Bryan Frank

Multiple-laboratory comparison of microarray platforms

Microarray technology is a powerful tool for measuring RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of cross-platform meta-analysis studies rapidly increases, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we noticed that none of the previously published papers consider differences between labs. For this study, a consortium of ten laboratories from the Washington, DC–Baltimore, USA, area was formed to compare data obtained from three widely used platforms using identical RNA samples. We used appropriate statistical analysis to demonstrate that there are relatively large differences in data obtained in labs using the same platform, but that the results from the best-performing labs agree rather well.

Independence and reproducibility across microarray platforms

Microarrays have been widely used for the analysis of gene expression, but the issue of reproducibility across platforms has yet to be fully resolved. To address this apparent problem, we compared gene expression between two microarray platforms: the short oligonucleotide Affymetrix Mouse Genome 430 2.0 GeneChip and a spotted cDNA array using a mouse model of angiontensin II–induced hypertension. RNA extracted from treated mice was analyzed using Affymetrix and cDNA platforms and then by quantitative RT-PCR (qRT-PCR) for validation of specific genes. For the 11,710 genes present on both arrays, we assessed the relative impact of experimental treatment and platform on measured expression and found that biological treatment had a far greater impact on measured expression than did platform for more than 90% of genes, a result validated by qRT-PCR. In the small number of cases in which platforms yielded discrepant results, qRT-PCR generally did not confirm either set of data, suggesting that sequence-specific effects may make expression predictions difficult to make using any technique.

Gene expression profiling of lymphoblastoid cell lines from monozygotic twins discordant in severity of autism reveals differential regulation of neurologically relevant genes

BackgroundThe autism spectrum encompasses a set of complex multigenic developmental disorders that severely impact the development of language, non-verbal communication, and social skills, and are associated with odd, stereotyped, repetitive behavior and restricted interests. To date, diagnosis of these neurologically based disorders relies predominantly upon behavioral observations often prompted by delayed speech or aberrant behavior, and there are no known genes that can serve as definitive biomarkers for the disorders.ResultsHere we demonstrate, for the first time, that lymphoblastoid cell lines from monozygotic twins discordant with respect to severity of autism and/or language impairment exhibit differential gene expression patterns on DNA microarrays. Furthermore, we show that genes important to the development, structure, and/or function of the nervous system are among the most differentially expressed genes, and that many of these genes map closely in silico to chromosomal regions containing previously reported autism candidate genes or quantitative trait loci.ConclusionOur results provide evidence that novel candidate genes for autism may be differentially expressed in lymphoid cell lines from individuals with autism spectrum disorders. This finding further suggests the possibility of developing a molecular screen for autism based on expressed biomarkers in peripheral blood lymphocytes, an easily accessible tissue. In addition, gene networks are identified that may play a role in the pathophysiology of autism.

Assessing unmodified 70-mer oligonucleotide probe performance on glass-slide microarrays

BackgroundLong oligonucleotide microarrays are potentially more cost- and management-efficient than cDNA microarrays, but there is little information on the relative performance of these two probe types. The feasibility of using unmodified oligonucleotides to accurately measure changes in gene expression is also unclear.ResultsUnmodified sense and antisense 70-mer oligonucleotides representing 75 known rat genes and 10 Arabidopsis control genes were synthesized, printed and UV cross-linked onto glass slides. Printed alongside were PCR-amplified cDNA clones corresponding to the same genes, enabling us to compare the two probe types simultaneously. Our study was designed to evaluate the mRNA profiles of heart and brain, along with Arabidopsis cRNA spiked into the labeling reaction at different relative copy number. Hybridization signal intensity did not correlate with probe type but depended on the extent of UV irradiation. To determine the effect of oligonucleotide concentration on hybridization signal, 70-mers were serially diluted. No significant change in gene-expression ratio or loss in hybridization signal was detected, even at the lowest concentration tested (6.25 μm). In many instances, signal intensity actually increased with decreasing concentration. The correlation coefficient between oligonucleotide and cDNA probes for identifying differentially expressed genes was 0.80, with an average coefficient of variation of 13.4%. Approximately 8% of the genes showed discordant results with the two probe types, and in each case the cDNA results were more accurate, as determined by real-time PCR.ConclusionsMicroarrays of UV cross-linked unmodified oligonucleotides provided sensitive and specific measurements for most of the genes studied.

