Cross-Platform Comparison of Microarray-Based Multiple-Class Prediction

High-throughput microarray technology has been widely applied in biological and medical decision-making research during the past decade. However, the diversity of platforms has made it a challenge to re-use and/or integrate datasets generated in different experiments or labs for constructing array-based diagnostic models. Using large toxicogenomics datasets generated using both Affymetrix and Agilent microarray platforms, we carried out a benchmark evaluation of cross-platform consistency in multiple-class prediction using three widely-used machine learning algorithms. After an initial assessment of model performance on different platforms, we evaluated whether predictive signature features selected in one platform could be directly used to train a model in the other platform and whether predictive models trained using data from one platform could predict datasets profiled using the other platform with comparable performance. Our results established that it is possible to successfully apply multiple-class prediction models across different commercial microarray platforms, offering a number of important benefits such as accelerating the possible translation of biomarkers identified with microarrays to clinically-validated assays. However, this investigation focuses on a technical platform comparison and is actually only the beginning of exploring cross-platform consistency. Further studies are needed to confirm the feasibility of microarray-based cross-platform prediction, especially using independent datasets

Glucocorticoids with different chemical structures but similar glucocorticoid receptor potency regulate subsets of common and unique genes in human trabecular meshwork cells

<p>Abstract</p> <p>Background</p> <p>In addition to their well-documented ocular therapeutic effects, glucocorticoids (GCs) can cause sight-threatening side-effects including ocular hypertension presumably via morphological and biochemical changes in trabecular meshwork (TM) cells. In the present study, we directly compared the glucocorticoid receptor (GR) potency for dexamethasone (DEX), fluocinolone acetonide (FA) and triamcinolone acetonide (TA), examined the expression of known GRα and GRβ isoforms, and used gene expression microarrays to compare the effects of DEX, FA, and TA on the complete transcriptome in two primary human TM cell lines.</p> <p>Methods</p> <p>GR binding affinity for DEX, FA, and TA was measured by a cell-free competitive radio-labeled GR binding assay. GR-mediated transcriptional activity was assessed using the GeneBLAzer beta-lactamase reporter gene assay. Levels of GRα and GRβ isoforms were assessed by Western blot. Total RNA was extracted from TM 86 and TM 93 cells treated with 1 μM DEX, FA, or TA for 24 hr and used for microarray gene expression analysis. The microarray experiments were repeated three times. Differentially expressed genes were identified by Rosetta Resolver Gene Expression Analysis System.</p> <p>Results</p> <p>The GR binding affinity (IC₅₀) for DEX, FA, and TA was 5.4, 2.0, and 1.5 nM, respectively. These values are similar to the GR transactivation EC₅₀of 3.0, 0.7, and 1.5 nM for DEX, FA, and TA, respectively. All four GRα translational isoforms (A-D) were expressed in TM 86 and TM 93 total cell lysates, however, the C and D isoforms were more highly expressed relative to A and B. All four GRβ isoforms (A-D) were also detected in TM cells, although GRβ-D isoform expression was lower compared to that of the A, B, or C isoforms. Microarray analysis revealed 1,968 and 1,150 genes commonly regulated by DEX, FA, and TA in TM 86 and TM 93, respectively. These genes included RGC32, OCA2, ANGPTL7, MYOC, FKBP5, SAA1 and ZBTB16. In addition, each GC specifically regulated a unique set of genes in both TM cell lines. Using Ingenuity Pathway Analysis (IPA) software, analysis of the data from TM 86 cells showed that DEX significantly regulated transcripts associated with RNA post-transcriptional modifications, whereas FA and TA modulated genes involved in lipid metabolism and cell morphology, respectively. In TM 93 cells, DEX significantly regulated genes implicated in histone methylation, whereas FA and TA altered genes associated with cell cycle and cell adhesion, respectively.</p> <p>Conclusion</p> <p>Human trabecular meshwork cells in culture express all known GRα and GRβ translational isoforms, and GCs with similar potency but subtly different chemical structure are capable of regulating common and unique gene subsets and presumably biologic responses in these cells. These GC structure-dependent effects appear to be TM cell-lineage dependent.</p

