates run on different days (Spearman's correlation 0.84 to 0.98). To determine whether quality data could be obtained from a broad range of input RNA, data obtained from amounts ranging from 25 ng to 800 ng were compared to those obtained at 200 ng. No effect across the range of RNA input was observed.
These results indicate that very small amounts of starting material are sufficient to allow sensitive miRNA profiling using the Illumina miRNA high-dimensional platform. Nonlinear biases were observed between replicates, indicating the need for abundance-dependent normalization. Overall, the performance characteristics of the Illumina miRNA profiling system were excellent.
BMC Medical Genomics 09/2009; 2:57. · 3.69 Impact Factor
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ABSTRACT: We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.
Journal of Proteome Research 03/2009; 8(5):2144-56. · 5.11 Impact Factor
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ABSTRACT: We describe biological and experimental factors that induce variability in reporter ion peak areas obtained from iTRAQ experiments. We demonstrate how these factors can be incorporated into a statistical model for use in evaluating differential protein expression and highlight the benefits of using analysis of variance to quantify fold change. We demonstrate the model's utility based on an analysis of iTRAQ data derived from a spike-in study.
Journal of Proteome Research 07/2008; 7(8):3091-101. · 5.11 Impact Factor
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ABSTRACT: Attenuated measles viruses are promising experimental anticancer agents currently being evaluated in a phase I dose escalation trial for ovarian cancer patients. Virus attachment, entry, and subsequent intercellular fusion between infected and uninfected neighboring cells are mediated via the two measles receptors (CD46 and SLAM). To minimize potential toxicity due to measles virus-associated immunosuppression and infection of nontarget tissues, we sought to develop an ovarian cancer exclusive fully retargeted measles virus.
Interactions of measles virus with its natural receptors were ablated, and a single-chain antibody (scFv) specific for alpha-folate receptor (FRalpha), a target overexpressed on 90% of nonmucinous ovarian cancer, was genetically engineered on the viral attachment protein (MV-alphaFR). Specificity of virus tropism was tested on tumor and normal cells. Biodistribution of measles virus infection was evaluated in measles-susceptible CD46 transgenic mice, whereas antitumor activity was monitored noninvasively by bioluminescence imaging in xenograft models. Tropism and fusogenic activity of MV-alphaFR was redirected exclusively to FRalpha without compromise to virus infectivity. In contrast to the parental virus, MV-alphaFR has no background infectivity on normal human cells. The antitumor activity of MV-alphaFR, as assessed by tumor volume reduction and overall survival increase, was equal to the parental virus in two models of human ovarian cancer (s.c. and i.p.).
A FR-exclusive ovarian cancer targeted oncolytic virus was generated and shown to be therapeutically effective, thus introducing a new modality for FR targeting and a candidate measles virus for clinical testing.
Clinical Cancer Research 11/2006; 12(20 Pt 1):6170-8. · 7.74 Impact Factor
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ABSTRACT: Motivation: Our goal was to develop a normalization technique that yields results similar to cyclic loess normalization and with speed comparable to quantile normalization. Results: Fastlo yields normalized values similar to cyclic loess and quantile normalization and is fast; it is at least an order of magnitude faster than cyclic loess and approaches the speed of quantile normalization. Furthermore, fastlo is more versatile than both cyclic loess and quantile normalization because it is model-based. Availability: The Splus function for fastlo normalization is available from the authors. 1
01/2004;