Voltage-Gated Na + Channel SCN5A Is a Key Regulator of a Gene Transcriptional Network That Controls Colon Cancer Invasion

Voltage-gated Na(+) channels (VGSC) have been implicated in the metastatic potential of human breast, prostate, and lung cancer cells. Specifically, the SCN5A gene encoding the VGSC isotype Na(v)1.5 has been defined as a key driver of human cancer cell invasion. In this study, we examined the expression and function of VGSCs in a panel of colon cancer cell lines by electrophysiologic recordings. Na(+) channel activity and invasive potential were inhibited pharmacologically by tetrodotoxin or genetically by small interfering RNAs (siRNA) specifically targeting SCN5A. Clinical relevance was established by immunohistochemistry of patient biopsies, with strong Na(v)1.5 protein staining found in colon cancer specimens but little to no staining in matched-paired normal colon tissues. We explored the mechanism of VGSC-mediated invasive potential on the basis of reported links between VGSC activity and gene expression in excitable cells. Probabilistic modeling of loss-of-function screens and microarray data established an unequivocal role of VGSC SCN5A as a high level regulator of a colon cancer invasion network, involving genes that encompass Wnt signaling, cell migration, ectoderm development, response to biotic stimulus, steroid metabolic process, and cell cycle control. siRNA-mediated knockdown of predicted downstream network components caused a loss of invasive behavior, demonstrating network connectivity and its function in driving colon cancer invasion.

Refinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancy.

Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics.

Model-driven multi-omic data analysis elucidates metabolic immunomodulators of macrophage activation.

Macrophages are central players in immune response, manifesting divergent phenotypes to control inflammation and innate immunity through release of cytokines and other signaling factors. Recently, the focus on metabolism has been reemphasized as critical signaling and regulatory pathways of human pathophysiology, ranging from cancer to aging, often converge on metabolic responses. Here, we used genome‐scale modeling and multi‐omics (transcriptomics, proteomics, and metabolomics) analysis to assess metabolic features that are critical for macrophage activation. We constructed a genome‐scale metabolic network for the RAW 264.7 cell line to determine metabolic modulators of activation. Metabolites well‐known to be associated with immunoactivation (glucose and arginine) and immunosuppression (tryptophan and vitamin D3) were among the most critical effectors. Intracellular metabolic mechanisms were assessed, identifying a suppressive role for de‐novo nucleotide synthesis. Finally, underlying metabolic mechanisms of macrophage activation are identified by analyzing multi‐omic data obtained from LPS‐stimulated RAW cells in the context of our flux‐based predictions. Our study demonstrates metabolisms role in regulating activation may be greater than previously anticipated and elucidates underlying connections between activation and metabolic effectors.

Molecular profiling of LGL leukemia reveals role of sphingolipid signaling in survival of cytotoxic lymphocytes

T-cell large granular lymphocyte (LGL) leukemia is characterized by clonal expansion of CD3(+)CD8(+) cells. Leukemic LGLs correspond to terminally differentiated effector-memory cytotoxic T lymphocytes (CTLs) that escape Fas-mediated activation-induced cell death (AICD) in vivo. The gene expression signature of peripheral blood mononuclear cells from 30 LGL leukemia patients showed profound dysregulation of expression of apoptotic genes and suggested uncoupling of activation and apoptotic pathways as a mechanism for failure of AICD in leukemic LGLs. Pathway-based microarray analysis indicated that balance of proapoptotic and antiapoptotic sphingolipid-mediated signaling was deregulated in leukemic LGLs. We further investigated sphingolipid pathways and found that acid ceramidase was constitutively overexpressed in leukemic LGLs and that its inhibition induced apoptosis of leukemic LGLs. We also showed that S1P(5) is the predominant S1P receptor in leukemic LGLs, whereas S1P(1) is down-regulated. FTY720, a functional antagonist of S1P-mediated signaling, induced apoptosis in leukemic LGLs and also sensitized leukemic LGLs to Fas-mediated death. Collectively, these results show a role for sphingolipid-mediated signaling as a mechanism for long-term survival of CTLs. Therapeutic targeting of this pathway, such as use of FTY720, may have efficacy in LGL leukemia.