Prenylation inhibitors stimulate both estrogen receptor α transcriptional activity through AF-1 and AF-2 and estrogen receptor β transcriptional activity

INTRODUCTION: We showed in a previous study that prenylated proteins play a role in estradiol stimulation of proliferation. However, these proteins antagonize the ability of estrogen receptor (ER) α to stimulate estrogen response element (ERE)-dependent transcriptional activity, potentially through the formation of a co-regulator complex. The present study investigates, in further detail, how prenylated proteins modulate the transcriptional activities mediated by ERα and by ERβ. METHODS: The ERE-β-globin-Luc-SV-Neo plasmid was either stably transfected into MCF-7 cells or HeLa cells (MELN cells and HELN cells, respectively) or transiently transfected into MCF-7 cells using polyethylenimine. Cells deprived of estradiol were analyzed for ERE-dependent luciferase activity 16 hours after estradiol stimulation and treatment with FTI-277 (a farnesyltransferase inhibitor) or with GGTI-298 (a geranylgeranyltransferase I inhibitor). In HELN cells, the effect of prenyltransferase inhibitors on luciferase activity was compared after transient transfection of plasmids coding either the full-length ERα, the full-length ERβ, the AF-1-deleted ERα or the AF-2-deleted ERα. The presence of ERα was then detected by immunocytochemistry in either the nuclei or the cytoplasms of MCF-7 cells. Finally, Clostridium botulinum C3 exoenzyme treatment was used to determine the involvement of Rho proteins in ERE-dependent luciferase activity. RESULTS: FTI-277 and GGTI-298 only stimulate ERE-dependent luciferase activity in stably transfected MCF-7 cells. They stimulate both ERα-mediated and ERβ-mediated ERE-dependent luciferase activity in HELN cells, in the presence of and in the absence of estradiol. The roles of both AF-1 and AF-2 are significant in this effect. Nuclear ERα is decreased in the presence of prenyltransferase inhibitors in MCF-7 cells, again in the presence of and in the absence of estradiol. By contrast, cytoplasmic ERα is mainly decreased after treatment with FTI-277, in the presence of and in the absence of estradiol. The involvement of Rho proteins in ERE-dependent luciferase activity in MELN cells is clearly established. CONCLUSIONS: Together, these results demonstrate that prenylated proteins (at least RhoA, RhoB and/or RhoC) antagonize the ability of ERα and ERβ to stimulate ERE-dependent transcriptional activity, potentially acting through both AF-1 and AF-2 transcriptional activities

Breast cancer oestrogen independence mediated by BCAR1 or BCAR3 genes is transmitted through mechanisms distinct from the oestrogen receptor signalling pathway or the epidermal growth factor receptor signalling pathway

INTRODUCTION: Tamoxifen is effective for endocrine treatment of oestrogen receptor-positive breast cancers but ultimately fails due to the development of resistance. A functional screen in human breast cancer cells identified two BCAR genes causing oestrogen-independent proliferation. The BCAR1 and BCAR3 genes both encode components of intracellular signal transduction, but their direct effect on breast cancer cell proliferation is not known. The aim of this study was to investigate the growth control mediated by these BCAR genes by gene expression profiling. METHODS: We have measured the expression changes induced by overexpression of the BCAR1 or BCAR3 gene in ZR-75-1 cells and have made direct comparisons with the expression changes after cell stimulation with oestrogen or epidermal growth factor (EGF). A comparison with published gene expression data of cell models and breast tumours is made. RESULTS: Relatively few changes in gene expression were detected in the BCAR-transfected cells, in comparison with the extensive and distinct differences in gene expression induced by oestrogen or EGF. Both BCAR1 and BCAR3 regulate discrete sets of genes in these ZR-75-1-derived cells, indicating that the proliferation signalling proceeds along distinct pathways. Oestrogen-regulated genes in our cell model showed general concordance with reported data of cell models and gene expression association with oestrogen receptor status of breast tumours. CONCLUSIONS: The direct comparison of the expression profiles of BCAR transfectants and oestrogen or EGF-stimulated cells strongly suggests that anti-oestrogen-resistant cell proliferation is not caused by alternative activation of the oestrogen receptor or by the epidermal growth factor receptor signalling pathway