Identification of Src transformation fingerprint in human colon cancer

We used a classical rodent model of transformation to understand the transcriptional processes, and hence the molecular and cellular events a given cell undergoes when progressing from a normal to a transformed phenotype. Src activation is evident in 80% of human colon cancer, yet the myriad of cellular processes effected at the level of gene expression has yet to be fully documented. We identified a Src ‘transformation fingerprint’ within the gene expression profiles of Src-transformed rat 3Y1 fibroblasts demonstrating a progression in transformation characteristics. To evaluate the role of this gene set in human cancer development and progression, we extracted the orthologous genes present on the Affymetrix Hu95A GeneChip™ (12k named genes) and compared expression profiles between the Src-induced rodent cell line model of transformation and staged colon tumors where Src is known to be activated. A similar gene expression pattern between the cell line model and staged colon tumors for components of the cell cycle, cytoskeletal associated proteins, transcription factors and lysosomal proteins suggests the need for co-regulation of several cellular processes in the progression of cancer. Genes not previously implicated in tumorigenesis were detected, as well as a set of 14 novel, highly conserved genes with here-to-fore unknown function. These studies define a set of transformation associated genes whose up-regulation has implications for understanding Src mediated transformation and strengthens the role of Src in the development and progression of human colon cancer. Supportive Supplemental Data can be viewed at http://pga.tigr.org/PGApubs.shtml.

Autocrine activation of an osteopontin-CD44-Rac pathway enhances invasion and transformation by H-RasV12

Activated forms of Ras family members are prevalent in many cancers where Ras mutants transduce signals essential for transformation, angiogenesis, invasion and metastasis. As a cancer progression model, we used NIH3T3 cells to explore the mechanism of Ras-induced tumorigenesis. Ras family mutants H-RasV12 and Rit79L strongly induced foci formation, while Rho family mutants RhoA-QL, Rac1-QL and Cdc42-QL were less effective. A comparison of downstream transcriptional targets of Ras and Rho family members using a 26 383 element cDNA microarray revealed that the osteopontin (OPN) gene exhibited the best correlation between magnitude of gene expression change and level of foci formation (r=0.96, P<0.001). In association with H-RasV12- and Rit79L-mediated transformation, foci secreted OPN protein and upregulated the OPN receptor CD44, suggesting the novel initiation of an aberrant OPN-CD44-Rac autocrine pathway. In support of this were the following observations. First, RGD-deficient OPN protein-binding activity was present in H-RasV12-transformed cells but not in control cells, and binding activity was inhibited by the CD44 blocking antibody. Second, foci formation, cell invasion and Rac activity were induced by H-RasV12 and inhibited by the CD44 blocking antibody. Third, foci formation by H-RasV12 was substantially reduced by a short interfering RNA (siRNA) specifically targeting OPN expression for knockdown. Fourth, H-RasV12-mediated transformation was not blocked by the GRGDS peptide, suggesting that OPN effects were not mediated by the integrins. Lastly, OPN knockdown affected the downstream expression of 160 ‘2nd tier’ genes, and at least a subset of these genes appears to be involved in transformation. Indeed, four genes were selected for knockdown, each resulting in a disruption of foci formation and/or invasion. These results underscore the role of aberrant autocrine signaling and transcriptional networking during tumorigenesis.