Global gene expression analysis of the mouse colonic mucosa treated with azoxymethane and dextran sodium sulfate

<p>Abstract</p> <p>Background</p> <p>Chronic inflammation is well known to be a risk factor for colon cancer. Previously we established a novel mouse model of inflammation-related colon carcinogenesis, which is useful to examine the involvement of inflammation in colon carcinogenesis. To shed light on the alterations in global gene expression in the background of inflammation-related colon cancer and gain further insights into the molecular mechanisms underlying inflammation-related colon carcinogenesis, we conducted a comprehensive DNA microarray analysis using our model.</p> <p>Methods</p> <p>Male ICR mice were given a single ip injection of azoxymethane (AOM, 10 mg/kg body weight), followed by the addition of 2% (w/v) dextran sodium sulfate (DSS) to their drinking water for 7 days, starting 1 week after the AOM injection. We performed DNA microarray analysis (Affymetrix GeneChip) on non-tumorous mucosa obtained from mice that received AOM/DSS, AOM alone, and DSS alone, and untreated mice at wks 5 and 10.</p> <p>Results</p> <p>Markedly up-regulated genes in the colonic mucosa given AOM/DSS at wk 5 or 10 included Wnt inhibitory factor 1 (<it>Wif1</it>, 48.5-fold increase at wk 5 and 5.7-fold increase at wk 10) and plasminogen activator, tissue (<it>Plat</it>, 48.5-fold increase at wk 5), myelocytomatosis oncogene (<it>Myc</it>, 3.0-fold increase at wk 5), and phospholipase A2, group IIA (platelets, synovial fluid) (<it>Plscr2</it>, 8.0-fold increase at wk 10). The notable down-regulated genes in the colonic mucosa of mice treated with AOM/DSS were the peroxisome proliferator activated receptor binding protein (<it>Pparbp</it>, 0.06-fold decrease at wk 10) and the transforming growth factor, beta 3 (<it>Tgfb3</it>, 0.14-fold decrease at wk 10). The inflammation-related gene, peroxisome proliferator activated receptor γ (<it>Pparγ </it>0.38-fold decrease at wk 5), was also down-regulated in the colonic mucosa of mice that received AOM/DSS.</p> <p>Conclusion</p> <p>This is the first report describing global gene expression analysis of an AOM/DSS-induced mouse colon carcinogenesis model, and our findings provide new insights into the mechanisms of inflammation-related colon carcinogenesis and the establishment of novel therapies and preventative strategies against carcinogenesis.</p

Functional analysis of multiple genomic signatures demonstrates that classification algorithms choose phenotype-related genes

Gene expression signatures of toxicity and clinical response benefit both safety assessment and clinical practice; however, difficulties in connecting signature genes with the predicted end points have limited their application. The Microarray Quality Control Consortium II (MAQCII) project generated 262 signatures for ten clinical and three toxicological end points from six gene expression data sets, an unprecedented collection of diverse signatures that has permitted a wide-ranging analysis on the nature of such predictive models. A comprehensive analysis of the genes of these signatures and their nonredundant unions using ontology enrichment, biological network building and interactome connectivity analyses demonstrated the link between gene signatures and the biological basis of their predictive power. Different signatures for a given end point were more similar at the level of biological properties and transcriptional control than at the gene level. Signatures tended to be enriched in function and pathway in an end point and model-specific manner, and showed a topological bias for incoming interactions. Importantly, the level of biological similarity between different signatures for a given end point correlated positively with the accuracy of the signature predictions. These findings will aid the understanding, and application of predictive genomic signatures, and support their broader application in predictive medicine

Membrane estrogen receptor-α levels predict estrogen-induced ERK1/2 activation in MCF-7 cells

INTRODUCTION: We examined the participation of a membrane form of estrogen receptor (mER)-α in the activation of mitogen-activated protein kinases (extracellular signal-regulated kinase [ERK]1 and ERK2) related to cell growth responses in MCF-7 cells. METHODS: We immunopanned and subsequently separated MCF-7 cells (using fluorescence-activated cell sorting) into mER-α-enriched (mER(high)) and mER-α-depleted (mER(low)) populations. We then measured the expression levels of mER-α on the surface of these separated cell populations by immunocytochemical analysis and by a quantitative 96-well plate immunoassay that distinguished between mER-α and intracellular ER-α. Western analysis was used to determine colocalized estrogen receptor (ER)-α and caveolins in membrane subfractions. The levels of activated ERK1 and ERK2 were determined using a fixed cell-based enzyme-linked immunosorbent assay developed in our laboratory. RESULTS: Immunocytochemical studies revealed punctate ER-α antibody staining of the surface of nonpermeabilized mER(high )cells, whereas the majority of mER(low )cells exhibited little or no staining. Western analysis demonstrated that mER(high )cells expressed caveolin-1 and caveolin-2, and that ER-α was contained in the same gradient-separated membrane fractions. The quantitative immunoassay for ER-α detected a significant difference in mER-α levels between mER(high )and mER(low )cells when cells were grown at a sufficiently low cell density, but equivalent levels of total ER-α (membrane plus intracellular receptors). These two separated cell subpopulations also exhibited different kinetics of ERK1/2 activation with 1 pmol/l 17β-estradiol (E(2)), as well as different patterns of E(2 )dose-dependent responsiveness. The maximal kinase activation was achieved after 10 min versus 6 min in mER(high )versus mER(low )cells, respectively. After a decline in the level of phosphorylated ERKs, a reactivation was seen at 60 min in mER(high )cells but not in mER(low )cells. Both 1A and 2B protein phosphatases participated in dephosphorylation of ERKs, as demonstrated by efficient reversal of ERK1/2 inactivation with okadaic acid and cyclosporin A. CONCLUSION: Our results suggest that the levels of mER-α play a role in the temporal coordination of phosphorylation/dephosphorylation events for the ERKs in breast cancer cells, and that these signaling differences can be correlated to previously demonstrated differences in E(2)-induced cell proliferation outcomes in these cell types

Identification of Functional Networks of Estrogen- and c-Myc-Responsive Genes and Their Relationship to Response to Tamoxifen Therapy in Breast Cancer

BACKGROUND: Estrogen is a pivotal regulator of cell proliferation in the normal breast and breast cancer. Endocrine therapies targeting the estrogen receptor are effective in breast cancer, but their success is limited by intrinsic and acquired resistance. METHODOLOGY/PRINCIPAL FINDINGS: With the goal of gaining mechanistic insights into estrogen action and endocrine resistance, we classified estrogen-regulated genes by function, and determined the relationship between functionally-related genesets and the response to tamoxifen in breast cancer patients. Estrogen-responsive genes were identified by transcript profiling of MCF-7 breast cancer cells. Pathway analysis based on functional annotation of these estrogen-regulated genes identified gene signatures with known or predicted roles in cell cycle control, cell growth (i.e. ribosome biogenesis and protein synthesis), cell death/survival signaling and transcriptional regulation. Since inducible expression of c-Myc in antiestrogen-arrested cells can recapitulate many of the effects of estrogen on molecular endpoints related to cell cycle progression, the estrogen-regulated genes that were also targets of c-Myc were identified using cells inducibly expressing c-Myc. Selected genes classified as estrogen and c-Myc targets displayed similar levels of regulation by estrogen and c-Myc and were not estrogen-regulated in the presence of siMyc. Genes regulated by c-Myc accounted for 50% of all acutely estrogen-regulated genes but comprised 85% (110/129 genes) in the cell growth signature. siRNA-mediated inhibition of c-Myc induction impaired estrogen regulation of ribosome biogenesis and protein synthesis, consistent with the prediction that estrogen regulates cell growth principally via c-Myc. The 'cell cycle', 'cell growth' and 'cell death' gene signatures each identified patients with an attenuated response in a cohort of 246 tamoxifen-treated patients. In multivariate analysis the cell death signature was predictive independent of the cell cycle and cell growth signatures. CONCLUSIONS/SIGNIFICANCE: These functionally-based gene signatures can stratify patients treated with tamoxifen into groups with differing outcome, and potentially identify distinct mechanisms of tamoxifen resistance